ArticlePDF Available

Training the brain: Fact and fad in cognitive and behavioral remediation

March 2012
Brain and Cognition 79(2):159-79

March 2012
79(2):159-79

DOI:10.1016/j.bandc.2012.02.006

Source
PubMed

Authors:

Sheida Rabipour

Douglas Mental Health University Institute

Putatively safe and effective for improving cognitive performance in both health and disease, products purported to train the brain appeal to consumers and healthcare practitioners. In an increasingly health-centered society, these applications constitute a burgeoning commercial market. Sparse evidence coupled with lack of scientific rigor, however, leaves claims concerning the impact and duration of such brain training largely unsubstantiated. On the other hand, at least some scientific findings seem to support the effectiveness and sustainability of training for higher brain functions such as attention and working memory. In the present paper we provide a tectonic integration and synthesis of cognitive training approaches. Specifically, we sketch the relative merits and shortcomings of these programs, which often appeal to parents who must choose between side-effect-laden medication and other less conventional options. Here we examine how neuroplasticity allows the healthy as well the impaired to benefit from cognitive training programs. We evaluate the evidence and consider whether brain training can be a stand-alone treatment or an adjunct to pharmacotherapy, outline promising future prospects, and highlight what training outcomes are plausible in line with available data. Future research would determine whether the field of brain training realizes its potential to revolutionize education and rehabilitation or withers away engulfed in controversy.

A list of select commercial software aiming to enhance or rehabilitate specific cognitive skills in health and pathology.

…

Figures - uploaded by Sheida Rabipour

Content may be subject to copyright.

Content uploaded by Sheida Rabipour

Content may be subject to copyright.

This article appeared in a journal published by Elsevier. The attached

copy is furnished to the author for internal non-commercial research

and education use, including for instruction at the authors institution

and sharing with colleagues.

Other uses, including reproduction and distribution, or selling or

licensing copies, or posting to personal, institutional or third party

websites are prohibited.

In most cases authors are permitted to post their version of the

article (e.g. in Word or Tex form) to their personal website or

institutional repository. Authors requiring further information

regarding Elsevier’s archiving and manuscript policies are

encouraged to visit:

http://www.elsevier.com/copyright

Author's personal copy

Special Invited Review

Training the brain: Fact and fad in cognitive and behavioral remediation

Sheida Rabipour

, Amir Raz

a,b,

⇑

Department of Neurology & Neurosurgery, McGill University, Canada

Departments of Psychiatry & Psychology, McGill University, Canada

article info

Article history:

Accepted 13 February 2012

Available online 30 March 2012

Keywords:

Attention

Brain training

Cognitive remediation

Computerized training programs

Neuroplasticity

Working memory

abstract

Putatively safe and effective for improving cognitive performance in both health and disease, products

purported to train the brain appeal to consumers and healthcare practitioners. In an increasingly

health-centered society, these applications constitute a burgeoning commercial market. Sparse evidence

coupled with lack of scientiﬁc rigor, however, leaves claims concerning the impact and duration of such

brain training largely unsubstantiated. On the other hand, at least some scientiﬁc ﬁndings seem to sup-

port the effectiveness and sustainability of training for higher brain functions such as attention and work-

ing memory. In the present paper we provide a tectonic integration and synthesis of cognitive training

approaches. Speciﬁcally, we sketch the relative merits and shortcomings of these programs, which often

appeal to parents who must choose between side-effect-laden medication and other less conventional

options. Here we examine how neuroplasticity allows the healthy as well the impaired to beneﬁt from

cognitive training programs. We evaluate the evidence and consider whether brain training can be a

stand-alone treatment or an adjunct to pharmacotherapy, outline promising future prospects, and high-

light what training outcomes are plausible in line with available data. Future research would determine

whether the ﬁeld of brain training realizes its potential to revolutionize education and rehabilitation or

withers away engulfed in controversy.

1. Introduction

Increasingly ubiquitous, training programs foster the putative

promise of enhancing or rehabilitating behavior and brain func-

tion. This trend comprises a burgeoning market of products alleged

to enhance cognition, emotion, thought and action. Catering to

individuals of all ages, but targeting young children and the elderly

in particular, such programs claim to beneﬁt healthy populations

as well as those diagnosed with speciﬁc disorders. Many commer-

cial programs take advantage of computerized training over the

Internet, offering the comfort and privacy of home-based brain

exercise. Appealing to a wide clientele – from the ambitious and

healthy to the desperate and sick – brain training targets parents

and professionals looking for an edge in a competitive society,

symptom relief, or a potential cure.

Broadly deﬁned, brain training refers to the engagement in a

speciﬁc program or activity that aims to enhance a cognitive skill

or general cognitive ability as a result of repetition over a circum-

scribed timeframe. Such training can produce changes measured at

the behavioral as well as the neuroanatomical and functional lev-

els. Many forms of brain training appear to improve cognitive func-

tion and emotional control, particularly programs that exercise

attention (Rueda, Posner, and Rothbart, 2005). By practicing games

or tasks that require choosing between two competing responses,

the training of attention aims to strengthen the neural networks

underlying control processes (Raz & Buhle, 2006). A strong modu-

lator of cognition and affect, attention refers to the selective focus

on speciﬁc aspects of our environment or to the concentration on

speciﬁc mental thoughts and operations (Raz & Buhle, 2006). Sim-

ilar to attention training (AT), many programs target working

memory (WM), a system that mediates temporary information

storage, modiﬁcation, and protection from interference (Bledowski,

Kaiser, & Rahm, 2010). Apart from attention and WM, studies sug-

gest that practicing sustained attention through meditation (Tang

& Posner, 2009), schooling (Diamond, Barnett, Thomas, & Munro,

2007), interaction with nature (Kaplan, 1995a), exercise (Kubesch

et al., 2009), and musical training (Kraus & Chandrasekaran,

2010) can also improve cognitive ability and emotional control.

The effects of such varied methods on cognitive ability and emo-

tional stability attest to the advantages of speciﬁc exercises.

http://dx.doi.org/10.1016/j.bandc.2012.02.006

Abbreviations: AT, attention training; WM, working memory; FFW-L, Fast

ForWord-Language; HRT, habit-reversal training; IBMT, integrative body-mind

training; BBC, British Broadcasting Corporation; AKTIVA, Active Cognitive Stimu-

lation-Prevention in the Elderly; TS, Tourette’s Syndrome; COI, conﬂicts of interest.

⇑

Corresponding author. Address: Institute of Community and Family Psychiatry,

4333 Cote Ste. Catherine, Montreal, QC, H3W 1E4 Canada.

E-mail address: Amir.Raz@McGill.ca (A. Raz).

Brain and Cognition 79 (2012) 159–179

Contents lists available at SciVerse ScienceDirect

Brain and Cognition

journal homepage: www.elsevier.com/locate/b&c

Author's personal copy

Brain training is especially relevant for developmental psycho-

pathology. This approach has potential to ameliorate undesired

symptoms of disorders such as attention deﬁcit hyperactivity dis-

order (ADHD), a condition characterized by deﬁcits in behavioral

inhibition associated with cognitive processes that mediate goal-

directed behaviors (Barkley, 1997). ADHD comprises a useful lens

through which researchers examine the effects of training. A spec-

trum disorder, ADHD contains various degrees of severity that in-

ﬂict mild to severe impairments, many of which relate to

executive attention and may improve as a result of training (Illes

& Sahakian, 2011). Currently, primary treatments for developmen-

tal psychopathologies such as ADHD often involve psychotropic

medications, which sometimes show marginal effects. Even these

effects, however, attenuate over time and can generate a number

of unwanted side-effects. As a result, parents and clinicians are of-

ten reluctant to embrace drug-based therapy despite the scarcity of

safe and effective treatment alternatives. Recent allegations add

controversy to this dilemma by claiming that certain psychiatrists

may have surreptitious ties with drug companies, biasing the re-

search surrounding the production and distribution of medication

for youth (‘‘Credibility Crisis in Pediatric Psychiatry,’’ 2008). In light

of such limitations in pharmacological-based remedies, brain

training may represent an attractive adjunct to common pharma-

cological treatment.

The generalizability of brain training represents one of the ma-

jor claims-to-fame of publicly distributed programs. With scarce

data to support advertised claims, however, patrons of brain train-

ing often invest considerable resources pursuing programs that

promote unsupported, arguably unrealistic, outcomes. While stud-

ies of computerized AT and working memory training (WMT)

show, perhaps unsurprisingly, that trainees can improve signiﬁ-

cantly on cognitive skills related to the intervention (Westerberg

et al., 2007), at least some ﬁndings suggest that training may gen-

eralize beyond task-speciﬁc skills and apply to untrained overarch-

ing abilities (Jaeggi, Buschkuehl, Jonides, & Perrig, 2008; Jaeggi

et al., 2010). Reported improvements sometimes extend to in-

creased ﬂuid intelligence, which refers to the ability to solve prob-

lems in novel situations (Buschkuehl & Jaeggi, 2010; Mackey, Hill,

Stone, & Bunge, 2010). Such transfer effects may result from over-

lapping neural networks in the prefrontal cortex (PFC), which

underlie both WM and ﬂuid intelligence (Gray, Chabris, & Braver,

2003; Klingberg, 2010). Claims regarding the transfer of practiced

skills to other untrained cognitive domains are contentious, how-

ever, because the appearance of transfer may, in fact, result from

training-to-task (Snyder, 2011). Speciﬁcally, training programs

may obliquely tax the very abilities that researchers subsequently

test (Diamond, 2011). In addition, being the wild west of neuropsy-

chology, many studies report experimental results using inade-

quate controls, if any (Papp, Walsh, & Snyder, 2009). Rather than

generalizability, therefore, the improvements observed throughout

various programs may arise due to reasons such as training-to-

task.

Apparent from adequately controlled studies, brain training is a

groundbreaking approach with potential to transform the pano-

rama of non-pharmacological therapy. Despite the mounting prev-

alence of such products, the immense potential of such

interventions for various populations, and the increasing evidence

both supporting and disclaiming the effectiveness of training, no

other article, to our knowledge, has thoroughly amalgamated the

evidence surrounding cognitive programs and the populations that

may beneﬁt from training. In the present article, we critically eval-

uate the validity of claims regarding various brain exercises and

cognitive remediation approaches. In an attempt to elucidate the

effectiveness of brain training, we examine the impact of these

programs in both healthy developing individuals and pathological

populations. We further investigate the potential use of such

training as an adjunct – or possible substitute – to current drug-

based therapies for children with psychopathologies. We conclude

by discussing speciﬁc conﬂicts that may hinder the advancement

of research in this ﬁeld and outline plausible outcomes of brain

training with regards to factors that may alleviate or aggravate

undesirable childhood behavior.

2. Neural and behavioral basis of brain training

Attention plays a central role in social behavior and academic

performance. Due to brain plasticity, training can alter the neural

correlates of attention and improve attentional control. In this sec-

tion, we focus on a current, widely recognized model that subdi-

vides attention into three separate systems. We discuss the

function of these systems as well as their related neural networks,

and delineate how these systems control behavior throughout

development. Ultimately, we underline why attention is a suitable

faculty to train in both children and adults.

2.1. Neuroplasticity and training

Brain training thrives on the lure of neuroplasticity, a change in

neural structure and function in response to experience or environ-

mental stimulation (Shaw, Lanius, & Vandendoel, 1994). Research

suggests that both genetic and environmental factors impact the

development and physical structure of the brain (Lenroot & Giedd,

2008). Investigations of executive attention in children have

uncovered notable disparities associated with socio-economic sta-

tus, even when performance levels are comparable (Hackman &

Farah, 2009; Mezzacappa, 2004). Other studies report that severe

stress and maltreatment experienced early in life can severely im-

pact neuroanatomy, showing reduced volumes and attenuated

development of several neural structures (Teicher et al., 2003). Ta-

ken together, these ﬁndings indicate that the developing brain is

susceptible to change in response to environmental stimuli.

Evidence suggests that neuroplastic processes are present in the

adult brain. Repeated practice of skills required for a profession, for

example, appears to induce lasting changes within neural struc-

ture; London taxi drivers display larger gray matter volumes in

neural areas associated with spatial memory (Maguire, Woollett,

& Spiers, 2006; Maguire et al., 1998), professional typists undergo

greater development of neural regions related to the programming

of motor tasks (Cannonieri, Bonilha, Fernandes, Cendes, & Li, 2007),

and musicians appear to acquire increased cortical representations

of their digits (Elbert, Pantev, Wienbruch, Rockstroh, & Taub, 1995)

as well as enlarged motor, auditory, and visual-spatial regions (Ga-

ser & Schlaug, 2003). Even among the elderly, neuroplasticity con-

tinues to facilitate changes leading to improvement in cognitive

function (Calero & Navarro, 2007). These studies indicate that the

greatest changes occur through repeated practice of a skill over

an extended period of time, even when learned in adulthood. In

addition, extensive training or practicing a speciﬁc new skill may

modify neural structures and functions over a relatively short per-

iod of time; magnetic resonance imaging (MRI) reveals increases in

gray matter volumes of regions associated with the processing of

complex visual motion in young adults, following 3 months of

training on a juggling task (Draganski et al., 2004). Diffusion tensor

imaging, furthermore, indicates changes in white matter conﬁgu-

ration after just 4 weeks of juggling (Scholz, Klein, Behrens, &

Johansen-Berg, 2009). Another study reported changes in the gray

matter density of medical students, following 3 months of exten-

sive studying for a medical school exam (Draganski et al., 2006).

Recent studies show, moreover, that increases in gray matter vol-

ume may occur following as little as 1 week of training in a partic-

ular task (Driemeyer, Boyke, Gaser, B üchel, & May, 2008).

160 S. Rabipour, A. Raz/ Brain and Cognition 79 (2012) 159–179

Author's personal copy

Functional and morphological changes in the adult brain may

therefore arise as a result of expertise in a ﬁeld as well as mastering

novel skills.

2.2. Attention networks

Attention encompasses distinct neural processes that mature

independently, at different stages of life. Fundamental to cognitive

function, attention begins to develop during childhood (Posner &

Rothbart, 2007b) and contributes to self-regulation, the ability to

regulate our thoughts and actions (Karoly, 1993; Raz & Buhle,

2006; Rueda, Posner, et al., 2005). William James ﬁrst proposed

that attention may contain multiple ‘‘varieties’’ (James, 1890),

deviating from long-held theories of attention as a unitary system.

A century later, Michael Posner further elaborated on this idea by

putting forth a theory in which attention consists of three highly

connected yet independent networks (Posner & Petersen, 1990).

This attention trilogy comprises the alerting, orienting, and execu-

tive attention systems (Posner & Rothbart, 2007a).

The alerting and orienting networks constitute the more prim-

itive components of attention; the alerting system denotes sus-

tained attention, vigilance, or alertness, and refers to response

readiness in preparation for an impending stimulus (Raz & Buhle,

2006). Sometimes considered the foundational form of attention,

the alerting system may continue developing well into adulthood

(Rueda, Fan, et al., 2004; Rueda, Posner, Rothbart, Davis-Stober,

2004). The orienting network, on the other hand, involves selecting

speciﬁc information from multiple sensory stimuli (Raz & Buhle,

2006). Believed to develop fully by the age of four, this network

mediates shifts of the sensory organs to bring objects of interest

into focus (Posner & Rothbart, 2007b).

Of the three attention networks, executive attention is most

pertinent to brain training. Also termed supervisory or selective

attention, executive attention mediates voluntary control and acti-

vates in situations requiring the monitoring and resolution of con-

ﬂict between computations in separate neural areas (Raz & Buhle,

2006). These conﬂicts may include planning or decision-making,

error detection, execution of new or ill-acquired responses,

involvement in stressful conditions, regulation of thoughts and

feelings and overcoming of habitual actions. Executive attention

involves processes of self-regulation that include effortful control,

the ability to suppress a dominant response in favor of a subdomi-

nant response (Kochanska, Murray, & Harlan, 2000), as well as

inhibitory control, the termination of an ongoing response (Scha-

char, Tannock, & Logan, 1993). Accordingly, measures of this sys-

tem often involve conﬂict-related tasks such as the Stroop task,

which requires participants to name the ink color of a color-word

by suppressing the tendency to read the word itself (Stroop, 1935).

In addition, executive attention plays a role in emotional regula-

tion, the control of emotional responses based on actions of the self

or others (Raz & Buhle, 2006). Neural correlates of executive atten-

tion lie within the lateral PFC, the ACC, and the basal ganglia, and

draw on the dopaminergic system (Posner & Rothbart, 2007b).

The ACC itself is believed to have several functionalities. While the-

ories initially implicated the dorsal portion in cognitive conﬂict

and the ventral–rostral portion in emotional conﬂict (Bush, Luu,

& Posner, 2000), recent evidence suggests that the dorsal ACC

may integrate negative affect, pain, and cognitive control to facili-

tate appropriate action based on punishment-related information

(Shackman et al., 2011). Furthermore, genes that modulate the

dopaminergic system strongly inﬂuence executive attention and

also appear to associate with impulse-control disorders such as

ADHD (Fan, Fossella, Sommer, Wu, & Posner, 2003; Fossella et al.,

2002). With rapid development commencing at 4 years of age,

the executive attention network may not change signiﬁcantly after

the age of seven (Rueda, Fan, et al., 2004; Rueda, Posner, et al.,

2004). This early development in executive attention appears to

have strong potential for environmental modiﬁcation, including

targeted training (Rueda, Rothbart, McCandliss, Saccomanno, Pos-

ner, 2005). By developing executive attention, children learn to

regulate cognition and behavior, and gradually conform to societal

norms.

Executive attention strongly links to WM in situations requiring

attentional control and focus. Similar to attention, WM is a modu-

lar system and is recruited during processes such as reading and

language comprehension, learning, and reasoning (Baddeley,

1992; Daneman & Carpenter, 1980; Tsianos, Germanakos, Lekkas,

Mourlas, & Samaras, 2010). Originally hypothesized to mediate

executive attention, WM is now believed to draw upon this net-

work in order to maintain and prioritize temporary stores of infor-

mation (D’Esposito, 2007; Jarrold & Towse, 2006). Neuroimaging

studies in humans and nonhuman primates consistently correlate

the use of WM with activation patterns involved in executive func-

tion, a faculty that encompasses executive attention, including cir-

cuits within the lateral PFC (D’Esposito, 2007; Klingberg, 2010).

These ﬁndings suggest that WM and executive attention rely upon

one another’s functionality to control and monitor speciﬁc neural

processes.

2.3. Attention and brain training: transfer of behavioral control

Studies suggest that the attention networks exert differential

control over behavior, with speciﬁc networks contributing more

strongly at certain stages of life (Gupta & Kar, 2009; Rueda, Fan,

et al., 2004; Rueda, Ponsner, et al., 2004). Whereas the executive

attention network plays a critical role in many adult pursuits, the

orienting network most strongly dictates behavior at earlier devel-

opmental periods. In infants as young as 3 months of age, visual

and auditory distraction can temporarily dampen distress (Posner,

Rothbart, Sheese, & Voelker, 2011). This early reliance on the ori-

enting network may underlie the relative novelty of environmental

stimuli for infants and children and often provides refuge for care-

givers seeking to soothe a distressed baby by using a distracter.

Similar effects have also been reported in adults (Harman, Roth-

bart, & Posner, 1997). Whereas infants rely most strongly on the

orienting network to carry out attentional shifts, adults incorporate

the executive attention system in addition to the potent orienting

signal (Kanske, Heissler, Schönfelder, Bongers, & Wessa, 2011). Sci-

entists are unsure, however, when the precise shift from orienting

to executive control occurs. Studies report the presence of rudi-

mentary forms of control through executive attention in the form

of cautious approach to novel stimuli (Sheese, Rothbart, Posner,

White, & Fraundorf, 2008) and behavioral inhibition during conﬂict

at 40 months of age (Jones, Rothbart, & Posner, 2003). By three to

4 years of age, children recognize errors and begin to display phys-

ical control strategies to inhibit inappropriate responses, although

verbal self-regulation of behavior tends to manifest later in life

(Jones et al., 2003). The gradual development of executive control

in children foreshadows its eventual control over behavior,

although the stage for this transfer of control between the orient-

ing and executive attention networks remains elusive.

The overwhelming tendency of infants to attend to novel stim-

uli in their external environment may serve an evolutionary pur-

pose and simultaneously facilitate the development of executive

attention (Posner & Rothbart, 2011). Whereas children – and cer-

tainly infants – are not expected to make executive decisions in

daily life, adults require a strong command of executive function

to thrive in society. Dependence on the rapidly-maturing orienting

network during early life allows infants to explore their surround-

ings and become acquainted with their new environment. Activa-

tion of the orienting network may also play a key role in the

maturation of the executive network through their complementary

S. Rabipour, A. Raz/ Brain and Cognition 79 (2012) 159–179 161

Author's personal copy

activation in response to presentation of novel stimuli (Posner

et al., 2011). In this fashion, caregiver interactions may promote

self-regulatory processing through regular activation of the execu-

tive network.

The control of emotion and behavior may occur through altered

planes of consciousness such as hypnosis. Scientists recognize that

children are considerably more hypnotizable than adults (Kohen &

Olness, 2011). This observation may arise from a natural tendency

to delegate control to the orienting network of attention, where an

external source – the child’s caregiver, for example – becomes the

source upon which children depend to regulate their behaviors and

emotions. Similarly, the hypnotic state promotes an external

source of control – this time, by the hypnotist. In such a way, the

hypnotic state may promote an increased reliance on the orienting

system for behavioral control, rather than the more commonly

used executive system (Posner & Rothbart, 2011). In adults, who

presumably have fully-developed attention systems, hypnosis af-

fords the opportunity to achieve different states of awareness, to

experience emotional realizations, and to perform neural computa-

tions that may otherwise have been difﬁcult to achieve. Highly

hypnotizable adults, for example, demonstrate elimination of con-

ﬂict-related interference on the Stroop task after receiving post-

hypnotic suggestion (Raz, 2004). Altered mental states may

therefore induce differential control over attentional networks

and may prove important for modulating behavior and emotion.

3. Origins and evolution of brain training

Whereas various cultural practices have inﬂuenced states of

attention for centuries, the implications of altered mental states

on cognitive function were sparsely documented before the late

20th century (Jevning, Wallace, & Beidebach, 1992). Studies in

the 1960s and 1970s on relaxation therapy and early forms of AT

were among the ﬁrst research efforts leading to modern behavioral

modiﬁcation paradigms (Douglas, Parry, Marton, & Garson, 1976;

Paul, 1969; Pressley, 1979). This era of research witnessed neuro-

psychological AT, which initially aimed to maximize the functional

independence and adjustment of individuals with brain damage

(Park & Ingles, 2001). The learning model of recovery (Stuss, Wino-

cur, & Robertson, 1999) triggered theories relating experience,

practice, and environment to the restoration of impaired capaci-

ties, substantiating the use of AT-like programs for cognitive reha-

bilitation. Following an early description concerning the

therapeutic value of self-monitoring and self-control (Kanfer,

1970), a vast literature has emerged regarding improving self-con-

trol in children, a population known to be ill-equipped at maintain-

ing composure in situations that may provoke inappropriate

behavior (Pressley, 1979). The potential to improve self-control

in children prompted scientists to explore these techniques as

non-pharmaceutical treatment alternatives for children with im-

pulse-control impairments. A program aiming to improve inhibi-

tory control in hyperactive children (Douglas et al., 1976)

included self-reinforcement strategies as well as verbalization

techniques. After teaching children to cope more effectively and

independently when faced with cognitive problems in social and

academic situations, the program facilitated signiﬁcant improve-

ments in performance on standardized intelligence tests. Following

such reports, scientists began to appreciate the implications of

training behavioral control in children.

Research has increasingly focused on training the attention sys-

tems as a means of altering behavior. Speciﬁc emphasis on AT orig-

inated with Attention Process Training, a cognitive rehabilitation

method through which scientists trained individuals with neuro-

logical impairments to employ speciﬁc subtypes of attention

(Tamm et al., 2008). In one promising study, individuals suffering

from brain injury showed signiﬁcant improvements in attentional

processing which lasted as long as 8 months following training

(Sohlberg & Mateer, 1987). In another study, patients with unilat-

eral neglect verbally regulated the sustained-attention network by

engaging in an analogous AT program (Robertson, Tegner, Tham,

Lo, & Nimmosmith, 1995) and displayed improvements in un-

trained tasks of sustained attention and neglect after the 5-h train-

ing period. These studies corroborate the use of targeted AT in

individuals with speciﬁc functional deﬁcits in their attention net-

works. In the spirit of rehabilitation, Benedict et al. (1994) created

a 15-h program to remediate the attentional ability of schizo-

phrenic patients using tasks aimed at increasing information pro-

cessing capacity. Although the schizophrenic population

improved performance on trained tasks, observed enhancements

in attention remained below the attentional baseline of controls

(Benedict et al., 1994). A later study, however, reported that

schizophrenic individuals with comparable baseline measures as

controls improved in vigilance, distractibility, and psychiatric sta-

tus following 18 AT sessions (Medalia, Aluma, Tryon, & Merriam,

1998). Research on AT branched out to target a variety of atten-

tion-based disorders. For example, studies in autistic children re-

ported improved attentional capacity that generalized to

untrained attention tasks as a result of training on joint-attention

tasks (Whalen & Schreibman, 2003). A study examining the 8-h

Pay Attention! program (Kerns, Eso, & Thomson, 1999) found

improvements in the attentive abilities and academic efﬁciency

of children with ADHD. Research efforts have rapidly expanded

the implementation of AT and similar variants to restore speciﬁc

deﬁcits in executive function and supplement these processes in

typically-developing individuals. One innovative attempt modiﬁed

a program used to train monkeys for space travel and created a

promising AT program for children. Following 5 days of training,

the study reported signiﬁcant improvements in performance of

both 4- and 6-year-old participants on tests of attention and intel-

ligence (Rueda, Rothbart, et al., 2005). In addition, electrophysio-

logical recordings demonstrated maturation of neural activation

patterns associated with the executive attention network to more

adult-like signals, including increased amplitude of the electroen-

cephalographic (EEG) N2 component. The study additionally dem-

onstrated an association between stronger effortful control,

decreased extraversion, and the long allele of the DAT1 dopamine

transporter gene. Thus, training programs that target attention ap-

pear to produce measurable structural and functional changes in

the brain.

4. Culture, lifestyle, and brain training practices

Brain training has signiﬁcantly impacted mainstream society.

From claims of improving the negative symptoms of psychopathol-

ogies and neurological impairments to assertions of signiﬁcantly

boosting cognitive skills among the healthy, commercialized soft-

ware and interactive programs are increasingly capturing the

interest of parents, educators, students, and clinicians (see Tables

1 and 2). Tutoring services (e.g., (Kumon North America, 2011; Syl-

van Learning, 2011)) entice parents looking to enhance the aca-

demic success of their children. While some practices appear to

produce measurable improvements in their target population, oth-

ers lack scientiﬁc rigor behind their claims. Here, we discuss the

data surrounding select brain training programs and techniques

in randomized-controlled studies, unless otherwise indicated.

4.1. Computerized training

Computerized cognitive exercises are among the most popular

forms of brain training. In a controlled study assessing the effects

162 S. Rabipour, A. Raz/ Brain and Cognition 79 (2012) 159–179

Author's personal copy

Table 1

A list of select commercial software aiming to enhance or rehabilitate speciﬁc cognitive skills in health and pathology.

Company (website) Product name Product type (as speciﬁed on website) Target population Scientiﬁcally published evaluations

BrainMaster Technologies, Inc.

(www.brainmaster.com/)

BrainMaster –

Neurofeedback

Systems

Neurofeedback training Individuals of all ages Martin and Johnson (2006)

Brain Train (braintrain.com/) Captain’s Log,

SoundSmart,

SmartDriver

Cognitive training Individuals of all ages with ADHD,

head injuries, Learning Disabilities,

schizophrenia, and other cognitive

impairments

Angelakis, Lubar, Stathopoulou, and Kounios, (2004) See

also: www.braintrain.com/main/

ivaplus_research_bibliography.htm www.braintrain.com/

main/cognitive_training_research.htm

TNT Reading

SmartMind 2

Cogmed (www.cogmed.com) Cogmed JM WM training for children and adults with attention

deﬁcits, learning disorders, brain injury or stroke, and

adults experiencing ‘‘information overload’’ or the

natural effects of aging

Ages 4–6 See: www.cogmed.com/references

Cogmed RM Ages 7 and up

Cogmed QM Adults

Cogniﬁt (www.cogniﬁt.com) Individualized

Training

System

Cognitive training Individuals of all ages See: www.cogniﬁt.com/science/scientiﬁc-validation

HAPPYneuron (www.happy-neuron.com/) Various games Exercising memory, attention, language, visual-spatial

and executive function skills

Individuals of all ages Croisile (2006)

Lumosity (www.lumosity.com/) Various games Exercising memory, attention, processing speed, and

problem-solving skills

Individuals of all ages Kesler, Lacayo, and Jo (2010)

MindHabits, Inc. (www.mindhabits.com/) MindHabits Exercises to decrease stress and improve conﬁdence Individuals of all ages Dandeneau and Baldwin (2004)

Nintendo (www.brainage.com) BrainAge Training with math- and literature-related activities Individuals of all ages

Posit Science (www.positscience.com) Brain Fitness Auditory training Older adults See: www.positscience.com/science/proven-in-labs

InSight Visual training

Drive Sharp Cognitive training for driving skills

Scientiﬁc Learning Corporation

(www.scilearn.com)

Fast ForWord Language and reading training – adjuncts to classroom

material

Kindergarten – grade 12 students Merzenich et al. (1996) and Fey et al. (2010)

Reading

Assistant

Children and adults wishing to build

vocabulary, ﬂuency and

comprehension.

Timocco (site.timocco.com) Growing with

Timocco

Training motor and cognitive skills Children with cerebral palsy, ADHD,

Developmental Coordination

Disorder, and Learning Disabilities

Unique Logic and Technology

(www.playattention.com)

Play Attention Attention training, memory training, cognitive skill

training, social skills training, motor skills training,

behavior shaping

Children with ADHD

Your Baby Can, LLC.

(www.yourbabycanread.com)

Your Baby Can

Read

Language training Infants

S. Rabipour, A. Raz/ Brain and Cognition 79 (2012) 159–179 163

Author's personal copy

of computerized AT and computer-assisted instruction (Rabiner,

Murray, Skinner, & Malone, 2010), children with attentional difﬁ-

culties improved in measures of attention, with more severe

symptoms showing larger improvements. In another study using

games that activate all three attention networks, children with

ADHD improved in academic skills and decreased ADHD symp-

tomatology, compared to controls (Shalev, Tsal, & Mevorach,

2007).

While the effectiveness of many commercial brain training

products is questionable, evidence suggests that some programs

facilitate marked improvements in cognitive function. One product

repeatedly demonstrated to improve WM capacity in both children

and adults is Cogmed, which entails training on WM tasks for

5 days per week over a period of 5–6 weeks. Using this software,

children with ADHD as well as healthy adults appear to improve

in measures of WM as a result of training (Klingberg, 2007; Kling-

berg et al., 2005).

Another widely used program is the Fast ForWord-Language

(FFW-L) software (Scientiﬁc Learning Corporation, 2011), adver-

tised to increase brain ﬁtness, accelerate learning, and improve

test scores for children (Semrud-Clikeman & Ellison, 2009). Exper-

iments without a proper control group included tasks of percep-

tual identiﬁcation and phonetic element recognition (Merzenich

et al., 1996). After training for 19–28 sessions of 20 min over a per-

iod of 4 weeks, children with language-based learning impair-

ments signiﬁcantly improved in auditory perception. Thousands

of public school districts in the United States incorporate the

FFW-L program into their curricula, and a large number of children

across North America use the product for both scholastic and ther-

apeutic purposes (Scientiﬁc Learning Corporation, 2011). Reports

published outside the peer-review scientiﬁc system suggest that

this program enables educational beneﬁts following repeated

practice (Schultz Center for Teaching, 2009). A recent study, fur-

thermore, demonstrated that children taking part in either the

FFW-L program or a narrative-based language intervention im-

proved on time-related effects of narrative measure and non-word

repetition (Fey, Finestack, Gajewski, Popescu, & Lewine, 2010). De-

spite these results, the participants did not display any signiﬁcant

inter-group variability in beneﬁts, suggesting that the FFW-L pro-

gram scarcely holds superior beneﬁts to conventional language

interventions (Fey et al., 2010). Hence, while FFW-L appears to

produce training-related gains in temporal processing of informa-

tion related to language development, the program hardly fosters

signiﬁcant improvements in language and reading ability. Reports

show, however, that training with FFW-L alongside a coach in-

creased neural activation in regions associated with selective audi-

tory attention – including the ACC – in children with speciﬁc

language impairment during language listening tasks, compared

to typically developing children who received no training (Stevens,

Fanning, Coch, Sanders, & Neville, 2008). These ﬁndings also ex-

tended to typically developing children, although to a lesser ex-

tents. Studies therefore suggest that the FFW-L program

improves auditory perception of stimulus tones and may indirectly

exercise executive attention.

4.1.1. Neurofeedback training

Neurofeedback, also called EEG biofeedback, represents another

computerized technique that appears to hold advantages for spe-

ciﬁc populations. This method entails training individuals to ac-

tively control and change their neural activation patterns by

viewing the brainwaves they emit a few milliseconds after they oc-

cur (Angelakis et al., 2007; Hammond, 2006). Administered in re-

search and clinical endeavors since the 1960s, neurofeedback

converts EEG signals from speciﬁc cortical areas to visual or audi-

tory representations that participants receive and subsequently at-

tempt to regulate through training (Congedo, Lubar, & Joffe, 2004).

Table 2

A list of select programs aiming to enhance speciﬁc skills related to academic performance in children.

Program name (website) Description Scientiﬁcally published evaluations

Arrowsmith School

(www.arrowsmithschool.org)

Cognitive exercises to improve learning dysfunctions that impact learning and social skills

Brain Gym International

(www.braingym.org)

Speciﬁc set of movements aiming to improve concentration and focus, memory, reading, writing, math, test-taking, physical

coordination, relationships, self-responsibility, organization skills, attitude

Center for Applied Special

Technology (www.cast.org)

Universal Design for Learning program that includes principles for curriculum development to provide equal opportunities to learn

for all individuals

See: http://www.cast.org/research/index.html

Kumon Learning Centers

(www.kumon.com)

Math and reading enrichment programs for children

Strategic Learning Centre

(www.strategiclearning.ca)

One-on-one teaching center to help children with learning disability, ADHD, dyslexia become better and more conﬁdent learners

Sylvan Learning

(tutoring.sylvanlearning.com)

Tutoring in various academic subjects for children

Tools of the Mind

(www.toolsofthemind.org)

Preschool and kindergarten curricula to improve self-regulation and executive function See: http://www.mscd.edu/extendedcampus/

toolsofthemind/about/effectiveness.shtml

University City Children’s Center

(uccc.org)

Early care and education system for values & character development, psychodynamic development, early literacy development

164 S. Rabipour, A. Raz/ Brain and Cognition 79 (2012) 159–179

Author's personal copy

More recently, neurofeedback systems leverage the increased spa-

tial precision of fMRI technology (deCharms, 2008).

Advertising to improve mental functioning and increase aware-

ness of brain states, neurofeedback companies (e.g., (BrainMaster

Technologies, 2009)) offer their products to individuals seeking

to sharpen their cognitive skills. Studies suggest that this tech-

nique may be beneﬁcial for enhancing cognitive function in elderly

populations (Angelakis et al., 2007) and in improving symptoms

associated with epilepsy (Kotchoubey et al., 1999; Tan et al.,

2009), substance abuse (Sokhadze, Cannon, & Trudeau, 2008),

and a number of psychiatric conditions (Heinrich, Gevensleben, &

Strehl, 2007). Neurofeedback appears particularly promising for

individuals diagnosed with ADHD. After training with this technol-

ogy, children with ADHD appear to increase scores on tests of intel-

ligence and continuous performance, improve cooperation and

school work in the classroom and demonstrate better attentional

and behavioral control (Monastra, 2005). Such beneﬁts reportedly

endure, in some cases, for several years following the intervention.

Similar reviews of randomized controlled trials in children with

ADHD (Fox, Tharp, & Fox, 2005; Monastra, 2005) report mixed

ﬁndings; while some children showed little or no training effects,

others demonstrated enhanced intelligence and signiﬁcant

improvements in attention, hyperactivity, and impulsivity. Studies

comparing neurofeedback to medication support such training as a

serious contender for non-pharmaceutical ADHD treatment. A 12-

week, controlled trial comparing neurofeedback with methylphe-

nidate treatment suggested that neurofeedback leads to similar

behavioral changes, with decreased parent and teacher reports of

ADHD-related symptoms in both groups (Fuchs, Birbaumer, Lut-

zenberger, Gruzelier, & Kaiser, 2003). Another study found no sig-

niﬁcant difference in either treatment effects or clinical

improvement of individuals with ADHD after 20 sessions of neuro-

feedback training or use of stimulant medication (Rossiter & LaVa-

qe, 1995). The sustainability of neurofeedback effects, however,

remains questionable and may vary on a case-by-case basis. Simi-

lar to other forms of computerized training, long-term therapy

using neurofeedback technology may prove effective for improving

disease-related symptoms of developmental psychopathologies,

especially when administered at childhood. Studies therefore pro-

vide compelling evidence for the potential of such training as a

non-pharmacological treatment alternative for a variety of neuro-

logical disorders.

4.2. Applied attention as school-based interventions

Student attentiveness is essential to a positive and productive

classroom dynamic and plays a fundamental role in shaping scho-

lastic performance (Duncan et al., 2008). Assessments of learning

approaches reveal that child attentiveness is positively associated

with academic competence and achievement, as well as relations

with both teachers and peers (Li-Grining, Votruba-Drzal, Maldona-

do-Carreno, & Haas, 2010). Variability in attentiveness may ac-

count for differences in child learning speed or the amount of

information children can extract from an event (Ruff & Rothbart,

1996). Studies on children with ADHD, moreover, reveal comorbid-

ities between the disorder and a number of learning difﬁculties,

especially pertaining to reading ability (Carlson, Tamm, & Gaub,

1997; Willcutt, Pennington, Olson, Chhabildas, & Hulslander,

2005; Willcutt, Pennington, Olson, & DeFries, 2007). An uncon-

trolled European study in 3 cohorts of children with ADHD not only

supported the association between scholastic impairment and

ADHD symptomatology, but reported a 2- to 10-fold increase in

impairments of reading, writing, and mathematics in children with

symptoms related more strongly to inattention (Rodriguez et al.,

2007). Thus, abounding evidence presents attention as an integral

component in the academic success of children.

Theories surrounding school readiness stipulate that children

must attain social–emotional competencies by practicing effortful

control in order to grasp the lessons learned in both social and aca-

demic settings (Liew, 2011). With fundamental roles during social

interactions, effortful control and emotional regulation draw upon

executive function to exert attentional and inhibitory control and

help children develop inter-personal relationships (Kochanska

et al., 2000; Liew, 2011; Ruff & Rothbart, 1996). At the start of

grade school, children exhibiting strong effortful control are more

likely to express social competence and have fewer behavior prob-

lems, whereas those who struggle to control attention and behav-

ior tend to develop impaired relationships with teachers and peers,

and have greater risk of developing academic difﬁculties (Liew,

2011; McClelland et al., 2007). Studies further show that the man-

ifestation of effortful control and other self-regulatory skills in ele-

mentary-age children correlates with higher grades, and may

improve early mathematical and literacy prowess (Liew, 2011).

Likewise, individuals with attention-related disorders such as

ADHD are generally impaired in social, academic, familial, and

occupational areas of life (de Boo & Prins, 2007). As a result,

school-based programs often involve AT to bolster effortful control

and emotional regulation (Kring & Sloan, 2010), critical to success

among peers in academic and other environments involving inter-

personal relations.

School-based interventions may particularly aid children of

lower socio-economic status – a population with marked deﬁcits

in control through executive function (Bierman, Nix, Greenberg,

Blair, Domitrovich, 2008; Hackman & Farah, 2009; Noble, McCand-

liss, & Farah, 2007; Stevens, Lauinger, & Neville, 2009). Programs

such as ‘‘Tools of the Mind’’ (Barnett et al., 2008; Diamond et al.,

2007) and the ‘‘Promoting Alternative Thinking Strategies’’ curric-

ulum, tested in the absence of matched-controls (Kelly, Longbot-

tom, Potts, & Williamson, 2004), for example, appear to decrease

behavioral problems and improve emotional understanding, exec-

utive function, and academic performance in children with disad-

vantaged socio-economic backgrounds. Similarly, studies

assessing the school-based ‘‘Head Start Research-based Develop-

mentally Informed’’ curriculum (Bierman, Domitrovich, et al.,

2008) demonstrate enhanced academic skills as well as improved

behavioral and emotional control in children. With increased

awareness of the importance of attentional processes in academic

and social settings, researchers are beginning to pool more re-

sources into developing effective training programs in schools.

Such programs may particularly beneﬁt disadvantaged children

and minimize their disparities in cognitive ability.

Acquiring proper social skills during childhood is essential for

shaping appropriate behavior and ensuring healthy development

(de Boo & Prins, 2007). Training children to exhibit effective social

skills appears to improve their social knowledge and assertiveness,

and may further generalize to the school setting (McBurnett &

Pﬁffner, 2008). Social skill training may be particularly relevant

for children with impulse-control disorders such as ADHD, who of-

ten experience peer rejection and social isolation due to aggressive

behavior and lack of inhibitory control (DuPaul, McGoey, Eckert, &

VanBrakle, 2001; McBurnett & Pﬁffner, 2008). Although individual

parameters such as extent of play and teaching strategies remain

widely debated in American school districts (Barnett et al., 2008),

social skills training appears to promote constructive peer interac-

tions among children.

4.3. Bilingualism

Contrary to the belief that bilingual education hinders cognitive

ability and dampens intelligence, proﬁciency in two languages ap-

pears to enhance the development of cognitive control systems

relating to attention. Bilinguals develop the capacity to indepen-

S. Rabipour, A. Raz/ Brain and Cognition 79 (2012) 159–179 165

Author's personal copy

dently process two languages, which requires selection of the cor-

rect lexical representations of one language while suppressing the

representations of the other (Costa, Hernández, & Sebastián-Gallés,

2008). Although scientists scarcely understand the mechanisms

underlying this ability, bilingual individuals may employ the exec-

utive attention system to suppress an unwanted linguistic re-

sponse much like inhibition during the Stroop task (Bialystok,

2010; Green, 1998). This process enables control over competing

neural networks and communication in the intended language,

thereby promote development of the underlying neural systems.

Indeed, research reveals that bilingual individuals perform better

at non-verbal problem solving tasks requiring inhibition of irrele-

vant responses and the formation of new conceptual representa-

tions compared to monolinguals (Bialystok & Martin, 2004).

Bilingual individuals, moreover, display quicker response times in

attention-related tasks – including trials involving conﬂict resolu-

tion – as well as more efﬁcient use of their alerting and executive

attention networks (Costa et al., 2008). As early as childhood, bil-

inguals appear to perform better on non-linguistic tasks requiring

attentional control (Bialystok & Majumder, 1998) and develop the

ability to exert selective attentional control earlier than monoling-

uals (Bialystok, 1999). Such advantages of bilingualism grow

increasingly powerful at old age, with research indicating that el-

derly bilinguals have signiﬁcantly greater inhibitory control com-

pared to monolinguals of the same age group (Bialystok, Craik, &

Ryan, 2006). Continuously switching between two languages may

further promote the capacity to maintain two sets of instructions

in mind and select the correct response in a particular situation –

another ability that is stronger in elderly bilingual populations

(Bialystok et al., 2006). Thus, having command of more than one

language appears to enhance executive function similarly to partic-

ipation in training programs. Bilingual education may therefore

represent a favorable tool for the development of executive control

in children and the further strengthening of this system through-

out adulthood.

4.4. Music training

Stemming in part from the widespread ‘‘Mozart effect’’ myth

(Steele, Bass, & Crook, 1999) – which suggests that spatiotemporal

abilities increase after listening to music composed by Mozart –

musical training increasingly captivates the public. Despite the fal-

lacy of the Mozart effect, evidence suggests that musical training

does produce signiﬁcant improvements in faculties such as verbal

memory (Chan, Ho, & Cheung, 1998; Ho, Cheung, & Chan, 2003)

and general intelligence, as demonstrated in children randomly as-

signed to either music training, drama, or no-training controls

(Schellenberg, 2004). Requiring a high degree of repetition, con-

centration, and devotion over many years of continuous practice,

this form of training shares many of the qualities possessed by

more structured cognitive training programs. Furthermore, music

training generates positive emotions, which have been linked with

improved plasticity (Altenmüller, 2009). Following 6 months of

piano keyboard training, children have demonstrated enhanced

spatiotemporal reasoning compared to children receiving private

computer lessons or no training (Rauscher et al., 1997). Studies

also show enhanced development of visuospatial WM ability and

non-verbal reasoning, in addition to increases in child IQ scores

as a result of musical training (Bergman Nutley, 2011). Musicians

have also displayed superior control in certain auditory tasks com-

pared to non-musicians (Bialystok & DePape, 2009). Recent re-

search further links musical proﬁciency to enhanced executive

control during conﬂict-related tasks unrelated to music (Bialystok

& DePape, 2009). Considering the attentional and WM load as well

as the knowledge of speciﬁc acoustic and syntactic rules that music

requires (Kraus & Chandrasekaran, 2010), this association is not

surprising. The widespread interest in musical training as a tool

for general cognitive enhancement therefore appears to have sci-

entiﬁc merit.

Due to the cognitive demands of musical practice, music train-

ing may facilitate changes that enhance the functionality of regions

related to auditory perception as well as executive attention. The

behavioral beneﬁts of music training are accompanied by struc-

tural modiﬁcations within speciﬁc brain regions, as well as changes

in gray matter volume (Gaser & Schlaug, 2003; Munte, Altenmuller,

& Jancke, 2002). In addition to the structural changes, music prac-

tice appears to alter neural activation patterns that underlie audi-

tory discrimination and executive attention. Musicians show more

pronounced neural signals in response to irrelevant sound signals

and can better detect meaningful information such as speech amid

a noisy background (Kraus & Chandrasekaran, 2010). Neuroimag-

ing studies further reveal an association between neural areas re-

lated to WM function and parietal brain regions during sight

reading of musical notes (Bergman Nutley, 2011). Hence, the com-

plex process of learning to play a musical instrument has inﬂu-

ences on neural function and anatomy that cannot be attributed

to pre-existing qualities, and may constitute another promising

form of brain training.

4.5. Physical exercise

Aside from advantages to physical health, exercise appears to

have a beneﬁcial impact on cognitive function, particularly in chil-

dren (Hillman, Erickson, & Kramer, 2008) and elderly individuals

(Colcombe & Kramer, 2003). The relatively recent infatuation with

sedentary lifestyle seen in developed countries creates the prece-

dent of minimal physical activity throughout a typical school or

work day. With childhood obesity on the rise and an increasing

prevalence of weight-related health conditions such as diabetes,

educational and public health campaigns attempt to heighten pub-

lic awareness about the importance of exercise to physical health.

Studies report that as little as 30 min of aerobic exercise per day

signiﬁcantly enhance children’s capacity for creativity and the

capacity to deduce several correct answers in response to a given

question (Tuckman & Hinkle, 1986) – a measure of cognitive ﬂex-

ibility (Diamond & Lee, 2011). Studies further indicate that aerobic

exercise may signiﬁcantly enhance executive function, improve

performance in mathematics, and increase activity in the PFC (Da-

vis et al., 2011). In addition, a meta-analysis of ﬁtness training pro-

grams revealed that ﬁtness programs encompassing aerobic

exercise may enhance executive control and visuospatial ability

in healthy but sedentary elderly adults (Colcombe & Kramer,

2003). The evaluated studies further reported improvements in

all of types of cognitive tasks and following all methods of training,

with combinations of strength and aerobic training producing

greater beneﬁts than aerobic exercise alone. Critics have nonethe-

less pointed out that many ﬁtness training studies do not ade-

quately control for experimenter involvement and, in some cases,

lack control groups altogether (Green & Bavelier, 2008). Therefore,

while aerobic exercise may promote the development of various

cognitive abilities in children and the elderly, proper controls are

necessary to discern the scientiﬁc validity of such claims.

4.6. Interaction with nature

Perhaps surprisingly to fervent believers in circumscribed train-

ing programs, regular interaction with nature appears to facilitate

improvements in cognitive function and behavioral control. Propo-

nents of the beneﬁcial effects of nature strive to increase outdoor

exposure lost to the industrial ideals of modern society, offering

nature retreats, environmental awareness workshops (Charles,

Louv, Bodner, Guns, & Stahl, 2009; Civic Results, 2008), and even

166 S. Rabipour, A. Raz/ Brain and Cognition 79 (2012) 159–179

Author's personal copy

university courses that teach students to harness nature as a con-

text for therapeutic interventions (Naropa University, 2011). Some

academic programs, moreover, educate children outdoors rather

than in traditional classrooms (Denison Pequotstepos Nature Cen-

ter, 2009; Forestry Commission Scotland, 2009) and, according to

teacher reports, appear to improve interpersonal work habits,

classroom behaviors, and engagement with the learning process.

Many of these programs stem from the attention restoration the-

ory, which posits that nature has the capacity to relieve the atten-

tion system of its functional load in order to restore effectiveness in

cognition (Kaplan, 1995b). According to this theory, nature pro-

vides a medium that requires less inhibition of competing stimuli,

giving executive function a chance to rest. Controlled and uncon-

trolled studies suggest, for example, that leisurely outdoor activity

may relieve ADHD symptomatology in children (Taylor & Kuo,

2009; Taylor, Kuo, & Sullivan, 2001). In addition, children who have

greater exposure to nature from their home environments appear

to attain superior attentional control (Wells, 2000) and to react

better in response to stressful life events, experiencing lower psy-

chological distress and higher perceptions of self-worth (Wells &

Evans, 2003). Studies suggest that walking in natural environments

as opposed to urban areas or viewing pictures of nature may im-

prove executive attention (Berman, Jonides, & Kaplan, 2008), and

that having near-home views of nature may improve concentra-

tion, inhibition, and self-discipline (Taylor, Kuo, & Sullivan, 2002).

Interacting with natural environments may therefore enable more

efﬁcient executive function and beneﬁt attention as well as self-

control.

4.7. Meditation training

Often regarded as methods of relaxation and mental clarity

alone, meditative practices aim to train attention and awareness

as a means of increasing control over mental processes (Walsh &

Shapiro, 2006). Meditation training programs often include one

or a combination of focused attention and open monitoring, two

common Buddhist techniques that target speciﬁc cognitive pro-

cesses (Slagter, Davidson, & Lutz, 2011). Focused attention medita-

tion involves voluntarily sustaining focus on a given object,

whereas open monitoring consists of non-reactively monitoring

the content of an ongoing experience, to become aware of the nat-

ure of associated cognitive or emotional patterns (Lutz, Slagter,

Dunne, & Davidson, 2008; Raffone & Srinivasan, 2010; Slagter

et al., 2011). Mindfulness is another common contemplative tech-

nique related to open monitoring (Raffone & Srinivasan, 2010) and

constitutes one of the most widely studied meditative practices

(Walsh & Shapiro, 2006). One deﬁnition describes mindfulness as

the practice of purposefully and objectively attending to thoughts,

emotions, and daily actions (Allen, Blashki, Gullone, & Melbourne-

Acad-Mindfulness-Interes, 2006; Tang & Posner, 2009). Meditation

therefore represents another technique that fosters the develop-

ment of cognitive and attentional capacity.

Studies have shown that training with open monitoring or fo-

cused attention can trigger neural processes underlying the execu-

tive attention system. Reports of activity in the ACC and in both the

medial and lateral areas of the PFC (Lutz et al., 2008; Raffone &

Srinivasan, 2010) suggest that meditation training (e.g., practicing

focused attention) improves conﬂict processing as well as emo-

tional- and self-regulation, with experienced meditators showing

increased activation in these areas compared to non-meditators

(Hölzel et al., 2007). In addition, focused attention and open mon-

itoring both associate with neural adaptations such as increased

regional blood ﬂow and glucose metabolism in the PFC and ACC

(Baijal & Gupta, 2008). Accordingly, studies show that meditators

who practice methods of either focused attention or mindfulness

can better sustain their attention (Valentine & Sweet, 1999) and

demonstrate improved performance on a number of conﬂict-re-

lated tasks. These include superior perception during binocular riv-

alry tasks (Lutz et al., 2008), reduced semantic processing required

for lexical decision tasks (Pagnoni, Cekic, & Guo, 2008), decreased

response variability for dichotic listening tasks (Lutz et al., 2009),

and increased mismatch negativity for auditory tones (Raffone &

Srinivasan, 2010). Neuroimaging studies additionally reveal that

regular meditators who practice open monitoring or focused atten-

tion may activate attention-related neural regions more efﬁciently

in response to conﬂict (Kozasa et al., in press). The beneﬁcial effects

of these meditative practices may be sustained throughout aging;

experienced meditators show fewer age-related declines in gray

matter volume of certain neural regions and display higher vol-

umes of several brain regions, including the PFC (Ott, Hölzel, &

Vaitl, 2011). Thus, speciﬁc forms of meditation can invoke activa-

tion of the executive attention system and may thereby improve

its functionality over time.

Recent evidence suggests that mindfulness meditation may en-

hance the neural processes underlying attention and WM. In light

of such ﬁndings, scientists are now considering the clinical impli-

cations of meditation training, particularly for conditions that in-

volve broad aspects of psychological well-being (Chiesa, Calati, &

Serretti, in press). Studies indicate that mindfulness training may

improve cognitive functioning and reduce stress, anxiety, negative

affect, and the symptoms associated with various diseases (Chiesa

et al., in press; Creswell, Way, Eisenberger, & Lieberman, 2007).

Adults and adolescents with ADHD, furthermore, have demon-

strated improvements of behavioral and neurocognitive impair-

ments following a mindfulness group-training program

(Zylowska et al., 2008). This program may have an additional

favorable impact on the development of inhibitory control and

self-regulation. While experience may increase the beneﬁts of

meditation, short-term training also appears to promote observa-

ble effects. A school-based mindfulness program in elementary-

aged children, for example, demonstrated improvements in behav-

ioral regulation and executive function after a mere 8 h of training,

administered over a period of 8 weeks (Flook et al., 2010). By pro-

moting a heightened state of concentration that triggers activity of

the attentional networks, meditative practices such as mindfulness

training may improve behavior (Jha, Krompinger, & Baime, 2007)

and prove useful – at least as ancillary treatment – for individuals

with attention-speciﬁc deﬁcits.

Despite the promise of meditative practices in improving cogni-

tive function, research surrounding this form of training has yet to

unearth optimal protocols and administration strategies that are

most beneﬁcial in various populations (Burke, 2010). A number

of factors contribute to this ambiguity, such as the use of different

scales to measure experimental ﬁndings and the scarce inclusion of

active control groups in studies (Davidson, 2010). An interesting

study addressing this latter issue incorporated sham meditation

as part of the experimental design and reported improvements in

psychological variables such as mood, depression ratings, and fati-

gue, following 3 days of mindfulness training (Zeidan, Johnson,

Gordon, & Goolkasian, 2010). Observed improvements in behavior,

however, may arise as a result of diverse meditative techniques. As

a result, in addition to incorporating active controls, studies exam-

ine combinations of potentially beneﬁcial training techniques with

hopes of creating variants that would induce maximal beneﬁts on

attention. One such variant, a Chinese technique known as integra-

tive body-mind training (IBMT), integrates aspects of several med-

itative practices (Tang & Posner, 2009). In one study, individuals

randomly assigned to practice IBMT for 5 days demonstrated sig-

niﬁcantly better attentional capacity and control over stress com-

pared to individuals who practiced other meditative techniques

during the same period of time (Tang et al., 2007). Furthermore,

a mere 3 h of this training program was enough to induce an

S. Rabipour, A. Raz/ Brain and Cognition 79 (2012) 159–179 167

Author's personal copy

increase in activation of the ACC and improve the self-regulation of

adult participants (Tang et al., 2010). Recently, Tang et al. (2010)

also showed that adults who trained in IBMT for 11 h had a higher

density of cortical white matter, including a region known to con-

nect the ACC with functionally important neural areas. Further re-

search is nonetheless required to properly attribute the different

components of meditative practices to the observed effects on cog-

nitive ability. Future studies may glean more precise information

by adequately controlling for all variables involved in speciﬁc pro-

grams to better parse the training components that promote such

positive outcomes.

4.8. Parenting

One of the strongest inﬂuences on childhood behavior is the

family setting, largely a function of parent or caregiver interactions

with a child. Animal studies attest to the importance of parenting,

with early monkey studies (Harlow & Mears, 1979) identifying the

primary purpose of nursing as a way to ensure intimate body con-

tact between mother and infant – essential for establishing sensory

stimulation that facilitates neural development (Illes & Sahakian,

2011). Rodent studies further show that maternal behaviors can re-

duce neuroendocrine response to stress (Liu et al., 1997) and even

alter the genetic expression underlying neuroendocrine and behav-

ioral stress responses (Weaver et al., 2004). Maternal behavior also

appears to promote synaptic development in the hippocampus, a

structure associated with memory, and may enhance spatial learn-

ing and memory in rats (Liu, Diorio, Day, Francis, & Meaney, 2000).

Such studies attest to the importance of parenting for the proper

development of cognitive ability and emotional stability.

The challenges of caring for children in a typical working-class

family increase for parents who have little support or assistance.

Studies suggest that disturbed family environments may contrib-

ute to the development of childhood psychopathologies. A review

of ADHD neurobiology, for example, identiﬁed six family-related

factors that signiﬁcantly correlated with the development of child-

hood mental disturbances, including severe marital discord, low

social class, large family size, paternal criminality, maternal mental

disorder, and foster placement (Faraone & Biederman, 1998). In

light of such reports, a number of therapeutic programs target par-

ents and families as a whole, and sometimes include supplemental

interventions for the children. One such program, the Community

Parent Education method, implements a 10-week parent education

program with concurrent social skill building for children and has

gathered evidence showing improved parenting skills and fewer

child behavior problems (Tamm et al., 2008). Parent training also

appears to improve inattention, over-activity, conduct problems,

compliance, and aggression in children (Wells, 2008). Following a

12-session mindfulness training program for mothers with no fo-

cus on behavior management, mother–child interactions improved

and child compliance increased (Singh et al., 2010). Other studies

suggest, moreover, that developing effortful control in children

may offset the effects of negative or neglectful parenting (Liew,

2011). These ﬁndings highlight the importance of parent–child

relationships and of using proper parenting methods to guide

behavioral development in children.

The added difﬁculty of raising children with developmental

psychopathologies often leads parents to resort to unjust or inef-

fective punitive measures. For this reason, a central feature of sev-

eral parent training approaches includes proper allocation of

attention and appropriate management of disorderly behavior.

One study of a program for ADHD-related behavior management

(Barkley, 1998) revealed that positive attention may in itself in-

duce greater compliance in younger children and further illus-

trated the importance of attending to child behavior in the

school setting in addition to other public environments. Expan-

sions to this program show beneﬁts of parent relaxation training

as well as stress-management (Wells, 2008). More recent parent

training paradigms have tested the effects of incorporating modern

technology or interactive components into the standard program.

Adding a sport or recreational component to a father-training pro-

gram, for example, may enhance the typical beneﬁts of these pro-

grams by not only improving behavior-related symptomatology

and peer-interactions, but by further increasing attendance and

satisfaction with the program, as well as homework compliance

(Fabiano et al., 2009). Similarly, an evaluation of a program imple-

menting internet-based training for mothers with infants at risk for

poor social–emotional development found increases in mother–

child interactions in addition to marginal improvements in impair-

ments associated with interactive behavior and depressive symp-

tomatology (Baggett et al., 2010). These studies indicate that,

through training, parents can learn to interact positively with their

children, thereby improving parent–child relationships and help-

ing parents teach children proper standards of behavior.

5. The effectiveness of training practices: examining the

evidence

In this section, we provide a critical examination of the impact

of cognitive training in both healthy and pathological individuals.

We investigate the generalizability of training and whether speciﬁc

exercise can transfer to other domains of cognitive function.

5.1. Generalizability and transferability: improving overall function or

just speciﬁc skills?

As brain training rises in popularity, mounting skepticism chal-

lenges the effectiveness of such programs on cognitive ability.

While brain training programs may improve performance on a spe-

ciﬁc subset of skills or tasks, the beneﬁts may not generalize to

other domains. One such example is the Bates Method, a behav-

ioral approach to improving visual acuity by altering attentional

states through practices such as hypnotherapy (Marg, 1952; Raz,

Marinoff, Zephrani, Schweizer, & Posner, 2004). Once considered

a groundbreaking technique for visual correction, the Bates Meth-

od was disproved by studies suggesting that attention can only

inﬂuence the priority or processing preference of the fovea, which

can impact parameters such as visual detection or reaction time

without improving visual acuity per se (Raz et al., 2004). Similarly,

a number of reviews have evaluated the quality and robustness of

training effects in an effort to determine the transferability of dif-

ferent brain training methods to other cognitive or behavioral

functions. Recent evidence has led many to believe that perhaps

they should not expect much from these methods. A group of Brit-

ish scientists, in collaboration with the British Broadcasting Corpo-

ration (BBC) television program ‘‘Bang Goes the Theory’’, stunned

participants and viewers of the program with the allegation that

computerized brain training does not beneﬁt general cognitive

ability (Owen et al., 2010). Employing the largest sample size ever

used in cognitive-training research, the study reported no signiﬁ-

cant increase in general cognitive performance following 6-weeks

of online training in WM tasks, apart from improvement in the

practiced tasks. In response to this negative outcome, countless

media articles suggested that brain training likely represents

wasted effort. Notwithstanding this gross generalization, largely

circulated by public media reports, a close examination of the

parameters used in the study reveals several limitations. Weak

environmental controls, insufﬁcient training duration, and a ques-

tionable study population limit possible conclusions. Furthermore,

the study involved a sample of healthy individuals, although re-

search suggests that individuals with lower baseline scores may

168 S. Rabipour, A. Raz/ Brain and Cognition 79 (2012) 159–179

Author's personal copy

beneﬁt more from such training. This study nonetheless accentu-

ates the need for more properly controlled studies, thorough anal-

ysis of the available data, and careful interpretation of results, to

determine the capacity for transfer of computerized brain training

programs.

The question of transferability is perhaps most relevant for

commercial products. The Cogmed program – advertised as effec-

tive in both healthy and pathological populations, both young

and old – is among the most thoroughly studied of these products.

In an inaugural study, children with ADHD and healthy adults who

trained with components of the Cogmed program showed general-

ized improvements in cognitive control and general ﬂuid intelli-

gence, with additional reduction in symptoms related to ADHD

in the pathological population (Klingberg, Forssberg, & Westerberg,

2002). The ﬁndings were later replicated in healthy adults (Olesen,

Westerberg, & Klingberg, 2004; Westerberg & Klingberg, 2007),

although both studies were unclear about the possibility of

improvements due to test–retest effects (Shipstead, Redick, &

Engle, 2010). A subsequent study in children with ADHD demon-

strated signiﬁcant improvements on measures of attention and

intelligence compared to controls, which persisted 3 months after

completing 25 sessions of visuo-spatial, backward-digit, and let-

ter-span tasks from the Cogmed program (Klingberg et al., 2005).

Notably, however, children randomly assigned to the control group

displayed increased scores at the 3-month evaluation period,

which may indicate insufﬁcient level of difﬁculty in the testing

measures used (Shipstead et al., 2010). Furthermore, parent – but

not teacher – reports indicated reductions in ADHD symptoms

(Klingberg et al., 2005). Following 20 sessions of training with Cog-

med, children with low WM capacity showed enhanced WM per-

formance that persisted for 6 months, relative to controls

(Holmes, Gathercole, & Dunning, 2009). Although this study ap-

peared to demonstrate generalizability to cognitive domains unre-

lated to the training, the participants did not improve on measures

of intelligence, reading, or mathematical reasoning, and follow-up

measures did not include comparisons to the control group (Ship-

stead et al., 2010). A replication of Klingberg et al. (2005) showed

that, compared to no-treatment controls, adolescents with ADHD

displayed improvements in inattentiveness and executive function,

as well as symptoms related to the disorder, as indexed by parent

reports (Beck, Hanson, Puffenberger, Benninger, & Benninger,

2010). These effects persisted at the 4-month follow-up assess-

ment, and were mirrored by near-signiﬁcant ﬁndings based on tea-

cher reports. Studies therefore suggest that certain commercial

brain training products may improve speciﬁc skills, although evi-

dence remains scarce regarding the transferability of training to

unrelated domains of cognitive function.

While computerized programs show promise along the short

term, studies often carry a number of caveats that restrict possible

interpretations of the experimental ﬁndings, and scarcely demon-

strate sustainability of more than several months. In children with

ADHD, for example, a program exercising verbal and visuo-spatial

short-term memory in addition to WM facilitated improvements

on measures of the trained abilities that lasted 6 months (Holmes

et al., 2010). Limitations of this study, however, include a lack of

control groups, direct ADHD measures, and transfer to IQ scores

(Shipstead et al., 2010). The transfer effects of brain training are

also inconsistent in healthy populations. In one study, participants

signiﬁcantly improved performance on the Stroop task in addition

to reading comprehension as a result of a 4-week WM training pro-

gram, but did not display increases in general ﬂuid intelligence or

in spatial reasoning (Chein & Morrison, 2010b). A different study

reported that, after participating in a WM-training program, pre-

school children exhibited better performance on attentional tasks

requiring monitoring, but did not show any improvements on

Stroop-like, inhibitory, or problem-solving tasks (Thorell, Lindq-

vist, Bergman Nutley, Bohlin, & Klingberg, 2009). After participat-

ing in 20 sessions of an adapted complex WM span task over 4-

weeks, healthy individuals improved on measures of temporary

memory and verbal reasoning and further increased their cognitive

control, as indexed by their performance on the Stroop task (Chein

& Morrison, 2010a). The participants also improved their reading

comprehension, which correlated with increases in spatial WM.

These ﬁndings suggest that this novel training paradigm may im-

prove certain aspects of general attentional mechanisms, such as

the management of information maintenance in concordance with

other neural processes (Chein & Morrison, 2010a). Such transfer of

WM training to untrained attention and memory tasks also ap-

pears in older adults (Berry et al., 2010). Although studies often re-

port promising ﬁndings, researchers have yet to reach a consensus

regarding suitable control groups, accurate measures of parame-

ters such as sustainability, and outcomes that simply result from

participation in a training program. As a result of such discrepan-

cies in experimental parameters and measurement tools, compar-

isons between studies that reportedly measure the same cognitive

or behavioral construct are difﬁcult to establish.

5.2. Effectiveness without efﬁcacy: ulterior beneﬁts of brain training

The advantages of brain training may reside in the nuances of

effectiveness rather than efﬁcacy. In clinical terms, efﬁcacy refers

to the ability of a substance, usually a pharmaceutical agent, to

produce a desired effect through a particular mechanism of action.

Effectiveness, on the other hand, refers to the practical use of a sub-

stance. Research has often revealed cases of efﬁcacy without effec-

tiveness (Glasgow, Lichtenstein, & Marcus, 2003); pharmaceutical

agents, for example, sometimes produce side-effects that are more

noxious than the condition they are meant to treat, thereby render-

ing them ineffective. In contrast, evidence also suggests that, in

some cases, a substance may prove effective without being efﬁca-

cious. Such phenomena may occur via the placebo effect, or posi-

tive effects associated with sham or irrelevant treatment

(Benedetti, Mayberg, Wager, Stohler, & Zubieta, 2005). Similarly,

although the improvements observed as a result of brain training

may be induced due to reasons other than the training itself, such

interventions may still be effective through an analogous placebo-

like effect. The variety of programs that improve cognition and

behavior, coupled with reports of little transferability of brain

training, leads to speculation that brain training may not contain

a speciﬁc mechanism of action. The act of providing treatment

for a particular condition, however, may in itself decrease the asso-

ciated symptoms (Kermen, Hickner, Brody, & Hasham, 2010; Til-

burt, Emanuel, Kaptchuk, Curlin, & Miller, 2008). Improvements

in cognitive performance may also occur as a result of motivational

factors, including active interest in individual performance (Green

& Bavelier, 2008). Brain training may therefore represent an effec-

tive intervention or potential treatment for clinical populations

even if research deems the speciﬁc mechanism tenuous.

6. Who can beneﬁt from brain training?

Brain training programs may impact an assortment of neurolog-

ical states. From the healthy to the neurologically impaired, pro-

grams aim to enhance or rehabilitate cognitive function in both

young and old. In this section, we examine evidence for the bene-

ﬁts of brain training programs in various populations.

6.1. Brain training in typical development

Evidence indicates that brain training can enhance healthy

neural development. Unlike pathological populations, typically

S. Rabipour, A. Raz/ Brain and Cognition 79 (2012) 159–179 169

Author's personal copy

developing children and adults train the brain to fortify skills al-

ready acquired in an effort to distinguish their abilities among

peers and thrive in an increasingly competitive society. While

the effects are often subtle, such training may sometimes yield dra-

matic results. One particularly effective technique comprises strat-

egy training, which involves learning effective approaches to

encode, maintain, and retrieve information from WM (Chein &

Morrison, 2010a). One study reported the memorization of 80 dig-

its after learning the strategy of grouping numbers into running

times (Ericsson & Chase, 1982). A more recent example of strategy

training is the story of Joshua Foer, the 2006 USA Memory Cham-

pion (Foer, 2011). A freelance journalist with no previous experi-

ence in competitive memorizing, Foer not only defeated his

competitors – experienced mnemonists – in the championship,

but also broke the world record in the speed card category. His

trick consisted of an age-old memorization technique by which

he trained himself to associate tedious facts, difﬁcult for the hu-

man brain to remember, with eccentric images that an individual

is unlikely to forget. Neuroimaging studies suggest that competi-

tive mnemonists and high-rankers of World Memory Champion-

ships use similar stratagems during performance of WM and

long-term verbal memory tasks (Maguire, Valentine, Wilding, &

Kapur, 2003). Despite having typical brain morphology compared

to controls, this population displays increased regional activation

of areas associated with spatial memory and navigation, which

may underlie the learning of route strategies to recall long lists

of items (Maguire et al., 2003). Therefore, typically developing

individuals may also display enormous improvements in perfor-

mance following speciﬁc types of training.

6.2. Training the aging brain

With mounting evidence for cognitive decline in the elderly,

brain training programs for geriatric populations seem increasingly

relevant and enticing. In 2005, a global prevalence study estimated

that 24 million individuals were living with dementia, of whom 3–

4 million were residing in North America, and that this number

would double every 20 years (Ferri et al., 2005). While the leading

cause of age-related dementia is Alzheimer’s disease (Ferri et al.,

2005), studies have identiﬁed a number of risk factors associated

with impaired cognitive ability including decreased physical activ-

ity (Laurin, Verreault, Lindsay, MacPherson, & Rockwood, 2001;

Yaffe, Barnes, Nevitt, Lui, & Covinsky, 2001), lack of education

(Callahan et al., 1996), health conditions such as diabetes and

hypertension (Kuo et al., 2005), and the presence of certain patho-

logical (McKeith et al., 1996) and genetic traits (Duff et al., 1996).

Reports of delayed cognitive decline as a result of brain training

have propelled a market of products aimed at preventing or even

reversing the effects of age on cognition. These programs, often

administered through computerized media or video game con-

soles, carry varying degrees of scientiﬁc validity. The popular Bra-

inAge program (Nintendo, 2007) is one prominent example among

the myriad of commercialized products that holds little scientiﬁc

evidence of efﬁcacy. A recent study using this game console, more-

over, suggests that elderly individuals work more efﬁciently using

a paper-and-pencil interface, although decreased technological

sophistication appears to evoke lower levels of arousal (Nacke,

Nacke, & Lindley, 2009). On the other hand, certain training tech-

niques have shown promise for the delay or prevention of neuro-

degenerative diseases. Animal studies indicate that enriched

environments may increase cognitive function (Arendash et al.,

2004) and reduce pathological traits for Alzheimer’s, including

neural deposition of amyloid protein (Lazarov et al., 2005). In hu-

mans, training appears to improve memory in individuals with

mild cognitive impairment (Belleville et al., 2011) or mild-to-mod-

erate Alzheimer’s (Zanetti et al., 1997). A recent evaluation by the

National Institutes of Health found little evidence for pharmaceu-

tical or dietary preventative measures for cognitive decline (Davig-

lus et al., 2010), underlining the importance of increasing research

pertaining to cognitive training in such populations. With positive

preliminary ﬁndings in elderly individuals with cognitive impair-

ments, this type of training may constitute a crucial source of

remediation for cognitive decline.

Training need not be circumscribed or even deviate from typical

daily activities. An interesting take on cognitive training in elderly

populations, the Active Cognitive Stimulation-Prevention in the El-

derly (AKTIVA) program entails engagement in leisurely activities

that nonetheless provide some form of cognitive stimulation (Tes-

ky, Thiel, Banzer, & Pantel, 2011). By combining cognitively

demanding activities previously shown to help prevent or delay

onset of dementia, AKTIVA offered a potentially fun and engaging

way to promote sustainability of cognitive function throughout

old age. A randomized controlled study assessing the effectiveness

of this program reported signiﬁcant improvements in speed of pro-

cessing in participants over 75 years of age, as well as subjective

ratings of age-related memory declines in participants younger

than 75 years of age. Overall, however, this study revealed no sig-

niﬁcant beneﬁts of the AKTIVA program compared to controls (Tes-

ky et al., 2011). While such paradigms may offer an enjoyable and

convenient method for training, these ﬁndings highlight the

importance of discerning what components underlie the success

of effective programs.

In healthy elderly populations, brain training appears to delay

the natural progression of cognitive decline by enhancing learning

capacity and speciﬁc forms of memory (Buiza et al., 2009; Park,

Kwon, Seo, Lim, & Song, 2009). The Advanced Cognitive Training

for Independent and Vital Elderly (ACTIVE) study (Jobe et al.,

2001) – the largest randomized controlled trial to date studying

cognitive decline in healthy elderly individuals – provides evidence

for the effectiveness of 10 1-h sessions of reasoning training, mem-

ory training, and speed of process training in improving perfor-

mance on the speciﬁc abilities trained (Ball et al., 2002).

Participants who received four additional reasoning and speed

training sessions at 11-months following program completion,

moreover, appeared to experience these beneﬁts to a signiﬁcantly

greater extent; these booster effects were not observed for the

memory training group. These effects were sustainable throughout

the 24-month follow-up (Ball et al., 2002), with later studies fur-

ther reporting delays in the decline of health-related quality of life

for speed-trained participants (Wolinsky et al., 2006) during the

same period of time. Nonetheless, effect sizes for these beneﬁts

were small and decreased over time. Furthermore, while reasoning

and speed training beneﬁted a relatively large percentage of partic-

ipants on the corresponding cognitive abilities tested, few partici-

pants improved on the memory-related cognitive abilities trained.

These improvements also generalized to cognitively demanding

daily abilities such as everyday processing speed and driving hab-

its, although only for the speed training group. Despite these ﬁnd-

ings, all participants remained functionally independent

throughout the course of the observation period (Ball et al.,

2002). A review of studies on cognitive training in healthy elderly

individuals nevertheless concluded that while such training may

effectively improve performance on tasks related to the training,

little evidence demonstrates generalizability to general cognitive

domains (Papp et al., 2009). Thus, although brain training may im-

prove speciﬁc cognitive abilities in the healthy elderly, this type of

intervention does not appear to improve overall cognitive function.

6.3. Training for recovery after stroke

Cognitive training also appears to beneﬁt the process of rehabil-

itation following stroke. Neuroimaging studies reveal that, once

170 S. Rabipour, A. Raz/ Brain and Cognition 79 (2012) 159–179

Author's personal copy

stroke recovery occurs, patients undergo structural changes within

the brain that enable functional compensation for damaged neural

areas (Stuss et al., 1999). While the most common impairments

experienced after stroke involve motor-related disabilities, cogni-

tive deﬁcits also manifest in a large percentage of patients and

may persist for years following the event (Langhorne, Bernhardt,

& Kwakkel, 2011; Skidmore et al., 2011). Evidence surrounding

the effectiveness of such interventions for stroke rehabilitation,

however, remains conﬂicting. On one hand, certain studies report

post-training improvements in functions such as alertness and sus-

tained attention (Lincoln, Majid, & Weyman, 2000), WM (Wester-

berg et al., 2007), as well as perception and spatial neglect

(Langhorne et al., 2011). One study revealed enhanced skill-acqui-

sition in stroke patients who participated in a meta-cognitive pro-

gram aimed at increasing their sense of autonomy (McEwen,

Polatajko, Davis, Huijbregts, & Ryan, 2010). Despite these encour-

aging results, the extent to which such training improves cognitive

function and whether it beneﬁts quality of life for patients is un-

clear. Furthermore, other cognitive functions often damaged by

stroke, such as linguistic ability, do not appear to improve signiﬁ-

cantly as a result of the cognitive training techniques used (De

Jong-Hagelstein et al., 2011). Cognitive remediation techniques

may therefore assist the natural recovery pattern in patients fol-

lowing stroke, although further study remains to elucidate the

most effective methods as well as the extent to which such training

measurably improves daily life.

6.4. The potential of brain training for psychopathology

With the dramatic surge in attention-related disorders, parents

and professionals are growing increasingly eager to optimize the

system of attention both in school and at work. One example is

ADHD, a disorder laced with symptoms relating to inattention,

hyperactivity-impulsivity, or a combination of the two (Barkley,

1997; Steinhausen, 2009; Wells, 2008). With an approximate prev-

alence of 5.3% worldwide, in boys more than in girls, ADHD is the

most common childhood-onset psychopathology and persists into

adulthood in 30–50% of clinically-diagnosed cases (Barkley, 1997;

Wallis, Russell, & Muenke, 2008). Another example is Tourette’s

Syndrome (TS), a neurodevelopmental impulse-control disorder

(Robertson, 2003). With a brief review of some complexities sur-

rounding the etiology and treatment of these disorders, we discuss

the potential of speciﬁc forms of brain training as alternatives to

medication.

6.4.1. The appeal of brain training to ADHD

ADHD affects neural structures associated with attentional pro-

cesses. Neuroimaging studies indicate that children with ADHD

have smaller global brain volumes compared to typically develop-

ing children, in addition to localized decreases in PFC, caudate, cer-

ebellum, and corpus callosum size (Kieling, Goncalves, Tannock, &

Castellanos, 2008; Steinhausen, 2009). Studies also report dimin-

ished activity in the circuits underlying executive attention,

including regions of the PFC and ACC (Spencer, Biederman, Wilens,

& Faraone, 2002), which may bring about the observed differences

in cognitive control. Developmental manifestations of ADHD can

be extremely pronounced and involve WM, speech internalization,

modulation of goal-directed behaviors, as well as self-regulation of

drive and affect (Faraone & Biederman, 1998). While these deﬁcits

may be more prominent in children, studies report analogous

impairments of attention, self-control, and time estimation in ado-

lescents with ADHD (Barkley, Edwards, Laneri, Fletcher, & Metevia,

2001).

ADHD is perhaps best recognized through the marked difﬁcul-

ties that children exhibit with interpersonal relationships. A study

in the United States found that, among a population of children

diagnosed with ADHD, over one third of parents reported signiﬁ-

cant emotional and behavioral difﬁculties in their children, with

nearly 40% reporting deﬁcits in aspects of daily living (Strine

et al., 2006). These difﬁculties may arise, in part, as a result of an

inferior capability to distinguish emotionally-charged facial

expressions (Pelc, Kornreich, Foisy, & Dan, 2006). In addition, stud-

ies show peer-rejection rates of children with ADHD span 52–82%,

which may be due to increased aggression, poorer social skills, and

inﬂated self-perception (Murray-Close et al., 2010). Such reports

indicate that children with ADHD stand to beneﬁt from programs

that may teach them to control their emotions and behavior.

Treatment options for ADHD are sparse and most commonly

comprise psychostimulant medication, which shows marginal

effectiveness. Improvements in the conduct and academic perfor-

mance of medicated children (Elia, Ambrosini, & Rapoport, 1999)

conﬁrm the short term efﬁcacy of psychostimulants, of which

methylphenidate and amphetamine are most commonly pre-

scribed. This type of medication appears to reduce characteristic

behaviors associated with ADHD, including inattentiveness, hyper-

activity, and impulsivity (The MTA Cooperative Group, 1999), with

additional improvements in compliance, aggression, and academic

achievement (Halperin & Healey, 2011). Reports further indicate

varying levels of improvement in performance and reaction time

on various WM and executive function tasks in individuals with

ADHD taking stimulant medication (Barnett et al., 2001; Swanson,

Baler, & Volkow, 2011). These studies suggest that psychostimu-

lant medication effectively decreases ADHD symptoms.

Current ADHD medication, however, has several limitations

that incite parents and professionals to demand superior treatment

options. First, while short term effects of these drugs are well doc-

umented, there is ongoing debate regarding the effects of long-

term psychostimulant consumption. While some studies report

continued stimulant efﬁcacy for a number of years following initial

treatment in children and adults (Bejerot, Ryden, & Arlinde, 2010;

The MTA Cooperative Group, 1999), high drop-out rates and ﬁnd-

ings of a drop-off in effect after a few years render the collective

evidence inconclusive at best (Swanson et al., 2011). Even the po-

sitive short-term beneﬁts of psychostimulant drugs come at the

price of unwanted side-effects and potential long-term risks. Both

methylphenidate and amphetamine trigger similar, dose-depen-

dent, adverse effects, of which insomnia and diminished appetite

– seen in approximately 80% of children with ADHD – are the most

common (Elia et al., 1999). Reports also identify cardiovascular

problems such as elevated resting heart-rate and blood pressure,

in addition to stunted growth and the development of tics (Bejerot

et al., 2010; Daughton, Liu, West, Swanson, & Kratochvil, 2010; Elia

et al., 1999). Another concern pertains to substance abuse, highly

comorbid with ADHD and sometimes triggered by continued stim-

ulant-use (Daughton et al., 2010; Szobot et al., 2011). Finally, not

all individuals respond to psychostimulants. Reports indicate that

70% of ADHD patients respond to the ﬁrst stimulant drug adminis-

tered, and an additional 10–20% respond if a second class of stim-

ulant is tried in succession (Daughton et al., 2010). These response

rates, however, do not appear to vary with ADHD subtype (Solanto

et al., 2009). These ﬁndings clearly warrant demand for safer and

more effective treatment options.

Scientists have attempted treating ADHD with alternate types

of medication, including non-stimulant drugs, antidepressants,

antipsychotic medication, and alpha-adrenergic agonists. While

non-stimulant medications have reportedly fewer side-effects

and long-term risks, their impact on ADHD symptoms is not as

strong as psychostimulants (Daughton et al., 2010). Likewise, anti-

depressant, antipsychotic, and alpha-agonist medications show

only mild efﬁcacy, although the ﬁndings come from small popula-

tions and include reports of adverse side-effects (Daughton et al.,

2010; Elia et al., 1999; Ipser & Stein, 2007). Reports of death in

S. Rabipour, A. Raz/ Brain and Cognition 79 (2012) 159–179 171

Author's personal copy

children taking a combinations of psychostimulants and alpha-

agonists, moreover, represent a clear illustration of the need to

determine the ramiﬁcations of taking several classes of drugs

simultaneously (Elia et al., 1999). Such reports suggest that these

types of drugs may not constitute viable alternatives to psycho-

stimulant treatment in ADHD.

Given the potentially noxious effects of psychostimulant medi-

cation and the relative ineffectiveness of other drug types, wide-

spread efforts aim to develop non-pharmacological therapies that

would regulate unwanted ADHD symptomatology without the

threat of long-term adverse effects. Currently, many studies indi-

cate that children with ADHD strongly beneﬁt from family therapy

– with particular emphasis on parent training – as well as social

skill training (Elia et al., 1999; McBurnett & Pﬁffner, 2008; Wells,

2008). Certainly, providing a more structured and supportive envi-

ronment may offset conditions that play a role in triggering the on-

set of ADHD symptoms in children, and has potential to markedly

improve the pathophysiological course of the disorder.

Cognitive treatments for ADHD entail brain training programs

and show promising effects in both children and adults (Galbiati

et al., 2009). Studies of programs such as Cogmed (Klingberg,

2008; Olesen et al., 2004), report improvements in both cognitive

ability and behavioral symptoms of ADHD (Halperin & Healey,

2011). Other programs appear to facilitate increased cognitive per-

formance and attentional ability in children, although these bene-

ﬁts do not always extend to improvements in behavior (Kerns

et al., 1999). The effects of certain forms of training, furthermore,

are comparable with the effects of medication (Klingberg et al.,

2005). Similar to pharmacotherapy, however, many of these train-

ing programs do not afford children the opportunity to develop

their own self-control (Singh et al., 2010). Cognitive training pro-

grams supplemented by interpersonal interactions may therefore

allow children to receive behavioral monitoring and continual

feedback, thereby teaching them to monitor their actions and re-

spond in a situation-appropriate manner. Programs for children

combining medication with cognitive training, including speciﬁc

forms of meditation, reveal signiﬁcant improvements in symptoms

related to inattention, impulsivity, and hyperactivity, as well as en-

hanced self-esteem and child-parent relationships (Rubia, 2009).

The reported improvements in cognitive performance and ADHD

symptomatology as a result of cognitive training attest to the

promise of such interventions as a component of ADHD treatment.

6.4.2. Brain training in Tourette’s Syndrome

While pharmacological options exist for the treatment of TS

(e.g., haloperidol, pimozide, or clonidine), general consensus posits

that such therapies are suboptimal, and prominent researchers

have recently lamented that medication therapies for TS are woe-

fully inadequate (Singer & Walkup, 1991). Drug efﬁcacy for TS is

inconsistent and unpredictable, and at best, offers only symptom-

atic relief (Peterson & Cohen, 1998). Beneﬁts often come at the ex-

pense of intolerable side-effects, including sedation, parkinsonism,

tardive dyskinesia, cognitive dulling, dry mouth, fatigue, dizziness,

weight gain, and metabolic problems (Swain, Scahill, Lombroso,

King, & Leckman, 2007). Most current treatments for TS are poten-

tially toxic to the central nervous system. Moreover, those treat-

ments tend to be terribly ineffective for many individuals and at

best provide a modest reduction of the symptomatology (Phelps,

2008). Specialists hence recognize the need for alternatives and

therapeutic adjuncts.

Behavioral interventions such as habit-reversal training (HRT)

have been shown to be effective in ameliorating the symptoms of

TS (Feldman, Storch, & Murphy, 2011; Himle, Woods, Piacentini,

& Walkup, 2006; Piacentini et al., 2010; Woods et al., 2011). We

have outlined how attentional interventions, including AT, can

aid in overcoming the debilitating symptoms of impulse control

disorders via improvements to this network, with a special focus

on TS (Raz, Keller, Norman, & Senechal, 2007). Similar to HRT, AT

reduced the symptoms of TS in a pilot study involving 12 experi-

mental and 12 control participants. Our preliminary ﬁndings sug-

gest that, compared to a control condition – watching popular

children’s videos, relaxing, and playing general video games with

intermittent dialogue pauses matching for child–adult interactions

– AT decreased visible tics and impulsivity in young individuals

with TS and increased their ability to regulate emotions and persist

with goals in the face of distractions. Findings from our pilot data

further purpose that these changes translate into an increase in the

quality of life (Raz, in press). Thus, tic-awareness programs, recog-

nizing internal urges, switching to voluntary behaviors that are

physically incompatible with the tic, relaxation guidance, and

learning to identify antecedents of the tics, appear to be a promis-

ing behavioral approach for people with TS.

7. The business of brain training and conﬂicts of interest

Brain training constitutes a lucrative market. Widespread con-

cern regarding cognitive decline in the aging population and obses-

sion with maximizing efﬁciency in school and at work have created

a society of brain trainers that spare little expense on cognitive ﬁt-

ness. With individual programs costing hundreds to thousands of

dollars, this industry feeds on growing consumer interest to yield

enormous proﬁt. In 2010, the Scientiﬁc Learning Corporation –

developer of programs such as FFW – generated revenues over

$43 million (Ernst, 2010). In the US alone, revenues of brain ﬁtness

software attained $265 million in 2008, increased from $100 mil-

lion in 2005 (Martin, 2009), and may accumulate revenues in the

billions by 2015. While healthcare systems have contributed a

large portion of this ﬁgure, individual consumers are playing an

increasingly prominent role, as are educational systems, athletic

organizations, and the US military (Fernandez, 2008). In addition,

programs targeting age-related cognitive decline represent a par-

ticularly proﬁtable market, with hundreds of retirement homes

now offering brain ﬁtness products to tenants. Hence, brain train-

ing is nothing short of big business.

The brain training industry sometimes engenders conﬂicts of

interest (COI) that could bias the scientiﬁc integrity of published

work. Similarly to pharmaceutical and medical device companies

(Brennan et al., 2006), distributors of cognitive exercise programs

often fund studies evaluating their product or assign product test-

ing to academic shareholders (Corporation, 2010; Pearson, 2011;

Scientiﬁc Learning Corporation, 2011). Such COI may impede the

objectivity of studies by provoking the omission of results unfavor-

able to the desired outcome or the reporting of ﬁndings that are

favorable to the funding companies (Easterbrook, Gopalan, Berlin,

& Matthews, 1991; Lexchin, Bero, Djulbegovic, & Clark, 2003;

Turner, Matthews, Linardatos, Tell, & Rosenthal, 2008). Alternately,

authors with ties to industry (Smith et al., 2009) may overextend

the interpretations of their results by emphasizing statistical sig-

niﬁcance while ignoring relatively small effect sizes that would

indicate little or no clinical signiﬁcance. Thus, COI potentially com-

promise the integrity of research.

COI are especially troubling in clinical contexts (e.g., psycho-

therapy, neurofeedback), where target populations may ultimately

rely on biased research and thereby overlook a more appropriate

remedy when searching for a treatment. Defenders of COI specu-

late that scientists may not obtain the funds necessary to conduct

research on potentially groundbreaking treatments or programs

without the beneﬁt of commercial support (Stossel, 2007, 2008).

In a similar vein, some brain training investigators working with

industry claim that separation of research and business is imprac-

tical because product distribution is less efﬁcient outside of

172 S. Rabipour, A. Raz/ Brain and Cognition 79 (2012) 159–179

Author's personal copy

commerce (Merzenich, 2011); however, little, if any, evidence sup-

ports this claim. The history of clinical research, furthermore, at-

tests to the dangers of distributing substances in need of more

rigorous testing before becoming publicly available (Brody,

2008). Proponents of COI also assert that segregation between clin-

ical goals and promotional motivation is impossible; even

researchers strive to put their work in a positive light and profes-

sionals of the medical ﬁeld advertise in order to attract clientele

(Stossel, 2007). However, unlike such conﬂicts, which are inherent

to human ambition, commercial COI result from voluntary choice

and are therefore avoidable (Kassirer, 2009b). Furthermore,

although researchers often claim that no incentive could compro-

mise their impartiality, evidence suggests that self-serving biases

occur subtly and unintentionally (Kassirer, 2009b). COI may there-

fore tarnish experimental ﬁndings and bias clinical practice.

The scientiﬁc community often considers disclosure to absolve

the existence of COI in research. Researchers who shelter them-

selves behind the veil of disclosure, however, merely attest to the

existence of a COI, but neither conﬁrm nor deny the existence of

partiality in their work (Kassirer, 2009a). The onus of identifying

bias therefore passes to individuals who have no objective measure

of the partiality of a study. In addition, disclosure may hinder the

objectivity of studies by allowing scientists to retain their favorable

ties with corporations so long as they make their potential partial-

ity known to the public. Instead of merely disclosing COI in re-

search and brushing the issue aside, a more effective stratagem

may include the elimination of potentially questionable relations,

the validation of scientiﬁc rigor within study design, and the inde-

pendent replication of all inﬂuential ﬁndings.

8. Conclusion

Brain training draws on both evidence and hype. Examination of

the ﬁndings reveals that consumers – largely oversold on individ-

ualized modules and programs (e.g., for ADHD) – often rely on

claims that are scientiﬁcally unsubstantiated. For these programs

to be clinically useful, they will have to accomplish what few inter-

ventions, if any, have achieved: generalize circumscribed labora-

tory and computer skills to tangible gains in the classroom,

during play, and in other ecological settings. This lofty goal, how-

ever, has hardly been achieved.

Few scholars have distinguished their research efforts by pro-

viding scientiﬁc evidence to support the impact of their computer-

ized training in both children and adults. Speciﬁc researchers have

demonstrated sustainable behavioral improvements using inde-

pendent programs. Following brief interventions, children have

demonstrated improvements in measures of non-verbal intelli-

gence, language development, and control over affect and execu-

tive function. In addition, electrophysiological and neuroimaging

studies report a shift of signature brainwaves toward more adult-

like patterns and maturation of neural modules implicated in

attention, respectively. Some of these beneﬁts further extend to

both healthy and pathological adults. These programs, however,

have rarely made a trailblazing breakthrough in improving symp-

toms and resolving impairments. In this regard, such approaches

to cognitive remediation show promise, but hardly represent

stand-alone treatments.

While computerized programs constitute the most accessible

form of brain training, researchers have shown beneﬁts from spe-

ciﬁc contemplative techniques and lifestyle-related practices. Pro-

grams encompassing mind–body meditative techniques in healthy

adults, for example, demonstrate training-related alterations of

white matter connectivity in neural areas associated with the exec-

utive attention system, and appear to alleviate feelings of stress

and pain. Meditation training has also proven beneﬁcial in adults

with ADHD, enhancing their performance on conﬂict and inhibition

tasks, and decreasing their reported symptoms related to the disor-

der. Other methods of training show similar beneﬁts for improving

cognitive function and behavioral control through executive atten-

tion. These include bilingualism, musical training, physical exer-

cise, regular interaction with nature, and proper parenting. Such

ﬁndings support practice in alternate forms of training that need

not involve circumscribed programs.

Cognitive training in psychopathology may represent an ad-

junct, if not a possible alternative, to some pharmacological treat-

ment options. Psychiatric treatment of developmental

psychopathologies largely relies on drug interventions. Pharmaco-

logical approaches may engender undesirable side effects and

sometimes carry only marginal beneﬁts, especially over time. With

the current credibility crisis surrounding pediatric psychiatry and

pharmacotherapeutics, crafting effective drug-free treatment alter-

natives seems highly relevant. Current ﬁndings, although prelimin-

ary, suggest that training options are safe, fun, and provide larger

gains for children who suffer from greater cognitive deﬁcits. Com-

bining training with medication, furthermore, appears to produce

maximal beneﬁts that exceed behavioral or pharmacological treat-

ments alone. Thus, given extant knowledge about available treat-

ment options, brain training paradigms may be worthy of

consideration, especially for populations with speciﬁc develop-

mental deﬁciencies.

Despite promising ﬁndings in both healthy and cognitively-im-

paired individuals, studies often contain a number of caveats that

weaken the interpretations drawn from experimental results. Such

limitations relate to inadequate controls and measures of cognitive

function, behavior, and training sustainability. The context of brain

training research, furthermore, sometimes contains COI that

prompt overly ambitious conclusions. Notably, studies indicate

that such training does not constitute a ‘‘quick ﬁx’’ for a lifetime

of impairments. Rather, long-term exposure and application of

the training is likely to create lasting results. These caveats high-

light the importance of skepticism concerning experimental ﬁnd-

ings as well as the possible necessity to re-evaluate current

research standards in this ﬁeld.

Incorporating brain training into school curricula – alongside

mainstream courses such as history, language, physical education,

and math – may provide the long-term exposure needed to reap

the beneﬁts. By mimicking Eastern traditions that integrate con-

templative practices into daily routine, cognitive training may have

some tangible beneﬁts to offer. In this regard, brain training likely

impacts parameters related to improved quality of life, including

self-esteem, depression, anxiety, and stress. While further research

will have to determine the forms of training that would most ben-

eﬁt speciﬁc populations, the effectiveness and sustainability of

such programs will likely depend on training frequency and meth-

od of delivery.

Acknowledgments

We would like to thank Rose Golinksi and members of the Raz

Lab for providing helpful comments on earlier versions of this

manuscript. In addition, Drs. Stephen Hinshaw, Deborah Leong,

and Kimberly Kerns provided important insights regarding content

and organization. Dr. Raz acknowledges the kind support of the

Canada Research Chair program, the Canadian Institutes of Health

Research, and the Natural Sciences and Engineering Research

Council of Canada.

References

Allen, N. B., Blashki, G., Gullone, E., & Melbourne-Acad-Mindfulness-Interes (2006).

Mindfulness-based psychotherapies: A review of conceptual foundations,

S. Rabipour, A. Raz/ Brain and Cognition 79 (2012) 159–179 173

Author's personal copy

empirical evidence and practical considerations. Australian and New Zealand

Journal of Psychiatry, 40(4), 285–294.

Altenmüller, E. (2009). Apollo’s gift and curse: Brain plasticity in musicians. Music &

Medicine, 70.

Angelakis, E., Lubar, J. F., Stathopoulou, S., & Kounios, J. (2004). Peak alpha

frequency: An electroencephalographic measure of cognitive preparedness.

Clinical Neurophysiology, 115(4), 887–897. http://dx.doi.org/10.1016/

j.clinph.2003.11.034.

Angelakis, E., Stathopoulou, S., Frymiare, J. L., Green, D. L., Lubar, J. F., & Kounios, J.

(2007). EEG neurofeedback: A brief overview and an example of peak alpha

frequency training for cognitive enhancement in the elderly. Clinical

Neuropsychologist, 21(1), 110–129.

Arendash, G. W., Garcia, M. F., Costa, D. A., Cracchiolo, J. R., Wefes, I. M., & Potter, H.

(2004). Environmental enrichment improves cognition in aged Alzheimer’s

transgenic mice despite stable [beta]-amyloid deposition. NeuroReport, 15(11),

1751–1754.

Baddeley, A. (1992). Working memory. Science, 255(5044), 556–559.

Baggett, K. M., Davis, B., Feil, E. G., Sheeber, L. B., Landry, S. H., Carta, J. J., et al. (2010).

Technologies for expanding the reach of evidence-based interventions:

Preliminary results for promoting social–emotional development in early

childhood. Topics in Early Childhood Special Education, 29(4), 226–238. http://

dx.doi.org/10.1177/0271121409354782.

Baijal, S., & Gupta, R. (2008). Meditation-based training: A possible intervention for

attention deﬁcit hyperactivity disorder. Psychiatry (Edgmont), 5(4), 48–55.

Ball, K., Berch, D. B., Helmers, K. F., Jobe, J. B., Leveck, M. D., Marsiske, M., et al.

(2002). Effects of cognitive training interventions with older adults. JAMA: The

Journal of the American Medical Association, 288(18), 2271–2281. http://

dx.doi.org/10.1001/jama.288.18.2271.

Barkley, R. A. (1997). Behavioral inhibition, sustained attention, and executive

functions: Constructing a unifying theory of ADHD. Psychological Bulletin,

121(1), 65–94.

Barkley, R. A. (1998). Attention-deﬁcit hyperactivity disorder: A handbook for diagnosis

and treatment (2nd ed.). New York: Guilford Press.

Barkley, R. A., Edwards, G., Laneri, M., Fletcher, K., & Metevia, L. (2001). Executive

functioning, temporal discounting, and sense of time in adolescents with

attention deﬁcit hyperactivity disorder (ADHD) and oppositional deﬁant

disorder (ODD). Journal of Abnormal Child Psychology, 29(6), 541–556.

Barnett, W. S., Jung, K., Yarosz, D. J., Thomas, J., Hornbeck, A., Stechuk, R., et al.

(2008). Educational effects of the tools of the mind curriculum: A randomized

trial. Early Childhood Research Quarterly, 23(3), 299–313. http://dx.doi.org/

10.1016/j.ecresq.2008.03.001.

Barnett, R., Maruff, P., Vance, A., Luk, E. S. L., Costin, J., Wood, C., et al. (2001).

Abnormal executive function in attention deﬁcit hyperactivity disorder: The

effect of stimulant medication and age on spatial working memory.

Psychological Medicine, 31(6), 1107–1115.

Beck, S. J., Hanson, C. A., Puffenberger, S. S., Benninger, K. L., & Benninger, W. B.

(2010). A controlled trial of working memory training for children and

adolescents with ADHD. Journal of Clinical Child and Adolescent Psychology,

39(6), 825–836. http://dx.doi.org/10.1080/15374416.2010.517162.

Bejerot, S., Ryden, E. M., & Arlinde, C. M. (2010). Two-year outcome of treatment

with central stimulant medication in adult attention-deﬁcit/hyperactivity

disorder: A prospective study. Journal of Clinical Psychiatry, 71(12),

1590–1597. http://dx.doi.org/10.4088/JCP.09m05168pur.

Belleville, S., Clément, F., Mellah, S., Gilbert, B., Fontaine, F., & Gauthier, S. (2011).

Training-related brain plasticity in subjects at risk of developing Alzheimer’s

disease. Brain, 134(6), 1623–1634. http://dx.doi.org/10.1093/brain/awr037.

Benedetti, F., Mayberg, H. S., Wager, T. D., Stohler, Christian. S., & Zubieta, J.-K.

(2005). Neurobiological mechanisms of the placebo effect. The Journal of

Neuroscience, 25(45), 10390–10402. http://dx.doi.org/10.1523/jneurosci.3458-

05.2005.

Benedict, R. H. B., Harris, A. E., Markow, T., McCormick, J. A., Nuechterlein, K. H., &

Asarnow, R. F. (1994). Effects of attention training on information-processing in

schizophrenia. Schizophrenia Bulletin, 20(3), 537–546.

Bergman Nutley, S. (2011). Development and training of higher order cognitive

functions and their interrelations. Stockholm: Karolinska Institutet.

Berman, M. G., Jonides, J., & Kaplan, S. (2008). The cognitive beneﬁts of interacting

with nature. Psychological Science, 19(12), 1207–1212. http://dx.doi.org/

10.1111/j.1467-9280.2008.02225.x.

Berry, A. S., Zanto, T. P., Clapp, W. C., Hardy, J. L., Delahunt, Peter. B., Mahncke, H. W.,

et al. (2010). The inﬂuence of perceptual training on working memory in older

adults. PLoS ONE, 5(7), e11537.

Bialystok, E. (1999). Cognitive complexity and attentional control in the bilingual

mind. Child Development, 70(3), 636–644. http://dx.doi.org/10.1111/1467-

8624.00046.

Bialystok, E. (2010). Bilingualism. Wiley Interdisciplinary Reviews: Cognitive Science,

1(4), 559–572. http://dx.doi.org/10.1002/wcs.43.

Bialystok, E., Craik, F. I. M., & Ryan, J. (2006). Executive control in a modiﬁed

antisaccade task: Effects of aging and bilingualism. Journal of Experimental

Psychology: Learning, Memory, and Cognition, 32(6), 1341–1354. http://

dx.doi.org/10.1037/0278-7393.32.6.1341.

Bialystok, E., & DePape, A. M. (2009). Musical expertise, bilingualism, and executive

functioning. Journal of Experimental Psychology – Human Perception and

Performance, 35(2), 565–574. http://dx.doi.org/10.1037/a0012735.

Bialystok, E., & Majumder, S. (1998). The relationship between bilingualism and the

development of cognitive processes in problem solving. Applied

Psycholinguistics, 19(01), 69–85. 10.1017/S0142716400010584.

Bialystok, E., & Martin, M. M. (2004). Attention and inhibition in bilingual children:

Evidence from the dimensional change card sort task. Developmental Science,

7(3), 325–339. http://dx.doi.org/10.1111/j.1467-7687.2004.00351.x.

Bierman, K. L., Domitrovich, C. E., Nix, R. L., Gest, S. D., Welsh, J. A., Greenberg, M. T.,

et al. (2008). Promoting academic and social–emotional school readiness: The

head start REDI program. Child Development, 79(6), 1802–1817. http://

dx.doi.org/10.1111/j.1467-8624.2008.01227.x.

Bierman, K. L., Nix, R. L., Greenberg, M. T., Blair, C., & Domitrovich, C. E. (2008).

Executive functions and school readiness intervention: Impact, moderation, and

mediation in the head start REDI program. Development and Psychopathology,

20(3), 821–843. http://dx.doi.org/10.1017/S0954579408000394.

Bledowski, C., Kaiser, J., & Rahm, B. (2010). Basic operations in working memory:

Contributions from functional imaging studies. Behavioural Brain Research,

214(2), 172–179. http://dx.doi.org/10.1016/j.bbr.2010.05.041.

BrainMaster Technologies, Inc. (2009). Neurofeedback Systems. <http://

www.brainmaster.com/>.

Brennan, T. A., Rothman, D. J., Blank, L., Blumenthal, D., Chimonas, S. C., Cohen, J. J.,

et al. (2006). Health industry practices that create conﬂicts of interest. JAMA:

The Journal of the American Medical Association, 295(4), 429–433. http://

dx.doi.org/10.1001/jama.295.4.429.

Brody, H. (2008). A reply to Thomas Stossel on the AMA-CEJA draft report: Risk-

beneﬁt ratio’’. Medscape Journal of Medicine, 10(7), 154.

Buiza, C., Gonzalez, M. F., Facal, D., Martinez, V., Diaz, U., Etxaniz, A., et al. (2009).

Efﬁcacy of cognitive training experiences in the elderly: Can technology help?

Lecture Notes in Computer Science, 5614, 324–333.

Burke, C. (2010). Mindfulness-based approaches with children and adolescents: A

preliminary review of current research in an emergent ﬁeld. Journal of Child and

Family Studies, 19(2), 133–144. http://dx.doi.org/10.1007/s10826-009-9282-x.

Buschkuehl, M., & Jaeggi, S. M. (2010). Improving intelligence: A literature review.

Swiss Medical Weekly, 140(19–20), 266–272.

Bush, G., Luu, P., & Posner, M. I. (2000). Cognitive and emotional inﬂuences in

anterior cingulate cortex. Trends in Cognitive Sciences, 4(6), 215–222.

Calero, M. D., & Navarro, E. (2007). Cognitive plasticity as a modulating variable on

the effects of memory training in elderly persons. Archives of Clinical

Neuropsychology, 22(1), 63–72.

Callahan, C. M., Hall, K. S., Hui, S. L., Musick, B. S., Unverzagt, F. W., & Hendrie, H. C.

(1996). Relationship of age, education, and occupation with dementia among a

community-based sample of African Americans. Archives of Neurology, 53(2),

134–140. http://dx.doi.org/10.1001/archneur.1996.00550020038013.

Cannonieri, G. C., Bonilha, L., Fernandes, P. T., Cendes, F., & Li, L. M. (2007). Practice

and perfect: Length of training and structural brain changes in experienced

typists. NeuroReport, 18(10), 1063–1066. 1010.1097/

WNR.1060b1013e3281a1030e1065.

Carlson, C. L., Tamm, L., & Gaub, M. (1997). Gender differences in children with

ADHD, ODD, and co-occurring ADHD/ODD identiﬁed in a school population.

Journal of the American Academy of Child & Adolescent Psychiatry, 36(12),

1706–1714. http://dx.doi.org/10.1097/00004583-199712000-00019.

Chan, A. S., Ho, Y.-C., & Cheung, M.-C. (1998). Music training improves verbal

memory. Nature, 396(6707), 128. http://dx.doi.org/10.1038/24075.

Charles, C., Louv, R., Bodner, L., Guns, B., & Stahl, D. (2009). Children and nature

2009: A Report on the movement to reconnect children to the natural world. In

Network (Ed.).

Chein, J. M., & Morrison, A. B. (2010a). Expanding the mind’s workspace: Training

and transfer effects with a complex working memory span task. Psychonomic

Bulletin & Review, 17(2), 193–199. http://dx.doi.org/10.3758/pbr.17.2.193.

Chein, Jason, & Morrison, Alexandra (2010b). Expanding the mind’s workspace:

Training and transfer effects with a complex working memory span task.

Psychonomic Bulletin & Review, 17(2), 193–199. http://dx.doi.org/10.3758/

pbr.17.2.193.

Chiesa, A., Calati, R., & Serretti, A. (in press). Does mindfulness training improve

cognitive abilities? A systematic review of neuropsychological ﬁndings. Clinical

Psychology Review.http://dx.doi.org/10.1016/j.cpr.2010.11.003.

Civic Results (2008). Community action guide: Building the children & nature

movement from the ground up. In Network (Ed.).

Colcombe, S., & Kramer, A. F. (2003). Fitness effects on the cognitive function of

older adults. Psychological Science, 14(2), 125–130. http://dx.doi.org/10.1111/

1467-9280.t01-1-01430.

Congedo, M., Lubar, J. F., & Joffe, D. (2004). Low-resolution electromagnetic

tomography neurofeedback. IEEE Transactions on Neural Systems and

Rehabilitation Engineering, 12(4), 387–397. http://dx.doi.org/10.1109/

tnsre.2004.840492.

Corporation, Posit Science (2010). Posit science brain training software. <http://

www.positscience.com/>.

Costa, A., Hernández, M., & Sebastián-Gallés, N. (2008). Bilingualism aids conﬂict

resolution: Evidence from the ANT task. Cognition, 106(1), 59–86. http://

dx.doi.org/10.1016/j.cognition.2006.12.013.

Credibility Crisis in Pediatric Psychiatry (2008). Nature Neuroscience, 11(9), 983.

http://dx.doi.org/10.1038/nn0908-983.

Creswell, J. D., Way, B. M., Eisenberger, N. I., & Lieberman, M. D. (2007). Neural

correlates of dispositional mindfulness during affect labeling. Psychosomatic

Medicine, 69(6), 560–565. http://dx.doi.org/10.1097/Psy.0b013e3180f6171f.

Croisile, B. (2006). Memory stimulation: Which scientiﬁc beneﬁts? Which

exercises? Revue de Gériatrie, 31, 421–433.

Dandeneau, S. P., & Baldwin, M. W. (2004). The inhibition of socially rejecting

information among people with high versus low self-esteem: The role of

attentional bias and the effects of bias reduction training. Journal of Social and

174 S. Rabipour, A. Raz/ Brain and Cognition 79 (2012) 159–179

Author's personal copy

Clinical Psychology, 23(4), 584–602. http://dx.doi.org/10.1521/jscp.

23.4.584.40306.

Daneman, M., & Carpenter, P. A. (1980). Individual-differences in working memory

and reading. Journal of Verbal Learning and Verbal Behavior, 19(4), 450–466.

Daughton, J., Liu, H., West, M., Swanson, D., & Kratochvil, C. J. (2010). Practical guide

to ADHD pharmacotherapy. Psychiatric Annals, 40(4), 210–217. http://

dx.doi.org/10.3928/00485713-20100330-03.

Davidson, R. J. (2010). Empirical explorations of mindfulness: Conceptual and

methodological conundrums. Emotion, 10(1), 8–11. http://dx.doi.org/10.1037/

a0018480.

Daviglus, M. L., Bell, C. C., Berrettini, W., Bowen, P. E., Connolly, E. S., Jr, Cox, N. J.,

et al. (2010). National institutes of health state-of-the-science conference

statement: Preventing Alzheimer disease and cognitive decline. Annals of

Internal Medicine, 153(3), 176–181.

Davis, C. L., Tomporowski, P. D., McDowell, J. E., Austin, B. P., Miller, P. H., Yanasak, N.

E., et al. (2011). Exercise improves executive function and achievement and

alters brain activation in overweight children: A randomized, controlled trial.

Health Psychology, 30(1), 91–98. http://dx.doi.org/10.1037/a0021766.

de Boo, G. M., & Prins, P. J. M. (2007). Social incompetence in children with ADHD:

Possible moderators and mediators in social-skills training. Clinical Psychology

Review, 27(1), 78–97. http://dx.doi.org/10.1016/j.cpr.2006.03.006.

De Jong-Hagelstein, M., Van De Sandt-Koenderman, W. M., Prins, N. D., Dippel, D. W.

J., Koudstaal, P. J., & Visch-Brink, E. G. (2011). Efﬁcacy of early cognitive-

linguistic treatment and communicative treatment in aphasia after stroke: A

randomised controlled trial (RATS-2). Journal of Neurology, Neurosurgery and

Psychiatry, 82(4), 399–404.

deCharms, R. C. (2008). Applications of real-time fMRI. Nature Reviews Neuroscience,

9(9), 720–729. http://dx.doi.org/10.1038/nrn2414.

Denison Pequotstepos Nature Center (2009). Nature based preschool parent

handbook. In Center (Ed.).

D’Esposito, M. (2007). From cognitive to neural models of working memory.

Philosophical Transactions of the Royal Society B – Biological Sciences, 362(1481),

761–772. http://dx.doi.org/10.1098/rstb.2007.2086.

Diamond, A. (2011). Personal communication.

Diamond, A., Barnett, W. S., Thomas, J., & Munro, S. (2007). Preschool program

improves cognitive control. Science, 318(5855), 1387–1388. http://dx.doi.org/

10.1126/science.1151148.

Diamond, A., & Lee, K. (2011). Interventions shown to aid executive function

development in children 4–12 years old. Science, 333(6045), 959–964.

Douglas, V. I., Parry, P., Marton, P., & Garson, C. (1976). Assessment of a cognitive

training program for hyperactive children. Journal of Abnormal Child Psychology,

4(4), 389–410.

Draganski, B., Gaser, C., Busch, V., Schuierer, G., Bogdahn, U., & May, A. (2004).

Neuroplasticity: Changes in grey matter induced by training – Newly honed

juggling skills show up as a transient feature on a brain-imaging scan. Nature,

427(6972), 311–312. http://dx.doi.org/10.1038/427311a.

Draganski, B., Gaser, C., Kempermann, G., Kuhn, H. G., Winkler, J., Buchel, C., et al.

(2006). Temporal and spatial dynamics of brain structure changes during

extensive learning. Journal of Neuroscience, 26(23), 6314–6317.

Driemeyer, J., Boyke, J., Gaser, C., B üchel, C., & May, A. (2008). Changes in gray

matter induced by learning – Revisited. PLoS ONE, 3(7).

Duff, K., Eckman, C., Zehr, C., Yu, X., Prada, C. M., Perez-Tur, J., et al. (1996). Increased

amyloid-b42(43) in brains of mice expressing mutant presenilin 1. Nature,

383(6602), 710–713.

Duncan, G. J., Dowsett, C. J., Claessens, A., Magnuson, K., Huston, A. C., Klebanov, P.,

et al. (2008). School readiness and later achievement (vol. 43, p. 1428, 2007).

Developmental Psychology, 44(1), 232. http://dx.doi.org/10.1037/0012-

1649.44.1.217.

DuPaul, G. J., McGoey, K. E., Eckert, T. L., & VanBrakle, J. (2001). Preschool children

with attention-deﬁcit/hyperactivity disorder: Impairments in behavioral, social,

and school functioning. Journal of the American Academy of Child and Adolescent

Psychiatry, 40(5), 508–515.

Easterbrook, P. J., Gopalan, R., Berlin, J. A., & Matthews, D. R. (1991). Publication bias

in clinical research. The Lancet, 337(8746), 867–872. http://dx.doi.org/10.1016/

0140-6736(91)90201-y.

Elbert, T., Pantev, C., Wienbruch, C., Rockstroh, B., & Taub, E. (1995). Increased

cortical representation of the ﬁngers of the left hand in string players. Science,

270(5234), 305–307. http://dx.doi.org/10.1126/science.270.5234.305.

Elia, J., Ambrosini, P. J., & Rapoport, J. L. (1999). Treatment of attention-deﬁcit-

hyperactivity disorder. New England Journal of Medicine, 340(10), 780–788.

Ericsson, K. A., & Chase, W. G. (1982). Exceptional memory. American Scientist, 70(6),

607–615.

Ernst & Young LLP. (2010). Scientiﬁc Learning Corp. (NMS: SCIL). <http://

www.mergentonline.com/competitors.php?compnumber=97992>.

Fabiano, G. A., Chacko, A., Pelham, W. E., Robb, J., Walker, K. S., Wymbs, F., et al.

(2009). A comparison of behavioral parent training programs for fathers of

children with attention-deﬁcit/hyperactivity disorder. Behavior Therapy, 40(2),

190–204.

Fan, J., Fossella, J., Sommer, T., Wu, Y., & Posner, M. I. (2003). Mapping the genetic

variation of executive attention onto brain activity. Proceedings of the National

Academy of Sciences of the United States of America, 100(12), 7406–7411.

Faraone, S. V., & Biederman, J. (1998). Neurobiology of attention-deﬁcit

hyperactivity disorder. Biological Psychiatry, 44(10), 951–958.

Feldman, Marissa A., Storch, E. A., & Murphy, T. K. (2011). Application of habit

reversal training for the treatment of tics in early childhood. Clinical Case

Studies, 10(2), 173–183. http://dx.doi.org/10.1177/1534650111400728.

Fernandez, A. (2008). The state of the brain ﬁtness market 2008. In SharpBrains

(Ed.), Brain ﬁtness series.<http://www.slideshare.net/AlvaroF/state-brain-

ﬁtness-market-2008> [Retrieved].

Ferri, C. P., Prince, M., Brayne, C., Brodaty, H., Fratiglioni, L., Ganguli, M., et al. (2005).

Global prevalence of dementia: A Delphi consensus study. The Lancet,

366(9503), 2112–2117. http://dx.doi.org/10.1016/s0140-6736(05)67889-0.

Fey, M. E., Finestack, L. H., Gajewski, B. J., Popescu, M., & Lewine, J. D. (2010). A

preliminary evaluation of fast forword-language as an adjuvant treatment in

language intervention. Journal of Speech Language and Hearing Research, 53(2),

430–449. http://dx.doi.org/10.1044/1092-4388(2009/08-0225.

Flook, L., Smalley, S. L., Kitil, M. J., Galla, B. M., Kaiser-Greenland, S., Locke, J., et al.

(2010). Effects of mindful awareness practices on executive functions in

elementary school children. Journal of Applied School Psychology, 26(1), 70–95.

Foer, J. (2011). Moonwalking with Einstein: The art and science of remembering

everything. New York: Penguin Press.

Forestry Commission Scotland (2009). Woods for learning: Increasing the use of

trees, woods, and forests for education. In Scotland (Ed.).

Fossella, J., Sommer, T., Fan, J., Wu, Y., Swanson, J., Pfaff, D., et al. (2002). Assessing

the molecular genetics of attention networks. BMC Neuroscience, 3(1), 14.

Fox, D. J., Tharp, D. F., & Fox, L. C. (2005). Neurofeedback: An alternative and

efﬁcacious treatment for attention deﬁcit hyperactivity disorder. Applied

Psychophysiology Biofeedback, 30(4), 365–373.

Fuchs, T., Birbaumer, N., Lutzenberger, W., Gruzelier, J. H., & Kaiser, J. (2003).

Neurofeedback treatment for attention-deﬁcit/hyperactivity disorder in

children: A comparison with methylphenidate. Applied Psychophysiology

Biofeedback, 28(1), 1–12.

Galbiati, S., Recla, M., Pastore, V., Liscio, M., Bardoni, A., Castelli, E., et al. (2009).

Attention remediation following traumatic brain injury in childhood and

adolescence. Neuropsychology, 23(1), 40–49. http://dx.doi.org/10.1037/a0013409.

Gaser, C., & Schlaug, G. (2003). Brain structures differ between musicians and non-

musicians. Journal of Neuroscience, 23(27), 9240–9245.

Glasgow, R. E., Lichtenstein, E., & Marcus, A. C. (2003). Why don’t we see more

translation of health promotion research to practice? Rethinking the efﬁcacy-

to-effectiveness transition. American Journal of Public Health, 93(8), 1261–1267.

http://dx.doi.org/10.2105/ajph.93.8.1261.

Gray, J. R., Chabris, C. F., & Braver, T. S. (2003). Neural mechanisms of general ﬂuid

intelligence. Nature Neuroscience, 6(3), 316–322. http://dx.doi.org/10.1038/

nn1014.

Green, D. W. (1998). Mental control of the bilingual lexico-semantic system.

Bilingualism: Language and Cognition, 1(2), 67–104.

Green, C. S., & Bavelier, D. (2008). Exercising your brain: A review of human brain

plasticity and training-induced learning. Psychology and Aging, 23(4), 692–701.

Gupta, R., & Kar, B. R. (2009). Development of attentional processes in ADHD and

normal children. In Narayanan (Ed.). Progress in brain research (Vol. 176,

pp. 259–276). Elsevier.

Hackman, D. A., & Farah, M. J. (2009). Socioeconomic status and the developing

brain. Trends in Cognitive Sciences, 13(2), 65–73. http://dx.doi.org/10.1016/

j.tics.2008.11.003.

Halperin, J. M., & Healey, D. M. (2011). The inﬂuences of environmental enrichment,

cognitive enhancement, and physical exercise on brain development: Can we

alter the developmental trajectory of ADHD? Neuroscience and Biobehavioral

Reviews, 35(3), 621–634. http://dx.doi.org/10.1016/j.neubiorev.2010.07.006.

Hammond, D. C. (2006). What is neurofeedback? Journal of Neurotherapy, 10(4),

25–36.

Harlow, H. F., & Mears, C. (1979). The human model: Primate perspectives.

Washington, New York: V.H. Winston; distributed solely by Halsted Press.

Harman, C., Rothbart, M. K., & Posner, M. I. (1997). Distress and attention

interactions in early infancy. Motivation and Emotion, 21(1), 27–43.

Heinrich, H., Gevensleben, H., & Strehl, U. (2007). Annotation: Neurofeedback –

Train your brain to train behaviour. Journal of Child Psychology and Psychiatry

and Allied Disciplines, 48(1), 3–16.

Hillman, C. H., Erickson, K. I., & Kramer, A. F. (2008). Be smart, exercise your heart:

Exercise effects on brain and cognition. Nature Reviews Neuroscience, 9(1),

58–65. http://dx.doi.org/10.1038/nrn2298.

Himle, M. B., Woods, D. W., Piacentini, J. C., & Walkup, J. T. (2006). Brief review of

habit reversal training for Tourette syndrome. Journal of Child Neurology, 21(8),

719–725. http://dx.doi.org/10.1177/08830738060210080101.

Ho, Y.-C., Cheung, M.-C., & Chan, A. S. (2003). Music training improves verbal but not

visual memory: Cross-sectional and longitudinal explorations in children.

Neuropsychology, 17(3), 439–450. http://dx.doi.org/10.1037/0894-4105.17.3.439.

Holmes, J., Gathercole, S. E., & Dunning, D. L. (2009). Adaptive training leads to

sustained enhancement of poor working memory in children. Developmental

Science, 12(4), F9–F15. http://dx.doi.org/10.1111/j.1467-7687.2009.00848.x.

Holmes, J., Gathercole, S. E., Place, M., Dunning, D. L., Hilton, K. A., & Elliott, J. G.

(2010). Working memory deﬁcits can be overcome: Impacts of training and

medication on working memory in children with ADHD. Applied Cognitive

Psychology, 24(6), 827–836. http://dx.doi.org/10.1002/acp. 1589.

Hölzel, B. K., Ott, U., Hempel, H., Hackl, A., Wolf, K., Stark, R., et al. (2007).

Differential engagement of anterior cingulate and adjacent medial frontal

cortex in adept meditators and non-meditators. Neuroscience Letters, 421(1),

16–21. http://dx.doi.org/10.1016/j.neulet.2007.04.074.

Illes, Judy, & Sahakian, B. J. (2011). The Oxford handbook of neuroethics. New York:

Oxford University Press.

Ipser, J., & Stein, D. J. (2007). Systematic review of pharmacotherapy of disruptive

behavior disorders in children and adolescents. Psychopharmacology (Berl),

191(1), 127–140. http://dx.doi.org/10.1007/s00213-006-0537-6.

S. Rabipour, A. Raz/ Brain and Cognition 79 (2012) 159–179 175

Author's personal copy

Jaeggi, S. M., Buschkuehl, M., Jonides, J., & Perrig, W. J. (2008). Improving ﬂuid

intelligence with training on working memory. Proceedings of the National

Academy of Sciences of the United States of America, 105(19), 6829–6833. http://

dx.doi.org/10.1073/pnas.0801268105.

Jaeggi, S. M., Studer-Luethi, B., Buschkuehl, M., Su, Y. F., Jonides, J., & Perrig, W. J.

(2010). The relationship between n-back performance and matrix reasoning –

Implications for training and transfer. Intelligence, 38(6), 625–635. http://

dx.doi.org/10.1016/j.intell.2010.09.001.

James, W. (1890). The principles of psychology (Vol. 1). New York, NY, US: Henry Holt

and Co..

Jarrold, C., & Towse, J. N. (2006). Individual differences in working memory.

Neuroscience, 139(1), 39–50. http://dx.doi.org/10.1016/

j.neuroscience.2005.07.002.

Jevning, R., Wallace, R. K., & Beidebach, M. (1992). The physiology of meditation – a

review – A wakeful hypometabolic integrated response. Neuroscience and

Biobehavioral Reviews, 16(3), 415–424.

Jha, A. P., Krompinger, J., & Baime, M. J. (2007). Mindfulness training modiﬁes

subsystems of attention. Cognitive Affective & Behavioral Neuroscience, 7(2),

109–119.

Jobe, J. B., Smith, D. M., Ball, K., Tennstedt, S. L., Marsiske, M., Willis, S. L., et al.

(2001). Active: A cognitive intervention trial to promote independence in older

adults. Controlled Clinical Trials, 22(4), 453–479. http://dx.doi.org/10.1016/

s0197-2456(01)00139-8.

Jones, L. B., Rothbart, M. K., & Posner, M. I. (2003). Development of executive

attention in preschool children. Developmental Science, 6(5), 498–504.

Kanfer, F. H. (1970). Self-monitoring – methodological limitations and clinical

applications. Journal of Consulting and Clinical Psychology, 35(2), 148.

Kanske, P., Heissler, J., Schönfelder, S., Bongers, A., & Wessa, M. (2011). How to

regulate emotion? Neural networks for reappraisal and distraction. Cerebral

Cortex, 21(6), 1379–1388. http://dx.doi.org/10.1093/cercor/bhq216.

Kaplan, S. (1995a). The restorative beneﬁts of nature – Toward an integrative

framework. Journal of Environmental Psychology, 15(3), 169–182.

Kaplan, S. (1995b). The restorative beneﬁts of nature: Toward an integrative

framework. Journal of Environmental Psychology, 15(3), 169–182. http://

dx.doi.org/10.1016/0272-4944(95)90001-2.

Karoly, P. (1993). Mechanisms of self-regulation – A systems view. Annual Review of

Psychology, 44, 23–52.

Kassirer, J. P. (2009a). Commentary: Disclosure’s failings: What is the alternative?

Academic Medicine, 84(9), 1180–1181. http://dx.doi.org/1110.1097/

ACM.1180b1013e3181b1117e1193.

Kassirer, J. P. (2009b). Medicine’s obsession with disclosure of ﬁnancial conﬂicts: Fixing

the wrong problem science and the media. London: Academic Press.

Kelly, B., Longbottom, J., Potts, F., & Williamson, J. (2004). Applying emotional

intelligence: Exploring the promoting alternative thinking strategies

curriculum. Educational Psychology in Practice: Theory, Research and Practice in

Educational Psychology, 20(3), 221–240.

Kermen, R., Hickner, J., Brody, H., & Hasham, I. (2010). Family physicians believe the

placebo effect is therapeutic but often use real drugs as placebos. Family

Medicine, 42(9), 636–642.

Kerns, K. A., Eso, K., & Thomson, J. (1999). Investigation of a direct intervention for

improving attention in young children with ADHD. Developmental

Neuropsychology, 16(2), 273–295.

Kesler, S. R., Lacayo, N. J., & Jo, B. (2010). A pilot study of an online cognitive

rehabilitation program for executive function skills in children with cancer-

related brain injury. Brain Injury, 25(1), 101–112. http://dx.doi.org/10.3109/

02699052.2010.536194.

Kieling, C., Goncalves, R. R. F., Tannock, R., & Castellanos, F. X. (2008). Neurobiology

of attention deﬁcit hyperactivity disorder. Child and Adolescent Psychiatric Clinics

of North America, 17(2), 285–307. http://dx.doi.org/10.1016/j.chc.2007.11.012.

Klingberg, T. (2007). Computerized training of working memory in children with

ADHD. European Neuropsychopharmacology, 17, S192–S193.

Klingberg, T. (2008). Computerized training of working memory. A promising

therapeutic strategy for ADHD. L’allenamento computerizzato della memoria

operativa. Una promettente strategia terapeutica nell’ADHD, 30(1), 25–26.

Klingberg, T. (2010). Training and plasticity of working memory. Trends in Cognitive

Sciences, 14(7), 317–324.

Klingberg, T., Fernell, E., Olesen, P. J., Johnson, M., Gustafsson, P., Dahlstrom, K., et al.

(2005). Computerized training of working memory in children with ADHD – A

randomized, controlled trial. Journal of the American Academy of Child and

Adolescent Psychiatry, 44(2), 177–186.

Klingberg, T., Forssberg, H., & Westerberg, H. (2002). Training of working memory in

children with ADHD. Journal of Clinical and Experimental Neuropsychology, 24(6),

781–791.

Kochanska, G., Murray, K. T., & Harlan, E. T. (2000). Effortful control in early

childhood: Continuity and change, antecedents, and implications for social

development. Developmental Psychology, 36(2), 220–232.

Kohen, D. P., & Olness, K. (2011). Hypnosis and hypnotherapy with children. New

York: Routledge.

Kotchoubey, B., Strehl, U., Holzapfel, S., Blankenhorn, V., Fröscher, W., & Birbaumer,

N. (1999). Negative potential shifts and the prediction of the outcome of

neurofeedback therapy in epilepsy. Clinical Neurophysiology, 110(4), 683–686.

http://dx.doi.org/10.1016/s1388-2457(99)00005-x.

Kozasa, E. H., Sato, J. R., Lacerda, S. S., Barreiros, M. A. M., Radvany, J., Russell, T. A.,

et al. (in press). Meditation training increases brain efﬁciency in an attention

task. Neuroimage.http://dx.doi.org/10.1016/j.neuroimage.2011.06.088.

Kraus, N., & Chandrasekaran, B. (2010). Music training for the development of

auditory skills. Nature Reviews Neuroscience, 11(8), 599–605. http://dx.doi.org/

10.1038/nrn2882.

Kring, A. M., & Sloan, D. M. (2010). Emotion regulation and psychopathology: A

transdiagnostic approach to etiology and treatment. New York, NY: Guilford Press.

Kubesch, S., Walk, L., Spitzer, M., Kammer, T., Lainburg, A., Heim, R., et al. (2009). A

30-minute physical education program improves students’ executive attention.

Mind, Brain, and Education, 3(4), 235–242.

Kumon North America, Inc. (2011). Kumon: Math. Reading. Success. <http://

www.kumon.com/>.

Kuo, H. K., Jones, R. N., Milberg, W. P., Tennstedt, S., Talbot, L., Morris, J. N., et al.

(2005). Effect of blood pressure and diabetes mellitus on cognitive and physical

functions in older adults: A longitudinal analysis of the advanced cognitive

training for independent and vital elderly cohort. Journal of the American

Geriatrics Society, 53(7), 1154–1161.

Langhorne, P., Bernhardt, J., & Kwakkel, G. (2011). Stroke rehabilitation. The Lancet,

377(9778), 1693–1702.

Laurin, D., Verreault, R., Lindsay, J., MacPherson, K., & Rockwood, K. (2001). Physical

activity and risk of cognitive impairment and dementia in elderly persons.

Archives of Neurology, 58(3), 498–504.

Lazarov, O., Robinson, J., Tang, Y.-P., Hairston, I. S., Korade-Mirnics, Z., Lee, V. M. Y.,

et al. (2005). Environmental enrichment reduces A[beta] levels and amyloid

deposition in transgenic mice. Cell, 120(5), 701–713. http://dx.doi.org/10.1016/

j.cell.2005.01.015.

Lenroot, R. K., & Giedd, J. N. (2008). The changing impact of genes and environment

on brain development during childhood and adolescence: Initial ﬁndings from a

neuroimaging study of pediatric twins. Development and Psychopathology, 20(4),

1161–1175. http://dx.doi.org/10.1017/s0954579408000552.

Lexchin, J., Bero, L. A., Djulbegovic, B., & Clark, O. (2003). Pharmaceutical industry

sponsorship and research outcome and quality: Systematic review. British

Medical Journal, 326(7400), 1167–1170. http://dx.doi.org/10.1136/

bmj.326.7400.1167.

Liew, J. (2011). Effortful control, executive functions, and education: bringing self-

regulatory and social–emotional competencies to the table. Child Development

Perspectives.

Li-Grining, C. P., Votruba-Drzal, E., Maldonado-Carreno, C., & Haas, K. (2010).

Children’s early approaches to learning and academic trajectories through ﬁfth

grade. Developmental Psychology, 46(5), 1062–1077. http://dx.doi.org/10.1037/

a0020066.

Lincoln, N. B., Majid, M. J., & Weyman, N. (2000). Cognitive rehabilitation for

attention deﬁcits following stroke. Cochrane Database of Systematic Reviews (4).

Liu, D., Diorio, J., Day, J. C., Francis, D. D., & Meaney, M. J. (2000). Maternal care,

hippocampal synaptogenesis and cognitive development in rats. Nature

Neuroscience, 3(8), 799–806. http://dx.doi.org/10.1038/77702.

Liu, D., Diorio, J., Tannenbaum, B., Caldji, C., Francis, D., Freedman, A., et al. (1997).

Maternal care, hippocampal glucocorticoid receptors, and hypothalamic-

pituitary–adrenal responses to stress. Science, 277(5332), 1659–1662. http://

dx.doi.org/10.1126/science.277.5332.1659.

Lutz, A., Slagter, H. A., Dunne, J. D., & Davidson, R. J. (2008). Cognitive–emotional

interactions – Attention regulation and monitoring in meditation. Trends in

Cognitive Sciences, 12(4), 163–169.

Lutz, A., Slagter, H. A., Rawlings, N. B., Francis, A. D., Greischar, L. L., & Davidson, R. J.

(2009). Mental training enhances attentional stability: Neural and behavioral

evidence. Journal of Neuroscience, 29(42), 13418–13427. http://dx.doi.org/

10.1523/jneurosci.1614-09.2009.

Mackey, A. P., Hill, S. S., Stone, S. I., & Bunge, S. A. (2010). Differential effects of

reasoning and speed training in children. Developmental Science.http://

dx.doi.org/10.1111/j.1467-7687.2010.01005.x.

Maguire, E. A., Burgess, N., Donnett, J. G., Frackowiak, R. S. J., Frith, C. D., & O’Keefe, J.

(1998). Knowing where and getting there: A human navigation network.

Science, 280(5365), 921–924. http://dx.doi.org/10.1126/science.280.5365.921.

Maguire, E. A., Valentine, E. R., Wilding, J. M., & Kapur, N. (2003). Routes to

remembering: The brains behind superior memory. Nature Neuroscience, 6(1),

90–95. http://dx.doi.org/10.1038/nn988.

Maguire, E. A., Woollett, K., & Spiers, H. J. (2006). London taxi drivers and bus

drivers: A structural MRI and neuropsychological analysis. Hippocampus, 16(12),

1091–1101. http://dx.doi.org/10.1002/hipo.20233.

Marg, E. (1952). Flashes of clear vision and negative accommodation with reference

to the Bates method of visual training. American Journal of Optometry & Archives

of American Academy of Optometry, 29(4), 167–184.

Martin, A. (2009). Brain ﬁtness industry set to boom. MarketWatch. <http://

articles.moneycentral.msn.com/Insurance/InsureYourHealth/brain-ﬁtness-

industry-set-to-boom.aspx> [Retrieved].

Martin, G., & Johnson, C. L. (2006). The Boys totem town neurofeedback project: A

pilot study of EEG biofeedback with incarcerated juvenile felons. Journal of

Neurotherapy, 9(3), 71–86. http://dx.doi.org/10.1300/J184v09n03_05.

McBurnett, K., & Pﬁffner, L. J. (2008). Attention deﬁcit hyperactivity disorder: Concepts,

controversies, new directions. New York: Informa Healthcare.

McClelland, M. M., Cameron, C. E., Connor, C. M. D., Farris, C. L., Jewkes, A. M., &

Morrison, F. J. (2007). Links between behavioral regulation and preschoolers’

literacy, vocabulary, and math skills. Developmental Psychology, 43(4), 947–959.

http://dx.doi.org/10.1037/0012-1649.43.4.947.

McEwen, S. E., Polatajko, H. J., Davis, J. A., Huijbregts, M., & Ryan, J. D. (2010). ‘There’s

a real plan here, and I am responsible for that plan’: Participant experiences

with a novel cognitive-based treatment approach for adults living with chronic

176 S. Rabipour, A. Raz/ Brain and Cognition 79 (2012) 159–179

Author's personal copy

stroke. Disability and Rehabilitation, 32(7), 541–550. http://dx.doi.org/10.3109/

09638280903180189.

McKeith, I. G., Galasko, D., Kosaka, K., Perry, E. K., Dickson, D. W., Hansen, L. A., et al.

(1996). Consensus guidelines for the clinical and pathologic diagnosis of

dementia with Lewy bodies (DLB): Report of the consortium on DLB

international workshop. Neurology, 47(5), 1113–1124.

Medalia, A., Aluma, M., Tryon, W., & Merriam, A. E. (1998). Effectiveness of attention

training in schizophrenia. Schizophrenia Bulletin, 24(1), 147–152.

Merzenich, M. (2011). Personal Communication.

Merzenich, M. M., Jenkins, W. M., Johnston, P., Schreiner, C., Miller, S. L., & Tallal, P.

(1996). Temporal processing deﬁcits of language-learning impaired children

ameliorated by training. Science, 271(5245), 77–81.

Mezzacappa, E. (2004). Alerting, orienting, and executive attention: Developmental

properties and sociodemographic correlates in an epidemiological sample of

young, urban children. Child Development, 75(5), 1373–1386.

Monastra, V. J. (2005). Electroencephalographic biofeedback (neurotherapy) as a

treatment for attention deﬁcit hyperactivity disorder: Rationale and empirical

foundation. Child and Adolescent Psychiatric Clinics of North America, 14(1),

55–82. http://dx.doi.org/10.1016/j.chc.2004.07.004.

Munte, T. F., Altenmuller, E., & Jancke, L. (2002). The musician’s brain as a model of

neuroplasticity. Nature Reviews Neuroscience, 3(6), 473–478. http://dx.doi.org/

10.1038/nrn843.

Murray-Close, D., Hoza, B., Hinshaw, S. P., Arnold, L. E., Swanson, J., Jensen, P. S., et al.

(2010). Developmental processes in peer problems of children with attention-

deﬁcit/hyperactivity disorder in the multimodal treatment study of children

with ADHD: Developmental cascades and vicious cycles. Development and

Psychopathology, 22(4), 785–802. http://dx.doi.org/10.1017/

s0954579410000465.

Nacke, L. E., Nacke, A., & Lindley, C. A. (2009). Brain training for silver gamers:

Effects of age and game form on effectiveness, efﬁciency, self-assessment, and

gameplay experience. Cyberpsychology and Behavior, 12(5), 493–499.

Naropa University (2011). Master of arts in transpersonal counseling psychology:

Wilderness therapy. In University (Ed.).

Nintendo, D. S. (2007). Brain age 2. <http://brainage.com/launch/index.jsp>.

Noble, K. G., McCandliss, B. D., & Farah, M. J. (2007). Socioeconomic gradients

predict individual differences in neurocognitive abilities. Developmental Science,

10(4), 464–480. http://dx.doi.org/10.1111/j.1467-7687.2007.00600.x.

Olesen, P. J., Westerberg, H., & Klingberg, T. (2004). Increased prefrontal and parietal

activity after training of working memory. Nature Neuroscience, 7(1), 75–79.

Ott, U., Hölzel, B.K., Vaitl, D. (2011). Brain structure and meditation. How spiritual

practice shapes the brain. Paper presented at the differences, Freiburg/Breisgau

2008.

Owen, A. M., Hampshire, A., Grahn, J. A., Stenton, R., Dajani, S., Burns, A. S., et al.

(2010). Putting brain training to the test. Nature, 465(7299), 775–U776. http://

dx.doi.org/10.1038/nature09042.

Pagnoni, G., Cekic, M., & Guo, Y. (2008). ‘‘Thinking about not-thinking’’: neural

correlates of conceptual processing during zen meditation. PLoS ONE, 3(9),

e3083.

Papp, K. V., Walsh, S. J., & Snyder, P. J. (2009). Immediate and delayed effects of

cognitive interventions in healthy elderly: A review of current literature and

future directions. Alzheimer’s and Dementia, 5(1), 50–60. http://dx.doi.org/

10.1016/j.jalz.2008.10.008.

Park, N. W., & Ingles, J. L. (2001). Effectiveness of attention rehabilitation after an

acquired brain injury: A meta-analysis. Neuropsychology, 15(2), 199–210. http://

dx.doi.org/10.1037/0894-4105.15.2.199.

Park, M. H., Kwon, D. Y., Seo, W. K., Lim, K. S., & Song, M. S. (2009). The effects of

cognitive training on community-dwelling elderly Koreans. Journal of

Psychiatric and Mental Health Nursing, 16(10), 904–909. http://dx.doi.org/

10.1111/j.1365-2850.2009.01467.x.

Paul, G. L. (1969). Physiological effects of relaxation training and hypnotic

suggestion. Journal of Abnormal Psychology, 74(4), 425.

Pearson (2011). Cogmed. <http://www.cogmed.com/>.

Pelc, K., Kornreich, C., Foisy, M. L., & Dan, B. (2006). Recognition of emotional facial

expressions in attention-deﬁcit hyperactivity disorder. Pediatric Neurology,

35(2), 93–97. http://dx.doi.org/10.1016/j.peidatrneurol.2006.01.014.

Peterson, B. S., & Cohen, D. J. (1998). The treatment of Tourette’s syndrome:

Multimodal, developmental intervention. Journal of Clinical Psychiatry, 59,

62–74.

Phelps, L. A. (2008). Tourette’s disorder: Genetic update, neurological correlates,

and evidence-based interventions. School Psychology Quarterly, 23(2), 282–289.

http://dx.doi.org/10.1037/1045-3830.23.2.282.

Piacentini, J., Woods, D. W., Scahill, L., Wilhelm, S., Peterson, A. L., Chang, S., et al.

(2010). Behavior therapy for children with Tourette disorder a randomized

controlled trial. [article]. JAMA: Journal of the American Medical Association,

303(19), 1929–1937.

Posner, M. I., Rothbart, M. K., Sheese, B. E., & Voelker, P. (2011). Control networks

and neuromodulators of early development. Developmental Psychology.

Posner, M. I., & Petersen, S. E. (1990). The attention system of the human brain.

Annual Review of Neuroscience, 13, 25–42.

Posner, M. I., & Rothbart, M. K. (2007a). Research on attention networks as a model

for the integration of psychological science. Annual Review of Psychology, 58.

Posner, M. I., & Rothbart, M. K. (2007b). Educating the human brain (1st ed.).

Washington, DC: American Psychological Association.

Posner, M. I., & Rothbart, M. K. (2011). Brain states and hypnosis research.

Consciousness and Cognition, 20(2), 325–327. http://dx.doi.org/10.1016/

j.concog.2009.11.008.

Pressley, M. (1979). Increasing children’s self-control through cognitive

interventions. Review of Educational Research, 49(2), 319–370.

Rabiner, D. L., Murray, D. W., Skinner, A. T., & Malone, P. S. (2010). A randomized

trial of two promising computer-based interventions for students with

attention difﬁculties. Journal of Abnormal Child Psychology, 38(1), 131–142.

http://dx.doi.org/10.1007/s10802-009-9353-x.

Raffone, A., & Srinivasan, N. (2010). The exploration of meditation in the

neuroscience of attention and consciousness. Cognitive Processing, 11(1), 1–7.

http://dx.doi.org/10.1007/s10339-009-0354-z.

Rauscher, F. H., Shaw, G. L., Levine, L. J., Wright, E. L., Dennis, W. R., & Newcomb, R. L.

(1997). Music training causes long-term enhancement of preschool children’s

spatial–temporal reasoning. Neurological Research, 19(1), 2–8.

Raz, A. (in press). Translational attention: From experiments in the lab to helping

the symptoms of individuals with Tourette’s syndrome. Consciousness and

Cognition.

Raz, A., & Buhle, J. (2006). Typologies of attentional networks. Nature Reviews

Neuroscience, 7(5), 367–379.

Raz, A., Keller, S., Norman, K., & Senechal, D. (2007). Elucidating Tourette’s

syndrome: Perspectives from hypnosis, attention and self-regulation. The

American Journal of Clinical Hypnosis, 49(4), 289–309.

Raz, A., Marinoff, G. P., Zephrani, Z. R., Schweizer, H. R., & Posner, M. I. (2004). See

clearly: Suggestion, hypnosis, attention, and visual acuity. International Journal

of Clinical and Experimental Hypnosis, 52(2), 159–187.

Raz, A. (2004). Atypical attention: Hypnosis and conﬂict reduction. In Posner (Ed.),

Cognitive neuroscience of attention. New York: Guilford Press.

Robertson, M. M. (2003). Diagnosing Tourette syndrome – Is it a common disorder?

Journal of Psychosomatic Research, 55(1), 3–6. http://dx.doi.org/10.1016/s0022-

3999(02)00580-9.

Robertson, I. H., Tegner, R., Tham, K., Lo, A., & Nimmosmith, I. (1995). Sustained

attention training for unilateral neglect – Theoretical and rehabilitation

implications. Journal of Clinical and Experimental Neuropsychology, 17(3),

416–430.

Rodriguez, A., Jaervelin, M. R., Obel, C., Taanila, A., Miettunen, J., Moilanen, I., et al.

(2007). Do inattention and hyperactivity symptoms equal scholastic

impairment? Evidence from three European cohorts. Bmc Public Health, 7.

http://dx.doi.org/10.1186/1471-2458-7-327.

Rossiter, T. R., & LaVaqe, T. J. (1995). A comparison of EEG biofeedback and

psychostimulants in treating attention deﬁcit/hyperactivity disorders. Journal of

Neurotherapy, 1(1), 48–59.

Rubia, K. (2009). The neurobiology of meditation and its clinical effectiveness in

psychiatric disorders. Biological Psychology, 82(1), 1–11. http://dx.doi.org/

10.1016/j.biopsycho.2009.04.003.

Rueda, M. R., Fan, J., McCandliss, B. D., Halparin, J. D., Gruber, D. B., Lercari, L. P., et al.

(2004). Development of attentional networks in childhood. Neuropsychologia,

42(8), 1029–1040. http://dx.doi.org/10.1016/j.neuropsychologia.2003.12.012.

Rueda, M. R., Posner, M. I., & Rothbart, M. K. (2005). The development of executive

attention: Contributions to the emergence of self-regulation. Developmental

Neuropsychology, 28(2), 573–594.

Rueda, M. R., Posner, M. I., Rothbart, M. K., & Davis-Stober, C. P. (2004). Development

of the time course for processing conﬂict: An event-related potentials study

with 4 year olds and adults. BMC Neuroscience, 5.http://dx.doi.org/10.1186/

1471-2202-5-39.

Rueda, M. R., Rothbart, M. K., McCandliss, B. D., Saccomanno, L., & Posner, M. I.

(2005). Training, maturation, and genetic inﬂuences on the development of

executive attention. Proceedings of the National Academy of Sciences of the United

States of America, 102(41), 14931–14936. http://dx.doi.org/10.1073/

pnas.0506897102.

Ruff, H. A., & Rothbart, M. K. (1996). Attention in early development: Themes and

variations. Oxford University Press.

Schachar, R. J., Tannock, R., & Logan, G. (1993). Inhibitory control, impulsiveness, and

attention-deﬁcit hyperactivity disorder. Clinical Psychology Review, 13(8), 721–739.

Schellenberg, E. G. (2004). Music lessons enhance IQ. Psychological Science, 15(8),

511–514. http://dx.doi.org/10.1111/j.0956-7976.2004.00711.x.

Scholz, J., Klein, M. C., Behrens, T. E. J., & Johansen-Berg, H. (2009). Training induces

changes in white-matter architecture. Nature Neuroscience, 12(11), 1370–1371.

http://dx.doi.org/10.1038/nn.2412. <http://www.nature.com/neuro/journal/

v12/n11/suppinfo/nn.2412_S1.html>.

Schultz Center for Teaching and Leadership (2009). Fast ForWord Longitudinal

Impact Study Jacksonville, FL. <http://www.schultzcenter.org/pdf/

fast_forword_brief.pdf> [Retrieved].

Scientiﬁc Learning Corporation (2011). Scientiﬁc learning: Fit brains learn better.

<http://www.scilearn.com/>.

Semrud-Clikeman, M., & Ellison, P. A. T. (2009). Language-related and learning

disorders child neuropsychology. US: Springer, pp. 275–327.

Shackman, A. J., Salomons, T. V., Slagter, H. A., Fox, A. S., Winter, J. J., & Davidson, R. J.

(2011). The integration of negative affect, pain and cognitive control in the

cingulate cortex. Nature Reviews Neuroscience, 12(3), 154–167. http://dx.doi.org/

10.1038/nrn2994. <http://www.nature.com/nrn/journal/v12/n3/suppinfo/

nrn2994_S1.html>.

Shalev, L., Tsal, Y., & Mevorach, C. (2007). Computerized progressive attentional

training (CPAT) program: Effective direct intervention for children with ADHD.

Child Neuropsychology, 13(4), 382–388. http://dx.doi.org/10.1080/

09297040600770787.

Shaw, C. A., Lanius, R. A., & Vandendoel, K. (1994). The origin of synaptic

neuroplasticity – Crucial molecules or a dynamical cascade. Brain Research

Reviews, 19(3), 241–263. http://dx.doi.org/10.1016/0165-0173(94)90014-0.

S. Rabipour, A. Raz/ Brain and Cognition 79 (2012) 159–179 177

Author's personal copy

Sheese, B. E., Rothbart, M. K., Posner, M. I., White, L. K., & Fraundorf, S. H. (2008).

Executive attention and self-regulation in infancy. Infant Behavior and

Development, 31(3), 501–510. http://dx.doi.org/10.1016/j.infbeh.2008.02.001.

Shipstead, Z., Redick, T. S., & Engle, R. W. (2010). Does working memory training

generalize? Psychologica Belgica, 50(3–4), 245–276.

Singer, H. S., & Walkup, J. T. (1991). Tourette syndrome and other tic disorders –

Diagnosis, pathophysiology and treatment. Medicine, 70(1), 15–32.

Singh, N., Singh, A., Lancioni, G., Singh, J., Winton, A., & Adkins, A. (2010).

Mindfulness training for parents and their children with ADHD increases the

children’s compliance. Journal of Child and Family Studies, 19(2), 157–166. http://

dx.doi.org/10.1007/s10826-009-9272-z.

Skidmore, E. R., Holm, M. B., Whyte, E. M., Dew, M. A., Dawson, D., & Becker, J. T.

(2011). The feasibility of meta-cognitive strategy training in acute inpatient

stroke rehabilitation: Case report. Neuropsychological Rehabilitation, 21(2),

208–223.

Slagter, H. A., Davidson, R. J., & Lutz, A. (2011). Mental training as a tool in the

neuroscientiﬁc study of brain and cognitive plasticity [hypothesis & theory].

Frontiers in Human Neuroscience, 5.http://dx.doi.org/10.3389/fnhum.2011.00017.

Smith, G. E., Housen, P., Yaffe, K., Ruff, R., Kennison, R. F., Mahncke, H. W., et al.

(2009). A cognitive training program based on principles of brain plasticity:

Results from the improvement in memory with plasticity-based adaptive

cognitive training (IMPACT) study. Journal of the American Geriatrics Society,

57(4), 594–603. http://dx.doi.org/10.1111/j.1532-5415.2008.02167.x.

Snyder, P. (2011). Personal Communication.

Sohlberg, M. M., & Mateer, C. A. (1987). Effectiveness of an attention-training

program. Journal of Clinical and Experimental Neuropsychology, 9(2), 117–130.

Sokhadze, T. M., Cannon, R. L., & Trudeau, D. L. (2008). EEG biofeedback as a

treatment for substance use disorders: Review, rating of efﬁcacy, and

recommendations for further research. Applied Psychophysiology Biofeedback,

33(1), 1–28.

Solanto, M., Newcorn, J., Vail, L., Gilbert, S., Ivanov, I., & Lara, R. (2009). Stimulant

drug response in the predominantly inattentive and combined subtypes of

attention-deﬁcit/hyperactivity disorder. Journal of Child and Adolescent

Psychopharmacology, 19(6), 663–671. http://dx.doi.org/10.1089/cap.2009.0033.

Spencer, T. J., Biederman, J., Wilens, T. E., & Faraone, S. V. (2002). Overview and

neurobiology of attention-deﬁcit/hyperactivity disorder. Journal of Clinical

Psychiatry, 63, 3–9.

Steele, K. M., Bass, K. E., & Crook, M. D. (1999). The mystery of the Mozart effect:

Failure to replicate. Psychological Science, 10(4), 366–369. http://dx.doi.org/

10.1111/1467-9280.00169.

Steinhausen, H. C. (2009). The heterogeneity of causes and courses of attention-

deﬁcit/hyperactivity disorder. Acta Psychiatrica Scandinavica, 120(5), 392–399.

http://dx.doi.org/10.1111/j.1600-0447.2009.01446.x.

Stevens, C., Fanning, J., Coch, D., Sanders, L., & Neville, H. (2008). Neural mechanisms

of selective auditory attention are enhanced by computerized training:

Electrophysiological evidence from language-impaired and typically

developing children. Brain Research, 1205, 55–69. http://dx.doi.org/10.1016/

j.brainres.2007.10.108.

Stevens, C., Lauinger, B., & Neville, H. (2009). Differences in the neural mechanisms

of selective attention in children from different socioeconomic backgrounds: An

event-related brain potential study. Developmental Science, 12(4), 634–646.

http://dx.doi.org/10.1111/j.1467-7687.2009.00807.x.

Stossel, T. P. (2007). Regulation of ﬁnancial conﬂicts of interest in medical practice

and medical research – A damaging solution in search of a problem. Perspectives

in Biology and Medicine, 50(1), 54–71.

Stossel, T. P. (2008). A biopsy of ﬁnancial conﬂicts of interest in medicine. Surgery,

143(2), 193–198. http://dx.doi.org/10.1016/j.surg.2007.11.013.

Strine, T. W., Lesesne, C. A., Okoro, C. A., McGuire, L. C., Chapman, D. P., Balluz, L. S.,

et al. (2006). Emotional and behavioral difﬁculties and impairments in everyday

functioning among children with a history of attention-deﬁcit/hyperactivity

disorder. Preventing Chronic Disease, 3(2), A52.

Stroop, J. R. (1935). Studies of interference in serial verbal reactions. Journal of

Experimental Psychology, 18, 643–662.

Stuss, D. T., Winocur, G., & Robertson, I. H. (1999). Cognitive neurorehabilitation.

Cambridge University Press.

Swain, J. E., Scahill, L., Lombroso, P. J., King, R. A., & Leckman, J. F. (2007). Tourette

syndrome and tic disorders: A decade of progress. Journal of the American

Academy of Child and Adolescent Psychiatry, 46(8), 947–968. http://dx.doi.org/

10.1097/chi.0b013e318068fbcc.

Swanson, J., Baler, R. D., & Volkow, N. D. (2011). Understanding the effects of

stimulant medications on cognition in individuals with attention-deﬁcit

hyperactivity disorder: A decade of progress. Neuropsychopharmacology, 36(1),

207–226. http://dx.doi.org/10.1038/npp.2010.160.

Sylvan Learning (2011). Sylvan learning. <http://tutoring.sylvanlearning.com/

index.cfm>.

Szobot, C. M., Roman, T., Hutz, M. H., Genro, J. P., Shih, M. C., Hoexter, M. Q., et al.

(2011). Molecular imaging genetics of methylphenidate response in ADHD and

substance use comorbidity. Synapse (New York, NY), 65(2), 154–159. http://

dx.doi.org/10.1002/syn.20829.

Tamm, L., McCandliss, B., Liang, A., Wigal, T. L., Posner, M. I., & Swanson, J. M. (2008).

Can attention itself be trained? Attention training for children at-risk for ADHD.

In McBurnett & Pﬁffer (Eds.), Attention deﬁcit hyperactivity disorder: Concepts,

controversies, new directions. New York, NY: Informa Healthcare.

Tan, G., Thornby, J., Hammond, D. C., Strehl, U., Canady, B., Arnemann, K., et al.

(2009). Meta-analysis of EEG biofeedback in treating epilepsy. Clinical EEG and

Neuroscience, 40(3), 173–179.

Tang, Y. Y., Lu, Q. L., Geng, X. J., Stein, E. A., Yang, Y. H., & Posner, M. I. (2010). Short-

term meditation induces white matter changes in the anterior cingulate.

Proceedings of the National Academy of Sciences of the United States of America,

107(35), 15649–15652. http://dx.doi.org/10.1073/pnas.1011043107.

Tang, Y. Y., Ma, Y. H., Wang, J., Fan, Y. X., Feng, S. G., Lu, Q. L., et al. (2007). Short-term

meditation training improves attention and self-regulation. Proceedings of the

National Academy of Sciences of the United States of America, 104(43),

17152–17156.

Tang, Y. Y., & Posner, M. I. (2009). Attention training and attention state training.

Trends in Cognitive Sciences, 13(5), 222–227. http://dx.doi.org/10.1016/

j.tics.2009.01.009.

Taylor, A. F., & Kuo, F. E. (2009). Children with attention deﬁcits concentrate better

after walk in the park. Journal of Attention Disorders, 12(5), 402–409. http://

dx.doi.org/10.1177/1087054708323000.

Taylor, A. F., Kuo, F. E., & Sullivan, W. C. (2001). Coping with add. Environment and

Behavior, 33(1), 54–77. http://dx.doi.org/10.1177/00139160121972864.

Taylor, A. F., Kuo, F. E., & Sullivan, W. C. (2002). Views of nature and self-discipline:

Evidence from inner city children. Journal of Environmental Psychology, 22(1–2),

49–63. http://dx.doi.org/10.1006/jevp. 2001.0241.

Teicher, M. H., Andersen, S. L., Polcari, A., Anderson, C. M., Navalta, C. P., & Kim, D. M.

(2003). The neurobiological consequences of early stress and childhood

maltreatment. Neuroscience and Biobehavioral Reviews, 27(1–2), 33–44. http://

dx.doi.org/10.1016/s0149-7634(03)00007-1.

Tesky, V. A., Thiel, C., Banzer, W., & Pantel, J. (2011). Effects of a group program to

increase cognitive performance through cognitively stimulating leisure

activities in healthy older subjects. GeroPsych: The Journal of

Gerontopsychology and Geriatric Psychiatry, 24(2), 83–92.

The MTA CooperativeGroup (1999). A 14-monthrandomized clinicaltrial of treatment

strategies for attention-deﬁcit/hyperactivity disorder. Archives of General

Psychiatry, 56(12), 1073–1086. http://dx.doi.org/10.1001/archpsyc.56.12.1073.

Thorell, L. B., Lindqvist, S., Bergman Nutley, S., Bohlin, G., & Klingberg, T. (2009).

Training and transfer effects of executive functions in preschool children.

Developmental Science, 12(1), 106–113. http://dx.doi.org/10.1111/j.1467-

7687.2008.00745.x.

Tilburt, J. C., Emanuel, E. J., Kaptchuk, T. J., Curlin, F. A., & Miller, F. G. (2008).

Prescribing ‘‘placebo treatments’’: Results of national survey of US internists

and rheumatologists. British Medical Journal, 337.http://dx.doi.org/10.1136/

bmj.a1938.

Tsianos, N., Germanakos, P., Lekkas, Z., Mourlas, C., & Samaras, G. (2010). Working

memory span and e-learning: The effect of personalization techniques on

learners’ performance. User Modeling, Adaptation, and Personalization,

Proceedings, 6075, 64–74.

Tuckman, B. W., & Hinkle, J. S. (1986). An experimental study of the physical and

psychological effects of aerobic exercise on schoolchildren. Health Psychology,

5(3), 197–207. http://dx.doi.org/10.1037/0278-6133.5.3.197.

Turner, E. H., Matthews, A. M., Linardatos, E., Tell, R. A., & Rosenthal, R. (2008).

Selective publication of antidepressant trials and its inﬂuence on apparent

efﬁcacy. New England Journal of Medicine, 358(3), 252–260. 10.1056/

NEJMsa065779.

Valentine, E. R., & Sweet, P. L. G. (1999). Meditation and attention: A comparison of

the effects of concentrative and mindfulness meditation on sustained attention.

Mental Health, Religion & Culture, 2(1), 59–70. http://dx.doi.org/10.1080/

13674679908406332.

Wallis, D., Russell, H. F., & Muenke, M. (2008). Review: Genetics of attention deﬁcit/

hyperactivity disorder. Journal of Pediatric Psychology, 33(10), 1085–1099.

http://dx.doi.org/10.1093/jpepsy/jsn049.

Walsh, R., & Shapiro, S. L. (2006). The meeting of meditative disciplines and Western

psychology – A mutually enriching dialogue. American Psychologist, 61(3),

227–239. http://dx.doi.org/10.1037/0003-066x.61.3.227.

Weaver, I. C. G., Cervoni, N., Champagne, F. A., D’Alessio, A. C., Sharma, S., Seckl, J. R.,

et al. (2004). Epigenetic programming by maternal behavior. Nature

Neuroscience, 7(8), 847–854. http://dx.doi.org/10.1038/nn1276. <http://

www.nature.com/neuro/journal/v7/n8/suppinfo/nn1276_S1.html>.

Wells, N. M. (2000). At home with nature: Effects of ‘‘greenness’’ on children’s

cognitive functioning. Environment and Behavior, 32(6), 775–795. http://

dx.doi.org/10.1177/00139160021972793.

Wells, K. C. (2008). Parent training in the treatment of ADHD. Attention deﬁcit

hyperactivity disorder: Concepts, controversies, new directions: Informa

Healthcare.

Wells, N. M., & Evans, G. W. (2003). Nearby nature. Environment and Behavior, 35(3),

311–330. http://dx.doi.org/10.1177/0013916503035003001.

Westerberg, H., Jacobaeus, H., Hirvikoski, T., Clevberger, P., Östensson, M. L., Bartfai,

A., et al. (2007). Computerized working memory training after stroke – A pilot

study. Brain Injury, 21(1), 21–29.

Westerberg, H., & Klingberg, T. (2007). Changes in cortical activity after training of

working memory – A single-subject analysis. Physiology & Behavior, 92(1–2),

186–192. http://dx.doi.org/10.1016/j.physbeh.2007.05.041.

Whalen, C., & Schreibman, L. (2003). Joint attention training for children with

autism using behavior modiﬁcation procedures. Journal of Child Psychology and

Psychiatry and Allied Disciplines, 44(3), 456–468.

Willcutt, E. G., Pennington, B. F., Olson, R. K., Chhabildas, N., & Hulslander, J. (2005).

Neuropsychological analyses of comorbidity between reading disability and

attention deﬁcit hyperactivity disorder: In search of the common deﬁcit.

Developmental Neuropsychology, 27(1), 35–78.

Willcutt, E. G., Pennington, B. F., Olson, R. K., & DeFries, J. C. (2007). Understanding

comorbidity: A twin study of reading disability and attention-deﬁcit/

178 S. Rabipour, A. Raz/ Brain and Cognition 79 (2012) 159–179

Author's personal copy

hyperactivity disorder. American Journal of Medical Genetics Part B –

Neuropsychiatric Genetics, 144B(6), 709–714. http://dx.doi.org/10.1002/

ajmg.b.30310.

Wolinsky, F. D., Unverzagt, F. W., Smith, D. M., Jones, R., Wright, E., & Tennstedt, S. L.

(2006). The effects of the ACTIVE cognitive training trial on clinically relevant

declines in health-related quality of life. Journals of Gerontology – Series B

Psychological Sciences and Social Sciences, 61(5), S281–S287.

Woods, D. W., Piacentini, J. C., Scahill, L., Peterson, A. L., Wilhelm, S., Chang, S., et al.

(2011). Behavior therapy for tics in children: Acute and long-term effects on

psychiatric and psychosocial functioning. Journal of Child Neurology, 26(7),

858–865. http://dx.doi.org/10.1177/0883073810397046.

Yaffe, K., Barnes, D., Nevitt, M., Lui, L. Y., & Covinsky, K. (2001). A prospective study

of physical activity and cognitive decline in elderly women: Women who walk.

Archives of Internal Medicine, 161(14), 1703–1708.

Zanetti, O., Binetti, G., Magni, E., Rozzini, L., Bianchetti, A., & Trabucchi, M. (1997).

Procedural memory stimulation in Alzheimer’s disease: Impact of a training

programme. Acta Neurologica Scandinavica, 95(3), 152–157. http://dx.doi.org/

10.1111/j.1600-0404.1997.tb00087.x.

Zeidan, F., Johnson, S. K., Gordon, N. S., & Goolkasian, P. (2010). Effects of brief and

sham mindfulness meditation on mood and cardiovascular variables. The

Journal of Alternative and Complementary Medicine, 16(8), 867–873. http://

dx.doi.org/10.1089/acm.2009.0321.

Zylowska, L., Ackerman, D. L., Yang, M. H., Futrell, J. L., Horton, N. L., Hale, T. S., et al.

(2008). Mindfulness meditation training in adults and adolescents with ADHD a

feasibility study. Journal of Attention Disorders, 11(6), 737–746. 10.1177/

1087054707308502.

S. Rabipour, A. Raz/ Brain and Cognition 79 (2012) 159–179 179

Efficacy of The Secret Trail of Moon (MOON) a personalized treatment video game for children and adolescents with ADHD based on cognitive training and emotional regulation: Protocol for a randomized clinical trial. (Preprint)

Article

Full-text available

Sep 2023

Background Attention deficit hyperactivity disorder (ADHD) is the most common neurodevelopmental disorder in childhood and adolescence, with a prevalence of 5% and associated difficulties and worse prognosis if undetected. Multimodal treatment is the treatment of choice. However, sometimes treatment can be insufficient or have drawbacks. Objective This study protocol aims to demonstrate the effectiveness of cognitive training through the serious video game The Secret Trail of Moon (MOON) in improving emotional regulation in people with ADHD. Methods This is a prospective, unicenter, randomized, unblinded, pre- and postintervention study. The groups will be randomized (MOON vs control) via an electronic case report form. The MOON intervention will be performed 2 times per week for 10 weeks (30 minutes per session). The first 5 weeks (10 sessions) will be conducted face-to-face at the Puerta de Hierro University Hospital, and the remaining weeks will be conducted via the internet at the participants’ homes. The total sample consists of 152 patients aged between 7 and 18 years. All participants have a clinical diagnosis of ADHD under pharmacological treatment. Data collection will be used to obtain demographic and clinical data. The data will be recorded using REDCap. Measures will be made through clinical scales for parents and objective tests of cognitive functioning in patients. Additional information on academic performance will be collected. The study has a power greater than 80% to detect differences. Student t test, 2-factor analysis of variance (ANOVA), and Mann-Whitney analyses will be performed according to each variable’s characteristics. Results The study was approved by the Research Ethics Committee of the Puerta de Hierro University Hospital on December 14, 2022. As of September 26, 2023, we have enrolled 62 participants, and 31 participants have completed the study. This clinical trial was funded by the Comunidad de Madrid (IND2020/BMD-17544). The approximate completion date is March 2024. Conclusions Serious video games such as MOON can be motivational tools that complement multimodal treatment for ADHD. Trial Registration ClinicalTrials.gov; NCT06006871; https://clinicaltrials.gov/study/NCT06006871 International Registered Report Identifier (IRRID) DERR1-10.2196/53191

Cognitive Training and Rehabilitation in AgingYaşlanmada Bilişsel Egzersiz ve Rehabilitasyon

Article

Full-text available

Mar 2024

Aging is a life stage in which progressive deterioration occurs in biological, psychological, and socio-cultural processes. Therefore, along with all the other changes observed in aging, cognitive change is inevitable. In older adulthood, the speed of processing information, the ability to remember contextual information such as where and when events occur, and executive function performance are impaired. Moreover, this change in cognitive processes causes the deterioration of functionality in daily life. Although it is well known that physical activity, nutrition, and social support play a key role in preventing the adverse effects of aging, the impact of cognitive training and rehabilitation have been relatively less studied. This review aims to examine cognitive training and rehabilitation practices applied to different cognitive processes (episodic memory, working memory, executive functions, attention and processing speed) to help compensate for or regain cognitive functions that are impaired in older adults. In this context, the effectiveness of the practices, the transfer of gains to different cognitive areas, and whether they are preserved for long periods were examined. The contribution of conscious and systematic practices, such as cognitive training and rehabilitation, in reducing the adverse effects of aging has been discussed.

Non-pharmacological treatment of Attention Deficit Disorder with or without Hyperactivity (ADHD). Overview and report of the first international symposium on the non-pharmacological management of ADHD

Article

Full-text available

Feb 2024
ENCEPHALE

tAttention Deficit Disorder with or without Hyperactivity (ADHD is a neurodevelopmental disorder which affects the day-to-day functioning of children and adults with this condition. Pharmacological treatment can reduce the symptoms associated with ADHD, but it has some limitations. The objective of this symposium is to determine the effects of non-pharmacological approaches on ADHD symptoms. Results indicate that the following intervention are promising approaches: cognitive behavioral therapy (CBT),mindfulness-based interventions (MBI), yoga, cognitive and metacognitive intervention, neurofeedback and parental training programs. Current research advocates multimodal approaches in conjunction with school or work accommodations integrating innovative technologies.

Executive control training for adolescents with ADHD: Study protocol for a randomized controlled trial

Article

Dec 2023
CONTEMP CLIN TRIALS

Preprint

Sep 2023

BACKGROUND Attention Deficit Hyperactivity Disorder (ADHD) is the most common neurodevelopmental disorder in childhood and adolescence (5%) with associated difficulties and worse prognosis if undetected. Multimodal treatment is the treatment of choice; however, sometimes treatment can be insufficient or have some drawbacks. OBJECTIVE To demonstrate the effectiveness of cognitive training through the serious video game “The Secret Trail of Moon” (MOON) in improving emotional regulation of people with ADHD. METHODS Design: prospective, unicenter, randomized, unblinded, PRE-POST intervention study. Randomization of the groups (MOON vs. Control) will be performed by electronic CRD. The MOON intervention will be performed 2 times per week for 10 weeks (30 minutes per session). The first five weeks (10 sessions) will be conducted face-to-face in Puerta de Hierro University Hospital; the remaining weeks will be conducted online at the participants' home. The clinical trial was registered in Clinical Trials NCT06006871. Sample: 152 patients aged between 7 and 18 years. All participants had a clinical diagnosis of ADHD (CGI between 3 and 6) under pharmacological treatment. Evaluation: Data collection will be used to obtain demographic and clinical data. The data will be recorded with an electronic CRD (REDCap). Measures will be made through clinical scales for parents and objective tests of cognitive functioning in patients. Additional information on academic performance will be collected. Statistical power analysis: The study has a power greater than 80% to detect differences. Statistical analysis: Classical statistics: T student, 2-factor ANOVA and Mann Whitney analyses will be performed according to the characteristics of each variable. Ethics: The study was approved by the Research Ethics Committee of the Puerta de Hierro University Hospital on December 14th, 2022. The authorization of the Spanish Agency of Medicines and Health Products was February 14th, 2023. Informed consent will be requested from legal guardians and minors protecting their personal data to the provisions of the Organic Law 3/2018 of 5 December, on Personal Data Protection and guarantee of digital rights. RESULTS To September 26, 2023, we have enrolled 62 participants. Thirty-one participants have completed the study. This clinical trial has been funded by the Comunidad de Madrid (Spain) IND2020/BMD-17544. The approximate completion date is March 2024. CONCLUSIONS Serious video games such as MOON can be motivational tools that complement multimodal treatment in ADHD. CLINICALTRIAL NCT06006871

New insight of exercise on dementia; combinatory effects of physical and cognitive exercise

Article

Apr 2024

Dementia is a progressive neurological disorder which is clinically characterized by memory loss, behavioral symptoms, and loss of ability to live a normal life. Dementia patients may have to cope with permanent and irreversible symptoms. Although a new drug for dementia with beta-amyloid-removal function has recently received FDA approval, the effect of delaying the progression of dementia is still insignificant, but the cost is expensive. On the other hand, studies on the effects of exercise in dementia have implied that the incidence of dementia or cognitive decline could be efficiently controlled by exercise. The cognitive neuroprotective effect of exercise was supported by cross-sectional studies in which physically fit seniors showed larger hippocampal or gray matter volumes than unfit seniors. In addition, multiple animal studies demonstrate that exercise promotes neuroplasticity through induction of neurotropic factors, with improved outcomes on cognitive functions. In this review, we discuss the effects of conventional mode of physical exercise, cognitive (neuromuscular) exercise, and combined exercise in the prevention of dementia, and highlight the prospects for new exercise programs using digital technology that are being recently developed to reduce cognitive decline. Exercise should be importantly considered as a non-pharmacological therapeutic strategy for cognitive decline and dementia.

Effectiveness of Cognitive Interventions Based on New Technologies on Cognitive Function of Children with Attention-Deficit/Hyperactivity Disorder in Iran: A Meta-Analysis Study

Article

Full-text available

Jun 2023

Lifestyle Factors and Cognitive Health

Chapter

Feb 2024

Ranjit Singha

This examination challenges the idea that mental health is exclusively influenced by genetic predisposition and aging. Lifestyle decisions substantially influence cognitive health, with social interaction, environmental influences, nutrition, physical activity, sleep quality, and stress management all playing pivotal roles. Meaningful social connections, a supportive environment, regular exercise, a balanced diet, adequate rest, and stress reduction are all associated with mental resilience. Although cognitive training programs exhibit potential, continuous evaluation remains imperative. An all-encompassing approach that considers emergent technologies in addition to socioeconomic and environmental variables is consistent with shifting viewpoints regarding cognitive well-being. The advancement of cognitive capacities and mental well-being is intergenerational, impacted by habitual decisions, healthy conduct, and nurturing surroundings on both the individual and societal scales.

Comparing the Effectiveness of Cognitive Rehabilitation Therapy and Mindfulness-Based Therapy on the Anxiety of Patients With Hypertension: A Randomized Clinical Trial

Article

Full-text available

Nov 2022

Background & Objectives: Hypertension is one of the most common chronic diseases in the world. It is considered one of the most important public health issues in the world and causes millions of deaths due to stroke and cardiovascular and kidney diseases. Research shows that people with hypertension suffer psychological, emotional, and social challenges. Stress, depression, and anxiety are among the most common psychological problems in this group of patients. Cognitive rehabilitation therapy and mindfulness-based therapy are among the treatments that studies have shown can affect anxiety. Therefore, the present study was conducted to compare the effects of cognitive rehabilitation therapy and mindfulness-based therapy on the anxiety of patients with hypertension. Methods: This double-blind clinical trial and quasi-experimental study has a pretest-posttest and follow-up design with a control group. The statistical population consisted of all the people with hypertension living in Rasht City, Iran, who were referred to the specialized heart hospital in the city in 2021. From this community, 51 qualified volunteers entered the study by the convenience sampling method and were randomly assigned to groups of cognitive rehabilitation therapy, mindfulness-based therapy, and control group (17 people in each group). The inclusion criteria were as follows: informed consent and willingness to participate in the research, having high blood pressure (according to the medical record), anxiety more than average (anxiety score 16-40 according to the Beck Anxiety Inventory), ability to read and write, age range from 30 to 60 years, not abusing drugs and alcohol, not suffering from severe personality and clinical disorders, lacking a history of head trauma and recent brain injuries, not receiving electric shock or special treatment in the last six months, and not participating in psychotherapy courses at the same time or in the last two months. The exclusion criteria were as follows: absence of more than two sessions, unwillingness to continue psychotherapy, a possible complication of the subject and the occurrence of an accident and the absence or event affecting the research variables. Beck Anxiety Inventory (Beck et al., 1988) was employed in this research. Cognitive rehabilitation therapy was conducted face-to-face and individually for the first experimental group (using the computer in 10 sessions of 60 minutes once a week) at the Cardiovascular Diseases Research Center located in Heshmat Hospital in Rasht. Mindfulness-based therapy sessions were held for 2 months (8 sessions, one 90-minute session each week) for another experimental group online (through Skyroom software) and the control group did not undergo any type of psychotherapy at the same time. For data analysis in descriptive statistics, mean and standard deviation chart were used. For inferential statistics, the Chi-square test, 1-way analysis of variance, analysis of variance of repeated measurements, and Bonferroni post hoc test were used. Data analysis was done in SPSS software version 26 at a significance level of 0.05. Results: The results showed that the effects of time (p<0.001), group (p<0.001), and the interaction of group and time (p<0.001) on the anxiety variable were significant. The posttest (p<0.001) and follow-up scores (p<0.001) of the anxiety variable in the mindfulness group and cognitive rehabilitation group decreased significantly compared to the pretest scores. In contrast, there was no significant difference between the anxiety scores of the control group at different times (p>0.05). There was a significant difference between cognitive rehabilitation and mindfulness groups in terms of effectiveness in the posttest and follow-up on reducing anxiety compared to the control group (p<0.001). While there was no significant difference between the two experimental groups in the posttest (p=0.616) and follow-up (p=0.221) in terms of effectiveness in reducing anxiety. Conclusion: According to the research findings, cognitive rehabilitation therapy and mindfulness-based therapy were effective on the anxiety of patients with hypertension, and there was no significant difference between the two therapies. Therefore, both types of psychotherapies are equally beneficial to help patients with hypertension manage a chronic and life-threatening disease.

Tele-Neuropsychology: From Science to Policy to Practice

Article

Sep 2023
ARCH CLIN NEUROPSYCH

Objective: The primary aim of this paper is to accelerate the number of randomized experimental studies of the reliability and validity in-home tele-neuropsychological testing (tele-np-t). Method: We conducted a critical review of the tele-neuropsychology literature. We discuss this research in the context of the United States' public and private healthcare payer systems, including the Centers for Medicare & Medicaid Services (CMS) and Current Procedural Terminology (CPT) coding system's telehealth lists, and existing disparities in healthcare access. Results: The number of tele-np publications has been stagnant since the onset of the COVID-19 pandemic. There are less published experimental studies of tele-neuropsychology (tele-np), and particularly in-home tele-np-t, than other tele-np publications. There is strong foundational evidence of the acceptability, feasibility, and reliability of tele-np-t, but relatively few studies of the reliability and validity of in-home tele-np-t using randomization methodology. Conclusions: More studies of the reliability and validity of in-home tele-np-t using randomization methodology are necessary to support inclusion of tele-np-t codes on the CMS and CPT telehealth lists, and subsequently, the integration and delivery of in-home tele-np-t services across providers and institutions. These actions are needed to maintain equitable reimbursement of in-home tele-np-t services and address the widespread disparities in healthcare access.

Mindfulness-Based Approaches with Children and Adolescents: A Preliminary Review of Current Research in an Emergent Field

Article

Full-text available

Feb 2010
J Child Fam Stud

Christine Burke

Interest in applications of mindfulness-based approaches with adults has grown rapidly in recent times, and there is an expanding research base that suggests these are efficacious approaches to promoting psychological health and well-being. Interest has spread to applications of mindfulness-based approaches with children and adolescents, yet the research is still in its infancy. I aim to provide a preliminary review of the current research base of mindfulness-based approaches with children and adolescents, focusing on MBSR/MBCT models, which place the regular practice of mindfulness meditation at the core of the intervention. Overall, the current research base provides support for the feasibility of mindfulness-based interventions with children and adolescents, however there is no generalized empirical evidence of the efficacy of these interventions. For the field to advance, I suggest that research needs to shift away from feasibility studies towards large, well-designed studies with robust methodologies, and adopt standardized formats for interventions, allowing for replication and comparison studies, to develop a firm research evidence base. KeywordsMindfulness meditation-Children-Adolescents-Families-Schools

Emotional and behavioral difficulties and impairments in everyday functioning among children with a history of attention-deficit/hyperactivity disorder

Article

Full-text available

Jan 2006

Introduction: Attention-deficit/hyperactivity disorder (ADHD) affects 3% to 7% of school-aged children and has been associated with a variety of comorbid mental illnesses and functional impairments, largely in clinical samples. However, little is known about the spectrum of emotional and behavioral problems and areas of impairment among children with a history of ADHD in nonclinical, nationally representative samples. Methods Data were analyzed from the 2003 National Health Interview Survey, an ongoing, computer-assisted, randomsample, personal-interview survey of the noninstitutionalized U.S. population. We examined the associations between history of parent-reported ADHD diagnosis and levels of parent-reported emotional and behavioral difficulties and related impairments among a nationally representative sample of U.S. children aged 4 to 17 years (n = 8681). The extended version of the Strengths and Difficulties Questionnaire was used to measure and score levels of difficulty and impairment. Results Approximately 5.9% of children had a history of ADHD diagnosis. Children with a history of ADHD were 6 times as likely as those without ADHD to have a high level of overall difficulties including emotional, conduct, and peer problems and were 9 times as likely to manifest a high level of impairment including interference with home life, friendships, classroom learning, and leisure activities. Conclusion: This study documents the significant level of current emotional and behavioral difficulties and impairments in everyday functioning experienced by children with a history of ADHD diagnosis, suggesting that people involved with the care of children - parents, health care providers, and teachers - need to be informed about the signs, symptoms, and appropriate treatment of ADHD and other comorbid disorders.

Neuroplasticity: changes in grey matter induced by training

Article

Full-text available

Feb 2004

Does the structure of an adult human brain alter in response to environmental demands? Here we use whole-brain magnetic-resonance imaging to visualize learning-induced plasticity in the brains of volunteers who have learned to juggle. We find that these individuals show a transient and selective structural change in brain areas that are associated with the processing and storage of complex visual motion. This discovery of a stimulus-dependent alteration in the brain's macroscopic structure contradicts the traditionally held view that cortical plasticity is associated with functional rather than anatomical changes.

Effectiveness of attention training after an acquired-brain injury: A meta-analysis of rehabilitation studies

Article

Full-text available

Apr 2001

The current study reviews the attention training literature after an acquired brain injury using mere-analytic procedures. Through computerized searches we identified 30 relevant studies involving a total of 359 patients. Overall performance, measured by d(+), improved significantly after training. Then the set of 30 studies were categorized according to whether the study evaluated training efficacy by comparing pre- and posttraining scores only or included a control as well. Results show that performance improved significantly after training when assessed by the pre-post only measure, but nut in the pre-post with control condition; Further analyses showed that performance in studies providing specific skills training improved significantly, whereas performance in studies providing general attention training did not. The implications of these results Tor rehabilitation are discussed. (C) 2000 Academic Press.

Attention Deficit Hyperactivity Disorder: A Handbook for Diagnosis and Treatment

Article

Feb 1994

Cognitive and emotional influences in anterior cingulate cortex

Article

Jun 2000

Anterior cingulate cortex (ACC) is a part of the brain's limbic system. Classically, this region has been related to affect, on the basis of lesion studies in humans and in animals. In the late 1980s, neuroimaging research indicated that ACC was active in many studies of cognition. The findings from EEG studies of a focal area of negativity in scalp electrodes following an error response led to the idea that ACC might be the brain's error detection and correction device. In this article, these various findings are reviewed in relation to the idea that ACC is a part of a circuit involved in a form of attention that serves to regulate both cognitive and emotional processing. Neuroimaging studies showing that separate areas of ACC are involved in cognition and emotion are discussed and related to results showing that the error negativity is influenced by affect and motivation. In addition, the development of the emotional and cognitive roles of ACC are discussed, and how the success of this regulation in controlling responses might be correlated with cingulate size. Finally, some theories are considered about how the different subdivisions of ACC might interact with other cortical structures as a part of the circuits involved in the regulation of mental and emotional activity.

Mental control of the bilingual lexicosemantic system

Article

Jan 1998
BILING-LANG COGN

D.W. Green

Executive Functioning, Temporal Discounting, and Sense of Time in Adolescents with Attention Deficit Hyperactivity Disorder (ADHD) and Oppositional Defiant Disorder (ODD)

Article

Dec 2001

Clinic-referred teens (ages 12–19) with ADHD and ODD (N = 101) were compared to community control (CC) teens, equated for age and sex, (N = 39) on a variety of psychological tasks assessing executive functioning (EF), temporal reward discounting, and time estimation and reproduction. A factor analysis reduced the EF measures to three dimensions, representing CPT Inattention, Working Memory, and CPT Inhibition. Results indicated that the ADHD group had significantly more CPT Inattention than the CC group. No differences were found for Working Memory or CPT Inhibition. The ADHD group displayed significantly greater temporal discounting of delayed hypothetical monetary rewards relative to immediate ones and manifested more impaired time reproduction, but not time estimation, than did the CC group. Main effects for level of IQ were found only on the Working Memory factor and largely did not interact with the group factor otherwise. The group differences in CPT Inattention, temporal discounting, and time reproduction were not a function of level of comorbid oppositional defiant disorder, delinquency, or anxiety–depression. Results are reasonably consistent with past research on EF and sense of time in children with ADHD and extend these findings to the adolescent age group. Problems with working memory and CPT inhibition found in prior studies of children with ADHD, however, were not evident here, perhaps owing to age-related improvements or insufficient task difficulty.

A 14-month randomized clinical trial of treatment strategies for attention-deficit/hyperactivity disorder. The MTA Cooperative Group. Multimodal Treatment Study of Children with ADHD

Article

Jan 1999

MTA Cooperative Group

Medicine's Obsession with Disclosure of Financial Conflicts

Chapter

Dec 2009

Jerome P. Kassirer

This chapter discusses the disclosure of financial conflicts in medical sciences. The principal threat of financial conflict of interest does not stem from its surreptitious nature but from its corrupting influence on the integrity of our medical information. Focusing on disclosure rather than on eliminating the conflicts is simply taking the easy way out. Disclosure is not the problem; lack of disclosure is not the problem. Bias from financial ties is the problem, and disclosure does not solve it. The chapter also defines that once a financial conflict is disclosed, a receiver of information must assess whether the conflict has had an influence on the information. Conflicts of interest influence individuals to be biased, but having a conflict of interest is no guarantee that an individual will be biased or act on that bias. Many people forget that just because someone has a conflict of interest is not an a priori reason for considering that person's opinion biased. Bias is often thought of as a deliberate choice of conflicted individuals.

Training the brain: Fact and fad in cognitive and behavioral remediation

Abstract and Figures

Recommended publications

Using Computer Databases in Student Problem Solving: A Study of Eight Social Studies Teachers' Class...

Accessibility through design

An educational hypertext system supporting radiographic image quality

Evaluation of Three Educational Online Delivery Approaches