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Working Memory and Specific Language
Impairment: An Update on the Relation and
Perspectives on Assessment and Treatment
James W. Montgomery
Beula M. Magimairaj
Mianisha C. Finney
Ohio University, Athens
Purpose: Children with specific language im-
pairment (SLI) demonstrate significant language
impairments despite normal-range hearing and
nonverbal IQ. Many of these children also show
marked deficits in working memory (WM) abilities.
However, the theoretical and clinical character-
ization of the association between WM and
language limitations in SLI is still sparse. Our
understanding of this association would benefit
greatly from an updated and thorough review of
the literature.
Method: We review the newest developments in
these areas from both a theoretical and clinical
perspective. Our intent is to provide researchers
and practicing clinicians (a) a conceptual frame-
work within which the association between WM
and language limitations of children with SLI
can be understood and (b) potentially helpful
suggestions for assessing and treating the
memory-language difficulties of children with SLI.
Conclusions: In the past 10 years, important
new theoretical insights into the range and nature
of WM deficits and relation between these
limitations and the language difficulties in SLI
have occurred. New, robust diagnostic assess-
ment tools and computerized treatment methods
designed to enhance children’s WM functioning
have also been developed. The assessment,
diagnosis, and treatment of the language diffi-
culties in SLI should consider the potential
influence of WM.
Key Words: children, specific language
impairment, working memory, language
Many children with specific language impairment
(SLI) exhibit significant working memory (WM)
deficits relative to same-age peers. In 2002,
Montgomery published a review article on what was known
about the WM deficits of children with SLI and the relation
of these deficits to these children’s language problems. Since
then, new and important insights into WM and language in
children with SLI and typically developing (TD) children
have occurred. We review these new developments. We cast
the WM deficits and their relation to SLI in broad theoretical
terms, which allows us to contextualize the WM issues
defining the current SLI literature. During this same period,
new WM assessment tools and computerized training meth-
ods designed to remediate the WM deficiencies of children
have been developed. Many of these tools are available to
the practicing speech-language pathologist (SLP). These new
developments and their clinical relevance to SLI will be
reviewed.
Children with SLI demonstrate normal-range hearing and
nonverbal intelligence and an absence of developmental
disability (e.g., autism or fragile X syndrome) yet marked
expressive and/or receptive language difficulties for their
age. Many children with SLI also exhibit limitations in WM.
WM refers to the mental processes allowing limited infor-
mation to be held in a temporary accessible state during
cognitive processing (Cowan, Nugent, Elliott, Ponomarev, &
Saults, 2005); that is, WM involves concurrent informa-
tion processing and storage. Because WM is considered a
primitive of higher level cognition (e.g., Unsworth & Engle,
2007), including fluid intelligence, language learning/
performance, and academic learning, it is important to un-
derstand its nature. The WM system includes various mech-
anisms and properties. Over the past decade, the range of
WM problems exhibited by children with SLI has broadened,
and the evidence implicating an association between the WM
and language difficulties in children with SLI has grown.
This said, it should be noted that children with SLI repre-
sent a heterogeneous population not only with respect to the
linguistic deficits they exhibit (Leonard, 1998) but also as to
whether they demonstrate WM limitations. Although WM
Tutorial
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limitations characterize many children with SLI, not all chil-
dren with SLI evidence such deficits (Archibald & Joanisse,
2009). The information in the present article reflects what
is known about children with SLI who do demonstrate WM
problems.
WM in TD Children
A Theoretical Backdrop
To better understand the SLI literature, it is important to
have some familiarity with the key issues defining the re-
cent developmental memory literature. The majority of WM
research has been conducted within Baddeley’soriginal
tripartite framework (Baddeley & Hitch, 1974). This model
describes WM as a multidimensional system comprising
three separable yet interactive mechanisms (Bayliss, Jarrold,
Baddeley, Gunn, & Leigh, 2005; Gathercole, 1999; Gavens
& Barrouillet, 2004; Towse, Hitch, & Hutton, 1998). One is
a domain-general central executive responsible for coordi-
nating and controlling the different activities within WM.
The executive has finite attentional resources (mental energy/
capacity) that are controlled in a flexible manner. Attentional
control is key, and its regulatory functions include such
things as allocation (the ability to devote mental energy to
different levels of a task), updating (changing the contents
of WM through attention switching), sustained attention
(the ability to attend selectively to a stimulus in the midst of
interference), and inhibition (the ability to block irrelevant
stimuli from WM or focus of attention; Baddeley, 1996;
Barkley, 1996; Lehto, Juujarvi, Kooistra, & Pulkkinen, 2003).
The executive is roughly similar to the view of WM espoused
by Cowan (Cowan, 1997; Cowan et al., 2005) as the acti-
vation of a subset of representations (e.g., words) stored in
long-term memory that momentarily occupy the focus of
attention, and by Engle (Engle & Kane, 2004; Unsworth &
Engle, 2007) as attentional capacity and control.
The second and third mechanisms correspond to two
domain-specific storage devices, one devoted to the tempo-
rary retention of verbal material, the phonological loop, and
the other to visuospatial input, the visuospatial sketchpad.
In this article, we focus on the loop, hereafter referred to as
phonological short-term memory (pSTM). Recently, Baddeley
(2000, 2003) proposed a fourth mechanism, the episodic
buffer. The buffer is assumed to function as a temporary
storage device and a processing system capable of integrating
inputs from pSTM and the visuospatial sketchpad into a
coherent episode/representation. It is thought to be important
to the processing and retention of large chunks of language
material such as connected speech. Because the buffer is a
newly proposed mechanism, it does not enjoy the same theo-
retical specificity and empirical validation as the other com-
ponents (Baddeley, 2003). Finally, though not a mechanism,
developmental memory researchers have begun to examine
processing speed as an important property of WM and a
potential factor in defining the capacity limits of WM (Bayliss
et al., 2005; Towse & Hitch, 1995; Towse et al., 1998). In-
terest in speed derives from earlier work revealing reliable
intercorrelations among processing speed, short-term mem-
ory (STM), chronological age, and higher level cognitive
abilities (Fry & Hale, 1996, 2000; Gathercole & Baddeley,
1993; Kail, 1991). We are interested in processing speed
because of its emerging association with WM and central
focus in the SLI literature.
The basic architecture of the tripartite model—that is,
central executive, pSTM, and visuospatial STM—seems to
be developed by about age 6 (Gathercole, Pickering, Ambridge,
& Wearing, 2004). The capacity of each component increases
from early childhood into adolescence (Gathercole, 1999;
Gathercole et al., 2004). The executive is significantly linked
to both storage devices beginning in early childhood. This
finding indicates that the executive is associated with the
coordination of the flow of information throughout WM
(Baddeley, 1996; Gathercole et al., 2004), and different WM
mechanisms develop in an integrated fashion from an early
age. Finally, pSTM and visuospatial STM appear to develop
relatively independently of each other, revealing their domain-
specificity (Gathercole et al., 2004; Jarvis & Gathercole,
2003).
WM capacity is assessed using various concurrent
processing-storage tasks. In listening span tasks, children
listen to sets of sentences that increase in number (e.g.,
“Pumpkins are purple”and “Fish can swim”) and are asked
to respond to the truth value of each sentence (processing
component) and recall as many sentence-final words from
each set (storage component; Gathercole et al., 2004; Pickering
& Gathercole, 2001). In counting span tasks, children count
arrays of dots while remembering the sums of dots on each
array; at the end of a set, they recall the sums from each array.
In operation span tasks, children perform multiple arithmetic
problems, store the answer to each problem or a separate
word presented after each problem, and then recall all the
answers or words at the end of the set. The developmental
pattern is that processing accuracy is high while storage
significantly improves. WM capacity is typically indexed by
item recall—that is, availability of storage in the face of
processing/interference.
Much developmental work has focused on explaining
increases in children’s WM capacity, examining the roles of
the central executive and STM (Barrouillet & Camos, 2001;
Barouillet, Gavens, Vergauwe, Gaillard, & Camos, 2009;
Bayliss et al., 2005; Bayliss, Jarrold, Gunn, & Baddeley,
2003; Gathercole et al., 2004; Irwin-Chase & Burns, 2000;
Karatekin, 2004). Research has shown that gains in capacity
are associated with increases in both of these mechanisms.
Some researchers have investigated the impact of processing
speed/efficiency (Bayliss et al., 2005; Towse & Hitch, 1995;
Towse et al., 1998). The idea behind the association between
speed and WM capacity centers on the possibility that the
slower the processing activity of a WM task is completed, the
greater the opportunity for the stored items to decay or be
forgotten. Only recently have researchers begun to investi-
gate the collective contributions of STM and processing
speed on WM performance (Bayliss et al., 2003, 2005;
Magimairaj, Montgomery, Marinellie, & McCarthy, 2009).
Bayliss et al. (2005) examined the individual and combined
contributions of storage and processing speed on 6–10-year-
old children’s WM capacity. Hierarchical linear regression
and structural equation modeling showed that age-related
increases in STM and processing speed contributed to
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developmental changes in WM capacity, with STM ac-
counting for greater variance than speed. Magimairaj et al.
(2009) replicated these findings in 6–12-year-old children.
Some have argued that increases in WM capacity may
also be driven by changes in attentional control. As children
grow older they become better at rapidly switching their
attention between the processing part of the task and remem-
bering the items in STM (Barrouillet et al., 2009; Conlin,
Gathercole, & Adams, 2005; Portrat, Camos, & Barrouillet,
2009). It is not difficult to see that attentional control (Engle,
2002; Unsworth & Engle, 2007) is closely related to the
idea of scope or focus of attention (Cowan, 1997; Cowan
et al., 2005) in that only a small bit of information can oc-
cupy the focus of attention at any given moment.
Relation of WM to Spoken Language Development
and Functioning
Lexical learning. Much developmental work investigat-
ing the relation between WM and language has centered on
word learning (Avons, Wragg, Cupples, & Lovegrove, 1998;
Gathercole & Baddeley, 1990b; Gathercole, Willis, Emslie,
& Baddeley, 1992). Most of this work has focused on pSTM,
which has been argued to function as an important language
learning device (Baddeley, Gathercole, & Papagno, 1998;
Gathercole, 2006; Gathercole & Baddeley, 1990b). Word
learning involves mapping sound to meaning. Using a variety
of methods, robust associations between pSTM and new
word learning have been reported for preschool-age children
through about age 8 (Bowey, 2001; Gathercole & Baddeley,
1989, 1990b; Gathercole, Service, Hitch, & Martin, 1997;
Jarrold, Thorn, & Stephens, 2009). The ability to hold novel
speech material in pSTM presumably permits children to
establish stable, long-term phonological representations of
new words in long-term memory (e.g., Jarrold et al., 2009).
As the lexicon grows, word entries become more phonolog-
ically refined and better organized, with one organizational
scheme involving words beginning with the same sound
being stored together (Luce & Pisoni, 1998). Phonological
STM and the ability to temporarily store new sound pat-
terns may be an important factor in young children’slexical
learning and organization. Although the relation of pSTM
and word learning weakens after age 8 (Gathercole, 1995;
Gathercole, Tiffany, Briscoe, Thorn, & the ALSPAC Team,
2005), there continues to be a significant link through ado-
lescence into adulthood (Atkins & Baddeley, 1998; Gupta,
2003).
Morphological and syntactic learning and functioning.
Some researchers (Plunkett & Marchman, 1993; Tomasello,
2000) argue that young children do not possess morpho-
logical rules (e.g., past tense), grammatical categories (e.g.,
subjects, verbs, and objects), and syntactic structure (e.g.,
subject-verb-object [SVO] and passive). Rather, children
initially learn whole phrases and only later discover under-
lying rules, categories, and structures by using the distribu-
tional properties/regularities of the input (Nelson, 1987;
Plunkett & Marchman, 1993; Tomasello, 2000). Phonolog-
ical STM may serve as a mediating or moderating mecha-
nism for this analytic process. Some support for this idea
comes from Adams and Gathercole (1995), who reported
that pSTM predicts quantity and quality of spontaneous
speech in 3-year-old children. They showed that high-
pSTM capacity children, compared with low-capacity chil-
dren, produced longer utterances containing a greater range
of syntactic structures and lexical diversity. Blake, Austin,
Cannon, Lisus, and Vaughan (1994) showed that STM is a
better predictor of mean length of utterance in preschoolers
than chronological or mental age. Because morphological
and syntactic learning entails building relational knowledge,
it is likely that several executive functions are involved;
however, little empirical work has directly addressed the
issue.
The influence of WM capacity in language comprehen-
sion is only beginning to receive attention. At the sentence
level, the more controlled studies have focused on the relation
of WM and complex sentence comprehension. WM has been
linked to the comprehension of object relative clause forms
(e.g., “The hippo that the lion kissed on the nose was running
into the jungle”) in young children (Roberts, Marinis, Felser,
& Clahsen, 2007). Children with greater WM capacity show
more accurate comprehension than low-capacity children.
Comprehension minimally involves storing a prior element
(noun phrase [NP] 1) in WM while processing new,incoming
input. However, WM capacity is likely just one important
mechanism. Being able to reactivate a stored element and
then integrate it into a developing local structure in a timely
manner are other WM-related skills underlying complex
sentence comprehension (Lewis, Vasishth, & Van Dyke,
2006; McElree, Foraker, & Dyer, 2003; Van Dyke, 2007).
Support for this wider view comes from a recent study by
Montgomery, Magimairaj, and O’Malley (2008). These
authors showed that 6–12-year-old children’s spoken com-
prehension of verbal be passives (“The little girl was kissed
by the woman”) is associated with WM capacity and pro-
cessing speed. At a more global level, children’s comprehen-
sion of narrative is predicted by WM capacity and processing
speed (Montgomery, Polunenko, & Marinellie, 2009). Be-
cause narratives entail large amounts of input and keeping
track of many representations, developing a coherent mental
model requires the storage, retrieval, and rapid integration
of multiple representations across large stretches of input.
WM and Speed of Processing in SLI
Relative to age peers, many children with SLI show
significant limitations in nearly all WM mechanisms as well
as speed of processing (see Table 1). Appreciation of these
limitations and the relation of these limitations to the lan-
guage deficits of these children have important practical
implications. Such knowledge may translate into building
more informed clinical profiles of these children’s cognitive-
linguistic strengths and weaknesses. Such knowledge, in
turn, may help inform clinical assessment, diagnosis, and
treatment.
STM Storage
Many children with SLI show marked limitations in STM
capacity. Gathercole and Baddeley (1990b) proposed the
phonological storage deficit hypothesis of SLI, claiming that
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the language impairment in SLI is secondary to a deficit in
phonological storage. Phonological STM is assessed using
various tasks such as digit span, word span, and nonword
repetition. In digit and word span, children are presented
increasingly longer lists of items and recall each list in serial
order. In nonword repetition, children imitate nonwords
varying in length. Regardless of task, children with SLI gen-
erally exhibit reduced pSTM relative to age peers (Archibald
& Gathercole, 2006; Ellis Weismer et al., 2000; Gathercole
& Baddeley, 1990b; R. Gillam, Cowan, & Day, 1995;
Montgomery, 2004; Montgomery & Evans, 2009).
Whether children with SLI evidence a developmental
increase in STM capacity has been little studied. Gray (2004)
reported an increase in capacity between 3 and 6 years. How-
ever, capacity may level off by about 11 years, as suggested
by findings of a longitudinal study by Conti-Ramsden and
Durkin (2007). Their findings are inconsistent with the de-
velopmental literature showing that pSTM capacity does not
asymptote until about 14–15 years in TD children (Gathercole,
1999; Gathercole et al., 2004). Finally, there is evidence that
the STM deficit of children with SLI may be confined to the
verbal modality, as children with SLI and age peers tend to
perform similarly on visuospatial STM tasks (Alloway &
Archibald, 2008; Archibald & Gathercole, 2006, 2007).
Central Executive
It has only been recently that SLI researchers have begun
to study the central executive, primarily in the context of
WM tasks. Aspects of the executive that have been assessed
include attentional capacity and several attentional functions—
that is, allocation, inhibitory control, updating, and sustained
attention.
Attentional capacity. Attentional capacity refers to the
limited mental activation/energy available to a person to
perform a given task (Just & Carpenter, 1992). Most SLI
studies have tested attentional capacity using verbal tasks
(Ellis Weismer, Evans, & Hesketh, 1999; Mainela-Arnold &
Evans, 2005; Montgomery, 2000a), but some investigators
have also begun to include nonlinguistic tasks (Alloway
& Archibald, 2008; Archibald & Gathercole, 2006, 2007;
Windsor, Kohnert, Loxtercamp, & Kan, 2008). Irrespective
of the nature of the task, many children with SLI show re-
duced performance relative to age peers.
Ellis Weismer et al. (1999) compared the attentional
capacity of children with SLI and age peers. Using the
Competing Language Processing Task (CLPT; Gaulin &
Campbell, 1994), these investigators reported that both groups
yielded similar comprehension, but the SLI group yielded
significantly poorer word recall. Similar results have been
reported by others (Archibald & Gathercole, 2006, 2007;
Mainela-Arnold & Evans, 2005; Marton & Schwartz, 2003;
Montgomery, 2000a, 2000b; Montgomery & Evans, 2009).
Because all these studies show that children with SLI can
manage both comprehension and recall when the demands
for recall are light (i.e., few items need to be recalled), the
interpretation has been that children with SLI have reduced
attentional capacity compared to age peers. Archibald and
Gathercole (2006, 2007) and Windsor et al. (2008) have
extended these findings and interpretation to the nonlinguistic
domain. Im-Bolter, Johnson, and Pascual-Leone (2006) cor-
roborated the capacity limitation hypothesis using a variety
TABLE 1. Working memory (WM) and processing speed of children with specific language impairment
(SLI) relative to age-matched peers.
WM/speed Relative to age peers
Short-term memory capacity
Verbal storage Poor
(Archibald & Gathercole, 2006, 2007; Ellis Weismer et al., 2000; Gathercole &
Baddeley, 1990b; Montgomery, 1995, 2004)
Visuospatial storage Similar
(Alloway & Archibald, 2008; Archibald & Gathercole, 2006, 2007)
WM capacity
Concurrent processing stor-
age
Poor
(Archibald & Gathercole, 2006, 2007; Ellis Weismer et al., 1999; Marton &
Schwartz, 2003; Montgomery, 2000a, 2000b; Montgomery & Evans, 2009)
Central executive
Attentional capacity Poor
(Archibald & Gathercole, 2006, 2007; Ellis Weismer et al., 1999;
Im-Bolter et al., 2006; Mainela-Ar nold & Evans, 2005; Montgomery & Evans, 2009)
Attentional allocation/shift-
ing
Similar
(Montgomery, 2000a, 2000b; Im-Bolter et al., 2006)
Updating Poor
(Im-Bolter et al., 2006)
Inhibition Poor
(Im-Bolter et al., 2006; Marton et al., 2007; Seiger-Gardner & Schwartz, 2008)
Sustained attention Poor
(Finneran et al., 2009; Montgomery, 2008; Montgomery, Polunenko,
& Marinellie, 2009; Spaulding et al., 2008)
Processing speed Poor
(Leonard et al., 2007; Miller et al., 2001; Windsor & Hwang, 1999; Windsor
et al., 2008)
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of independent measures of attentional capacity. Collectively,
such findings and interpretation are consistent with the gen-
eral WM literature characterizing attentional capacity as a
domain-general cognitive attribute (Baddeley, 1996; Cowan,
1997; Cowan et al., 2005; Unsworth & Engle, 2007). Finally,
it is not clear whether children with SLI exhibit develop-
mental increase in attentional capacity, as there are no studies
directly addressing the issue.
Attentional control. Im-Bolter et al. (2006) evaluated three
attentional control functions in children with SLI. Using a
variety of independent tasks, they assessed shifting, updating,
and inhibitory control. Shifting, which is roughly analogous
to Baddeley’s (1996) resource allocation, is the ability to
devote attention between two different levels of a task (e.g.,
the processing and storage parts of a WM task) or to two
different tasks (Im-Bolter et al., 2006). Updating refers to
maintaining focus at a given level of a task and adding new
content to the focus of attention (e.g., adding to a list of to-be-
remembered items in storage in a WM task). Inhibition refers
to preventing irrelevant stimuli from entering WM or focus
of attention. Three key findings emerged: Relative to age-
mates, children with SLI exhibited comparable shifting, poorer
updating of WM, and poorer inhibitory control. Such findings
advance the SLI literature in two important ways. First, they
offer independent evidence that children with SLI have re-
duced attentional capacity, not poor allocation, and poor in-
hibitory control (also see Bishop & Norbury, 2005; R. Gillam
et al., 1995; Lum & Bavin, 2007; Mainela-Arnold & Evans,
2005; Marton, Kelmenson, & Pinkhasova, 2007; Seiger-
Gardner & Schwartz, 2008). Second, children with SLI have
trouble updating the contents of WM.
One other executive function has begun to be studied in
SLI—sustained attention, which is the ability to maintain
attention over time to identify a target in the midst of a stream
of nontargets (Awh, Vogel, & Oh, 2006). Emerging data
indicate that many children with SLI have trouble sustaining
attention (Finneran, Francis, & Leonard, 2009; Montgomery,
2008; Montgomery, Evans, & Gillam, 2009; Spaulding,
Plante, & Vance, 2008). Brain mechanisms responsible for
attention, including sustained attention, appear to be the same
as those supporting WM (Jonides, Lacey, & Nee, 2005; Silver
& Feldman, 2005). This proposal is important because
Ellis Weismer, Plante, Jones, and Tomblin (2005) provide
functional magnetic resonance imaging data showing that
the coordinated pattern of activation of brain regions asso-
ciated with attentional control, memory processes, and lan-
guage encoding and retrieval are different in adolescents with
SLI than in age peers. Adolescents with SLI show an over-
reliance on a less functional network of brain regions subserving
these mental functions and overall lower levels of neural
activation.
Speed of Processing
Processing speed in SLI has been studied from two per-
spectives: a rapid rate temporal processing point of view
(Stark & Tallal, 1988; Tallal & Stark, 1981; Tallal et al., 1996;
Tallal, Stark, & Mellits, 1985a, 1985b) and, more recently, a
generalized cognitive slowing perspective (Kail, 1994; Miller,
Kail, Leonard, & Tomblin, 2001; Windsor & Hwang, 1999;
Windsor, Milbrath, Carney, & Rakowski, 2001). Tallal and
associates have claimed that children with SLI have special
trouble processing rapidly presented information, linguistic
or nonlinguistic, and that this difficulty directly hinders their
language processing and language learning. A generalized
slowing perspective takes a broader view. This account
suggests that many children with SLI are slower at all mental
processes, including perceptual, cognitive, and linguistic,
by a proportional amount relative to age peers, irrespective
of the nature and modality of the task (Kail, 1994; Leonard
et al., 2007; Miller et al., 2001; Windsor & Hwang, 1999;
Windsor et al., 2001). Processing speed within this frame-
work emphasizes the amount of cognitive work that can be
completed in a given unit of time (Kail & Salthouse, 1994;
Salthouse, 1996, 2000). The assumption is that if information
is not processed with sufficient speed it is vulnerable to decay
and/or interference. Although many children with SLI are
slower processors than age-mates through adolescence, they
do appear to show developmental improvement in linguistic/
nonlinguistic processing speed between 6 and 11 years
(Montgomery, 2005).
Recall that developmental memory researchers regard
processing speed as an important property of the WM system
and have begun to examine its potential influence in defining
the capacity limits of WM. Its inclusion in SLI research has
only been recent. Archibald and Gathercole (2007) examined
whether the WM deficit in SLI is related to limitations in
STM and processing speed. Children with SLI were com-
pared to age peers and to younger children matched for recep-
tive vocabulary. Children completed separate verbal and
visuospatial tasks related to storage, processing speed, and
WM capacity. The four WM tasks crossed verbal and visuo-
spatial processing and storage (i.e., verbal processing + verbal
storage, verbal processing + visuospatial storage, visuospatial
processing + verbal storage, visuospatial processing +
visuospatial storage). For the STM tasks, the SLI group
performed like age peers in both domains but better than
language controls. For processing speed, the SLI group was
significantly slower in both domains than age peers but
faster than younger children. On the WM tasks, the SLI group
performed significantly worse than age controls on both WM
tasks but only for those involving verbal storage. Relative
to language controls, the SLI group performed significantly
better on the WM tasks requiring visuospatial storage and
comparably on the tasks involving verbal storage. This pat-
tern of results was interpreted to mean that, relative to age
peers, the limited WM capacity of children with SLI was due
to a combination of a verbal-specific storage deficit and
slower domain-general processing. Importantly, as pointed
out by the authors, it is likely that deficits in executive-
attention mechanisms also had a negative impact on the WM
capacity of the children with SLI—for example, sustained
attention (Montgomery, 2008; Spaulding et al., 2008), in-
hibitory control (Im-Bolter et al., 2006; Marton et al., 2007),
and updating (Im-Bolter et al., 2006).
Linguistic Influences on WM Capacity
The WM capacity of children with SLI is influenced not
just by WM-related factors but also by linguistic factors.
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Mainela-Arnold and Evans (2005) showed that, relative to
age peers, word recall on the CLPT by children with SLI was
significantly affected by the frequency of the words, with
low-frequency items being recalled with less accuracy than
high-frequency items. These findings led to a different theo-
retical description of the WM capacity deficit in SLI. The
authors argued that WM capacity and linguistic knowledge
are not separable mental constructs. Rather WM capacity
reflects the activation of specific representations in long-term
memory (Cowan, 1997; Cowan et al., 2005; MacDonald &
Christiansen, 2002). In this view, limited WM capacity in
SLI is a reflection of weak linguistic representation (Bishop,
2000; Dollaghan, 1998; Mainela-Arnold, Evans, & Coady,
2008), with the strength, access, and retrieval of represen-
tation being dependent on input frequencies (MacDonald &
Christiansen, 2002). Low-frequency words reflect a case
of weak representation driving poor WM storage and re-
trieval because such words are experienced less often and
hence are subject to slower/less accurate processing and
retrieval than high-frequency words (Juhasz, 2005).
WM and Language in SLI
Deficits in WM and processing speed in children with SLI
could lead to widespread negative effects in language learn-
ing and functioning, including partial processing of words,
grammatical forms, and syntactic structures. Poor ability
to process input could lead to protracted language learning
during which children need more exposures to the words and
structures of the language before they are integrated into the
language system (Leonard et al., 2007). Limitations might
affect not only acquisition of representation but also language
process, that is, the efficiency with which children store,
access, retrieve, and coordinate stored representations in the
moment-to-moment input and output processing of language.
While claims of cause-and-effect relations between the WM,
processing speed, and language limitations in SLI await
data from psychometric, developmental, and intervention
studies, there is mounting evidence of an association.
WM and Lexical Learning
Relative to age peers, children with SLI show slower vo-
cabulary growth (Paul, 1996; Rescorla, Roberts, & Dahlsgaard,
1997) and smaller lexicons (Watkins, Kelly, Harbers, &
Hollis, 1995). Gathercole and Baddeley (1990a) proposed
in a seminal article that the language difficulties in SLI may
be secondary to a deficit in pSTM capacity. In this hypoth-
esis, these children should have trouble learning new words
because of a difficulty encoding and/or storing novel phono-
logical material in pSTM, and consequently establishing
long-term phonological representations of new words. Early
anecdotal evidence suggested this might be the case (Oetting,
Rice, & Swank, 1995; Rice, Cleave, & Oetting, 2000; Rice,
Oetting, Marquis, Bode, & Pae, 1994). Oetting et al. (1995), in
a quick incidental word-learning study, found that a group
of 6–8-year-old children with SLI learned fewer unfamiliar
words than age peers as these words appeared in brief video
stories containing simple, familiar language structures. Rice
et al. (1994, 2000) showed that children with SLI, compared
with age peers, learned fewer unfamiliar words. In each of
the above studies, learning was indexed by comprehension
performance.
Remarkably few studies have directly investigated the
above-mentioned relation of pSTM and word learning. Gray
(2004) asked whether pSTM would predict novel word learn-
ing in a group of 3–6-year-old children with SLI and age
peers. Children completed nonword repetition and digit span
tasks and a fast mapping task in which they heard names of
eight novel two-syllable words three times. Learning was
assessed via comprehension and production. The SLI group
performed worse than age controls on both pSTM tasks and
the comprehension and production measures. No signifi-
cant correlation emerged between pSTM and comprehension
or production in the SLI group. Gray interpreted the lack
of correlation to mean that a pSTM deficit does not constrain
the word learning of children with SLI.
Two different possibilities exist that might explain the lack
of correlation reported by Gray (2004). First, children with
SLI represent a heterogeneous population. For many chil-
dren with SLI, vocabulary represents a relative strength (cf.
Leonard, 1998). Inspection of the scores of the SLI group
in the Gray study revealed that the SLI group performed
within the normal limits on the Peabody Picture Vocabulary
Test, an index of receptive vocabulary knowledge. Also,
not all children with SLI have memory problems (Archibald
& Joanisse, 2009). An absence of correlation appears con-
sistent with the possibility that the SLI group, although
attaining lower word-learning and STM scores than age
peers, had no marked lexical or pSTM deficits. Alternatively,
Gathercole (2006) recently modified the original pSTM def-
icit hypothesis. She argued that a pSTM deficit alone was
insufficient to cause language problems. Instead, a combina-
tion of memory deficits places children at risk for language
difficulties. In this view, a WM deficit, for example, may
be more influential than a pSTM weakness in defining an
association between memory and vocabulary in SLI.
WM and Morphological Learning and Processing
The relation of WM and grammatical morpheme learn-
ing and processing in SLI has received surprisingly little
research attention. Ellis Weismer (1996) examined the impact
of WM capacity on the morphological learning of a group of
children with SLI and age-matched children. Children com-
pleted the CLPT and a fast mapping task in which they were
exposed to two novel morphemes (a vowel) appended to
words embedded in a short carrier phrase presented at normal,
fast, and slow rates. Ellis Weismer reasoned that morpheme
learning, indexed by comprehension and production of the
novel inflected words, should correlate with WM. Relative to
age peers, the SLI group yielded significantly reduced word
recall on the CLPT. On the morpheme learning task, both
groups showed comparable comprehension. By contrast, the
SLI group produced fewer inflected words in the fast rate
condition than age peers. Morpheme production in the fast
rate condition in the SLI group was also moderately corre-
lated with CLPT score. The good comprehension by the SLI
group should come as no surprise. The morphemes were
vowels and were likely easily detectable in the input, thus
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freeing up attentional resources allowing the children to
glean the grammatical function of the segment. The produc-
tion and correlation findings suggest that the production of
newly learned grammatical morphemes stretches the WM
and processing speed of children with SLI. The need to ac-
cess a newly learned inflection and append it to a verb while
simultaneously formulating and producing the rest of the
sentence in a timely fashion apparently exceeds the overall
processing capacity of children with SLI.
One might argue that the morpheme learning (comprehen-
sion, production) that took place in Ellis Weismer’s explicit
learning task is fundamentally different than the learning that
occurs in natural language environments. Clearly, there are
differences in the structure of the learning contexts, but there
are important similarities between the two in terms of the
mental operations underlying morpheme learning. According
to the processing capacity account of Leonard and colleagues
(Leonard, 1998; Leonard, Eyer, Bedore, & Grela, 1997),
morpheme learning involves children (a) perceiving an in-
flected word and comparing it with its bare stem counterpart,
(b) hypothesizing the grammatical function of the marker, and
(c) placing it in a morphological paradigm. Moreover, these
operations must be completed in a timely way to ensure
correct morphological analysis. Such a learning process relies
on WM in that children must be able to store the novel in-
flected word, retrieve from long-term memory its bare stem
counterpart, and simultaneously perform a morphological
analysis of the novel inflected word before the marker decays.
Inflectional learning in the children with SLI in the Ellis
Weismer (1996) study, as indexed by production, was likely
hindered because of limitations in WM capacity and speed
of processing (Leonard et al., 1997).
Many children with SLI also have trouble processing per-
ceptually weak inflections during running speech (Montgomery
& Leonard, 1998, 2006). These investigators, using a word-
monitoring reaction time task, contrasted the online process-
ing of perceptually nonsalient markers (past tense –ed, third
person singular –s) with a perceptually stronger marker
(present progressive –ing). In both studies, relative to age
peers, the SLI group showed no sensitivity to the presence of
the –ed and –smarkers. However, the SLI group, like age
peers, showed sensitivity to the -ing marker. These results
suggest an interaction between the nature of the input and
SLI processing capacity. Poor processing capacity would
entail slower access and retrieval of perceptually weak mark-
ers from long-term memory and slower integration of in-
flected words into a developing sentence meaning. The
implication of poor processing is that many children with
SLI are at risk for constructing incomplete/inaccurate rep-
resentations of the speaker’s input.
WM and Sentence Comprehension
Children with SLI exhibit poorer sentence comprehension
than age peers, including understanding lengthy SVO sen-
tences containing dependent clause material (“The little boy
who is standing is hugging the girl who is sitting”) and sen-
tences that violate SVO order such as passives (“The girl
was kissed by the lady on the head”) and object relative sen-
tences (“The dog that the cat bit was running away”). The
latter sentences are especially difficult because a word or
phrase occupies a syntactic position that is different from the
position that determines its semantic role, thus requiring
complex syntactic processing (Friedman & Novogrodsky,
2004; van der Lely, 1996, 1998). In the sentences above, NP1
appears in a subject position but functions as a patient. To
recover the SVO order of such sentences, children must move
NP1 behind the verb (gap) using a “syntactic movement”
operation. Researchers ascribing to a syntax-specific view
to explain such SLI comprehension problems (Friedman &
Novogrodsky, 2004; Marshall & van der Lely, 2006; van der
Lely, 2005) argue that the comprehension deficits are due
to a syntax problem. Those who argue from a more domain-
general perspective (Bishop, 1997, 2006; Montgomery &
Evans, 2009) propose that the comprehension problems are
secondary to general cognitive processing limitations (e.g.,
WM and speed of processing).
Phonological STM and sentence comprehension. Several
studies have examined the role of pSTM in SVO sentence
comprehension by children with SLI (Montgomery, 1995,
2000a, 2000b, 2004; Montgomery & Evans, 2009). Few
studies have examined its role in complex structures such as
passives (Montgomery & Evans, 2009; Norbury, Bishop, &
Briscoe, 2002). Evidence supporting the role of pSTM in
SVO comprehension is mixed. Montgomery (1995) revealed
a correlation between pSTM and the comprehension of SVOs
containing embedded clause material (e.g., “The girl who
is laughing is touching the boy”or “The little boy who is
standing is hugging the girl who is sitting”). Montgomery and
Evans (2009) likewise reported a significant correlation be-
tween pSTM and SVO comprehension in children with SLI,
but not in age peers or younger memory-matched children.
Results suggest that comprehension of simple grammar in-
volves significant mental resources by children with SLI but
not TD children. However, other studies have reported no
correlation in children with SLI (Montgomery, 2000a, 2000b,
2004). With respect to passives, the two studies investigating
the association between pSTM and passive comprehension
have yielded mixed results. Whereas Norbury et al. (2002)
reported a significant correlation, Montgomery and Evans
(2009) reported no correlation.
WM capacity and sentence comprehension. We exam-
ined the role of WM capacity in children’s online sentence
processing (Montgomery, 2000a) and offline comprehension
(Montgomery, 2000b; Montgomery & Evans, 2009). In both
studies, children completed a concurrent verbal processing-
storage task. In the online study, children with SLI who were
age-matched and younger syntax-matched children com-
pleted a WM task and a word-monitoring task (Montgomery,
2000a) in which they pressed a button upon hearing a target
word in the sentence. Results showed that (a) the SLI and
younger groups performed similarly across tasks but worse
than the CA group and (b) WM did not correlate with simple
sentence processing (word recognition) in any group. The
findings were interpreted to mean that the immediate pro-
cessing of simple SVO forms does not entail significant WM,
even for children with SLI. SVOs place little demand on
WM presumably because (a) there is no need to hold NP1
in WM since it occupies a preverbal position and receives its
agent role directly from the verb and (b) NP2 appears in a
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postverbal position and receives its patient assignment. We
also examined the relation of WM and offline comprehension
of short and long SVOs in the same three groups of children in
another study (Montgomery, 2000b). Results showed that
(a) the SLI and younger groups yielded similar scores on the
WM task but worse scores than the CA group and (b) the
SLI group comprehended fewer long sentences than either
control group. Because the SLI and younger groups were not
memory matched, we concluded that the SLI group’sWM
deficit hindered their comprehension because the additional
information processing demands inherent in such offline
comprehension paradigms exceeded their WM abilities.
Sustained auditory attention and sentence comprehension.
To our knowledge, only two studies have examined the
relation of sustained attention and sentence comprehension
(Montgomery, 2008; Montgomery et al., 2009). In both stud-
ies, 6–11-year-old children with SLI and age peers com-
pleted a continuous performance task. In the online sentence
processing study (Montgomery, 2008), children responded
to a target word appearing at the beginning, middle, or end of
the sentence. In the offline sentence comprehension study
(Montgomery et al., 2009), children selected a picture corre-
sponding to the sentence they heard. We predicted that a
correlation should occur between sustained attention and
sentence processing/comprehension on the assumption that
accurate sentence processing/comprehension requires main-
taining attention over the course of the sentence. Relative
to age peers, the SLI group in each study showed (a) signif-
icantly poorer sustained attention, ( b) poorer sentence process-
ing (slower word recognition reaction time to target words)
and poorer sentence comprehension, and (c) a correlation
between attention and comprehension. We interpreted such
results to mean that the immediate processing and compre-
hension of simple grammar involves significant mental
effort by children with SLI but not age peers, suggesting that
simple grammar is not yet processed automatically by chil-
dren with SLI.
WM and Standardized Language Performance
The issue of how WM and processing speed might relate to
SLI performance on standardized language tests has begun to
be addressed (Leonard et al., 2007; Montgomery & Windsor,
2007). Interestingly, data from both studies mirror the devel-
opmental WM literature showing the relative importance of
STM over processing speed (Bayliss et al., 2005; Magimairaj
et al., 2009). Leonard et al. (2007) conducted a large-scale
study in which multiple measures of WM, processing speed,
and language were administered to large samples of children
with SLI and age-matched peers. Factor analytic techniques
were used to determine how much variance in composite
language score could be accounted for by WM and pro-
cessing speed in the combined samples. Results showed that
significantly more variance in language was accounted for by
WM capacity than processing speed, suggesting that WM
plays a predominant role in children’s standardized language
functioning. By extension, WM capacity limitations play a
stronger role than processing speed in explaining the poor
language test scores of children with SLI. Montgomery and
Windsor (2007) reported similar findings. They examined the
contribution of pSTM and processing speed on the receptive
and expressive scores of a group of children with SLI and age
peers. Regression analyses showed that for the SLI group
pSTM accounted for more variance than processing speed in
both the receptive and expressive scores. They argued that the
language tests were especially taxing of pSTM. For the age
peers, neither pSTM nor speed accounted for any unique
variance in language, suggesting that the language measures
fell within the limits of these children’s pSTM and processing
speed.
WM Limitations and Language-Based
Learning Disabilities
Robust evidence indicates that WM supports the acqui-
sition of complex academic skills and knowledge across a
variety of language-based literacy areas, including reading,
writing, and mathematics (Bull & Scerif, 2001; Cain, Oakhill,
& Bryant, 2004; Seigneuric, Ehrlich, Oakhill, & Yuill, 2000;
Swanson & Berninger, 1996a). A separate literature shows
that students with WM deficits exhibit various learning
disabilities (i.e., reading, writing, and mathematics; DeJong,
1998; Swanson & Beebe-Frankenberger, 2004; Swanson
& Berninger, 1996a, 1996b). Relatedly, large-scale studies
show that individual differences in WM relate to variation
in academic achievement among school-age children, with
low-WM students attaining lower achievement (Gathercole,
Brown, & Pickering, 2003; Gathercole et al., 2004). Because
of the relation of WM and language difficulties in SLI and the
presence of language-based academic deficits in SLI (Catts,
Adlof, & Ellis Weismer, 2006; Silliman, Butler, & Wallach,
2002), the SLP should have some familiarity with these
associations to better inform her or his clinical assessment
and treatment of the memory-language problems in school-
age children with SLI.
Clinical Implications
As Johnston (1999) stated, even though the interpretation
of the evidence for a connection between the cognitive and
language deficits in SLI may not be definitive, treatment of
children with SLI is ultimately guided by our theoretical
commitment and a cost-benefit analysis of assuming or not
assuming a link. Assuming a link has the lower immediate
clinical cost, as clinicians have the option of broadening the
scope of treatment if language-based approaches yield min-
imal outcome (see below for more on this point). Our belief
in the existence of a connection is guided by our theoretical
orientation and interpretation of the extant literature.
Assessment Suggestions
Central to the assessment process is determining to what
extent a student’s language problems and academic struggles
are related to a deficit in linguistic knowledge, deficient WM
abilities, slower processing speed, or a combination of fac-
tors. Regarding linguistic competence, it is critical to deter-
mine the range and level of linguistic knowledge of the
student using various standardized language tools as well as
performing systematic task analyses. While performance on
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standardized tests is generally taken as an index of language
knowledge, performance may be affected by poor general
processing abilities (Leonard et al., 2007; Montgomery &
Windsor, 2007). Through careful and systematic task anal-
ysis and observation, it may be possible to identify perfor-
mance patterns within and across tests that implicate WM
and speed of processing issues; we discuss this below.
The SLP should be able to estimate and infer students’
WM and processing speed based on performance on various
standardized and nonstandardized tools and their ability to
manage these abilities in the service of language-based prob-
lem solving. With respect to standardized measures, WM
problems can be identified in two ways: (a) screening using
subtests from IQ tests and (b) performance on specific mem-
ory tests. The various subtests from IQ tests are not available
to the SLP to administer. Importantly, however, several mem-
ory tests have become available for use by the SLP.
It has been suggested that the diagnosis of memory impair-
ment should be based on inclusionary and exclusionary
criteria, and should be made independent of other cognitive
abilities (Gathercole & Alloway, 2006). An inclusionary
criterion entails students attaining a score that falls greater
than 1 SD below the mean on a standardized memory mea-
sure, irrespective of IQ. Exclusionary criteria involve the
absence of hearing and articulation deficits (Gathercole &
Alloway, 2006). The reader is referred to Gathercole and
Alloway (2006) for an in-depth discussion of the diagnostic
process and use of various assessment tools. Table 2 lists a
variety of standardized tools and informal methods available
to all licensed SLPs to assess school-age children’s WM and
processing speed.
Estimating STM capacity. The digits forward subtest from
the Wechsler Intelligence Scale for Children—Third Edition
(Wechsler, 1991) and the Test of Memory and Learning
(Reynolds & Bigler, 1994) as well as the word order sub-
test from the Kaufman Assessment Battery for Children
(Kaufman & Kaufman, 1983) are three screening measures
that can provide an estimate of STM. Each test requires
children to recall a series of digits or words in the order they
have been presented. Although the SLP is not licensed to
administer these measures, the results from such tests often
can be made available to the SLP to incorporate into her
or his clinical profile of a student.
Several standardized memory tests are available to prac-
ticing SLPs for clinical use. One is the Automated Working
Memory Assessment (AWMA) by Alloway (2007). The
AWMA, appropriate for ages 4 to 22 years, has several STM
tests, including digit recall, recalling words, recalling non-
words (assessing verbal STM), block recall, and visual matrix
memory (assessing visual STM). An important companion
measure is the Working Memory Rating Scale (WMRS;
Alloway, Gathercole, & Kirkland, 2008 ), a 22-item behavioral
TABLE 2. Standardized tools and informal assessment methods available to the speech-language
pathologist to assess WM and processing speed in children with SLI.
Mechanism/property Assessment method
Short-term memory (STM) capacity
Verbal STM Automated Working Memory Assessment (Alloway, 2007)
Visuospatial STM Working Memory Rating Scale (Alloway et al., 2008)
The Children’s Test of Nonword Repetition (Gathercole &
Baddeley, 1996)
Working Memory Test Battery for Children (Pickering &
Gathercole, 2001)
Nonword Repetition Task—nonstandardized (Dollaghan &
Campbell, 1998)
WM capacity
Verbal WM capacity Automated Working Memory Assessment (Alloway, 2007)
Visuospatial WM capacity Working Memory Rating Scale (Alloway et al., 2008)
Working Memory Test Battery for Children (Pickering &
Gathercole, 2001)
Recalling Sentences subtest of the CELF–4 (Semel et al.,
2003)
Test of Narrative Language (Gillam & Pearson, 2004)
Understanding Spoken Paragraphs subtest of the CELF–4
(Semel et al., 2003)
Central executive properties and functions
Attentional capacity Task analyses
Attentional allocation
Processing speed
Word level Test of Word Finding, Second Edition (German, 2000)
Rapid Automatic Naming subtest of the CELF–4 (Semel
et al., 2003)
Rapid Automatized Naming and Rapid Alternating Stimulus
Tests (Wolf & Denkla, 2005)
Sentence and discourse levels Task analyses
Note. CELF–4 = Clinical Evaluation of Language Fundamentals, Fourth Edition.
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rating scale designed for teachers to help identify children
with WM problems. The WMRS has been conormed with the
AWMA, thus providing a reliable tool to screen children’s
memory abilities. A low score on the WMRS in combination
with a low score on the AWMA or another standardized mem-
ory measure would provide converging evidence that a
student has memory problems.
A second test is the Working Memory Test Battery for
Children (WMTB–C; Pickering & Gathercole, 2001). The
WMTB–C (appropriate for ages 5 to 15 years) includes four
subtests of verbal STM (digit recall, word list matching, word
list recall, and nonword repetition) and two visuospatial sub-
tests (block recall and mazes memory). A third test is the
Children’s Test of Nonword Repetition (Gathercole &
Baddeley, 1996), appropriate for 4–8-year-old children.
Although not a normed test, the Nonword Repetition Task
by Dollaghan and Campbell (1998) is also available.
Estimating WM capacity. Students’WM capacity may
be estimated by using various subtests from the AWMA
(Alloway, 2007) and WMTB–C (Pickering & Gathercole,
2001). The AWMA includes a verbal WM subtest and a
visuospatial WM subtest. The WMTB–C includes three sub-
tests (listening span, backward digit recall, and counting
span). The listening span task invites students to perform
concurrent verbal processing and storage. Backward digit
recall asks students to repeat increasingly longer lists of
digits in the reverse order they heard them. The storage com-
ponent entails remembering the digits, and the processing
component involves reversing the order of the numbers. In
counting span, children count the number of dots on a stim-
ulus page and then recall the number of dots from each page
of dots that was presented. The SLP may also wish to ad-
minister a sentence repetition task such as the one from the
Clinical Evaluation of Language Fundamentals, Fourth Edi-
tion (CELF–4; Semel, Wiig, & Secord, 2003). Children are
asked to repeat verbatim a range of sentences varying in
length and complexity. The task has been shown to reliably
identify children with SLI who have memory difficulties
(Archibald & Joanisse, 2009; Conti-Ramsden, Botting, &
Faragher, 2001; Stokes, Wong, Fletcher, & Leonard, 2006).
Some authors argue that the task assesses WM capacity
and linguistic knowledge (Conti-Ramsden et al., 2001), but
others suggest that it taps the episodic buffer (Gathercole &
Alloway, 2006). While the underlying mechanism support-
ing sentence repetition needs resolving, the clinical use of
sentence imitation in identifying children with memory
problems appears strong.
The SLP may also wish to perform careful task analyses
(e.g., Lahey & Bloom, 1994) of standardized language tests
and error analyses of children’s performance to gain impor-
tant clues about whether weak WM abilities may have
contributed to their poor language performances. Take, for
example, the Word Classes Receptive subtest of the CELF–4
(Semel et al., 2003) for children 9 years and older. Some
children may have trouble with this task not because of a
lack of familiarity with the lexical material but because of
the WM demands of the task. For instance, they may have
trouble remembering the four stimulus words that are pre-
sented (e.g., fence, window, glass, and rug) while simulta-
neously comparing the semantic association among the words
to decide which two are related in some fashion. These com-
parison and decision-making processes must be completed
in a timely manner before any of the words are forgotten. At
the sentence level, SLPs may administer the Recalling Sen-
tences subtest of the CELF–4 as an output measure and
perform a pattern analysis to determine the nature of chil-
dren’s errors (e.g., primarily ill grammatical repetitions or
loss of information).
Assessing school-age children’s memory for narrative is
also critical given the importance of narrative in children’s
social and academic development (Hicks, 1991; Paul & Smith,
1993; Peterson, Jesso, & McCabe, 1999). Clinicians may wish
to administer the Test of Narrative Language (R. Gillam &
Pearson, 2004) and/or the Understanding Spoken Paragraphs
subtest of the CELF–4. The Test of Narrative Language is
appropriate for 5–11-year-old children, and the CELF–4
subtest is appropriate from 9 to 21 years of age. Poor memory
may be inferred based on the children’s performance on the
various probe questions asked, while story retelling can be
evaluated in terms of whether their responses may reflect a
loss of information.
Estimating speed of processing. There are few commer-
cially available standardized tests designed to assess chil-
dren’s speed of input and /or output processing. There are,
however, tests designed to examine the rate and accuracy
of lexical access/retrieval, that is, rapid automatic naming
tests, including the Rapid Automatized Naming and Rapid
Alternating Stimulus Tests (Wolf & Denkla, 2005); Test
of Word Finding, Second Edition (German, 2000); and the
Rapid Automatic Naming subtest of the CELF–4(Semel
et al., 2003). Each of these tests requires children to name
pictures such as colors, objects, and numbers as quickly and
accurately as possible.
Beyond the word level, however, there are no standardized
instruments to evaluate the speed at which students are able
to process language. Importantly, though, clinicians may be
able to draw reasonable inferences about the speed of students’
input and output processing by engaging in careful and sys-
tematic observation of students’language performance under
different “loading”conditions during various language ac-
tivities. On the input side, clinicians may systematically vary
their speaking rate as they present language material that
varies in volume and complexity. Presenting variable amounts
of simple and complex language material at different speaking
rates can allow the clinician to observe to what degree the
memory and comprehension of material are affected by input
rate. It would be predicted that increases in language com-
plexity and volume would lead to decreased comprehension
(Leonard et al., 2007; Montgomery, 2005, 2006; Montgomery
& Windsor, 2007). On the output side, systematically vary-
ing the time children have to complete various language
production tasks (e.g., single word retrieval, sentence pro-
duction, narrative, description, and explanation) may pro-
vide clinicians information about how children manage the
multiple memory and language demands under different
output requirements. From these observations, clinicians
may gain a sense of the conditions under which children
have trouble coordinating their language and memory
functioning, information that may be valuable in planning
intervention.
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Intervention Suggestions
The intervention techniques SLPs use to remediate the
language and cognitive deficits in school-age students with
SLI should be grounded in the principles of evidence-based
practice (EBP). The clinical decision-making process should
be informed by a combination of scientific evidence, expe-
rience of the clinician, and the client’s (and parents’) needs
(S. Gillam & Gillam, 2006). The present article focuses on the
relation of cognition and language in students with SLI. Ac-
cordingly, the focus of intervention centers on remediating
the weak cognitive processing of these children with the
intent of promoting stronger language abilities.
Structuring intervention with students with SLI to include
training of cognitive processes would seem to be important
for four reasons. First, students with SLI, especially those
with receptive impairments, show resistance to language
intervention (Bishop, Adams, & Rosen, 2006; Law, Garrett,
& Nye, 2004) and inconsistent response to treatment de-
signed to ameliorate their syntactic processing deficit (Ebbels,
2007). It would seem that non-language-based treatments
should begin to be considered.
Second, there exist no intervention studies focusing on
improving the language abilities of students in the middle
grades and beyond (Cirrin & Gillam, 2008). Third, there are
no published EBP guidelines for providing language inter-
vention to school-age children with SLI (S. Gillam & Gillam,
2006). In the absence of such guidelines, Gillam and Gillam
offer a seven-step clinical decision-making process in which
SLPs integrate research evidence with their own clinical
expertise/experience and training, and the needs of the student
(and parents). Given this state of affairs, we propose that this
process should consider other reliable sources of emerging
evidence, particularly from psychology, to support the use of
alternative treatment approaches such as memory training
with students with SLI.
Fourth, it has been suggested by some SLI researchers
(Bishop et al., 2006) that failure to factor into language
intervention the cognitive processing limitations of students
with SLI will likely lead to poor outcomes. The suggestions
for cognitive training offered below clearly must undergo
rigorous and systematic investigation with children with SLI
before EBP acceptance can be established. Finally, readers
may wish to refer to Gathercole and Alloway (2006) for
additional treatment suggestions.
Phonological STM training. Teaching verbal rehearsal
strategies may prove helpful to children with SLI for certain
language situations. One strategy involves more efficient
use of the phonological loop. The phonological loop not
only involves storage but also includes a rehearsal process
(Baddeley, 1996) designed to refresh and maintain the con-
tents of STM. Maintaining the contents of STM is important
in a variety of everyday situations, including remembering
instructions, new names, and phone numbers, as well as ver-
bally directing attention from one element of a task to another
element. Age-related improvements in rehearsal strategies
begin in the elementary school years (Gathercole, 1998;
Lehmann & Hasselhorn, 2007; Ornstein & Naus, 1985;
Schneider & Sodian, 1997) and show qualitative shifts from
labeling (using a single item name only once) or passive
rehearsal (single item rehearsals) to cumulative rehearsal
(consisting of multi-item rehearsal). These strategies benefit
from explicit training, with evidence indicating that train-
ing can enhance STM capacity (Kail, 1990), metacognitive
functioning (Siegler, 2000), and WM capacity (Lehmann &
Hasselhorn, 2007). Critically, there is emerging evidence
that rehearsal training can enhance the STM storage/recall of
children with SLI (Gill, Klecan-Aker, Roberts, & Fredenburg,
2003), as well as other children with language problems
(Loomes, Rasmussen, Pei, Manji, & Andrew, 2008).
WM capacity training. The adult and childhood literatures
are rich with examples of robust correlations between WM
performance and higher order cognitive functioning, includ-
ing fluid intelligence, reading comprehension, and mathe-
matics. Important new developments have also taken place in
the experimental psychology literature regarding the impact
of explicit training of WM capacity. There is strong emerging
evidence that training WM capacity leads to increases not
only in WM capacity but also in fluid intelligence in adults
(Jaeggi et al., 2007; Jaeggii, Buschkuehl, Jonides, & Perrig,
2008; Westerberg & Klingberg, 2007). Even more important,
there are emerging and robust developmental data showing
similar training effects in children, both TD children and
children with various learning difficulties. For instance, WM
capacity training has been shown to lead to improved WM
capacity as well as reading comprehension accuracy and
reading speed in young elementary school–age children
(Loosli, Buschkuehl, Perrig, & Jaeggi, 2008). Training in
WM has also been shown to transfer to improvements in
sustained attention in TD preschool-age children (Thorell,
Lindqvist, Nutley, Bohlin, & Klingberg, 2009). Finally, simi-
lar WM capacity training has been shown to lead to signifi-
cant increases in WM capacity, nonverbal reasoning, and
attention functioning in children diagnosed with attention
deficit/ hyperactivity disorder (Klingberg, Forssberg, &
Westerberg, 2002; Klingberg et al., 2005). Collectively, the
findings from the basic and applied psychology literatures
suggest that training WM capacity may hold promise with
children with SLI.
The purpose of training WM capacity is to help students
with SLI enhance their WM capacity, thereby allowing them
to better manage the dual demands of information processing
and storage during the solving of various language-related
activities. There are now several available computerized pro-
grams that may be beneficial to children with SLI. We should
note that we are not advocating for one program or another,
as there are no comparative data showing the efficacy of any
given program. Rather, our intent is to provide SLPs a starting
point to identify and evaluate on an ongoing basis potentially
appropriate programs for use with children with SLI. Table 3
presents a list of some available programs.
One such training program can be found as part of the
AWMA battery of Alloway (2007). The AWMA includes an
interactive training component (i.e., “Jungle Memory”)in
which children play a variety of games designed to enhance
WM capacity in the context of reading and math. The online
Web site “Soak Your Brain”offers WM training that uses
an n-back task. In an n-back task, an individual is presented
variable length series of items (digits, words, pictures) in
which an item is repeated at specific intervals relative to other
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stimuli. In a two-back letter task, for example, a listener
would respond each time he or she hears the same letter
(sound) appearing two letters ago. The task relates to WM
because successful performance relies on the listener holding
short sequences of letters in memory (storage) while count-
ing back one, two, or three letters (processing) to identify a
letter match. Cogmed Working Memory Training also offers
WM training. The activities require users to remember a
sequence of numbers, letters, or patterns in increasingly chal-
lenging conditions. Common attributes of each of these
programs are that the activities are adaptive to individual
users’ability level and progress, and users are provided clear
feedback about their performance.
Findings that children with SLI seem to struggle with
verbal storage more than visuospatial storage (Archibald &
Gathercole, 2006, 2007) would suggest that the SLP begin
WM training in the visuospatial domain. Visual stimuli might
afford the children maximum opportunity to begin to learn
how to manage their WM resources under more storage-
friendly conditions. Once children demonstrate good response
from trainingunder these conditions, clinicians could switch to
auditory stimuli. Stimulus type selection should be possible
because some of these programs (e.g., n-back training from
Soak Your Brain) offer this flexibility. The SLP may dis-
cover that training in the visuospatial domain transfers to the
auditory-verbal modality such that children will need less
training to reach a similar criterion level. Importantly, find-
ings reported by Thorell et al. (2009) indicate that such trans-
fer occurs in preschool TD children. A final strategy could be
to combine verbal and visual input during training to help
children manage the demands of cross-modal information
processing and storage that are common to academic learning
(e.g., listening/reading language material that also includes
corresponding graphics).
Compensating for slower processing speed. Many stu-
dents with SLI tend to reveal significantly slower processing
than age peers. The Fast ForWord Language intervention
program (FFW-L; Scientific Learning Corporation, 1998) is
a popular computerized program designed to improve the
processing speed and language processing abilities of chil-
dren with SLI (Merzenich et al., 1996; Tallal et al., 1996). The
FFW-L program is designed to change the rate of processing
and subsequently the language abilities of children with
SLI by providing them practice with processing acoustically/
temporally modified syllable, word, and sentence material.
Children begin by listening and responding to acoustically
exaggerated stimuli. As stimulus recognition and comprehen-
sion improve, the acoustic properties of the stimuli are
modified to approximate normal speech rate.
At least two large-scale randomized controlled trials have
compared the efficacy of FFW-L and traditional language
intervention approaches at improving the general language
abilities of students with SLI (Cohen et al., 2005; R. Gillam
et al., 2008). Results of both studies indicate that FFW-L
and traditional interventions are equally effective (effect size
ranging from small to large) in bringing about immediate
gains in general language abilities of students with SLI. The
results of Gillam et al. further showed that the gains were
maintained 6 months after training. Such findings are impor-
tant because they indicate that traditional, lower tech, lower
priced interventions can yield comparable gains in the gen-
eral language abilities of students with SLI as higher tech,
more expensive interventions such as FFW-L.
Concluding Remarks
In this article, we reviewed the new developments that
have occurred in the childhood memory and SLI literature
regarding the association between WM, processing speed,
and language. We also reviewed the new developments that
have taken place in the childhood memory literature regard-
ing the development of new robust diagnostic assessment
tools to assess children’s WM abilities. Critically, several of
these tools are available for use by licensed SLPs. By com-
pleting standardized and/or nonstandardized targeted mem-
ory and processing speed assessments, coupled with careful
cognitive-linguistic analyses of the language and academic
tasks performed by students, the SLP should be in a stronger
position to build a profile of cognitive-linguistic strengths
and weaknesses of children with SLI. Information about
new computerized methods from the childhood memory
literature that might be potentially useful in remediating the
memory problems of children with SLI was also provided.
Hopefully, the information provided in this article will
provide SLPs with a new framework and tools to include
in their clinical arsenal to aid in the diagnosis and treat-
ment of the cognitive-linguistic limitations of children with
SLI.
Finally, though important gains have been made in the
past 10 years, much remains to be learned about the (a) WM
TABLE 3. Potential WM training and informal techniques to address the slower processing speed in children with SLI.
WM/speed Treatment approach Available tools
Phonological STM capacity Verbal rehearsal training
WM capacity Computerized WM capacity training Automated Working Memory Assessment
(Alloway, 2007)
Cogmed Working Memory Training
(www.neurodevelopmentcenter.com/index.php?id=128)
Soak Your Brain (www.soakyourhead.com/)
Processing speed Computerized training Fast ForWord Language (Scientific Learning Corporation, 1998;
Acoustic manipulation of input to children
Use exaggerated speech
Provide additional processing time
Note: Fast ForWord Language proves no more effective than
traditional language interventions in improving language skills.)
Montgomery et al.: Working Memory and Language in SLI 89
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and processing speed of children with SLI, (b) the associa-
tion of these abilities with the language learning and perfor-
mance of children with SLI and TD children, and (c) best
practices regarding the diagnosis and treatment of the
memory-language limitations of children with SLI.
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Received April 11, 2009
Accepted September 27, 2009
DOI: 10.1044/1058-0360(2009/09-0028)
Contact author: James Montgomery, Ohio University—Hearing,
Speech & Language Sciences, Grover Center W218,
Athens, OH 45701-2959. E-mail: montgoj1@ohio.edu.
94 American Journal of Speech-Language Pathology •Vol. 19 •78–94 •February 2010
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DOI: 10.1044/1058-0360(2009/09-0028)
online Nov 30, 2009;
19, 78-94 originally publishedAmerican Journal of Speech-Language Pathology,
2010
James W. Montgomery Beula M. Magimairaj and Mianisha C. Finney
Relation and Perspectives on Assessment and Treatment
Working Memory and Specific Language Impairment: An Update on the
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