Neurocognitive mechanisms underlying working memory encoding and retrieval in Attention-Deficit/Hyperactivity Disorder

Abstract

Working memory (WM) impairments in ADHD have been consistently reported along with deficits in attentional control. Yet, it is not clear which specific WM processes are affected in this condition. A deficient coupling between attention and WM has been reported. Nevertheless, most studies focus on the capacity to retain information rather than on the attention-dependent stages of encoding and retrieval. The current study uses a visual short-term memory binding task, measuring both behavioral and electrophysiological responses to characterize WM encoding, binding and retrieval comparing ADHD and non-ADHD matched adolescents. ADHD exhibited poorer accuracy and larger reaction times than non-ADHD on all conditions but especially when a change across encoding and test displays occurred. Binding manipulation affected equally both groups. Encoding P3 was larger in the non-ADHD group. Retrieval P3 discriminated change only in the non-ADHD group. Binding-dependent ERP modulations did not reveal group differences. Encoding and retrieval P3 were significantly correlated only in non-ADHD. These results suggest that while binding processes seem to be intact in ADHD, attention-related encoding and retrieval processes are compromised, resulting in a failure in the prioritization of relevant information. This new evidence can also inform recent theories of binding in visual WM.

Full text

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Neurocognitive mechanisms
underlying working memory
encoding and retrieval in Attention-
Decit/Hyperactivity Disorder
Rodrigo Ortega1,2, Vladimir López3,4, Ximena Carrasco5, María Josena Escobar2,
Adolfo M. García
6,7,8,9, Mario A. Parra10,11 & Francisco Aboitiz4 ✉
Working memory (WM) impairments in ADHD have been consistently reported along with decits in
attentional control. Yet, it is not clear which specic WM processes are aected in this condition. A
decient coupling between attention and WM has been reported. Nevertheless, most studies focus
on the capacity to retain information rather than on the attention-dependent stages of encoding and
retrieval. The current study uses a visual short-term memory binding task, measuring both behavioral
and electrophysiological responses to characterize WM encoding, binding and retrieval comparing
ADHD and non-ADHD matched adolescents. ADHD exhibited poorer accuracy and larger reaction
times than non-ADHD on all conditions but especially when a change across encoding and test displays
occurred. Binding manipulation aected equally both groups. Encoding P3 was larger in the non-
ADHD group. Retrieval P3 discriminated change only in the non-ADHD group. Binding-dependent ERP
modulations did not reveal group dierences. Encoding and retrieval P3 were signicantly correlated
only in non-ADHD. These results suggest that while binding processes seem to be intact in ADHD,
attention-related encoding and retrieval processes are compromised, resulting in a failure in the
prioritization of relevant information. This new evidence can also inform recent theories of binding in
visual WM.
Attention-Decit/Hyperactivity Disorder (ADHD) is a highly prevalent neurodevelopmental disorder charac-
terized by attentional diculties, hyperactivity and impulsivity1–3. Nevertheless, attention is neither the only
cognitive process aected in this condition nor the most aected one. For instance, the search for specic impair-
ments in selective attention and orienting attention in ADHD has not yielded consistent results4–6. Among other
cognitive processes, frontal executive functions impairments are consistently reported in ADHD7,8. Moreover,
Working Memory (WM) impairment is considered a signicant cognitive feature dierentiating between ADHD
and non-ADHD children9.
e predominant theoretical model of WM is Baddeley’s multi-component model10,11. WM is dened as a
limited-capacity system responsible for encoding, retaining or maintaining, and manipulating cognitive rep-
resentations of stimuli. Such memory system encompasses independent phonological (PH) and visuospatial (VS)
subsystems, and a central executive (CE) component, responsible for the attentional control. A fourth compo-
nent, the episodic buer, was later added12. Other authors, like Cowan13 or Engle14, have proposed WM models
1Departamento de Psicología, Facultad de Ciencias Sociales, Universidad de Chile, Santiago, Chile. 2Center for Social
and Cognitive Neuroscience (CSCN), Escuela de Psicología, Universidad Adolfo Ibáñez, Santiago, Chile. 3Escuela de
Psicología, Facultad de Ciencias Sociales, Ponticia Universidad Católica de Chile, Santiago, Chile. 4Laboratorio de
Neurociencias Cognitivas, Departamento de Psiquiatría, Centro Interdisciplinario de Neurociencias, Facultad de
Medicina, Ponticia Universidad Católica de Chile, Santiago, Chile. 5Servicio de Neurología y Psiquiatría, Hospital
de Niños Dr. Luis Calvo Mackenna, Facultad de Medicina, Universidad de Chile, Santiago, Chile. 6Universidad de
San Andrés, Buenos Aires, Argentina. 7National Scientic and Technical Research Council (CONICET), Buenos Aires,
Argentina. 8Faculty of Education, National University of Cuyo, Mendoza, Argentina. 9Departamento de Lingüística y
Literatura, Facultad de Humanidades, Universidad de Santiago de Chile, Santiago, Chile. 10School of Psychological
Sciences and Health, University of Strathclyde, Glasgow, UK. 11Facultad de psicología, Universidad Autónoma del
Caribe, Barranquilla, Colombia. ✉e-mail: faboitiz@puc.cl
OPEN
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that emphasize the predominant role of attention throughout WM stages. Attentional involvement in each mem-
ory stage has also been a matter of debate. It has been suggested that attention is necessary for encoding, updating
and retrieval but has a limited role during retention15.
In the experimental psychology literature, several studies have been reported which aimed to investigate the
extent to which binding surface features in visual WM is an automatic or an attentional demanding function16–19.
e evidence gathered to date suggests that binding of features in visual WM requires no more attentional
resources than processing individual features. e consistency of these ndings across a thorough experimental
series, led Allan Baddeley to revise the WM model20. Such a revision tried to address the concept and function of
the episodic buer; a WM component wherein binding functions were thought to be carried out via the support
from attention. Despite the attractiveness of these studies, they focused on healthy samples of university students
who, although subjected to experimental manipulations of attention, may have enough available resources to cope
with attentional interference and still perform the task at a high level of accuracy. It would be highly desirable to
further investigate visual WM binding in individuals with attentional disorders, such as those diagnosed with
ADHD.
Traditionally, WM is considered part of the executive functions. Both WM and executive functions, have been
criticized due to their limited specication3,9. Nevertheless, processes like conict detection, detecting mismatch
from expectations, shiing or interrupting a response, and the eortful allocation and maintenance of attention
and working memory resources towards the attainment of a future goal appear to be compromised in ADHD9.
Metanalytic studies suggest that processes such as executive attention, working memory, along with decision
making factors like motivation and reward are central to understand the ADHD cognitive prole21. Reaction
times variability is also considered part of this cognitive prole3.
When children, adolescents and adults with ADHD are assessed, WM and other executive dysfunctions stand
out as the ones with the most reliable discriminative power21. Regarding the specic WM decit in ADHD both,
phonological and visuospatial components seem to be aected, being the task demands on the central executive
(CE) one of the key moderators to explain the results22,23. at is, the most sensitive WM tasks in ADHD are those
with high demands of CE component. For example, those that require the participants to remember stimuli and
later recall them in a dierent pattern than the originally presented, or those that require to compare a newly pre-
sented stimulus with a representation in WM and to update that representation. ADHD subtype (predominantly
Inattentive or Combined) seems to have no signicant eect on WM dysfunction, perhaps due to their shared
inattention symptomatology24,25.
e close relationship between selective attention and WM has long been considered a natural candidate to
explain WM impairments in ADHD26. ese impairments have been related to academic underachievement due
to poor acquisition of cognitive skills in children, which may also have a long-term impact in social development
and quality of life27,28. Unfortunately, despite the consensus about the relevance of WM decits in ADHD, the
precise mechanisms that aect ADHD performance in WM tasks are poorly understood29,30. Moreover, WM
training seems to have a limited benecial impact on ADHD, even when a signicant improvement in WM per-
formance is achieved31. is emphasizes the need to understand and empirically document the nature of the WM
impairment in ADHD in relation with other process such as attention, to improve the development of diagnostic
or intervention tools.
Electrophysiological measures such as event related potentials (ERP) are especially useful to study WM, as
they allow to dierentiate stages of encoding, retention and retrieval which cannot be directly inferred from
behavioral responses. Encoding and retrieval are systematically associated with P3-like ERP components32,33.
Interestingly, reduced P3 amplitude in ADHD has been described both in children34 and adults35. e retention
stage is commonly studied by means of contralateral delayed activity (CDA) which is sensitive to WM load and
capacity36. is ERP component is a negative slow deection usually detected at contralateral parietal sites that
exhibit larger amplitude (compared to the ipsilateral sites) as the number of items in WM increases37.
Change detection tasks (CDT) have proved to be a successful paradigm to specically explore attention and
WM16–19,38. is task usually consists of the presentation of an array of stimuli for a short period of time (S1),
which must be kept in memory (retention period) until the presentation of a test stimuli array (S2), where the
subject must respond whether the test stimuli is the same or dierent (Trial Type). is design allows the eval-
uation of the three stages described for WM: encoding, retention and retrieval. In a recent study, Spronk et al.29
used a CDT to evaluate the impact of distractors on the retention capacity of WM, by comparing adolescents
and adults with ADHD and healthy controls. ey found that adolescents were more aected than adults by the
presence of distractors but found no dierences regarding encoding and retention between groups. However,
this study evaluated only up to the retention period and not later stages where the subject must contrast the tar-
get with the memory representation and generate a response. Post-retention is highly overlooked in most WM
and ADHD studies34,39. Nevertheless, ADHD diculties in working memory updating and retrieval have been
previously reported using a dierent WM task39. Additionally, previous results of our groups suggest that the use
of cognitive resources and particularly attentional resources in ADHD reects a dierential style more than a
decit pattern or a decient capacity1,2. Such types of functional impairments could well aect the use of WM in
the post-retention period more than the process of forming representations in WM. us, an accurate character-
ization of encoding and retrieval working memory stages in ADHD could be relevant to better understand WM
role in this condition.
In summary, consensus exists regarding a poor performance of subjects with ADHD in tasks that explore
WM functioning. Nonetheless, there is no clear evidence concerning which process or mechanism is actually
compromised. Moreover, whether this decit depends on encoding, retention, or retrieval processes (or some
combination of them) is still unknown. Likewise, the retrieval of the information from WM is also an important
and mostly overlooked stage that should be explored in ADHD.
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Here we develop a novel approach aimed to explore functional indicators (behavioral and electrophysiolog-
ical) of the dierent WM stages to further our knowledge on their role in the ADHD related WM impairment.
Parra et al.40 designed a visual short-term memory binding task that allows studying binding and change detec-
tion controlling the potential inuence of the spatial location and spatial relations within the stimuli arrays. It
has allowed to describe specic patterns of WM impairment in other conditions (e.g. Alzheimer’s Disease)20,40,41.
In the present study we use a modied version of this experimental design that diers from previous studies
controlling two possible confounding aspects. First, it minimizes the possibility of linguistic rehearsal by using
no nameable polygons and non-primary colors as stimuli. Second, it allows controlling the use of spatial cues by
changing the spatial location of stimuli between S1 and S2 displays. WM binding is studied by contrasting blocks
in which all shapes are presented in black, so only the shape should be retained (Shape-Only) and others in which
the binding of shape and color is necessary to solve the task (Color-Shape binding).
Taking into account the ADHD performance on other related tasks, as well as evidence gleaned from the
experimental psychology literature, we expect in this study that impaired attention would impact on both encod-
ing and retrieval, resulting in a poorer overall performance in ADHD participants42,43. is would be especially
manifest when S2 stimuli are dierent from S1. e need for WM binding (color and shape) could impact overall
behavioral performance in all participants, but we expect no specic dierences regarding ADHD diagnosis. At
the electrophysiological level, we predict that encoding and retrieval impairment in ADHD will be associated
with a reduced amplitude of the corresponding P3 ERP components. Additionally, we expect that these electro-
physiological markers should be correlated (i.e., P3 at encoding with P3 at retrieval stages). In the retrieval stage,
group dierences should be more evident when S1 and S2 are dierent. Notwithstanding, these electrophysiolog-
ical patterns should hold regardless of whether individual or bound features are the memoranda.
Methods
Participants. A group of 18 adolescents diagnosed by a certified pediatric neurologist with ADHD
Combined Subtype according to the DSM-V criteria, that were being treated at the neurology service of the Luis
Calvo-Mackenna Children’s Hospital in Santiago and an equal number of non-ADHD adolescents, from public
schools of the same metropolitan area, voluntarily participated in the study. eir ages were from 12 to 14 years
(12.61 ± 0.80). ey were matched by age (ADHD: 12.66 ± 0.76, non-ADHD: 12.55 ± 0.85, F(1, 34) = 0.16832,
p = 0.68419), IQ (ADHD: 99.66 ± 7.12, non-ADHD: 103.66 ± 7.17, F(1, 34) = 2.8138, p = 0.10263) and educa-
tional level (school grade). A complete clinical neurological and psychological evaluation was conducted in all
the participants to rule out any potential confound. at included Conner ‘s Rating scale for parents and teachers,
MINI-KID, STAI anxiety inventory and WISC III test. Subjects with antecedents of any other Neurological or
Psychiatric disease were excluded from the study. Comorbid symptoms of anxiety and conduct disorder were
observed, but no ADHD participant met the criteria for any mayor comorbid disorder. ey were being treated
with methylphenidate for at least four months, but suspended medication 24 hours prior to the study.
e required sample size was calculated a priori using G*Power 344 according to the sample sizes, statistical
power and eect sizes described in previous studies using the same task and/or comparing the same dependent
variables45,46. Expecting a small to moderate eect sizes, the required sample size was of 16 participants per group.
Recruitment of participants were conducted according to the standards set forth in the Declaration of
Helsinki. Aer a clear explanation of the purpose and nature of the research they were asked to formally express
their williness to participate. Informed consent was obtained from a parent and/or legal guardian and participants
also signed an informed assent form. ey were explicitly informed that they were free to nish their partici-
pation at any moment without any question. e whole protocol was examined, approved and followed by the
ethical committee of the Pontical Catholic University of Chile.
Experimental design. This experimental design is an adaptation from previous studies of our
group20,40,41,45,47,48, in particular one adapted for EEG recordings and presenting additional control of potential
confounding such as linguistic rehearsal and spatial information49.
Stimuli. No nameable geometric shapes and non-primary colors were used to minimize verbal rehearsal40. Two
arrays, of three items each, were presented to the le and to the right of a xation cross. Each array was presented
using a virtual 3×3 grid (4° horizontally x 8° vertically), 3° to the le and right of a central xation cross on a grey
background. Each item size was 1° and was, at least, 2° apart from any other item. Items for the study display (S1)
were randomly selected from a set of eight polygons and eight colors and randomly allocated to the 9 positions
within the virtual grid. During the test phase (S2), the same three locations used during the study phase were used
but items locations were interchanged. Hence, items were never presented in the same locations across the study
and test display. By this way, spatial location was render uninformative (see Fig.1).
Design. e task consisted of four blocks counterbalanced across participants. Two of them were of the shape-only
condition where the stimuli consisted of three shapes in black color. e other two were Shape-Color Binding con-
dition and stimuli were three colored shapes. For each block there was a short practice session (8 trials per block)
followed by the test. Each block presented 80 trials (40 right and 40 le of which 20 are same trials – “Same”, S1 = S2 -
and 20 are dierent – “Dierent”, S1 ≠ S2 – trials). In the last case, two shapes or two colors were replaced by dierent
ones. ere was a total of 320 trials. e total duration of this task was approximately 35 minutes.
During each trial a xation cross was presented, and participants were asked to keep their eyes on it and to
press a key to initiate the trial. Fixation remained on screen throughout the trial. Aer 400 ms, two arrows were
presented for other 400 ms above and below xation. Arrows direction indicated which side should be attended.
Aer a delay of 600 ms the S1 array was presented for 1000 ms, followed by a 1000 ms retention interval. en, the
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S2 array is presented and remained on until the participant responded “Same” or “Dierent”, by pressing a specic
key with their dominant hand.
Experimental procedure. EEG recording sessions began by asking participants to sit comfortably in a dimly lit,
electrically and acoustically shielded room. A shin rest device was used to reduce unwanted head movements.
Participants receive standard verbal instructions about the experimental procedure and the experimental task. All
participants were evaluated individually.
Data acquisition. Electrophysiological signals were recorded using a NeuroScan 40-channel Digital
Electroencephalograph with a high-resolution NuAmp amplier. A 40-channel cap (Quick-Cap) from the same com-
pany was used for electrode placement following the international 10/20 electrode sites and linked mastoids as the
reference. Impedances were kept below 5 k throughout the recordings. A/D sampling frequency was set at 1000 Hz.
A band-pass digital lter between 0.1 and 30 Hz was later applied to remove unwanted frequency components. Two
additional bipolar derivations were used to monitor vertical and horizontal ocular movements (VEOG, HEOG).
Data analyses. For behavioral data, the percentage of correct responses (accuracy) and reaction times (RTs)
were measured in all subjects and conditions. Regarding ERPs, oine EEG signals were analyzed using EEGLAB/
ERPLAB Matlab toolbox50,51. Eye movements or blink artefacts were corrected using ICA (Independent compo-
nent analysis). Remaining trials that contained voltage uctuations exceeding ±100 μV (microvolts), transients
exceeding ±100 μV, or electro-oculogram activity exceeding ±50 μV were rejected. Artifact free waveforms were
segmented into 1200 ms epochs starting 200 ms before the onset of S1 and S2 arrays. Separate average waveforms
for each condition were generated.
We used a mixed model ANOVA with repeated measures for behavioral (RT, accuracy) and ERP variables.
e Encoding period of ERP components analysis has two levels: (1) Group (ADHD vs no-ADHD); and (2)
Condition (Single Shape vs. Shape-Color Binding). For the retrieval period (ERP components and behavioral
results), a three levels analysis was performed: 1) Group (ADHD vs no-ADHD); 2) Condition (Single Shape vs.
Shape-Color Binding); and 3) Trail type (Same vs. Dierent). All statistical calculations on ERPs were performed
using individual waveforms. Mean amplitude in the windows 100–130 ms for P1, 180–210 ms for N1, 320–430 ms
for early-P3, 430–600 ms for encoding late-P3, and 320–430 for Retrieval P3 were selected. P1 and N1 amplitudes
were measured on the occipital region (electrodes O1, Oz, O2) yielding similar results. Encoding early and late
P3 and retrieval P3 were measured in Parieto-Occipital midline region (electrodes CPz, Pz, Oz). Selection of
electrodes sites and ERP measures was conducted following the recommendations previously described for this
type of procedures52. For simplicity, only the results from posterior midline (Pz and Oz) were shown. Post hoc
comparisons were assessed with Tukey HSD test. Greenhouse-Geisser and Bonferroni corrections were applied
to compensate for violations of sphericity and multiple comparisons. Only statistically signicant results of ERPs
Figure 1. Schematic view of the experimental task. Le: Shape-Only condition, Dierent trial type. Right:
Color-Shape condition, Same trial type. Time in milliseconds (ms).
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(p < 0.05) were used to test the association among sequential ERP components. Correlations were explored using
Pearson’s correlation coecient (r). Fisher’s R to Z procedure was later used to compare correlations coecients53.
Follow up Bayesian analysis were performed to explore non-signicant interactions in early and late encoding P3
components using JASP soware 0.11.154.
Results
Behavioral Results. Regarding accuracy, the ADHD group showed a poorer performance on all condi-
tions (F(1, 34) = 10.047, p = 0.00322, η2 = 0.23) compared to the non-ADHD group. ere was a signicant and
expected main eect for condition type, whereby Only-Shape resulted in better performance (F(1, 34) = 39.803,
p = 0.00000, η2 = 0.54) than Color-Shape condition, but no Group x Condition interaction (F(1, 34) = 0.020,
p = 0.88969, η2 = 0.00) was found. Trial Type (same or dierent) was also signicant. When S2 was dierent from
the S1, a signicant reduction in the hit rate (F(1,34) = 13.817, p = 0.00072, η2 = 0.29) was observed. A signicant
interaction was found between Group and Trail Type (F(1,34) = 5.2559, p = 0.02818, η2 = 0.13). Post-hoc analyses
showed a signicant drop of performance in the ADHD group during dierent trials (i.e., S2 dierent from S1)
(MSE = 0.01165, df = 66.789, p = 0.0017) (see Fig.2).
Figure 2. Behavioral results, Accuracy and Reactions Times. ADHD: black bars, non-ADHD: grey bars. Time
in seconds (s).
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Regarding reaction times (RTs), the ADHD group showed slower responses than the non-ADHD group in
all conditions (F(1,34) = 13.035, p = 0.00097, η2 = 0.28). e Color-shape condition showed slower RTs than the
Only-Shape condition (F(1,34) = 6.2918, p = 0.01706, η2 = 0.16). No other eects were observed.
In summary, ADHD had longer RTs and a poorer performance on all conditions but especially in the dierent
trials. Binding manipulation aected equally ADHD and non-ADHD participants.
Electrophysiological Results. The P1 component at encoding showed larger amplitudes for the
Shape-Only condition (F(1,34)=12.304, p = 0.00129, η2 = 0.27) compared to the Color-Shape condition. No
dierences in amplitude between groups were observed (F(1,34)=00440, p = 0.94751, η2 = 0.00). e following
N1 component showed no amplitudes dierences between groups (F(1,34)=0.08056, p = 0.77826, η2 = 0.00), or
conditions (F(1,34)=1.3163, p = 0.25927, η2 = 0.03). Aer this negativity, a wide P3-like positivity was identi-
ed in the parieto-occipital region of the scalp, with a peak around 340 ms and extended in time up to 600 ms.
e earlier segment of this component, between 320 to 430 ms, exhibited larger amplitude in the non-ADHD
group than in the ADHD (F(1,34)=5.3294, p = 0.02718, η2 = 0.14), no signicant amplitude dierence by con-
dition (F(1,34)=2.9067, p = 0.0973, η2 = 0.07) or Group x Condition interaction (F(1,34)=0.1811, p = 0.67310,
η2 = 0.00) were found. e later part of this positivity (430–600) also showed larger amplitude in the non-ADHD
(F(1,34)=6.4352, p = 0.01595, η2 = 0.16), and larger amplitudes for the Color-shape condition (F(1,34)=5.8871,
p = 0.02071, η2 = 0.15). Again, no significant Group x Condition interaction (F(1,34)=2.4440, p = 0.12723,
η2 = 0.06) was found (see Fig.3). A follow up analysis using a Bayesian approach to explore the odds in favor of
null hypothesis regarding the Group x Condition Interactions showed moderate support for the null in the P3
early window (BF10 = 0.3111) and strong support in the P3 late windows (BF10 = 0.014).
A similar P3 like positive wave was evoked by S2. is retrieval P3 showed no signicant main eect for
groups (F(1,34)=0.26277, p = 0.61154, η2 = 0.00). ere was a signicant main eect of trial type, due to larger
P3 amplitude in the Same trials compare to the Dierent ones (F(1,34)=4.9394, p = 0.03301, η2 = 0.13). A statisti-
cally signicant interaction between group and Trial type was observed (F(1,34)=4.3989, p = 0.04347, η2 = 0.11).
Follow up post-hoc contrasts showed that while P3 amplitude dierentiated between Same and Dierent trials
in the non-ADHD group (MSE = 12.724, df = 37.905, p = 0.0216), it was not the case for the ADHD group
(MSE = 12.724, df = 37.905, p = 0.9996) (see Fig.4).
In summary, P3 at encoding was larger in the non-ADHD group. P3 at retrieval discriminated the presence
or absence of a change only in the non-ADHD group. Binding-dependent ERP modulations were not sensitive
to group membership.
Associations among sequential ERPs at dierent stages. e amplitude of the encoding early-P3
signicantly correlated with that of the retrieval period, both in the Same (r = 0.48077, p = 0.00299) and Dierent
(r = 0.38179, p = 0.02157) trial types. Follow up analysis showed that these signicant correlations were driven by
the results from the non-ADHD group: Same (r = 0.50955, p = 0.03077) and Dierent (r = 0.49540, p = 0.03656).
e equivalent analysis in the ADHD group showed no signicant correlation: Same (r = 0.35457, p = 0.14881)
and Dierent (r = 0.25418, p = 0.30877) (see Fig.5). Comparing the correlation coecients between the groups
using Fischer’s R to Z approach resulted in non-discriminative observed Z: Same Z(obs)= 0.5230, Dierent Z(obs)=
0.7750.
Discussion
In the present study, we found a poorer overall performance and larger RTs in ADHD versus non-ADHD partic-
ipants. Particularly, ADHD participants produced signicantly fewer hits (i.e., correctly detect if S1 and S2 were
dierent). e electrophysiological results evidenced signicant dierences between the groups in ERP compo-
nents elicited during encoding and signicant interaction Group x Trial Type during retrieval. e need to bind
color and shape resulted in no signicant Group x Condition interaction, suggesting that ADHD has no dieren-
tial impact on binding functions carried out in WM. ere was a signicant correlation between the amplitude
of the P3 component elicited during encoding and that elicited during retrieval that was signicant only in the
non-ADHD group. ese results have important implications for our understanding of the involvement of WM
in ADHD and the functional organization of this cognitive function. We discuss these implications below.
Implications for WM functions in ADHD. e behavioral results of the current study supported our orig-
inal hypothesis. All participants showed better accuracy in the “Shape-Only” than in the “Color-Shape” condi-
tion. is result has been previously observed in other studies using similar experimental designs20,45. ey are
interpreted as the cost of integrating features into objects to be kept in WM and are in line with the predictions
from the feature integration theory55. Additionally, all participants performed better when the study (S1) and the
test arrays (S2) were composed of the same items relative to trials where they had to detect and report changes
happening in the test array. at is, when they had to update the WM representation to account for a change.
ese results are in line with previous studies using similar WM tasks40,56. Our hypothesis of ADHD’s poorer
performance in all conditions was also conrmed, supporting previous reports in the literature9,21,42. Interestingly,
this was signicantly increased when a WM updating was needed.
Traditionally, poor behavioral performance of ADHD individuals on WM tasks has been explained in terms
of a dysfunctional attentional process that impairs proper use of WM resources57. For instance, a decient l-
tering of the incoming information could overload WM, rendering it also decient58,59. is idea implies that
attention and WM resources operate in tandem to process the available stimuli with the former supporting the
latter. Nevertheless, the characterization of attention impairments in ADHD does not support this notion. e
idea of a decient ltering in ADHD causing an overload of working memory and resources depletion has been
disputed58,59. Previous studies from our group1,2 point in a dierent direction. First, although ADHD do have
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problems when dealing with distractors it is not necessarily due to a decient attentional ltering. Instead, they
seem to follow task relative relevance to select and pay attention to objects2. Furthermore, several studies have
proven that specic attention decits in ADHD could be elusive5. e most consistent nding points to a dys-
function in executive attention, as part of a more general executive functions impairment that also include WM60
(but see also3). In this way, administering attention and WM resources seems to be the most typical problem.
erefore, a clear description of how the dierent WM sub-processes (encoding, binding-retention and retrieval)
operate in this population and how they relate to each other (and to attention) seems critical to understand WM
decits in ADHD.
Figure 3. Encoding stage ERPs and topographic maps. Color-Shape: blue lines, Shape-Only: red lines. ADHD:
solid lines, non-ADHD: dashed lines. Amplitudes in Microvolts (µV). Time in milliseconds (ms).
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As previously stated, behavioral responses do not allow to discriminate between the dierent WM stages and
their potential contribution to the impairment. ERPs have a high temporal resolution and dierent components
have been described as functional indicators of distinct attention and WM processes. Attention allocation impacts
the amplitude of early components of the visual ERP (P1, N1), increasing their amplitude61. In the present study,
we found signicant amplitude dierences between conditions but no dierences between groups. ese ndings
also point against a decient early visual ltering as a mechanism that could explain attention-WM impairment
in ADHD1,2. On the contrary, the P3 component has been linked to working memory and attention since its ear-
liest descriptions62. P3 amplitude has been suggested to indicate working memory updating32 but also resource
allocation63. e amplitude of P3 is known to be aected by attention allocation and, interestingly, a reduced P3
amplitude has been reported in ADHD patients through a wide variety of cognitive tests34.
In the present study, the encoding and the retrieval periods were characterized by the presence of the P3 like
component elicited by the study array and the test array respectively. In both cases these components had larger
amplitude in non-ADHD than in ADHD. ese WM-related P3 components have been previously reported in
several WM tasks33,64. Its amplitude has been related with the ecacy of encoding and retrieval65,66. For example,
Friedman and Johnson67 found that items subsequently recognized or remembered elicited larger encoding P3 than
those that were later missed. In this line, the decreased P3 amplitude in ADHD would point to a decient WM
encoding process. is way of interpreting P3 amplitude falls within the frame of the “context updating theory”
proposed by Donchin and Coles32 which suggested that P3 amplitude reects the eort to continuously update new
relevant information to the representation held in WM. Another view (non-necessarily opposite) suggests that P3
amplitude reects the allocation of attentional resources necessary to categorize stimuli for encoding and to discrim-
inate its relevance in the retrieval stage64. Although the exact meaning of WM-related P3 amplitude modulations
Figure 4. Retrieval stage ERPs and topographic maps. Same: blue lines, Dierent: red lines. ADHD: solid lines,
non-ADHD: dashed lines. Amplitudes in Microvolts (µV). Time in milliseconds (ms).
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is still a matter of discussion, the correlation between its amplitude and WM eciency seems reliable. WM rep-
resentations are exible and can be modulated dynamically according to changing goals and expectations68, and
such process requires dynamic allocation of attention and representation updating which modulates P3 amplitude.
Regarding the retrieval stage, we found larger P3 amplitude for the “Same” condition compared to the
“Dierent” one. ese eects are in line with previous results described as the new-old eect in studies of recog-
nition memory69, where larger P3 amplitudes are reported for the old items compared to new ones. It has been
suggested that such amplitude modulation reects activity from a recollection-sensitive regions in the lateral
parietal cortex, functionally indexing the representation of recollected information66. Alternatively, in the context
of a change detection task, this amplitude modulation could also be interpreted as reecting a more exhaustive
memory search in the “Same” condition until the presence of a change has been ruled out. e latter view is con-
sistent with the notion that correctly detecting change implies recollection while detecting “sameness” or absence
Figure 5. Encoding and Retrieval P3 component Amplitudes correlations. Pearson’s correlation coecient (r).
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of change, involve identifying familiarity70. Taken together the results from the P3 component presented here
suggest that both the encoding and retrieval WM processes could be compromised in ADHD.
e amplitude of Encoding and Retrieval P3 components were signicantly correlated both in the same
and in the different trial types. This correlation was apparently driven by the results from the non-ADHD
group. Nevertheless, a follow up analysis comparing correlations coefficients between groups resulted
non-discriminative, probably due to limited sample size. Given the sequential nature of the task and the probable
participation of attention both during encoding and retrieval the correlations of this neurophysiological indica-
tors was an expected result but needs further conrmation using a larger sample of participants.
Another WM process that could potentially account for the impairments seen in ADHD is the binding process
itself. at is the construction of an integrative process of objects in WM. In the current work we did not nd signi-
cant dierence between groups regarding the binding condition (Shape-Only Vs. Color-Shape), neither behaviorally
nor electrophysiologically. Even though, the Color-Shape condition resulted in larger reaction times in all partici-
pants. To our knowledge this is rst study to assess WM binding processes in ADHD. e lack of group dierences
could be explained by that fact that the neural system subserving binding processes has been reported to involve
a posterior network of parietal, temporal and occipital areas20, and not the Prefrontal Cortex anterior executive
network usually reported to be aected in ADHD71. It should be noted that parietal regions have also been reported
to be aected in ADHD72. Nevertheless, metanalytic studies suggest that ADHD impairments in dierent neural
networks are closely related to the tasks or domains being evaluated71,73. While parietal dysfunctions in ADHD have
been mostly related to attentional orienting tasks (right inferior parietal cortex)73, visuospatial working memory
tasks have been mostly correlated with frontal regions dysfunctions74. ese ndings have important implications
for current understanding of the functional organization of WM which we address in the next section. According to
our results, binding functions carried out in WM seem to be intact in ADHD. Nevertheless, more specic studies are
undoubtfully needed to explore in depth WM binding in this condition71.
In this context, our results could be interpreted as a failure in ADHD adolescents to update WM representa-
tions to accomplish task demands or a failure in the prioritization of representations as suggested by Myers et
al.75. is could potentially impact dierent subprocesses. First, during the encoding stage reduced P3 amplitude
could reect decient attention allocation to the relevant aspects when creating a representation. en, during
the retrieval stage the smaller P3 amplitude in ADHD, which also fails to discriminate between “Same” and
“Dierent” (as it occurs in the non-ADHD group) could be interpreted as evidence of a widespread failure to
assign post-selection priority to the representations held in memory and their posterior update to solve the task
at hand. is seems to be especially clear when the test stimuli were dierent from the study ones.
Implications for the functional organization WM. This study provides valuable evidence to fur-
ther assess recent positions regarding the functional organization of WM. A question that has received sub-
stantial attention in recent years is whether binding functions operating in WM require additional attentional
resources17–19. oroughly conducted experiments have manipulated attention during visual WM binding tasks
using dierent approaches and all have failed to demonstrate that binding requires resources above and beyond
those needed to process individual features. Baddeley12 envisaged that the episodic buer was the WM compo-
nent where such binding operations would occur supported by attention. Should this proposal be valid, any WM
operation requiring binding would be dramatically aected if attentional resources are not available during such
operation. Clearly, that was not the case in the series of experiments above described. ese consistent ndings
led Baddeley and collaborators16 to revise the WM models and reconsider the function of the episodic buer. e
new revision suggests that low-level binding functions, such as those needed to integrate surface features and
form objects identity, can be carried out outside the episodic buer, being areas in the posterior part of the brain
likely neural correlates20. However, a potential limitation of these experiments is that attention was experimen-
tally manipulated making it possible that individual dierences in attentional resources would have impacted on
such outcomes. A more reliable approach would involve individuals with attentional impairments such as those
diagnosed with ADHD. In the current study we addressed this issue in such a population. We have conrmed that
individuals with attention impairment, as demonstrated by their clinical proles and general WM functions, are
still able to hold bound information in WM. is is the rst study reporting such ndings which, to the authors’
views, support the notion that such binding operations could be automatic.
A potential account for such relation between attention and binding function of WM has been linked to
the type of attention needed to support this function. While executive attention seemingly driven by functions
of the prefrontal cortex might be crucial for binding operations happening within the episodic buer16, other
bottom-up low-level attentional functions might support the binding of surface features within integrated objects.
Such functions, which are seemingly supported by a posterior network involving parietal, temporal and occipital
areas20,45,49,76, might be less vulnerable to conditions impacting on attention such as ADHD or even depression40.
Recent studies have pointed to a functional integration decit of connectivity-based pathophysiologic process
in ADHD77–80. Control networks recruited during WM tasks are sensitive to neurodevelopmental factors which
aect the patterns of connectivity integration/and segregation81. A signicant body of literature suggests that
frontal networks, as those sub-serving WM, seem to be aected in ADHD82–85. is would explain the overall
WM impairment seen in these patients in the current study.
Limitations and future directions. e current study has limitations that should be addressed in future
studies. First, current and previous studies use no nameable geometric shapes and non-primary colors trying to
avoid phonological coding of non-verbal material20,45. is approach reduces but can’t ensure the complete avoid-
ance of implicit verbal rehearsal86. e presence of such strategy was not measure and its potential impact can’t
be ruled out. Future studies should consider this in their design to directly address this issue. Second, ADHD is
a complex, multisystem and highly heterogenic condition. Although inattention is probably its most consistent
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characteristic, the presence of the diagnosis cannot be equated to a constant or stable decit. ere is large intra
and inter subject’s variability. e inferences regarding the relations between WM, binding and Attention should
be further investigated using dierent experimental designs and larger sample sizes. ird, future studies should
separate more systematically attention and working memory and also should address the potential impact of
stimulant medication on WM decits in ADHD, as well as, dierent ADHD subtypes.
is work opens a new agenda investigating the role of inter-coupling among attention and WM process and
networks in ADHD and other neuropsychiatric conditions that impact on these cognitive abilities. In sum, stud-
ying the interaction between attentional guided dynamic prioritization and WM in ADHD could be a promising
approach to understand the pathophysiology of the condition and to rene understanding of models of memory.
Data availability
e datasets generated during the current study are available from the corresponding author on reasonable
request.
Received: 20 August 2019; Accepted: 14 April 2020;
Published: xx xx xxxx
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Acknowledgements
This study was supported by postdoctoral grant CONICYT/FONDECYT 3150195, and CONICYT PAI/
Concurso Nacional Inserción de Capital Humano Avanzado en la Academia Convocatoria año 2017 PAI79170011
grant to RO, and by CONICYT/FONDECYT 1160258 to FA and VL. VL work was also supported by CONICYT/
FONDECYT 1150241. MAP work was supported by Alzheimer’s Society, Grant # AS-R42303.A.M.G.work was
supported byCONICET andPrograma Interdisciplinario de Investigación Experimental en Comunicación y
Cognición (PIIECC), Facultad de Humanidades, USACH. Patricia Opazo provided valuable technical assistance.
Author contributions
R.O., V.L. and M.A.P. formulated the hypotheses and adapted the experimental design. X.C., V.L. and M.J.E.
conducted the neurological and psychological evaluation of participants. R.O. collected the data. R.O., V.L.
performed the analysis of the data and wrote the manuscript. F.A., M.A.P. and A.M.G. contributed to the
theoretical and methodological framework and critically contributed to the nal version of the manuscript. All
authors reviewed and approved the manuscript.
Competing interests
e authors declare no competing interests.
Additional information
Correspondence and requests for materials should be addressed to F.A.
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