Project DyAdd: implicit learning in adult dyslexia and ADHD

Distinct reinforcement learning profiles distinguish between language and attentional neurodevelopmental disorders

BACKGROUND

Theoretical models posit abnormalities in cortico-striatal pathways in two of the most common neurodevelopmental disorders (Developmental dyslexia, DD, and Attention deficit hyperactive disorder, ADHD), but it is still unclear what distinct cortico-striatal dysfunction might distinguish language disorders from others that exhibit very different symptomatology. Although impairments in tasks that depend on the cortico-striatal network, including reinforcement learning (RL), have been implicated in both disorders, there has been little attempt to dissociate between different types of RL or to compare learning processes in these two types of disorders. The present study builds upon prior research indicating the existence of two learning manifestations of RL and evaluates whether these processes can be differentiated in language and attention deficit disorders. We used a two-step RL task shown to dissociate model-based from model-free learning in human learners.

RESULTS

Our results show that, relative to neurotypicals, DD individuals showed an impairment in model-free but not in model-based learning, whereas in ADHD the ability to use both model-free and model-based learning strategies was significantly compromised.

CONCLUSIONS

Thus, learning impairments in DD may be linked to a selective deficit in the ability to form action-outcome associations based on previous history, whereas in ADHD some learning deficits may be related to an incapacity to pursue rewards based on the tasks' structure. Our results indicate how different patterns of learning deficits may underlie different disorders, and how computation-minded experimental approaches can differentiate between them.

Can adults with developmental dyslexia apply statistical knowledge to a new context?

We investigated transfer of artificial grammar learning in adults with and without dyslexia in 3 experiments. In Experiment 1, participants implicitly learned an artificial grammar system and were tested on new items that included the same symbols. In Experiment 2, participants were given practice with letter strings and then tested on strings created with a different letter set. In Experiment 3, participants were given practice with shapes and then tested on strings created with different shapes. Results show that in Experiment 1, both groups demonstrated utilization of pre-trained instances in the subsequent grammaticality judgement task, while in Experiments 2 (orthographic) and 3 (nonorthographic), only typically developed participants demonstrated application of knowledge from training to test. A post hoc analysis comparing between the experiments suggests that being trained and tested on an orthographic task leads to better performance than a nonorthographic task among typically developed adults but not among adults with dyslexia. Taken together, it appears that following extensive training, individuals with dyslexia are able to form stable representations from sequential stimuli and use them in a subsequent task that utilizes strings of similar symbols. However, the manipulation of the symbols challenges this ability.

A failure of sleep-dependent consolidation of visuoperceptual procedural learning in young adults with ADHD

ADHD has been associated with cortico-striatal dysfunction that may lead to procedural memory abnormalities. Sleep plays a critical role in consolidating procedural memories, and sleep problems are an integral part of the psychopathology of ADHD. This raises the possibility that altered sleep processes characterizing those with ADHD could contribute to their skill-learning impairments. On this basis, the present study tested the hypothesis that young adults with ADHD have altered sleep-dependent procedural memory consolidation. Participants with ADHD and neurotypicals were trained on a visual discrimination task that has been shown to benefit from sleep. Half of the participants were tested after a 12-h break that included nocturnal sleep (sleep condition), whereas the other half were tested after a 12-h daytime break that did not include sleep (wakefulness condition) to assess the specific contribution of sleep to improvement in task performance. Despite having a similar degree of initial learning, participants with ADHD did not improve in the visual discrimination task following a sleep interval compared to neurotypicals, while they were on par with neurotypicals during the wakefulness condition. These findings represent the first demonstration of a failure in sleep-dependent consolidation of procedural learning in young adults with ADHD. Such a failure is likely to disrupt automatic control routines that are normally provided by the non-declarative memory system, thereby increasing the load on attentional resources of individuals with ADHD.

Cognitive mechanisms of statistical learning and segmentation of continuous sensory input

Two classes of cognitive mechanisms have been proposed to explain segmentation of continuous sensory input into discrete recurrent constituents: clustering and boundary-finding mechanisms. Clustering mechanisms are based on identifying frequently co-occurring elements and merging them together as parts that form a single constituent. Bracketing (or boundary-finding) mechanisms work by identifying rarely co-occurring elements that correspond to the boundaries between discrete constituents. In a series of behavioral experiments, I tested which mechanisms are at play in the visual modality both during segmentation of a continuous syllabic sequence into discrete word-like constituents and during recognition of segmented constituents. Additionally, I explored conscious awareness of the products of statistical learning—whole constituents versus merged clusters of smaller subunits. My results suggest that both online segmentation and offline recognition of extracted constituents rely on detecting frequently co-occurring elements, a process likely based on associative memory. However, people are more aware of having learnt whole tokens than of recurrent composite clusters.

Identifying gaps in using artificial intelligence to support students with intellectual disabilities from education and health perspectives

Purpose

Students with developmental/intellectual disabilities (ID/DD) often have serious health issues that require additional medical care and supervision. Serious health issues also mean increased absence and additional lags in academic achievement and development of adaptive and social skills. The incorporation of artificial intelligence in the education of a child with ID/DD could ameliorate the educational, adaptive and social skill gaps that occur as a direct result of persistent health problems.

Design/methodology/approach

The literature regarding the use of artificial intelligence in education for students with ID/DD was collected systematically from international online databases based on specific inclusion and exclusion criteria. The collected articles were analyzed deductively, looking for the different gaps in the domain. Based on the literature, an artificial intelligence–based architecture is proposed and sketched.

Findings

The findings show that there are many gaps in supporting students with ID/DD through the utilization of artificial intelligence. Given that the majority of students with ID/DD often have serious and chronic and comorbid health conditions, the potential use of health information in artificial intelligence is even more critical. Therefore, there is a clear need to develop a system that facilitates communication and access to health information for students with ID/DD, one that provides information to caregivers and education providers, limits errors, and, therefore, improves these individuals' education and quality of life.

Practical implications

This review highlights the gap in the current literature regarding using artificial intelligence in supporting the education of students with ID/DD. There is an urgent need for an intelligent system in collaboration with the updated health information to improve the quality of services submitted for people with intellectual disabilities and as a result improving their quality of life.

Originality/value

This study contributes to the literature by highlighting the gaps in incorporating artificial intelligence and its service to individuals with ID/DD. The research additionally proposes a solution based on the confounding variables of students’ health and individual characteristics. This solution will provide an automated information flow as a functional diagnostic and intervention tool for teachers, caregivers and parents. It could potentially improve the educational and practical outcomes for individuals with ID/DD and, ultimately, their quality of life.

Procedural Sequence Learning in Attention Deficit Hyperactivity Disorder: A Meta-Analysis

Previous literature proposes that the motor deficits in Attention Deficit Hyperactivity Disorder (ADHD) may be attributed to impairments of the procedural memory network, a long-term memory system involved in sensorimotor and cognitive skill development. A handful of studies have explored procedural sequence learning in ADHD, but findings have been inconsistent. A meta-analysis was conducted to begin to establish whether procedural sequence learning deficits exist in ADHD. The results of seven studies comprising 213 participants with ADHD and 257 participants with typical development (TD) generated an average standardized mean difference of 0.02 (CI95 -0.35, 0.39) that was not significant. Heterogeneity was significant across studies and could be partially attributed to the age of participants. We argue that procedural sequence learning appears to be preserved in ADHD and discuss potential explanations for and against this finding.

An evolutionary account of intermodality differences in statistical learning

The cognitive mechanisms underlying statistical learning are engaged for the purposes of speech processing and language acquisition. However, these mechanisms are shared by a wide variety of species that do not possess the language faculty. Moreover, statistical learning operates across domains, including nonlinguistic material. Ancient mechanisms for segmenting continuous sensory input into discrete constituents have evolved for general-purpose segmentation of the environment and been readopted for processing linguistic input. Linguistic input provides a rich set of cues for the boundaries between sequential constituents. Such input engages a wider variety of more specialized mechanisms operating on these language-specific cues, thus potentially reducing the role of conditional statistics in tokenizing a continuous linguistic stream. We provide an explicit within-subject comparison of the utility of statistical learning in language versus nonlanguage domains across the visual and auditory modalities. The results showed that in the auditory modality statistical learning is more efficient with speech-like input, while in the visual modality efficiency is higher with nonlanguage input. We suggest that the speech faculty has been important for individual fitness for an extended period, leading to the adaptation of statistical learning mechanisms for speech processing. This is not the case in the visual modality, in which linguistic material presents a less ecological type of sensory input.

Project DyAdd: Non-linguistic Theories of Dyslexia Predict Intelligence

Two themes have puzzled the research on developmental and learning disorders for decades. First, some of the risk and protective factors behind developmental challenges are suggested to be shared and some are suggested to be specific for a given condition. Second, language-based learning difficulties like dyslexia are suggested to result from or correlate with non-linguistic aspects of information processing as well. In the current study, we investigated how adults with developmental dyslexia or ADHD as well as healthy controls cluster across various dimensions designed to tap the prominent non-linguistic theories of dyslexia. Participants were 18–55-year-old adults with dyslexia (n = 36), ADHD (n = 22), and controls (n = 35). Non-linguistic theories investigated with experimental designs included temporal processing impairment, abnormal cerebellar functioning, procedural learning difficulties, as well as visual processing and attention deficits. Latent profile analysis (LPA) was used to investigate the emerging groups and patterns of results across these experimental designs. LPA suggested three groups: (1) a large group with average performance in the experimental designs, (2) participants predominantly from the clinical groups but with enhanced conditioning learning, and (3) participants predominantly from the dyslexia group with temporal processing as well as visual processing and attention deficits. Despite the presence of these distinct patterns, participants did not cluster very well based on their original status, nor did the LPA groups differ in their dyslexia or ADHD-related neuropsychological profiles. Remarkably, the LPA groups did differ in their intelligence. These results highlight the continuous and overlapping nature of the observed difficulties and support the multiple deficit model of developmental disorders, which suggests shared risk factors for developmental challenges. It also appears that some of the risk factors suggested by the prominent non-linguistic theories of dyslexia relate to the general level of functioning in tests of intelligence.

Neuromagnetic speech discrimination responses are associated with reading-related skills in dyslexic and typical readers

Poor neural speech discrimination has been connected to dyslexia, and may represent phonological processing deficits that are hypothesized to be the main cause for reading impairments. Thus far, neural speech discrimination impairments have rarely been investigated in adult dyslexics, and even less by examining sources of neuromagnetic responses. We compared neuromagnetic speech discrimination in dyslexic and typical readers with mismatch fields (MMF) and determined the associations between MMFs and reading-related skills. We expected weak and atypically lateralized MMFs in dyslexic readers, and positive associations between reading-related skills and MMF strength. MMFs were recorded to a repeating pseudoword /ta-ta/ with occasional changes in vowel identity, duration, or syllable frequency from 43 adults, 21 with confirmed dyslexia. Phonetic (vowel and duration) changes elicited left-lateralized MMFs in the auditory cortices. Contrary to our hypothesis, MMF source strengths or lateralization did not differ between groups. However, better verbal working memory was associated with stronger left-hemispheric MMFs to duration changes across groups, and better reading was associated with stronger right-hemispheric late MMFs across speech-sound changes in dyslexic readers. This suggests a link between neural speech processing and reading-related skills, in line with previous work. Furthermore, our findings suggest a right-hemispheric compensatory mechanism for language processing in dyslexia. The results obtained promote the use of MMFs in investigating reading-related brain processes.

Dyslexia Diagnosis by EEG Temporal and Spectral Descriptors: An Anomaly Detection Approach

Diagnosis of learning difficulties is a challenging goal. There are huge number of factors involved in the evaluation procedure that present high variance among the population with the same difficulty. Diagnosis is usually performed by scoring subjects according to results obtained in different neuropsychological (performance-based) tests specifically designed to this end. One of the most frequent disorders is developmental dyslexia (DD), a specific difficulty in the acquisition of reading skills not related to mental age or inadequate schooling. Its prevalence is estimated between 5% and 12% of the population. Traditional tests for DD diagnosis aim to measure different behavioral variables involved in the reading process. In this paper, we propose a diagnostic method not based on behavioral variables but on involuntary neurophysiological responses to different auditory stimuli. The experiments performed use electroencephalography (EEG) signals to analyze the temporal behavior and the spectral content of the signal acquired from each electrode to extract relevant (temporal and spectral) features. Moreover, the relationship of the features extracted among electrodes allows to infer a connectivity-like model showing brain areas that process auditory stimuli in a synchronized way. Then an anomaly detection system based on the reconstruction residuals of an autoencoder using these features has been proposed. Hence, classification is performed by the proposed system based on the differences in the resulting connectivity models that have demonstrated to be a useful tool for differential diagnosis of DD as well as a method to step towards gaining a better knowledge of the brain processes involved in DD. The results corroborate that nonspeech stimulus modulated at specific frequencies related to the sampling processes developed in the brain to capture rhymes, syllables and phonemes produces effects in specific frequency bands that differentiate between controls and DD subjects. The proposed method showed relatively high sensitivity above 0.6, and up to 0.9 in some of the experiments.

Multi-Source Interference Task paradigm to enhance automatic and controlled processes in ADHD

BACKGROUND

The role of automatic and controlled processes in children with Attention deficit hyperactivity disorder (ADHD) has recently been debated. Most theories on ADHD assume that core deficits are related to controlled processes and executive function.

AIMS

The main aim of the present study is to examine automatic and controlled attention in children with ADHD, compared to TD subjects.

METHODS AND PROCEDURES

Twenty ADHD-I children, 20 with ADHD-C and 20 typical developing children performed the Block-Formed Multi-Source Interference Task (MSIT) both in incongruent and congruent conditions.

OUTCOME AND RESULTS

Results show that clinical groups had a poorer performance than the TD group in both conditions.

CONCLUSIONS AND IMPLICATIONS

This study demonstrated that children with ADHD exhibit a deficit both in automatic and controlled processes.

Are there shared neural correlates between dyslexia and ADHD? A meta-analysis of voxel-based morphometry studies

BACKGROUND

Dyslexia and Attention-deficit/hyperactivity disorder (ADHD) are highly comorbid neurodevelopmental disorders (estimates of 25-40% bidirectional comorbidity). Previous work has identified strong genetic and cognitive overlap between the disorders, but neural overlap is relatively unexplored. This study is a systematic meta-analysis of existing voxel-based morphometry studies to determine whether there is any overlap in the gray matter correlates of both disorders.

METHODS

We conducted anatomic likelihood estimate (ALE) meta-analyses of voxel-based morphometry studies in which individuals with dyslexia (15 studies; 417 cases, 416 controls) or ADHD (22 studies; 898 cases, 763 controls) were compared to typically developing controls. We generated ALE maps for dyslexia vs. controls and ADHD vs. controls using more conservative (p < .001, k = 50) and more lenient (p < .005, k = 50) thresholds. To determine the overlap of gray matter correlates of dyslexia and ADHD, we examined the statistical conjunction between the ALE maps for dyslexia vs. controls and ADHD vs. controls (false discovery rate [FDR] p < .05, k = 50, 5000 permutations).

RESULTS

Results showed largely distinct gray matter differences associated with dyslexia and ADHD. There was no evidence of statistically significant gray matter overlap at our conservative threshold, and only one region of overlap in the right caudate at our more lenient threshold. Reduced gray matter in the right caudate may be relevant to shared cognitive correlates in executive functioning and/or procedural learning. The more general finding of largely distinct regional differences in gray matter between dyslexia and ADHD suggests that other neuroimaging modalities may be more sensitive to overlapping neural correlates, and that current neuroimaging recruitment approaches may be hindering progress toward uncovering neural systems associated with comorbidity.

CONCLUSIONS

The current study is the first to meta-analyze overlap between gray matter differences in dyslexia and ADHD, which is a critical step toward constructing a multi-level understanding of this comorbidity that spans the genetic, neural, and cognitive levels of analysis.

Statistical learning abilities of children with dyslexia across three experimental paradigms

Statistical learning (SL) difficulties have been suggested to contribute to the linguistic and non-linguistic problems observed in children with dyslexia. Indeed, studies have demonstrated that children with dyslexia experience problems with SL, but the extent of the problems is unclear. We aimed to examine the performance of children with and without dyslexia across three distinct paradigms using both on- and offline measures, thereby tapping into different aspects of SL. 100 children with and without dyslexia (aged 8-11, 50 per group) completed three SL tasks: serial reaction time (SRT), visual statistical learning (VSL), and auditory nonadjacent dependency learning (A-NADL). Learning was measured through online reaction times during exposure in all tasks, and through offline questions in the VSL and A-NADL tasks. We find significant learning effects in all three tasks, from which we conclude that, collapsing over groups, children are sensitive to the statistical structures presented in the SRT, VSL and A-NADL tasks. No significant interactions of learning effect with group were found in any of the tasks, so we cannot conclude whether or not children with dyslexia perform differently on the SL tasks than their TD peers. These results are discussed in light of the proposed SL deficit in dyslexia.

Procedural and declarative learning in dyslexia

The procedural deficit hypothesis claims that impaired procedural learning is at least partly responsible for the deficits in learning to read seen in children with developmental dyslexia. This study used a reading ability-matched design to examine group differences in both procedural and declarative learning. Both children with dyslexia and typically developing children demonstrated procedural learning on a serial reaction time task, although learning in the typically developing group increased at a greater rate towards the end of the task compared with children with dyslexia. However, these results do not provide strong evidence for the procedural deficit hypothesis, because poorer procedural learning in the group with dyslexia may reflect impairments in motor learning, rather than sequence specific procedural learning. In addition, neither group showed a relationship between procedural learning and reading ability.

Evidence of stable individual differences in implicit learning

There is a fundamental psychological and neuropsychological distinction between explicit and implicit memory, and it has been proposed that whereas there are stable trait individual differences in explicit memory ability, there are not such differences across people for implicit learning. There is, however, little evidence about whether or not there are stable trait differences in implicit learning. Here we performed a test-retest reliability study with healthy young adults in which they performed four implicit learning tasks (artificial grammar learning, probabilistic classification, serial response, and implicit category learning) twice, about a week apart. We found medium (by Cohen's guidelines) test-retest reliability for three of the tasks: probabilistic classification, serial response, and implicit category learning, suggesting that differences in implicit learning ability are more stable than originally thought. In addition, implicit learning on all tasks was unrelated to explicit measures: we did not find any correlation between implicit learning measures and independent measures of IQ, working memory, or explicit learning ability. These findings indicate that implicit learning, like explicit learning, varies reliably across individuals.

Atypical predictive processing during visual statistical learning in children with developmental dyslexia: an event-related potential study

Previous research suggests that individuals with developmental dyslexia perform below typical readers on non-linguistic cognitive tasks involving the learning and encoding of statistical-sequential patterns. However, the neural mechanisms underlying such a deficit have not been well examined. The aim of the present study was to investigate the event-related potential (ERP) correlates of sequence processing in a sample of children diagnosed with dyslexia using a non-linguistic visual statistical learning paradigm. Whereas the response time data suggested that both typical and atypical readers learned the statistical patterns embedded in the task, the ERP data suggested otherwise. Specifically, ERPs of the typically developing children (n = 12) showed a P300-like response indicative of learning, whereas the children diagnosed with a reading disorder (n = 8) showed no such ERP effects. These results may be due to intact implicit motor learning in the children with dyslexia but delayed attention-dependent predictive processing. These findings are consistent with other evidence suggesting that differences in statistical learning ability might underlie some of the reading deficits observed in developmental dyslexia.

Review of EEG-based pattern classification frameworks for dyslexia

Dyslexia is a disability that causes difficulties in reading and writing despite average intelligence. This hidden disability often goes undetected since dyslexics are normal and healthy in every other way. Electroencephalography (EEG) is one of the upcoming methods being researched for identifying unique brain activation patterns in dyslexics. The aims of this paper are to examine pros and cons of existing EEG-based pattern classification frameworks for dyslexia and recommend optimisations through the findings to assist future research. A critical analysis of the literature is conducted focusing on each framework’s (1) data collection, (2) pre-processing, (3) analysis and (4) classification methods. A wide range of inputs as well as classification approaches has been experimented for the improvement in EEG-based pattern classification frameworks. It was uncovered that incorporating reading- and writing-related tasks to experiments used in data collection may help improve these frameworks instead of using only simple tasks, and those unwanted artefacts caused by body movements in the EEG signals during reading and writing activities could be minimised using artefact subspace reconstruction. Further, support vector machine is identified as a promising classifier to be used in EEG-based pattern classification frameworks for dyslexia.

Understanding developmental language disorder - the Helsinki longitudinal SLI study (HelSLI): a study protocol

BACKGROUND

Developmental language disorder (DLD, also called specific language impairment, SLI) is a common developmental disorder comprising the largest disability group in pre-school-aged children. Approximately 7% of the population is expected to have developmental language difficulties. However, the specific etiological factors leading to DLD are not yet known and even the typical linguistic features appear to vary by language. We present here a project that investigates DLD at multiple levels of analysis and aims to make the reliable prediction and early identification of the difficulties possible. Following the multiple deficit model of developmental disorders, we investigate the DLD phenomenon at the etiological, neural, cognitive, behavioral, and psychosocial levels, in a longitudinal study of preschool children.

METHODS

In January 2013, we launched the Helsinki Longitudinal SLI study (HelSLI) at the Helsinki University Hospital ( http://tiny.cc/HelSLI ). We will study 227 children aged 3-6 years with suspected DLD and their 160 typically developing peers. Five subprojects will determine how the child's psychological characteristics and environment correlate with DLD and how the child's well-being relates to DLD, the characteristics of DLD in monolingual versus bilingual children, nonlinguistic cognitive correlates of DLD, electrophysiological underpinnings of DLD, and the role of genetic risk factors. Methods include saliva samples, EEG, computerized cognitive tasks, neuropsychological and speech and language assessments, video-observations, and questionnaires.

DISCUSSION

The project aims to increase our understanding of the multiple interactive risk and protective factors that affect the developing heterogeneous cognitive and behavioral profile of DLD, including factors affecting literacy development. This accumulated knowledge will form a heuristic basis for the development of new interventions targeting linguistic and non-linguistic aspects of DLD.

Current perspectives on the cerebellum and reading development

The dominant neural models of typical and atypical reading focus on the cerebral cortex. However, Nicolson et al. (2001) proposed a model, the cerebellar deficit hypothesis, in which the cerebellum plays an important role in reading. To evaluate the evidence in support of this model, we qualitatively review the current literature and employ meta-analytic tools examining patterns of functional connectivity between the cerebellum and the cerebral reading network. We find evidence for a phonological circuit with connectivity between the cerebellum and a dorsal fronto-parietal pathway, and a semantic circuit with cerebellar connectivity to a ventral fronto-temporal pathway. Furthermore, both cerebral pathways have functional connections with the mid-fusiform gyrus, a region implicated in orthographic processing. Consideration of these circuits within the context of the current literature suggests the cerebellum is positioned to influence both phonological and word-based decoding procedures for recognizing unfamiliar printed words. Overall, multiple lines of research provide support for the cerebellar deficit hypothesis, while also highlighting the need for further research to test mechanistic hypotheses.

Implicit sequence learning is preserved in dyslexic children

This study investigates the implicit sequence learning abilities of dyslexic children using an artificial grammar learning task with an extended exposure period. Twenty children with developmental dyslexia participated in the study and were matched with two control groups-one matched for age and other for reading skills. During 3 days, all participants performed an acquisition task, where they were exposed to colored geometrical forms sequences with an underlying grammatical structure. On the last day, after the acquisition task, participants were tested in a grammaticality classification task. Implicit sequence learning was present in dyslexic children, as well as in both control groups, and no differences between groups were observed. These results suggest that implicit learning deficits per se cannot explain the characteristic reading difficulties of the dyslexics.

Visual artificial grammar learning in dyslexia: A meta-analysis

BACKGROUND

Literacy impairments in dyslexia have been hypothesized to be (partly) due to an implicit learning deficit. However, studies of implicit visual artificial grammar learning (AGL) have often yielded null results.

AIMS

The aim of this study is to weigh the evidence collected thus far by performing a meta-analysis of studies on implicit visual AGL in dyslexia.

METHODS AND PROCEDURES

Thirteen studies were selected through a systematic literature search, representing data from 255 participants with dyslexia and 292 control participants (mean age range: 8.5-36.8 years old).

RESULTS

If the 13 selected studies constitute a random sample, individuals with dyslexia perform worse on average than non-dyslexic individuals (average weighted effect size=0.46, 95% CI [0.14 … 0.77], p=0.008), with a larger effect in children than in adults (p=0.041; average weighted effect sizes 0.71 [sig.] versus 0.16 [non-sig.]). However, the presence of a publication bias indicates the existence of missing studies that may well null the effect.

CONCLUSIONS AND IMPLICATIONS

While the studies under investigation demonstrate that implicit visual AGL is impaired in dyslexia (more so in children than in adults, if in adults at all), the detected publication bias suggests that the effect might in fact be zero.

The role of feedback in implicit and explicit artificial grammar learning: a comparison between dyslexic and non-dyslexic adults

The importance of feedback for learning has been firmly established over the past few decades. The question of whether feedback plays a significant role in the statistical learning abilities of adults with dyslexia, however, is currently unresolved. Here, we examined the role of feedback in grammaticality judgment, type of structural knowledge, and confidence rating in both typically developed and dyslexic adults. We implemented two artificial grammar learning experiments: implicit and explicit. The second experiment was directly analogous to the first experiment in all respects except training format: the standard memorization instruction was replaced with an explicit rule-search instruction. Each experiment was conducted with and without performance feedback. While both groups showed significantly improved learning in the feedback-based explicit artificial grammar learning task, only the typically developed adults demonstrated higher levels of conscious structural knowledge. The present study demonstrates that the basis for the grammaticality judgment of adults with dyslexia differs from that of typically developed adults, regardless of increase in the level of explicitness.

Statistical learning and dyslexia: a systematic review

The existing literature on developmental dyslexia (hereafter: dyslexia) often focuses on isolating cognitive skills which differ across dyslexic and control participants. Among potential correlates, previous research has studied group differences between dyslexic and control participants in performance on statistical learning tasks. A statistical learning deficit has been proposed to be a potential cause and/or a marker effect for early detection of dyslexia. It is therefore of practical importance to evaluate the evidence for a group difference. From a theoretical perspective, such a group difference would provide information about the causal chain from statistical learning to reading acquisition. We provide a systematic review of the literature on such a group difference. We conclude that there is insufficient high-quality data to draw conclusions about the presence or absence of an effect.

Feedback-based probabilistic category learning is selectively impaired in attention/hyperactivity deficit disorder

Although Attention-Deficit Hyperactivity Disorder (ADHD) is closely linked to executive function deficits, it has recently been attributed to procedural learning impairments that are quite distinct from the former. These observations challenge the ability of the executive function framework solely to account for the diverse range of symptoms observed in ADHD. A recent neurocomputational model emphasizes the role of striatal dopamine (DA) in explaining ADHD's broad range of deficits, but the link between this model and procedural learning impairments remains unclear. Significantly, feedback-based procedural learning is hypothesized to be disrupted in ADHD because of the involvement of striatal DA in this type of learning. In order to test this assumption, we employed two variants of a probabilistic category learning task known from the neuropsychological literature. Feedback-based (FB) and paired associate-based (PA) probabilistic category learning were employed in a non-medicated sample of ADHD participants and neurotypical participants. In the FB task, participants learned associations between cues and outcomes initially by guessing and subsequently through feedback indicating the correctness of the response. In the PA learning task, participants viewed the cue and its associated outcome simultaneously without receiving an overt response or corrective feedback. In both tasks, participants were trained across 150 trials. Learning was assessed in a subsequent test without a presentation of the outcome or corrective feedback. Results revealed an interesting disassociation in which ADHD participants performed as well as control participants in the PA task, but were impaired compared with the controls in the FB task. The learning curve during FB training differed between the two groups. Taken together, these results suggest that the ability to incrementally learn by feedback is selectively disrupted in ADHD participants. These results are discussed in relation to both the ADHD dopaminergic dysfunction model and recent findings implicating procedural learning impairments in those with ADHD.

Paired Associate Learning Tasks and their Contribution to Reading Skills

Associative learning has been identified as one of several non-linguistic processes involved in reading acquisition. However, it has not been established whether it is an independent process that contributes to reading performance on its own or whether it is a process that is embedded in other linguistic skills (e.g., phonological awareness or phonological memory) and, therefore, contributing to reading performance indirectly. Research has shown that performance on tasks assessing associative learning, e.g., paired-associate learning (PAL) tasks, is lower in children with specific reading difficulties compared to typical readers. We explored the differential associations of two distinct verbal-visual PAL tasks (the Bala Bbala Graphogame, BBG, and a Foreign Language Learning Task, FLLT) with reading skills (word reading and pseudo-word decoding), controlling for phonological awareness, rapid naming, and letter and digit span in children at risk for reading disabilities and their typically developing peers. Our study sample consisted of 110 children living in rural Zambia, ranging in age from 7 to 18 years old (48.1% female). Multivariate analyses of covariance were used to explore the group differences in reading performance. Repeated-measures ANCOVA was used to examine children's learning across the PAL tasks. The differential relationships between both PAL tasks and reading performance were explored via structural equation modeling. The main result was that the children at risk for reading difficulties had lower performance on both PAL tasks. The BBG was a significant predictor for both word reading and pseudo-word decoding, whereas the FLLT-only for word reading. Performance on the FLLT partially mediated the association between phonological awareness and word reading. These results illustrate the partial independence of associative learning from other reading-related skills; the specifics of this relationship vary based on the type of PAL task administered.

Evaluating the consequences of impaired monitoring of learned behavior in attention-deficit/hyperactivity disorder using a Bayesian hierarchical model of choice response time

OBJECTIVE

Performance monitoring deficits have been proposed as a cognitive marker involved in the development of attention-deficit/hyperactivity disorder (ADHD), but it is unclear whether these deficits cause impairment when established action sequences conflict with environmental demands. The current study applies a novel data-analytic technique to a well-established sequence learning paradigm to investigate reactions to disruption of learned behavior in ADHD.

METHOD

Children (ages 8-12) with and without ADHD completed a serial reaction time task in which they implicitly learned an 8-item sequence of keypresses over 5 training blocks. The training sequence was replaced with a novel sequence in a transfer block, and returned in 2 subsequent recovery blocks. Response time (RT) data were fit by a Bayesian hierarchical version of the linear ballistic accumulator model, which permitted the dissociation of learning processes from performance monitoring effects on RT.

RESULTS

Sequence-specific learning on the task was reflected in the systematic reduction of the amount of evidence required to initiate a response, and was unimpaired in ADHD. When the novel sequence onset, typically developing children displayed a shift in their attentional state while children with ADHD did not, leading to worse subsequent performance compared to controls.

CONCLUSIONS

Children with ADHD are not impaired in learning novel action sequences, but display difficulty monitoring their implementation and engaging top-down control when they become inadequate. These results support theories of ADHD that highlight the interactions between monitoring processes and changing cognitive demands as the cause of self-regulation and information-processing problems in the disorder. (PsycINFO Database Record