Rule-based and information-integration perceptual category learning in children with attention-deficit/hyperactivity disorder

Preferential Choice to Exert Cognitive Effort in Children with ADHD: a Diffusion Modelling Account

Greater sensitivity to the cost of effortful engagement has long been implicated in the development of Attention Deficit Hyperactivity Disorder (ADHD). The current study evaluated preferential choice to engage in demanding tasks, and did so in combination with computational methods to interrogate the process of choice. Children aged 8-12 with (n = 49) and without (n = 36) ADHD were administered the cognitive effort discounting paradigm (COG-ED, adapted from Westbrook et al., 2013). Diffusion modelling was subsequently applied to the choice data to allow for a better description of the process of affective decision making. All children showed evidence of effort discounting, but, contrary to theoretical expectations, there was no evidence that children with ADHD judged effortful tasks to be lower in subjective value, or that they maintained a bias towards less effortful tasks. However, children with ADHD developed a much less differentiated mental representation of demand than their non-ADHD counterparts even though familiarity with and exposure to the experience of effort was similar between groups. Thus, despite theoretical arguments to the contrary, and colloquial use of motivational constructs to explain ADHD-related behavior, our findings strongly argue against the presence of greater sensitivity to costs of effort or reduced sensitivity to rewards as an explanatory mechanism. Instead, there appears to be a more global weakness in the metacognitive monitoring of demand, which is a critical precursor for cost-benefit analyses that underlie decisions to engage cognitive control.

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.

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.

Visual statistical learning and integration of perceptual priors are intact in attention deficit hyperactivity disorder

Background

Deficits in visual statistical learning and predictive processing could in principle explain the key characteristics of inattention and distractibility in attention deficit hyperactivity disorder (ADHD). Specifically, from a Bayesian perspective, ADHD may be associated with flatter likelihoods (increased sensory processing noise), and/or difficulties in generating or using predictions. To our knowledge, such hypotheses have never been directly tested.

Methods

We here test these hypotheses by evaluating whether adults diagnosed with ADHD (n = 17) differed from a control group (n = 30) in implicitly learning and using low-level perceptual priors to guide sensory processing. We used a visual statistical learning task in which participants had to estimate the direction of a cloud of coherently moving dots. Unbeknown to the participants, two of the directions were more frequently presented than the others, creating an implicit bias (prior) towards those directions. This task had previously revealed differences in other neurodevelopmental disorders, such as autistic spectrum disorder and schizophrenia.

Results

We found that both groups acquired the prior expectation for the most frequent directions and that these expectations substantially influenced task performance. Overall, there were no group differences in how much the priors influenced performance. However, subtle group differences were found in the influence of the prior over time.

Conclusion

Our findings suggest that the symptoms of inattention and hyperactivity in ADHD do not stem from broad difficulties in developing and/or using low-level perceptual priors.

A Randomized Controlled Trial of an Integrated Brain, Body, and Social Intervention for Children With ADHD

Objective: This study evaluated the efficacy of an Integrated Brain, Body, and Social (IBBS) intervention for children with ADHD. Treatment consisted of computerized cognitive remediation training, physical exercises, and a behavior management strategy. Method: Ninety-two children aged 5 to 9 years with ADHD were randomly assigned to 15 weeks of IBBS or to treatment-as-usual. Primary outcome measures included blinded clinician ratings of ADHD symptoms and global clinical functioning. Secondary outcome measures consisted of parent and teacher ratings of ADHD and neurocognitive tests. Results: No significant treatment effects were found on any of our primary outcome measures. In terms of secondary outcome measures, the IBBS group showed significant improvement on a verbal working memory task; however, this result did not survive correction for multiple group comparisons. Conclusion: These results suggest that expanding cognitive training to multiple domains by means of two training modalities does not lead to generalized improvement of ADHD symptomatology.

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.

The role of differential outcomes-based feedback on procedural memory

In categorization tasks, two memory systems may be involved in the learning of categories: one explicit and rule-based system and another implicit and procedure-based system. Learning of rule-based categories relies on some form of explicit reasoning, whereas procedural memory underlies information-integration category-learning tasks, in which performance is maximized only if information of two (or more) dimensions is integrated. The present study aimed at investigating the role of how feedback is administered, whether differential or non-differential, in procedural learning. An information-integration category-learning task was designed, where the to-be-categorized stimuli differed in two dimensions. Participants were randomly assigned to two groups: one group received the reinforcers for correct categorizations differentially, one for each category (the differential outcomes procedure, DOP), and the other group received the reinforcers randomly (the non-differential outcomes procedure, NOP). The participants of the DOP group showed better procedural learning in the categorization task, compared to the NOP group. Moreover, the analysis of learning strategies revealed that more participants developed more optimal strategies in the DOP group than in the NOP group. These results extend the benefits of the differential outcomes-based feedback to non-declarative memory tasks and help better understand the role of feedback in procedural learning.

Effects of Integrated Brain, Body, and Social (IBBS) intervention on ERP measures of attentional control in children with ADHD

A primary goal of this study was to examine the impact of an Integrated Brain, Body, and Social (IBBS) intervention (multi-faceted treatment consisting of computerized cognitive training, physical exercise, and behavior management) on ERPs of attentional control (P3 & N2) in children with ADHD. The secondary goal was to test the differences between children with and without ADHD on ERP and Go/No-Go behavioral measures. A total of twenty-nine participants (M age = 7.14 years; 52% male; 41.4% white) recruited from the IBBS efficacy study comparing IBBS to Treatment-As-Usual (TAU) completed a Go/No-Go task before and after treatment as brain activity was recorded using EEG. Thirty-four matched healthy controls (HC) completed the same EEG procedures at a single time point. Following treatment, the Go P3 latency was significantly earlier for the IBBS group relative to the TAU group. No treatment effects were found on any behavioral measures. Prior to treatment, there was a significant difference between the ADHD group and HC group for the N2 difference wave. Children with ADHD also showed slower reaction times on behavioral measures. Although this pilot study did not reveal robust treatment effects, it suggests that IBBS may prevent the worsening of attentional systems in the brain and larger studies are needed for replication purposes.

Category-Induced Transfer of Visual Perceptual Learning

Visual perceptual learning (VPL) refers to a long-term enhancement of visual task performance as a result of visual experience [1-6]. VPL is generally specific for the trained visual feature, meaning that training on a feature leads to performance enhancement only on the feature and those in its close vicinity. In the meantime, visual perception is often categorical [7-10]. This may partially be because the ecological importance of a stimulus is usually determined by the category to which the stimulus belongs (e.g., snake, lightning, and fish) [11]. Thus, it would be advantageous to an observer if encountering or working on a feature from a category increases sensitivity to features under the same category. However, studies of VPL have used uncategorized features. Here, we found a category-induced transfer of VPL, where VPL of an orientation transferred to untrained orientations within the same category as the trained orientation, but not orientations from the different category. Furthermore, we found that, although category learning transferred to other locations in the visual field, the category-induced transfer of VPL occurred only when visual stimuli for the category learning and those for VPL training were presented at the same location. These results altogether suggest that feature specificity in VPL is greatly influenced by cognitive processing, such as categorization in a top-down fashion. In an environment where features are categorically organized, VPL may be more generalized across features under the same category. Such generalization implies that VPL is of more ecological significance than has been thought.

Feedback Timing Modulates Probabilistic Learning in Adults with ADHD

Attention deficit hyperactivity disorder (ADHD) has been associated primarily with executive function deficits. Emerging findings suggest, however, that procedural learning may be compromised as well. To this effect, we recently showed that feedback-based procedural learning is selectively impaired in ADHD, results that coincide with dopaminergic alterations associated with ADHD. Key questions, however, remain unresolved, among which are the learning conditions that may improve procedural learning in ADHD. Here we examined feedback-based probabilistic learning during conditions that engage procedural and declarative learning systems to different degrees, depending on feedback timing. ADHD and control participants carried out a probabilistic learning task in which they were required to learn to associate between cues and outcomes, where outcomes were presented either immediately or with a short/long delays. Whereas performance in probabilistic learning in ADHD participants was comparable to controls in delayed feedback conditions, during both learning and test phases, their performance diminished when feedback was immediate. Furthermore, ADHD symptom severity was negatively correlated with the ability to learn from immediate feedback. These results suggest that feedback-based probabilistic learning can be improved in ADHD, provided appropriate conditions. By shifting the load from midbrain/striatal systems to declarative memory mechanisms, behavioral performance in ADHD populations can be remediated.

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.

Developmental changes between childhood and adulthood in passive observational and interactive feedback-based categorization rule learning

As children start attending school they are more likely to face situations where they have to autonomously learn about novel object categories (e.g. by reading a picture book with descriptions of novel animals). Such autonomous observational category learning (OCL) gradually complements interactive feedback-based category learning (FBCL), where a child hypothesizes about the nature of a novel object, acts based on his prediction, and then receives feedback indicating the correctness of his prediction. Here we tested OCL and FBCL skills of elementary school children and adults. In both conditions, participants performed complex rule-based categorization tasks that required associating novel objects with novel category-labels. We expected children to perform better in FBCL tasks than in OCL tasks, whereas adults to be skilled in both tasks. As hypothesized, in early-phase learning children performed better in FBCL tasks than in OCL tasks. Unexpectedly, adults performed somewhat better in OCL tasks. Early-phase FBCL performance in the two age groups was matched, but the OCL performance of adults was higher than that of children. In late-phase learning there was only an age group main effect (adults > children). Moreover, performance in post-learning categorization tasks, that did not require label recollection, indicated that in FBCL tasks children were likely to directly learn the associations between an object and a category label, whereas in the OCL tasks they were likely to first learn which feature-dimensions were relevant. These findings shed light on developmental changes in cognitive control and learning mechanisms. Implications for educational settings are discussed.

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

Unraveling the nature of autism: finding order amid change

In this article, we hypothesize that individuals with autism spectrum disorder (ASD) are born with a deficit in invariance detection, which is a learning process whereby people and animals come to attend the relatively stable patterns or structural regularities in the changing stimulus array. This paper synthesizes a substantial body of research which suggests that a deficit in the domain-general perceptual learning process of invariant detection in ASD can lead to a cascade of consequences in different developmental domains. We will outline how this deficit in invariant detection can cause uncertainty, unpredictability, and a lack of control for individuals with ASD and how varying degrees of impairments in this learning process can account for the heterogeneity of the ASD phenotype. We also describe how differences in neural plasticity in ASD underlie the impairments in perceptual learning. The present account offers an alternative to prior theories and contributes to the challenge of understanding the developmental trajectories that result in the variety of autistic behaviors.