A connectionist model of category learning by individuals with high-functioning autism spectrum disorder

Category learning in autistic individuals: A meta-analysis

Learning new categories is a fundamental human skill. In the present article, we report the first comprehensive meta-analysis of category learning in autism. Including studies comparing groups of autistic and nonautistic individuals, we investigated whether autistic individuals differ in category learning from nonautistic individuals. In addition, we examined moderator variables accounting for variability between studies. A multilevel meta-analysis of k = 50 studies examining n = 1,220 autistic and n = 1,445 nonautistic individuals based on 112 effect sizes in terms of the standardized mean difference revealed lower-level category learning skills for autistic compared with nonautistic individuals, g = -0.55, 95% CI = [-0.73, -0.38], p < .0001. According to moderator analyses, the significant amount of heterogeneity, Q(111) = 617.88, p < .0001, was explained by only one of the moderator variables under investigation-namely, study language. For the remaining variables-namely, age, year of publication, risk of bias, type of control group, IQ of autistic group, percentage of male autistic participants, type of category, type of task, and type of dependent measure-there were no significant effects. Although hat values and Cook's distance statistics confirmed the robustness of findings, results of Egger's test and a funnel plot suggested the presence of publication bias reflecting an overrepresentation of disadvantageous findings for autistic groups. Objectives for future work include identifying additional moderator variables, examining downstream effects of suboptimal category learning skills, and developing interventions.

Atypical cognitive training-induced learning and brain plasticity and their relation to insistence on sameness in children with autism

Children with autism spectrum disorders (ASDs) often display atypical learning styles; however, little is known regarding learning-related brain plasticity and its relation to clinical phenotypic features. Here, we investigate cognitive learning and neural plasticity using functional brain imaging and a novel numerical problem-solving training protocol. Children with ASD showed comparable learning relative to typically developing children but were less likely to shift from rule-based to memory-based strategy. While learning gains in typically developing children were associated with greater plasticity of neural representations in the medial temporal lobe and intraparietal sulcus, learning in children with ASD was associated with more stable neural representations. Crucially, the relation between learning and plasticity of neural representations was moderated by insistence on sameness, a core phenotypic feature of ASD. Our study uncovers atypical cognitive and neural mechanisms underlying learning in children with ASD, and informs pedagogical strategies for nurturing cognitive abilities in childhood autism.

Atypical cognitive training-induced learning and brain plasticity and their relation to insistence on sameness in children with autism

Children with autism spectrum disorders (ASD) often display atypical learning styles, however little is known regarding learning-related brain plasticity and its relation to clinical phenotypic features. Here, we investigate cognitive learning and neural plasticity using functional brain imaging and a novel numerical problem-solving training protocol. Children with ASD showed comparable learning relative to typically developing children but were less likely to shift from rule-based to memory-based strategy. Critically, while learning gains in typically developing children were associated with greater plasticity of neural representations in the medial temporal lobe and intraparietal sulcus, learning in children with ASD was associated with more stable neural representations. Crucially, the relation between learning and plasticity of neural representations was moderated by insistence on sameness, a core phenotypic feature of ASD. Our study uncovers atypical cognitive and neural mechanisms underlying learning in children with ASD, and informs pedagogical strategies for nurturing cognitive abilities in childhood autism.

Neural Networks Track the Logical Complexity of Boolean Concepts

The language of thought hypothesis and connectionism provide two main accounts of category acquisition in the cognitive sciences. However, it is unclear to what extent their predictions agree. In this article, we tackle this problem by comparing the two accounts with respect to a common set of predictions about the effort required to acquire categories. We find that the two accounts produce similar predictions in the domain of Boolean categorization, however, with substantial variation depending on the operators in the language of thought.

Neural network modeling of altered facial expression recognition in autism spectrum disorders based on predictive processing framework

The mechanism underlying the emergence of emotional categories from visual facial expression information during the developmental process is largely unknown. Therefore, this study proposes a system-level explanation for understanding the facial emotion recognition process and its alteration in autism spectrum disorder (ASD) from the perspective of predictive processing theory. Predictive processing for facial emotion recognition was implemented as a hierarchical recurrent neural network (RNN). The RNNs were trained to predict the dynamic changes of facial expression movies for six basic emotions without explicit emotion labels as a developmental learning process, and were evaluated by the performance of recognizing unseen facial expressions for the test phase. In addition, the causal relationship between the network characteristics assumed in ASD and ASD-like cognition was investigated. After the developmental learning process, emotional clusters emerged in the natural course of self-organization in higher-level neurons, even though emotional labels were not explicitly instructed. In addition, the network successfully recognized unseen test facial sequences by adjusting higher-level activity through the process of minimizing precision-weighted prediction error. In contrast, the network simulating altered intrinsic neural excitability demonstrated reduced generalization capability and impaired emotional clustering in higher-level neurons. Consistent with previous findings from human behavioral studies, an excessive precision estimation of noisy details underlies this ASD-like cognition. These results support the idea that impaired facial emotion recognition in ASD can be explained by altered predictive processing, and provide possible insight for investigating the neurophysiological basis of affective contact.

Prototype-based category learning in autism: A review

Similarity-based categorization, as an important cognitive skill, can be performed by abstracting a categories' central tendency, the so-called prototype, or by memorizing individual exemplars of a category. The flexible selection of an appropriate strategy is crucial for effective cognitive functioning. The detail-focused cognitive style in individuals with autism spectrum disorders (ASD) has been hypothesized to specifically impair prototype-based categorization but to leave exemplar-based categorization unimpaired. We first give an overview of approaches to investigate prototype-based abstraction in the prototype-distortion task, with an emphasis on model-based approaches suitable to discern the two strategies on the individual level. The second part summarizes literature speaking to prototype-based categorization in ASD using that task. Despite considerable inconsistencies, most studies appear to confirm that autistic individuals have more difficulties to perform prototype-distortion tasks than non-autistic individuals. We highlight how inconsistencies in literature can be resolved by taking the differences in task designs into account. The current review illustrates the need for sensitive computational approaches, suitable to detect hidden individual differences and potential compensatory strategies.

Perceptual category learning in autism spectrum disorder: Truth and consequences

The ability to categorize is fundamental to cognitive development. Some categories emerge effortlessly and rapidly while others can take years of experience to acquire. Children with autism spectrum disorder (ASD) are often able to name and sort objects, suggesting that their categorization abilities are largely intact. However, recent experimental work shows that the categories formed by individuals with ASD may diverge substantially from those that most people learn. This review considers how atypical perceptual category learning can affect cognitive development in children with ASD and how atypical categorization may contribute to many of the socially problematic symptoms associated with this disorder. Theoretical approaches to understanding perceptual processing and category learning at both the behavioral and neural levels are assessed in relation to known alterations in perceptual category learning associated with ASD. Mismatches between the ways in which children learn to organize perceived events relative to their peers and adults can accumulate over time, leading to difficulties in communication, social interactions, academic performance, and behavioral flexibility.

Beyond intervention into daily life: A systematic review of generalisation following social communication interventions for young children with autism

Researchers have generally considered autistic individuals to have difficulties generalising learned skills across novel contexts. Successful generalisation is necessary for an intervention to have benefits in everyday life beyond the original learning environment. We conducted a systematic review of randomised controlled trials of early social communication interventions for children with autism in order to explore generalisation and its measurement. We identified nine RCTs that provided evidence of initial target learning and measured generalisation, of which eight demonstrated at least some successful generalisation across people, settings, and/or activities. The findings did not support the widely reported generalisation 'difficulties' associated with autism. However, generalisation was not consistent across all skills within studies, and one study found no generalisation despite evidence for initial target learning within the intervention context. In general, there are few methodologically sound social communication intervention studies exploring generalisation in autism and no consensus on how it should be measured. In particular, failure to demonstrate initial learning of target skills within the intervention setting and an absence of formal mediation analyses of the hypothesised mechanisms limit current research. We outline a framework within which measurement of generalisation can be considered for use in future trials. To maximise the effectiveness of interventions, the field needs to gain a better understanding of the nature of generalisation among autistic individuals and what additional strategies may further enhance learning. Autism Res 2020, 13: 506-522. © 2020 The Authors. Autism Research published by International Society for Autism Research published by Wiley Periodicals, Inc. LAY SUMMARY: It is generally considered that autistic individuals experience difficulties applying things they have learned in one context into different settings (e.g. from school to home). This is important to consider for intervention studies. Our review does not support a complete lack of generalisation but instead suggests that after early social communication intervention, autistic children can transfer some skills to new contexts. Overall, there is limited research in this area and further work is needed.

Diminished neural adaptation during implicit learning in autism

Neuroimaging studies have shown evidence of disrupted neural adaptation during learning in individuals with autism spectrum disorder (ASD) in several types of tasks, potentially stemming from frontal-posterior cortical underconnectivity (Schipul et al., 2012). The aim of the current study was to examine neural adaptations in an implicit learning task that entails participation of frontal and posterior regions. Sixteen high-functioning adults with ASD and sixteen neurotypical control participants were trained on and performed an implicit dot pattern prototype learning task in a functional magnetic resonance imaging (fMRI) session. During the preliminary exposure to the type of implicit prototype learning task later to be used in the scanner, the ASD participants took longer than the neurotypical group to learn the task, demonstrating altered implicit learning in ASD. After equating task structure learning, the two groups' brain activation differed during their learning of a new prototype in the subsequent scanning session. The main findings indicated that neural adaptations in a distributed task network were reduced in the ASD group, relative to the neurotypical group, and were related to ASD symptom severity. Functional connectivity was reduced and did not change as much during learning for the ASD group, and was related to ASD symptom severity. These findings suggest that individuals with ASD show altered neural adaptations during learning, as seen in both activation and functional connectivity measures. This finding suggests why many real-world implicit learning situations may pose special challenges for ASD.

Heterogeneity in perceptual category learning by high functioning children with autism spectrum disorder

Previous research suggests that high functioning (HF) children with autism spectrum disorder (ASD) sometimes have problems learning categories, but often appear to perform normally in categorization tasks. The deficits that individuals with ASD show when learning categories have been attributed to executive dysfunction, general deficits in implicit learning, atypical cognitive strategies, or abnormal perceptual biases and abilities. Several of these psychological explanations for category learning deficits have been associated with neural abnormalities such as cortical underconnectivity. The present study evaluated how well existing neurally based theories account for atypical perceptual category learning shown by HF children with ASD across multiple category learning tasks involving novel, abstract shapes. Consistent with earlier results, children’s performances revealed two distinct patterns of learning and generalization associated with ASD: one was indistinguishable from performance in typically developing children; the other revealed dramatic impairments. These two patterns were evident regardless of training regimen or stimulus set. Surprisingly, some children with ASD showed both patterns. Simulations of perceptual category learning could account for the two observed patterns in terms of differences in neural plasticity. However, no current psychological or neural theory adequately explains why a child with ASD might show such large fluctuations in category learning ability across training conditions or stimulus sets.

Modeling possible effects of atypical cerebellar processing on eyeblink conditioning in autism

Autism is unique among other disorders in that acquisition of conditioned eyeblink responses is enhanced in children, occurring in a fraction of the trials required for control participants. The timing of learned responses is, however, atypical. Two animal models of autism display a similar phenotype. Researchers have hypothesized that these differences in conditioning reflect cerebellar abnormalities. The present study used computer simulations of the cerebellar cortex, including inhibition by the molecular layer interneurons, to more closely examine whether atypical cerebellar processing can account for faster conditioning in individuals with autism. In particular, the effects of inhibitory levels on delay eyeblink conditioning were simulated, as were the effects of learning-related synaptic changes at either parallel fibers or ascending branch synapses from granule cells to Purkinje cells. Results from these simulations predict that whether molecular layer inhibition results in an enhancement or an impairment of acquisition, or changes in timing, may depend on (1) the sources of inhibition, (2) the levels of inhibition, and (3) the locations of learning-related changes (parallel vs. ascending branch synapses). Overall, the simulations predict that a disruption in the balance or an overall increase of inhibition within the cerebellar cortex may contribute to atypical eyeblink conditioning in children with autism and in animal models of autism.

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.