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

Transitive inference in a clinical childhood sample with a focus on autism spectrum disorder

Transitive inference (TI) has a long history in the study of human development. There have, however, few pediatric studies that report clinical diagnoses have tested trial-and-error TI learning, in which participants infer item relations, rather than evaluate them explicitly from verbal descriptions. Children aged 8-10 underwent a battery of clinical assessments and received a range of diagnoses, potentially including autism spectrum disorder (ASD), attention-deficit hyperactive disorder (ADHD), anxiety disorders (AD), specific learning disorders (SLD), and/or communication disorders (CD). Participants also performed a trial-and-error learning task that tested for TI. Response accuracy and reaction time were assessed using a statistical model that controlled for diagnostic comorbidity at the group level. Participants in all diagnostic categories showed evidence of TI. However, a model comparison analysis suggested that those diagnosed with ASD succeeded in a qualitatively different way, responding more slowly to each choice and improving faster across trials than their non-ASD counterparts. Additionally, TI performance was not associated with IQ. Overall, our data suggest that superficially similar performance levels between ASD and non-ASD participants may have resulted from a difference in the speed-accuracy tradeoff made by each group. Our work provides a preliminary profile of the impact of various clinical diagnoses on TI performance in young children. Of these, an ASD diagnosis resulted in the largest difference in task strategy.

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.

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.

Benefits of fading in perceptual learning are driven by more than dimensional attention

Individuals learn to classify percepts effectively when the task is initially easy and then gradually increases in difficulty. Some suggest that this is because easy-to-discriminate events help learners focus attention on discrimination-relevant dimensions. Here, we tested whether such attentional-spotlighting accounts are sufficient to explain easy-to-hard effects in auditory perceptual learning. In two experiments, participants were trained to discriminate periodic, frequency-modulated (FM) tones in two separate frequency ranges (300–600 Hz or 3000–6000 Hz). In one frequency range, sounds gradually increased in similarity as training progressed. In the other, stimulus similarity was constant throughout training. After training, participants showed better performance in their progressively trained frequency range, even though the discrimination-relevant dimension across ranges was the same. Learning theories that posit experience-dependent changes in stimulus representations and/or the strengthening of associations with differential responses, predict the observed specificity of easy-to-hard effects, whereas attentional-spotlighting theories do not. Calibrating the difficulty and temporal sequencing of training experiences to support more incremental representation-based learning can enhance the effectiveness of practice beyond any benefits gained from explicitly highlighting relevant dimensions.

Autism As a Disorder of High Intelligence

A suite of recent studies has reported positive genetic correlations between autism risk and measures of mental ability. These findings indicate that alleles for autism overlap broadly with alleles for high intelligence, which appears paradoxical given that autism is characterized, overall, by below-average IQ. This paradox can be resolved under the hypothesis that autism etiology commonly involves enhanced, but imbalanced, components of intelligence. This hypothesis is supported by convergent evidence showing that autism and high IQ share a diverse set of convergent correlates, including large brain size, fast brain growth, increased sensory and visual-spatial abilities, enhanced synaptic functions, increased attentional focus, high socioeconomic status, more deliberative decision-making, profession and occupational interests in engineering and physical sciences, and high levels of positive assortative mating. These findings help to provide an evolutionary basis to understanding autism risk as underlain in part by dysregulation of intelligence, a core human-specific adaptation. In turn, integration of studies on intelligence with studies of autism should provide novel insights into the neurological and genetic causes of high mental abilities, with important implications for cognitive enhancement, artificial intelligence, the relationship of autism with schizophrenia, and the treatment of both autism and intellectual disability.