Neural correlates of cognitive variability in childhood autism and relation to heterogeneity in decision-making dynamics

Iuculano, Teresa; Padmanabhan, Aarthi; Chen, L.; Nicholas, Jonathan; Mitsven, Samantha G.; Angeles, Carlo de los; Menon, Vinod

doi:10.1016/j.dcn.2020.100754

Cited by 23 publications

(29 citation statements)

References 78 publications

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“…At the same time, the healthy controls showed a negative correlation. In this study, accuracy and RT remained unchanged in ASD and controls while the decision thresholds were significantly higher (Karalunas et al, 2018;Iuculano et al, 2020). Pirrone et al (2017) found that ASD participants showed higher thresholds while accuracy and drift rate were unaffected.…”

Section: Autism Spectrum Disorders (Asd)mentioning

confidence: 42%

Neural Substrates of the Drift-Diffusion Model in Brain Disorders

Gupta

Bansal

Alashwal

et al. 2022

Front. Comput. Neurosci.

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Many studies on the drift-diffusion model (DDM) explain decision-making based on a unified analysis of both accuracy and response times. This review provides an in-depth account of the recent advances in DDM research which ground different DDM parameters on several brain areas, including the cortex and basal ganglia. Furthermore, we discuss the changes in DDM parameters due to structural and functional impairments in several clinical disorders, including Parkinson's disease, Attention Deficit Hyperactivity Disorder (ADHD), Autism Spectrum Disorders, Obsessive-Compulsive Disorder (OCD), and schizophrenia. This review thus uses DDM to provide a theoretical understanding of different brain disorders.

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Section: Autism Spectrum Disorders (Asd)mentioning

confidence: 42%

Neural Substrates of the Drift-Diffusion Model in Brain Disorders

Gupta

Bansal

Alashwal

et al. 2022

Front. Comput. Neurosci.

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“…Karalunas et al 20 reported that autistic individuals had reduced drift rates compared to non-autistic individuals c.f. 17 , but Kirchner et al 19 and Iuculano et al 21 found no group differences in this parameter. Combining the results of these studies together, it seems that differences in boundary separation between autistic and non-autistic individuals may be ubiquitous across tasks, while differences in drift-rate and non-decision time might depend on the task and age of participants.…”

Section: Figure 1 Schematic Representation Of the Main Diffusion Model Parametersmentioning

confidence: 89%

“…While group differences in drift-rate are likely to be task dependent, the existing literature has shown relatively consistent differences between autistic and non-autistic participants in boundary separation [17][18][19][20][21] (but see [79], which appears to find little difference in boundary separation between groups for a perceptual task). Our results are in the hypothesised direction, with autistic children having slightly wider boundary separation than typically developing children on average.…”

Section: Discussionmentioning

confidence: 99%

“…Three further studies have used the diffusion model with autistic populations to understand stereotypical attitudes in an implicit association task 19 , performance in the correct 'go' trials of a response inhibition stop-task 20 and numerical addition problems 21 . In all studies, autistic individuals were reported to display a more cautious response style than nonautistic individuals, in line with the findings of Pirrone et al 17,18 .…”

Section: Figure 1 Schematic Representation Of the Main Diffusion Model Parametersmentioning

confidence: 99%

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Behavioural and neural indices of perceptual decision-making in autistic children during visual motion tasks

Manning¹,

Hassall²,

Hunt³

et al. 2021

Preprint

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Many studies report atypical responses to sensory information in autistic individuals, yet it is not clear which stages of processing are affected, with little consideration given to decision-making processes. We combined diffusion modelling with high-density EEG to identify which processing stages differ between 50 autistic and 50 typically developing children aged 6-14 years during two visual motion tasks. Our pre-registered hypotheses were that autistic children would show task-dependent differences in sensory evidence accumulation, alongside a more cautious decision-making style and longer non-decision time across tasks. We tested these hypotheses using hierarchical Bayesian diffusion models with a rigorous blind modelling approach, finding no conclusive evidence for our hypotheses. Using a data-driven method, we identified a response-locked centro-parietal component previously linked to the decision-making process. The build-up in this component did not consistently relate to evidence accumulation in autistic children. This suggests that the relationship between the EEG measure and diffusion-modelling is not straightforward in autistic children. Compared to a related study of children with dyslexia, motion processing differences appear less pronounced in autistic children. Our results also provide weak evidence that ADHD symptoms moderate perceptual decision-making in autistic children.

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“…This increase in diagnostic sensitivity has on the other hand led to an increasing recognition of heterogeneity of diagnosed individuals (Hong et al, 2018;Hong et al, 2020a;Lombardo et al, 2019), and challenges for specificity (Mottron and Bzdok, 2020). This high variability is present at the phenotypic level of behavioral symptoms and at the level of genetic mechanisms previously associated with ASD (Bernard Paulais et al, 2019;Iuculano et al, 2020;Jeste and Geschwind, 2014), and renders the study of autism particularly challenging. As etiology and pathophysiology remain largely unclear and similarly heterogeneous, efforts have increasingly shifted to neuroimaging techniques to identify intermediary autism phenotypes (Bernhardt et al, 2017;Hong et al, 2019).…”

Section: Introductionmentioning

confidence: 99%

Functional idiosyncrasy has a shared topography with group-level connectivity alterations in autism

Benkarim

Paquola

Park

et al. 2020

Preprint

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Autism spectrum disorder (ASD) is commonly understood as a network disorder, yet case-control analyses against typically-developing controls (TD) have yielded somewhat inconsistent patterns of results. The current work was centered on a novel approach to profile functional network idiosyncrasy, the inter-individual variability in the association between functional network organization and brain anatomy, and we tested the hypothesis that idiosyncrasy contributes to connectivity alterations in ASD. Studying functional network idiosyncrasy in a multi-centric dataset with 157 ASD and 172 TD, our approach revealed higher idiosyncrasy in ASD in the default mode, somatomotor and attention networks together with reduced idiosyncrasy in the lateral temporal lobe. Idiosyncrasy was found to increase with age in both ASD and TD, and was significantly correlated with symptom severity in the former group. Association analysis with structural and molecular brain features indicated that patterns of functional network idiosyncrasy were not correlated with ASD-related cortical thickness alterations, but closely with the spatial expression patterns of intracortical ASD risk genes. In line with our main hypothesis, we could demonstrate that idiosyncrasy indeed plays a strong role in the manifestation of connectivity alterations that are measurable with conventional case-control designs and may, thus, be a principal driver of inconsistency in the autism connectomics literature. These findings support important interactions between the heterogeneity of individuals with an autism diagnosis and group-level functional signatures, and help to consolidate prior research findings on the highly variable nature of the functional connectome in ASD. Our study promotes idiosyncrasy as a potential individualized diagnostic marker of atypical brain network development.

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Neural correlates of cognitive variability in childhood autism and relation to heterogeneity in decision-making dynamics

Cited by 23 publications

References 78 publications

Neural Substrates of the Drift-Diffusion Model in Brain Disorders

Neural Substrates of the Drift-Diffusion Model in Brain Disorders

Behavioural and neural indices of perceptual decision-making in autistic children during visual motion tasks

Functional idiosyncrasy has a shared topography with group-level connectivity alterations in autism

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