scholarly journals Atypical development of subcortico-cortical effective connectivity in autism

2021 ◽  
Author(s):  
Luigi Lorenzini ◽  
Guido van Wingen ◽  
Leonardo Cerliani
Keyword(s):  
Cognitive Processing ◽  
Sensory Processing ◽  
Data Exchange ◽  
Effective Connectivity ◽  
Sensory Information ◽  
Autism Spectrum ◽  
Cortical Processing ◽  
Imaging Data ◽  
Brain Imaging Data ◽  
Atypical Development

Hypersensitivity, stereotyped behaviors and attentional problems in autism spectrum disorder (ASD) are compatible with inefficient filtering of undesired or irrelevant sensory information at early stages of neural processing. This could stem from delays in the neurotypical development of the functional segregation between cortical and subcortical brain processes, as suggested by previous findings of overconnectivity between primary sensory regions and deep brain nuclei in ASD. To test this hypothesis, we used dynamic causal modelling to quantify the effect of age on the development of (1) cortical functional segregation from subcortical activity and (2) directional influence of subcortical activity on cortical processing in 166 participants with ASD and 193 typically developing controls (TD) from the Autism Brain Imaging Data Exchange (ABIDE). We found that in TD participants age was significantly associated with increased functional segregation of cortical sensory processing from subcortical activity, paralleled by a decreased influence of subcortical activity on cortical processing. Instead these effects were highly reduced and mostly absent in ASD participants, suggesting a delayed or arrested development of the segregation between subcortical and cortical sensory processing in ASD. This atypical configuration of subcortico-cortical connectivity in ASD can result in an excessive amount of unprocessed sensory information relayed to the cortex, which is likely to impact cognitive functioning in everyday situations where it is beneficial to limit the influence of basic sensory information on cognitive processing, such as activities requiring focused attention or social interactions.

scholarly journals An Autism Spectrum Disorder Adaptive Identification Based on the Elimination of Brain Connections: A Proof of Long-Range Underconnectivity

2021 ◽  
Author(s):  
Fatima zahra Benabdallah ◽  
Ahmed Drissi El Maliani ◽  
Dounia Lotfi ◽  
Rachid Jennane ◽  
Mohammed El hassouni
Keyword(s):  
Autism Spectrum Disorder ◽  
Functional Connectivity ◽  
Long Range ◽  
Data Exchange ◽  
Brain Connectivity ◽  
Brain Regions ◽  
Autism Spectrum ◽  
Spectrum Disorder ◽  
Imaging Data ◽  
Brain Imaging Data

Abstract Autism spectrum disorder (ASD) is theoretically characterized by alterations in functional connectivity between brain regions. Many works presented approaches to determine informative patterns that help to predict autism from typical development. However, most of the proposed pipelines are not specifically designed for the autism problem, i.e they do not corroborate with autism theories about functional connectivity. In this paper, we propose a framework that takes into account the properties of local connectivity and long range under-connectivity in the autistic brain. The originality of the proposed approach is to adopt elimination as a technique in order to well emerge the autistic brain connectivity alterations, and show how they contribute to differentiate ASD from controls. Experimental results conducted on the large multi-site Autism Brain Imaging Data Exchange (ABIDE) show that our approach provides accurate prediction up to 70% and succeeds to prove the existence of deficits in the long-range connectivity in the ASD subjects brains.

scholarly journals Cross-species machine learning improves diagnostic classification of human psychiatric disorders

2019 ◽  
Author(s):  
Yafeng Zhan ◽  
Jianze Wei ◽  
Jian Liang ◽  
Xiu Xu ◽  
Ran He ◽  
...  
Keyword(s):  
Machine Learning ◽  
Psychiatric Disorders ◽  
Brain Imaging ◽  
Data Exchange ◽  
Autism Spectrum ◽  
Diagnostic Classification ◽  
Imaging Data ◽  
Primate Model ◽  
Compulsive Disorder ◽  
Brain Imaging Data

AbstractPsychiatric disorders often exhibit shared (co-morbid) symptoms, raising controversies over accurate diagnosis and the overlap of their neural underpinnings. Because the complexity of data generated by clinical studies poses a formidable challenge, we have pursued a reductionist framework using brain imaging data of a transgenic primate model of autism spectrum disorder (ASD). Here we report an interpretable cross-species machine learning approach which extracts transgene-related core regions in the monkey brain to construct the classifier for diagnostic classification in humans. The cross-species classifier based on core regions, mainly distributed in frontal and temporal cortex, identified from the transgenic primate model, achieved an accuracy of 82.14% in one clinical ASD cohort obtained from Autism Brain Imaging Data Exchange (ABIDE-I), significantly higher than the human-based classifier (61.31%, p < 0.001), which was validated in another independent ASD cohort obtained from ABIDE-II. Such monkey-based classifier generalized to achieve a better classification in obsessive-compulsive disorder (OCD) cohorts, and enabled parsing of differential connections to right ventrolateral prefrontal cortex being attributable to distinct traits in patients with ASD and OCD. These findings underscore the importance of investigating biologically homogeneous samples, particularly in the absence of real-world data adequate for deconstructing heterogeneity inherited in the clinical cohorts.One Sentence SummaryFeatures learned from transgenic monkeys enable improved diagnosis of autism-related disorders and dissection of their underlying circuits.

scholarly journals Increased contrast of the grey-white matter boundary in the motor, visual and auditory areas in Autism Spectrum Disorders

2019 ◽  
Author(s):  
Marion Fouquet ◽  
Nicolas Traut ◽  
Anita Beggiato ◽  
Richard Delorme ◽  
Thomas Bourgeron ◽  
...  
Keyword(s):  
White Matter ◽  
Data Exchange ◽  
Primary Motor Cortex ◽  
Autism Spectrum ◽  
Imaging Data ◽  
Sensory Motor ◽  
Magnetic Resonance Imaging Mri ◽  
Brain Imaging Data

AbstractThe contrast of the interface between the neocortical grey matter and the white matter is emerging as an important neuroimaging phenotype for several brain disorders. To date, a single in vivo study has analysed the cortical grey-to-white matter percent contrast (GWPC) on Magnetic Resonance Imaging (MRI), and has shown a significant decrease of this contrast in several areas in individuals with Autism Spectrum Disorder (ASD). Our goal was to replicate this study across a larger cohort, using the multicenter data from the Autism Brain Imaging Data Exchange 1 and 2 gathering data from 2,148 subjects. Multiple linear regression was used to study the effect of the diagnosis of ASD on the GWPC. Contrary to the first study, we found a statistically significant increase of GWPC among individuals with ASD in left auditory and bilateral visual sensory areas, as well as in the left primary motor cortex. These results were still statistically significant after inclusion of cortical thickness as covariate. There are numerous reports of sensory-motor atypicalities in patients with ASD, which may be the reason for the differences in GWPC that we observed. Further investigation could help us determine the potential role of a defect or a delay in intra-cortical myelination of sensory-motor regions in ASD. Code: https://github.com/neuroanatomy/GWPC.

scholarly journals Cerebellar volume in autism: Meta-analysis and analysis of the ABIDE cohort

2017 ◽  
Author(s):  
Nicolas Traut ◽  
Anita Beggiato ◽  
Thomas Bourgeron ◽  
Richard Delorme ◽  
Laure Rondi-Reig ◽  
...  
Keyword(s):  
Autism Spectrum Disorder ◽  
Effect Size ◽  
Data Exchange ◽  
Meta Analysis ◽  
Autism Spectrum ◽  
Imaging Data ◽  
Autism Diagnosis ◽  
Cerebellar Volume ◽  
Cerebellar Anatomy ◽  
Brain Imaging Data

AbstractCerebellar volume abnormalities have been often suggested as a possible endophenotype for autism spectrum disorder (ASD). We aimed at objectifying this possible alteration by performing a systematic meta-analysis of the literature, and an analysis of the Autism Brain Imaging Data Exchange (ABIDE) cohort. Our meta-analysis sought to determine a combined effect size of ASD diagnosis on different measures of the cerebellar anatomy, as well as the effect of possible factors of variability across studies. We then analysed the cerebellar volume of 328 patients and 353 controls from the ABIDE project. The meta-analysis of the literature suggested a weak but significant association between ASD diagnosis and increased cerebellar volume (p=0.049, uncorrected), but the analysis of ABIDE did not show any relationship. The studies in the literature were generally underpowered, however, the number of statistically significant findings was larger than expected. Although we could not provide a conclusive explanation for this excess of significant findings, our analyses would suggest publication bias as a possible reason. Finally, age, sex and IQ were important sources of cerebellar volume variability, however, independent of autism diagnosis.

scholarly journals Behavioural profiling of autism connectivity abnormalities

BJPsych Open ◽  
2020 ◽  
Vol 6 (1) ◽  
Author(s):  
William Snyder ◽  
Vanessa Troiani
Keyword(s):  
Functional Diversity ◽  
Data Exchange ◽  
Brain Regions ◽  
Autism Spectrum ◽  
Brain Disorders ◽  
Imaging Data ◽  
Functional Magnetic Resonance ◽  
Magnetic Resonance Imaging Data ◽  
Brain Imaging Data ◽  
Functionally Diverse

Background Brain regions are functionally diverse, and a given region may engage in a variety of tasks. This functional diversity of brain regions may be one factor that has prevented the finding of consistent biomarkers for brain disorders such as autism spectrum disorder (ASD). Thus, methods to characterise brain regions would help to determine how functional abnormalities contribute to affected behaviours. Aims As the first illustration of the meta-analytic behavioural profiling procedure, we evaluated how the regions with disrupted connectivity in ASD contributed to various behaviours. Method Connectivity abnormalities were determined from a published degree centrality group comparison based on functional magnetic resonance imaging data from the Autism Brain Imaging Data Exchange. Using BrainMap's database of task-based neuroimaging studies, behavioural profiles were created for abnormally connected regions by relating these regions to tasks activating them. Results Hyperconnectivity in ASD brains was significantly related to memory, attention, reasoning, social, execution and speech behaviours. Hypoconnectivity was related to vision, execution and speech behaviours. Conclusions The procedure outlines the first clinical neuroimaging application of a behavioural profiling method that estimates the functional diversity of brain regions, allowing for the relation of abnormal functional connectivity to diagnostic criteria. Behavioural profiling and the computational insights it provides can facilitate better understanding of the functional manifestations of various disorders, including ASD.

scholarly journals Sensory processing of children and students with autism spectrum disorder and typical development in relation to gender and age

2021 ◽  
Vol 20 (3) ◽  
pp. 185-201
Author(s):  
Ana Roknić ◽  
Sanja Vuković
Keyword(s):  
Autism Spectrum Disorder ◽  
Sensory Processing ◽  
Sensory Information ◽  
Autism Spectrum ◽  
Spectrum Disorder ◽  
Sensory Profile ◽  
Typical Development ◽  
Educational Plan ◽  
Gender And Age ◽  
Sensory Profiles

Introduction. Sensory processing is a neurobiological process in which a person uses their senses, sends information to an appropriate reception and processing center, and responds to environmental stimulations. Previous research has shown that sensory processing difficulties are more common among people with autism spectrum disorder than among people of the typical population. Objectives. The aim of this paper was to determine the patterns of sensory processing in subjects of the typical population and subjects with autism spectrum disorder, as well as gender and age differences in sensory profiles in these groups of subjects. Methods. Using The Child Sensory Profile 2 as the measuring instrument, the characteristics of sensory processing were examined in 120 subjects of both genders, 60 subjects with autism spectrum disorder and 60 subjects of typical development, ages three to 13 years and 11 months. Results. The obtained results show that there are differences between the two groups of respondents and that these differences occur in all nine subscales of the instrument. It was found that subjects with autismspectrumdisorder hadmore difficulty in processing sensory information compared to subjects of the typical population, especially in the domain of tactile perception. The results also show that the quality of sensory information processing in both groups of respondents improved with age. In relation to the respondents' gender, the obtained differences were significant in the domain of the total score of the instrument, in favor of the boys, but this was not observed in the measurements on all subscales. Conclusion. In accordance with the above findings, when creating an individual educational plan, it is necessary to take into account all the specifics of sensory processing of children with autism spectrum disorder.

scholarly journals Cerebellar Volume in Autism: Literature Meta-analysis and Analysis of the Autism Brain Imaging Data Exchange Cohort

2018 ◽  
Vol 83 (7) ◽  
pp. 579-588 ◽  
Author(s):  
Nicolas Traut ◽  
Anita Beggiato ◽  
Thomas Bourgeron ◽  
Richard Delorme ◽  
Laure Rondi-Reig ◽  
...  
Keyword(s):  
Brain Imaging ◽  
Data Exchange ◽  
Meta Analysis ◽  
Imaging Data ◽  
Cerebellar Volume ◽  
Brain Imaging Data

scholarly journals Sex-dependent and sex-independent brain resting-state functional connectivity in children with autism spectrum disorder

2016 ◽  
Author(s):  
Xin Di ◽  
Bharat B Biswal
Keyword(s):  
Autism Spectrum Disorder ◽  
Functional Connectivity ◽  
Resting State ◽  
Data Exchange ◽  
Brain Regions ◽  
Autism Spectrum ◽  
Spectrum Disorder ◽  
Imaging Data ◽  
Resting State Functional Connectivity ◽  
Main Effects

Background: Males are more likely to suffer from autism spectrum disorder (ASD) than females. As to whether females with ASD have similar brain alterations remain an open question. The current study aimed to examine sex-dependent as well as sex-independent alterations in resting-state functional connectivity in individuals with ASD compared with typically developing (TD) individuals. Method: Resting-state functional MRI data were acquired from the Autism Brain Imaging Data Exchange (ABIDE). Subjects between 6 to 20 years of age were included for analysis. After matching the intelligence quotient between groups for each dataset, and removing subjects due to excessive head motion, the resulting effective sample contained 28 females with ASD, 49 TD females, 129 males with ASD, and 141 TD males, with a two (diagnosis) by two (sex) design. Functional connectivity among 153 regions of interest (ROIs) comprising the whole brain was computed. Two by two analysis of variance was used to identify connectivity that showed diagnosis by sex interaction or main effects of diagnosis. Results: The main effects of diagnosis were found mainly between visual cortex and other brain regions, indicating sex-independent connectivity alterations. We also observed two connections whose connectivity showed diagnosis by sex interaction between the precuneus and medial cerebellum as well as the precunes and dorsal frontal cortex. While males with ASD showed higher connectivity in these connections compared with TD males, females with ASD had lower connectivity than their counterparts. Conclusions: Both sex-dependent and sex-independent functional connectivity alterations are present in ASD.

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