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 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.

scholarly journals The functional brain organization of an individual predicts measures of social abilities in autism spectrum disorder: Predicting symptoms in autism with brain imaging

2018 ◽  
Author(s):  
Evelyn MR Lake ◽  
Emily S Finn ◽  
Stephanie M Noble ◽  
Tamara Vanderwal ◽  
Xilin Shen ◽  
...  
Keyword(s):  
Autism Spectrum Disorder ◽  
Functional Connectivity ◽  
Brain Imaging ◽  
Data Exchange ◽  
Autism Spectrum ◽  
Spectrum Disorder ◽  
Imaging Data ◽  
Brain Organization ◽  
Functional Brain ◽  
Functional Brain Organization

ABSTRACTAutism Spectrum Disorder (ASD) is associated with multiple complex abnormalities in functional brain connectivity measured with functional magnetic resonance imaging (fMRI). Despite much research in this area, to date, neuroimaging-based models are not able to characterize individuals with ASD with sufficient sensitivity and specificity; this is likely due to the heterogeneity and complexity of this disorder. Here we apply a data-driven subject-level approach, connectome-based predictive modeling, to resting-state fMRI data from a set of individuals from the Autism Brain Imaging Data Exchange. Using leave-one-subject-out and split-half analyses, we define two functional connectivity networks that predict continuous scores on the Social Responsiveness Scale (SRS) and Autism Diagnostic Observation Schedule (ADOS) and confirm that these networks generalize to novel subjects. Notably, these networks were found to share minimal anatomical overlap. Further, our results generalize to individuals for whom SRS/ADOS scores are unavailable, predicting worse scores for ASD than typically developing individuals. In addition, predicted SRS scores for individuals with attention-deficit/hyperactivity disorder (ADHD) from the ADHD-200 Consortium are linked to ADHD symptoms, supporting the hypothesis that the functional brain organization changes relevant to ASD severity share a component associated with attention. Finally, we explore the membership of predictive connections within conventional (atlas-based) functional networks. In summary, our results suggest that an individual’s functional connectivity profile contains information that supports dimensional, non-binary classification in ASD, aligning with the goals of precision medicine and individual-level diagnosis.

scholarly journals A-24 Metacognition and behavioral regulation associated with distinct connectivity patterns in autism spectrum disorder

2019 ◽  
Vol 34 (6) ◽  
pp. 883-883
Author(s):  
H Bednarz ◽  
R Kana
Keyword(s):  
Autism Spectrum Disorder ◽  
Executive Function ◽  
Data Exchange ◽  
Brain Connectivity ◽  
Autism Spectrum ◽  
Spectrum Disorder ◽  
Parent Ratings ◽  
Behavioral Regulation ◽  
Imaging Data ◽  
Frontal Pole

Abstract Objective Executive function (EF) deficits are well documented in children with autism spectrum disorder (ASD)1-2 and are commonly measured clinically using parent ratings3. No studies have investigated whether parent ratings of EF predict brain connectivity in ASD. Aim Examine whether the Behavior Rating Inventory of Executive Function (BRIEF) predicts functional brain connectivity in ASD. Method Resting-state fMRI and behavioral data were obtained from the Autism Brain Imaging Data Exchange (ABIDE-II) database6 (n = 106 ASD, ages 5-13). ROI-to-ROI (Region of Interest) connectivity was computed for 132 ROIs spanning the whole brain, defined using Conn Toolbox. Multiple regression analyses examined the effect of BRIEF metacognition on connectivity while controlling for BRIEF behavioral regulation, and vice versa. Age, sex, and full-scale IQ were included as covariates. FDR correction was used (p < 0.05). Results More severe deficits in metacognition were associated with stronger connectivity between the left hippocampus and several ROIs, including the cerebellum and planum temporale. More severe deficits in metacognition were associated with weaker right hippocampus – right frontal pole connectivity. More severe deficits in behavioral regulation were associated with stronger connectivity between subcortical regions (i.e., thalamus, putamen, and caudate) and regions involved in motor (superior frontal gyrus) and limbic systems (cingulate gyrus). More severe behavioral regulation deficits were associated with weaker cerebellar-cerebellar connectivity. Conclusions Findings suggest that parent-ratings of metacognitive abilities in children with ASD are associated with hippocampal connectivity, while behavioral regulation abilities are associated with thalamic and striatum connections. These results build upon previous studies of metacognition and behavioral regulation 5,6.

scholarly journals Constructing high-order functional connectivity network based on central moment features for diagnosis of autism spectrum disorder

PeerJ ◽  
2021 ◽  
Vol 9 ◽  
pp. e11692
Author(s):  
Qingsong Xie ◽  
Xiangfei Zhang ◽  
Islem Rekik ◽  
Xiaobo Chen ◽  
Ning Mao ◽  
...  
Keyword(s):  
Autism Spectrum Disorder ◽  
Functional Connectivity ◽  
Neurological Diseases ◽  
Brain Connectivity ◽  
Brain Regions ◽  
Autism Spectrum ◽  
Central Moment ◽  
High Order ◽  
Spectrum Disorder ◽  
Moment Feature

The sliding-window-based dynamic functional connectivity network (D-FCN) has been becoming an increasingly useful tool for understanding the changes of brain connectivity patterns and the association of neurological diseases with these dynamic variations. However, conventional D-FCN is essentially low-order network, which only reflects the pairwise interaction pattern between brain regions and thus overlooking the high-order interactions among multiple brain regions. In addition, D-FCN is innate with temporal sensitivity issue, i.e., D-FCN is sensitive to the chronological order of its subnetworks. To deal with the above issues, we propose a novel high-order functional connectivity network framework based on the central moment feature of D-FCN. Specifically, we firstly adopt a central moment approach to extract multiple central moment feature matrices from D-FCN. Furthermore, we regard the matrices as the profiles to build multiple high-order functional connectivity networks which further capture the higher level and more complex interaction relationships among multiple brain regions. Finally, we use the voting strategy to combine the high-order networks with D-FCN for autism spectrum disorder diagnosis. Experimental results show that the combination of multiple functional connectivity networks achieves accuracy of 88.06%, and the best single network achieves accuracy of 79.5%.

scholarly journals Graph Ricci Curvatures Reveal Disease-related Changes in Autism Spectrum Disorder

2021 ◽  
Author(s):  
Pavithra Elumalai ◽  
Yasharth Yadav ◽  
Nitin Williams ◽  
Emil Saucan ◽  
Jürgen Jost ◽  
...  
Keyword(s):  
Autism Spectrum Disorder ◽  
Resting State ◽  
Neurodevelopmental Disorders ◽  
Data Exchange ◽  
Meta Analysis ◽  
Resting State Fmri ◽  
Brain Regions ◽  
Autism Spectrum ◽  
Spectrum Disorder ◽  
The Brain

Autism Spectrum Disorder (ASD) is a set of neurodevelopmental disorders that pose a significant global health burden. Measures from graph theory have been used to characterise ASD-related changes in resting-state fMRI functional connectivity networks (FCNs), but recently developed geometry-inspired measures have not been applied so far. In this study, we applied geometry-inspired graph Ricci curvatures to investigate ASD-related changes in resting-state fMRI FCNs. To do this, we applied Forman-Ricci and Ollivier-Ricci curvatures to compare networks of ASD and healthy controls (N = 1112) from the Autism Brain Imaging Data Exchange I (ABIDE-I) dataset. We performed these comparisons at the brain-wide level as well as at the level of individual brain regions, and further, determined the behavioral relevance of region-specific differences with Neurosynth meta-analysis decoding. We found brain-wide ASD-related differences for both Forman-Ricci and Ollivier-Ricci curvatures. For Forman-Ricci curvature, these differences were distributed across 83 of the 200 brain regions studied, and concentrated within the Default Mode, Somatomotor and Ventral Attention Network. Meta-analysis decoding identified the brain regions showing curvature differences as involved in social cognition, memory, language and movement. Notably, comparison with results from previous non-invasive stimulation (TMS/tDCS) experiments revealed that the set of brain regions showing curvature differences overlapped with the set of brain regions whose stimulation resulted in positive cognitive or behavioural outcomes in ASD patients. These results underscore the utility of geometry-inspired graph Ricci curvatures in characterising disease-related changes in ASD, and possibly, other neurodevelopmental disorders.

scholarly journals Reduced long-range functional connectivity in young children with autism spectrum disorder

2014 ◽  
Vol 10 (2) ◽  
pp. 248-254 ◽  
Author(s):  
Mitsuru Kikuchi ◽  
Yuko Yoshimura ◽  
Hirotoshi Hiraishi ◽  
Toshio Munesue ◽  
Takanori Hashimoto ◽  
...  
Keyword(s):  
Autism Spectrum Disorder ◽  
Functional Connectivity ◽  
Young Children ◽  
Long Range ◽  
Children With Autism ◽  
Autism Spectrum ◽  
Spectrum Disorder ◽  
Young Children With Autism

Atypicalities in the developmental trajectory of cortico-striatal functional connectivity in autism spectrum disorder

Autism ◽  
2021 ◽  
pp. 136236132110419
Author(s):  
Zeng-Hui Ma ◽  
Bin Lu ◽  
Xue Li ◽  
Ting Mei ◽  
Yan-Qing Guo ◽  
...  
Keyword(s):  
Autism Spectrum Disorder ◽  
Functional Connectivity ◽  
Brain Connectivity ◽  
Autism Spectrum ◽  
Spectrum Disorder ◽  
Typically Developing ◽  
Sensorimotor Network ◽  
Intrinsic Functional Connectivity ◽  
Age Related ◽  
Atypical Development

The last decades of neuroimaging research has revealed atypical development of intrinsic functional connectivity within and between large-scale cortical networks in autism spectrum disorder, but much remains unknown about cortico-subcortical developmental connectivity atypicalities. This study examined cortico-striatal developmental intrinsic functional connectivity changes in autism spectrum disorder and explored how those changes may be correlated with autistic traits. We studied 49 individuals with autism spectrum disorder and 52 age-, sex-, and head motion–matched typically developing individuals (5–30 years old (14.0 ± 5.6)) using resting-state functional magnetic resonance imaging. Age-related differences in striatal intrinsic functional connectivity were compared between the two groups by adopting functional network–based parcellations of the striatum as seeds. Relative to typically developing individuals, autism spectrum disorder individuals showed atypical developmental changes in intrinsic functional connectivities between almost all striatal networks and sensorimotor network/default network, with connectivity increasing with age in the autism spectrum disorder group and decreasing or constant in typically developing individuals. Age-related degree centrality and voxel-mirrored homotopic connectivity atypicalities in sensorimotor network/default network and voxel-mirrored homotopic connectivity disruptions in striatal regions were also observed in autism spectrum disorder. Significant correlations were found between cortico-striatal intrinsic functional connectivities and Autism Diagnostic Observation Schedule communication/repetitive and restricted-behavior subscores in autism spectrum disorder. Our results indicated that developmental atypicalities of cortico-striatal intrinsic functional connectivities might contribute to the neuropathology of autism spectrum disorder. Lay abstract Autism spectrum disorder has long been conceptualized as a disorder of “atypical development of functional brain connectivity (which refers to correlations in activity levels of distant brain regions).” However, most of the research has focused on the connectivity between cortical regions, and much remains unknown about the developmental changes of functional connectivity between subcortical and cortical areas in autism spectrum disorder. We used the technique of resting-state functional magnetic resonance imaging to explore the developmental characteristics of intrinsic functional connectivity (functional brain connectivity when people are asked not to do anything) between subcortical and cortical regions in individuals with and without autism spectrum disorder aged 6–30 years. We focused on one important subcortical structure called striatum, which has roles in motor, cognitive, and affective processes. We found that cortico-striatal intrinsic functional connectivities showed opposite developmental trajectories in autism spectrum disorder and typically developing individuals, with connectivity increasing with age in autism spectrum disorder and decreasing or constant in typically developing individuals. We also found significant negative behavioral correlations between those atypical cortico-striatal intrinsic functional connectivities and autistic symptoms, such as social-communication deficits, and restricted/repetitive behaviors and interests. Taken together, this work highlights that the atypical development of cortico-subcortical functional connectivity might be largely involved in the neuropathological mechanisms of autism spectrum disorder.

scholarly journals Modulation of striatal functional connectivity differences in adults with and without autism spectrum disorder in a single-dose randomized trial of cannabidivarin

2021 ◽  
Vol 12 (1) ◽  
Author(s):  
Charlotte M. Pretzsch ◽  
Dorothea L. Floris ◽  
Bogdan Voinescu ◽  
Malka Elsahib ◽  
Maria A. Mendez ◽  
...  
Keyword(s):  
Autism Spectrum Disorder ◽  
Functional Connectivity ◽  
Repeated Measures ◽  
Autism Spectrum ◽  
Spectrum Disorder ◽  
Controlled Study ◽  
Imaging Data ◽  
Small Pilot Study ◽  
Double Blind ◽  
Methodological Aspects

Abstract Background Autism spectrum disorder (ASD) has a high cost to affected individuals and society, but treatments for core symptoms are lacking. To expand intervention options, it is crucial to gain a better understanding of potential treatment targets, and their engagement, in the brain. For instance, the striatum (caudate, putamen, and nucleus accumbens) plays a central role during development and its (atypical) functional connectivity (FC) may contribute to multiple ASD symptoms. We have previously shown, in the adult autistic and neurotypical brain, the non-intoxicating cannabinoid cannabidivarin (CBDV) alters the balance of striatal ‘excitatory–inhibitory’ metabolites, which help regulate FC, but the effects of CBDV on (atypical) striatal FC are unknown. Methods To examine this in a small pilot study, we acquired resting state functional magnetic resonance imaging data from 28 men (15 neurotypicals, 13 ASD) on two occasions in a repeated-measures, double-blind, placebo-controlled study. We then used a seed-based approach to (1) compare striatal FC between groups and (2) examine the effect of pharmacological probing (600 mg CBDV/matched placebo) on atypical striatal FC in ASD. Visits were separated by at least 13 days to allow for drug washout. Results Compared to the neurotypicals, ASD individuals had lower FC between the ventral striatum and frontal and pericentral regions (which have been associated with emotion, motor, and vision processing). Further, they had higher intra-striatal FC and higher putamenal FC with temporal regions involved in speech and language. In ASD, CBDV reduced hyperconnectivity to the neurotypical level. Limitations Our findings should be considered in light of several methodological aspects, in particular our participant group (restricted to male adults), which limits the generalizability of our findings to the wider and heterogeneous ASD population. Conclusion In conclusion, here we show atypical striatal FC with regions commonly associated with ASD symptoms. We further provide preliminary proof of concept that, in the adult autistic brain, acute CBDV administration can modulate atypical striatal circuitry towards neurotypical function. Future studies are required to determine whether modulation of striatal FC is associated with a change in ASD symptoms. Trial registration clinicaltrials.gov, Identifier: NCT03537950. Registered May 25th, 2018—Retrospectively registered, https://clinicaltrials.gov/ct2/show/NCT03537950?term=NCT03537950&draw=2&rank=1.

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