scholarly journals Homozygous loss of autism-risk geneCNTNAP2results in reduced local and long-range prefrontal functional connectivity

2016 ◽  
Author(s):  
Adam Liska ◽  
Alice Bertero ◽  
Ryszard Gomolka ◽  
Mara Sabbioni ◽  
Alberto Galbusera ◽  
...  
Keyword(s):  
Functional Connectivity ◽  
Long Range ◽  
Brain Connectivity ◽  
Resting State Fmri ◽  
Autism Spectrum ◽  
Loss Of Function ◽  
Functional Impairments ◽  
Social Investigation ◽  
Reduced Frequency ◽  
Cortical Regions

AbstractFunctional connectivity aberrancies, as measured with resting-state fMRI (rsfMRI), have been consistently observed in the brain of autism spectrum disorders (ASD) patients. However, the genetic and neurobiological underpinnings of these findings remain unclear. Homozygous mutations in Contactin Associated Protein-like 2 (CNTNAP2), a neurexin-related cell-adhesion protein, are strongly linked to autism and epilepsy. Here we used rsfMRI to show that homozygous mice lackingCntnap2exhibit reduced long-range and local functional connectivity in prefrontal and midline brain “connectivity hubs”. Long-range rsfMRI connectivity impairments affected heteromodal cortical regions and were prominent between fronto-posterior components of the mouse default-mode network (DMN), an effect that was associated with reduced social investigation, a core “autism trait” in mice. Notably, viral tracing revealed reduced frequency of prefrontal-projecting neural clusters in the cingulate cortex ofCntnap2−/−mutants, suggesting a possible contribution of defective mesoscale axonal wiring to the observed functional impairments. Macroscale cortico-cortical white matter organization appeared to be otherwise preserved in these animals. These findings reveal a key contribution of ASD-associated gene CNTNAP2 in modulating macroscale functional connectivity, and suggest that homozygous loss-of-function mutations in this gene may predispose to neurodevelopmental disorders and autism through a selective dysregulation of connectivity in integrative prefrontal areas.

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.

Influence of Primary Auditory Cortex in the Characterization of Autism Spectrum in Young Adults using Brain Connectivity Parameters and Deep Belief Networks: An fMRI Study

2020 ◽  
Vol 16 (9) ◽  
pp. 1059-1073
Author(s):  
Vidhusha Srinivasan ◽  
N. Udayakumar ◽  
Kavitha Anandan
Keyword(s):  
Functional Connectivity ◽  
Auditory Cortex ◽  
Language Processing ◽  
Brain Connectivity ◽  
Primary Auditory Cortex ◽  
Autism Spectrum ◽  
Belief Networks ◽  
Deep Belief Networks ◽  
High Functioning ◽  
Low Functioning

Background: The spectrum of autism encompasses High Functioning Autism (HFA) and Low Functioning Autism (LFA). Brain mapping studies have revealed that autism individuals have overlaps in brain behavioural characteristics. Generally, high functioning individuals are known to exhibit higher intelligence and better language processing abilities. However, specific mechanisms associated with their functional capabilities are still under research. Objective: This work addresses the overlapping phenomenon present in autism spectrum through functional connectivity patterns along with brain connectivity parameters and distinguishes the classes using deep belief networks. Methods: The task-based functional Magnetic Resonance Images (fMRI) of both high and low functioning autistic groups were acquired from ABIDE database, for 58 low functioning against 43 high functioning individuals while they were involved in a defined language processing task. The language processing regions of the brain, along with Default Mode Network (DMN) have been considered for the analysis. The functional connectivity maps have been plotted through graph theory procedures. Brain connectivity parameters such as Granger Causality (GC) and Phase Slope Index (PSI) have been calculated for the individual groups. These parameters have been fed to Deep Belief Networks (DBN) to classify the subjects under consideration as either LFA or HFA. Results: Results showed increased functional connectivity in high functioning subjects. It was found that the additional interaction of the Primary Auditory Cortex lying in the temporal lobe, with other regions of interest complimented their enhanced connectivity. Results were validated using DBN measuring the classification accuracy of 85.85% for high functioning and 81.71% for the low functioning group. Conclusion: Since it is known that autism involves enhanced, but imbalanced components of intelligence, the reason behind the supremacy of high functioning group in language processing and region responsible for enhanced connectivity has been recognized. Therefore, this work that suggests the effect of Primary Auditory Cortex in characterizing the dominance of language processing in high functioning young adults seems to be highly significant in discriminating different groups in autism spectrum.

Inter-Hemispherical Investigations on the Functional Connectivity in Controls and Autism Spectrum Using Resting State fMRI

2020 ◽  
pp. 169-186
Author(s):  
S. Vidhusha ◽  
A. Kavitha
Keyword(s):  
Functional Connectivity ◽  
Granger Causality ◽  
Resting State ◽  
Cognitive Task ◽  
Resting State Fmri ◽  
Autism Spectrum ◽  
Control Group ◽  
Neural Connectivity ◽  
Activation Patterns ◽  
The Brain

Autism spectrum disorders are connected with disturbances of neural connectivity. Functional connectivity is typically examined during a cognitive task, but also exists in the absence of a task. While a number of studies have performed functional connectivity analysis to differentiate controls and autism individuals, this work focuses on analyzing the brain activation patterns not only between controls and autistic subjects, but also analyses the brain behaviour present within autism spectrum. This can bring out more intuitive ways to understand that autism individuals differ individually. This has been performed between autism group relative to the control group using inter-hemispherical analysis. Indications of under connectivity were exhibited by the Granger Causality (GC) and Conditional Granger Causality (CGC) in autistic group. Results show that as connectivity decreases, the GC and CGC values also get decreased. Further, to demark the differences present within the spectrum of autistic individuals, GC and CGC values have been calculated.

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

scholarly journals Local and long-range functional connectivity is reduced in concert in autism spectrum disorders

2013 ◽  
Vol 110 (8) ◽  
pp. 3107-3112 ◽  
Author(s):  
S. Khan ◽  
A. Gramfort ◽  
N. R. Shetty ◽  
M. G. Kitzbichler ◽  
S. Ganesan ◽  
...  
Keyword(s):  
Autism Spectrum Disorders ◽  
Functional Connectivity ◽  
Long Range ◽  
Autism Spectrum ◽  
Spectrum Disorders

scholarly journals Functional connectivity differences in early infancy precede autism symptoms: a multivariate pattern analysis

2019 ◽  
Author(s):  
Abigail Dickinson ◽  
Manjari Daniel ◽  
Andrew Marin ◽  
Bilwaj Goanker ◽  
Mirella Dapretto ◽  
...  
Keyword(s):  
Functional Connectivity ◽  
Cognitive Abilities ◽  
Pattern Analysis ◽  
Brain Connectivity ◽  
Familial Risk ◽  
Autism Spectrum ◽  
Support Vector ◽  
Multivariate Pattern Analysis ◽  
Autism Symptoms ◽  
Multivariate Pattern

AbstractFunctional brain connectivity is altered in children and adults with autism spectrum disorder (ASD). Mapping pre-symptomatic functional disruptions in ASD could identify infants based on neural risk, providing a crucial opportunity to mediate outcomes before behavioral symptoms emerge.Here we quantify functional connectivity using scalable EEG measures of oscillatory phase coherence (6-12Hz). Infants at high and low familial risk for ASD (N=65) underwent an EEG recording at 3 months of age and were assessed for ASD symptoms at 18 months using the Autism Diagnostic Observation Schedule-Toddler Module. Multivariate pattern analysis was used to examine early functional patterns that are associated with later ASD symptoms.Support vector regression (SVR) algorithms accurately predicted observed ASD symptoms at 18 months from EEG data at 3 months (r=0.76, p=0.02). Specifically, lower frontal connectivity and higher right temporo-parietal connectivity predicted higher ASD symptoms. The SVR model did not predict non-verbal cognitive abilities at 18 months (r=0.15, p=0.36), suggesting specificity of these brain alterations to ASD.These data suggest that frontal and temporo-parietal dysconnectivity play important roles in the early pathophysiology of ASD. Early functional differences in ASD can be captured using EEG during infancy and may inform much-needed advancements in the early detection of ASD.

scholarly journals The relationship between spatial configuration and functional connectivity of brain regions

2017 ◽  
Author(s):  
Janine D. Bijsterbosch ◽  
Mark W. Woolrich ◽  
Matthew F. Glasser ◽  
Emma C. Robinson ◽  
Christian F. Beckmann ◽  
...  
Keyword(s):  
Functional Connectivity ◽  
Spatial Configuration ◽  
Brain Connectivity ◽  
Brain Activity ◽  
Spatial Arrangement ◽  
Brain Regions ◽  
Imaging Data ◽  
Functional Regions ◽  
Cortical Regions ◽  
The Relationship

AbstractBrain connectivity is often considered in terms of the communication between functionally distinct brain regions. Many studies have investigated the extent to which patterns of coupling strength between multiple neural populations relates to behavior. For example, studies have used "functional connectivity fingerprints" to characterise individuals' brain activity. Here, we investigate the extent to which the exact spatial arrangement of cortical regions interacts with measures of brain connectivity. We find that the shape and exact location of brain regions interact strongly with the modelling of brain connectivity, and present evidence that the spatial arrangement of functional regions is strongly predictive of non-imaging measures of behaviour and lifestyle. We believe that, in many cases, cross-subject variations in the spatial configuration of functional brain regions are being interpreted as changes in functional connectivity. Therefore, a better understanding of these effects is important when interpreting the relationship between functional imaging data and cognitive traits.

scholarly journals Diffusion property and functional connectivity of superior longitudinal fasciculus underpin human metacognition

2020 ◽  
Author(s):  
Yunxuan Zheng ◽  
Danni Wang ◽  
Qun Ye ◽  
Futing Zou ◽  
Yao Li ◽  
...  
Keyword(s):  
Functional Connectivity ◽  
Structural Integrity ◽  
Diffusion Tensor ◽  
Memory Task ◽  
Resting State Fmri ◽  
Precentral Gyrus ◽  
Superior Longitudinal Fasciculus ◽  
Anterior Portion ◽  
Inferior Parietal Cortex ◽  
Cortical Regions

AbstractMetacognition as the capacity of monitoring one’s own cognition operates across domains. Here, we addressed whether metacognition in different cognitive domains rely on common or distinct neural substrates with combined diffusion tensor imaging (DTI) and functional magnetic resonance imaging (fMRI) techniques. After acquiring DTI and resting-state fMRI data, we asked participants to perform a temporal-order memory task and a perceptual discrimination task, followed by trial-specific confidence judgments. DTI analysis revealed that the structural integrity (indexed by fractional anisotropy) in the anterior portion of right superior longitudinal fasciculus (SLF) was associated with both perceptual and mnemonic metacognitive abilities. Using perturbed mnemonic metacognitive scores produced by inhibiting the precuneus using TMS, the mnemonic metacognition scores did not correlate with individuals’ SLF structural integrity anymore, revealing the relevance of this tract in memory metacognition. In order to further verify the involvement of several cortical regions connected by SLF, we took the TMS-targeted precuneus region as a seed in a functional connectivity analysis and found the functional connectivity between precuneus and two SLF-connected regions (inferior parietal cortex and precentral gyrus) differentially mediated mnemonic but not perceptual metacognition performance. These results illustrate the importance of SLF and a putative white-matter grey-matter circuitry that supports human metacognition.

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.

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