scholarly journals Granger Causality among Graphs and Application to Functional Brain Connectivity in Autism Spectrum Disorder

Entropy ◽  
2021 ◽  
Vol 23 (9) ◽  
pp. 1204
Author(s):  
Adèle Helena Ribeiro ◽  
Maciel Calebe Vidal ◽  
João Ricardo Sato ◽  
André Fujita
Keyword(s):  
Autism Spectrum Disorder ◽  
Granger Causality ◽  
Brain Connectivity ◽  
Graph Model ◽  
Autism Spectrum ◽  
Spectrum Disorder ◽  
Sensor Technology ◽  
Model Parameters ◽  
Time Varying ◽  
Random Graph Model

Graphs/networks have become a powerful analytical approach for data modeling. Besides, with the advances in sensor technology, dynamic time-evolving data have become more common. In this context, one point of interest is a better understanding of the information flow within and between networks. Thus, we aim to infer Granger causality (G-causality) between networks’ time series. In this case, the straightforward application of the well-established vector autoregressive model is not feasible. Consequently, we require a theoretical framework for modeling time-varying graphs. One possibility would be to consider a mathematical graph model with time-varying parameters (assumed to be random variables) that generates the network. Suppose we identify G-causality between the graph models’ parameters. In that case, we could use it to define a G-causality between graphs. Here, we show that even if the model is unknown, the spectral radius is a reasonable estimate of some random graph model parameters. We illustrate our proposal’s application to study the relationship between brain hemispheres of controls and children diagnosed with Autism Spectrum Disorder (ASD). We show that the G-causality intensity from the brain’s right to the left hemisphere is different between ASD and controls.

scholarly journals Sex Differences in Functional Connectivity Between Resting State Brain Networks in Autism Spectrum Disorder

2021 ◽  
Author(s):  
Vânia Tavares ◽  
Luís Afonso Fernandes ◽  
Marília Antunes ◽  
Hugo Ferreira ◽  
Diana Prata
Keyword(s):  
Autism Spectrum Disorder ◽  
Sex Differences ◽  
Resting State ◽  
Brain Connectivity ◽  
Autism Spectrum ◽  
Spectrum Disorder ◽  
Control Networks ◽  
Highly Sensitive ◽  
Female Specific ◽  
Main Effects

AbstractFunctional brain connectivity (FBC) has previously been examined in autism spectrum disorder (ASD) between-resting-state networks (RSNs) using a highly sensitive and reproducible hypothesis-free approach. However, results have been inconsistent and sex differences have only recently been taken into consideration using this approach. We estimated main effects of diagnosis and sex and a diagnosis by sex interaction on between-RSNs FBC in 83 ASD (40 females/43 males) and 85 typically developing controls (TC; 43 females/42 males). We found increased connectivity between the default mode (DM) and (a) the executive control networks in ASD (vs. TC); (b) the cerebellum networks in males (vs. females); and (c) female-specific altered connectivity involving visual, language and basal ganglia (BG) networks in ASD—in suggestive compatibility with ASD cognitive and neuroscientific theories.

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 Alpha connectivity and inhibitory control in adults with autism spectrum disorder

2020 ◽  
Vol 11 (1) ◽  
Author(s):  
Veronica Yuk ◽  
Benjamin T. Dunkley ◽  
Evdokia Anagnostou ◽  
Margot J. Taylor
Keyword(s):  
Autism Spectrum Disorder ◽  
Everyday Life ◽  
Inhibitory Control ◽  
Response Inhibition ◽  
Brain Connectivity ◽  
Autism Spectrum ◽  
Spectrum Disorder ◽  
Alpha Band ◽  
Brain Functions ◽  
Adults With Asd

Abstract Background Individuals with autism spectrum disorder (ASD) often report difficulties with inhibition in everyday life. During inhibition tasks, adults with ASD show reduced activation of and connectivity between brain areas implicated in inhibition, suggesting impairments in inhibitory control at the neural level. Our study further investigated these differences by using magnetoencephalography (MEG) to examine the frequency band(s) in which functional connectivity underlying response inhibition occurs, as brain functions are frequency specific, and whether connectivity in certain frequency bands differs between adults with and without ASD. Methods We analysed MEG data from 40 adults with ASD (27 males; 26.94 ± 6.08 years old) and 39 control adults (27 males; 27.29 ± 5.94 years old) who performed a Go/No-go task. The task involved two blocks with different proportions of No-go trials: Inhibition (25% No-go) and Vigilance (75% No-go). We compared whole-brain connectivity in the two groups during correct No-go trials in the Inhibition vs. Vigilance blocks between 0 and 400 ms. Results Despite comparable performance on the Go/No-go task, adults with ASD showed reduced connectivity compared to controls in the alpha band (8–14 Hz) in a network with a main hub in the right inferior frontal gyrus. Decreased connectivity in this network predicted more self-reported difficulties on a measure of inhibition in everyday life. Limitations Measures of everyday inhibitory control were not available for all participants, so this relationship between reduced network connectivity and inhibitory control abilities may not be necessarily representative of all adults with ASD or the larger ASD population. Further research with independent samples of adults with ASD, including those with a wider range of cognitive abilities, would be valuable. Conclusions Our findings demonstrate reduced functional brain connectivity during response inhibition in adults with ASD. As alpha-band synchrony has been linked to top-down control mechanisms, we propose that the lack of alpha synchrony observed in our ASD group may reflect difficulties in suppressing task-irrelevant information, interfering with inhibition in real-life situations.

Classification of Autism Spectrum Disorder from EEG-based Functional Brain Connectivity Analysis

2021 ◽  
pp. 1-27
Author(s):  
Noura Alotaibi ◽  
Koushik Maharatna
Keyword(s):  
Machine Learning ◽  
Autism Spectrum Disorder ◽  
Brain Connectivity ◽  
Phase Locking ◽  
Children With Autism ◽  
Autism Spectrum ◽  
Spectrum Disorder ◽  
Functional Brain ◽  
Graph Theoretic ◽  
Phase Locking Value

Abstract Autism is a psychiatric condition that is typically diagnosed with behavioral assessment methods. Recent years have seen a rise in the number of children with autism. Since this could have serious health and socioeconomic consequences, it is imperative to investigate how to develop strategies for an early diagnosis that might pave the way to an adequate intervention. In this study, the phase-based functional brain connectivity derived from electroencephalogram (EEG) in a machine learning framework was used to classify the children with autism and typical children in an experimentally obtained data set of 12 autism spectrum disorder (ASD) and 12 typical children. Specifically, the functional brain connectivity networks have quantitatively been characterized by graph-theoretic parameters computed from three proposed approaches based on a standard phase-locking value, which were used as the features in a machine learning environment. Our study was successfully classified between two groups with approximately 95.8% accuracy, 100% sensitivity, and 92% specificity through the trial-averaged phase-locking value (PLV) approach and cubic support vector machine (SVM). This work has also shown that significant changes in functional brain connectivity in ASD children have been revealed at theta band using the aggregated graph-theoretic features. Therefore, the findings from this study offer insight into the potential use of functional brain connectivity as a tool for classifying ASD children.

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.

Cross-sensory gating in schizophrenia and autism spectrum disorder: EEG evidence for impaired brain connectivity?

2009 ◽  
Vol 47 (7) ◽  
pp. 1728-1732 ◽  
Author(s):  
Maurice J.C.M. Magnée ◽  
Bob Oranje ◽  
Herman van Engeland ◽  
René S. Kahn ◽  
Chantal Kemner
Keyword(s):  
Autism Spectrum Disorder ◽  
Brain Connectivity ◽  
Sensory Gating ◽  
Autism Spectrum ◽  
Spectrum Disorder

scholarly journals Classification of autism spectrum disorder using supervised learning of brain connectivity measures extracted from synchrostates

2014 ◽  
Vol 11 (4) ◽  
pp. 046019 ◽  
Author(s):  
Wasifa Jamal ◽  
Saptarshi Das ◽  
Ioana-Anastasia Oprescu ◽  
Koushik Maharatna ◽  
Fabio Apicella ◽  
...  
Keyword(s):  
Autism Spectrum Disorder ◽  
Supervised Learning ◽  
Brain Connectivity ◽  
Autism Spectrum ◽  
Spectrum Disorder

Recognition and management of bladder bowel dysfunction in children with autism spectrum disorder

2021 ◽  
Vol 14 (6) ◽  
pp. e242646
Author(s):  
Shilpee Raturi ◽  
Fay Xiangzhen Li ◽  
Chui Mae Wong
Keyword(s):  
Autism Spectrum Disorder ◽  
Parental Education ◽  
Brain Connectivity ◽  
Children With Autism ◽  
Bowel Dysfunction ◽  
Autism Spectrum ◽  
Spectrum Disorder ◽  
Bladder Function ◽  
Children With Asd ◽  
Bladder Bowel Dysfunction

Children with autism spectrum disorder (ASD) with rigidities, anxiety or sensory preferences may establish a pattern of holding urine and stool, which places them at high risk of developing bladder bowel dysfunction (BBD). BBD, despite being common, is often unrecognised in children with ASD. With this case report of a 7-year-old girl with ASD presenting with acute retention of urine, we attempt to understand the underlying factors which may contribute to the association between BBD and ASD. Literature review indicates a complex interplay of factors such as brain connectivity changes, maturational delay of bladder function, cognitive rigidities and psychosocial stressors in children with ASD may possibly trigger events which predispose some of them to develop BBD. Simple strategies such as parental education, maintaining a bladder bowel diary and treatment of constipation may result in resolution of symptoms.

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