Investigations on the Brain Connectivity Parameters for Co-Morbidities of Autism Using EEG

2018 ◽  
Vol 10 (2) ◽  
pp. 50-65 ◽  
Author(s):  
Vishnu Priya K. ◽  
Kavitha A.
Keyword(s):  
Brain Connectivity ◽  
Autism Spectrum ◽  
Autistic Children ◽  
Eeg Signals ◽  
Biomarker Identification ◽  
Stable Pattern ◽  
Behavioral Abnormalities ◽  
The Brain ◽  
Potential Biomarkers ◽  
Morbid Conditions

This article describes how the Autism Spectrum Disorder (ASD) is a collection of heterogeneous disorders with prevalent cognitive and behavioral abnormalities. ASD is generally considered a life-long disability occurring as a stand-alone disorder but it occurs with possible co-morbid conditions. Electroencephalography (EEG) studies have been identified as one of the most widely used tool for assessing the cognitive functions with strong evidences of stable pattern of EEG associated with ASD. With the understanding of the co-morbidities and the pathophysiology, it needs an appropriate signal processing routine. Hence, this article focuses on the electrophysiological biomarker identification from the acquired EEG signals of low-functioning autistic children to distinguish between the various co-morbidities of autism. Results show that the power, coherence and brain connectivity estimators determined from EEG can be potential biomarkers. The identified biomarkers can thus act as supportive tools for the physician in clinically assessments of Autistic children with difference co-morbidities who differ widely.

scholarly journals Genetic Approaches Using Zebrafish to Study the Microbiota–Gut–Brain Axis in Neurological Disorders

Cells ◽  
2021 ◽  
Vol 10 (3) ◽  
pp. 566
Author(s):  
Jae-Geun Lee ◽  
Hyun-Ju Cho ◽  
Yun-Mi Jeong ◽  
Jeong-Soo Lee
Keyword(s):  
Neurological Disorders ◽  
Genetic Model ◽  
Molecular Genetic ◽  
Autism Spectrum ◽  
Behavioral Abnormalities ◽  
Bidirectional Signaling ◽  
Intestinal Dysbiosis ◽  
The Central Nervous System ◽  
The Brain

The microbiota–gut–brain axis (MGBA) is a bidirectional signaling pathway mediating the interaction of the microbiota, the intestine, and the central nervous system. While the MGBA plays a pivotal role in normal development and physiology of the nervous and gastrointestinal system of the host, its dysfunction has been strongly implicated in neurological disorders, where intestinal dysbiosis and derived metabolites cause barrier permeability defects and elicit local inflammation of the gastrointestinal tract, concomitant with increased pro-inflammatory cytokines, mobilization and infiltration of immune cells into the brain, and the dysregulated activation of the vagus nerve, culminating in neuroinflammation and neuronal dysfunction of the brain and behavioral abnormalities. In this topical review, we summarize recent findings in human and animal models regarding the roles of the MGBA in physiological and neuropathological conditions, and discuss the molecular, genetic, and neurobehavioral characteristics of zebrafish as an animal model to study the MGBA. The exploitation of zebrafish as an amenable genetic model combined with in vivo imaging capabilities and gnotobiotic approaches at the whole organism level may reveal novel mechanistic insights into microbiota–gut–brain interactions, especially in the context of neurological disorders such as autism spectrum disorder and Alzheimer’s disease.

scholarly journals Investigating EEG Signals of Autistic Individuals Using Detrended Fluctuation Analysis

2021 ◽  
Vol 38 (5) ◽  
pp. 1515-1520
Author(s):  
Menaka Radhakrishnan ◽  
Karthik Ramamurthy ◽  
Avantika Kothandaraman ◽  
Gauri Madaan ◽  
Harini Machavaram
Keyword(s):  
Detrended Fluctuation Analysis ◽  
Autism Spectrum ◽  
Brain Diseases ◽  
Fluctuation Analysis ◽  
Typically Developing ◽  
Eeg Signals ◽  
Self Similarity ◽  
Detrended Fluctuation ◽  
Electroencephalogram Eeg ◽  
The Brain

To record all electrical activity of the human brain, an electroencephalogram (EEG) test using electrodes attached to the scalp is conducted. Analysis of EEG signals plays an important role in the diagnosis and treatment of brain diseases in the biomedical field. One of the brain diseases found in early ages include autism. Autistic behaviours are hard to distinguish, varying from mild impairments, to intensive interruption in daily life. The non-linear EEG signals arising from various lobes of the brain have been studied with the help of a robust technique called Detrended Fluctuation Analysis (DFA). Here, we study the EEG signals of Typically Developing (TD) and children with Autism Spectrum Disorder (ASD) using DFA. The Hurst exponents, which are the outputs of DFA, are used to find out the strength of self-similarity in the signals. Our analysis works towards analysing if DFA can be a helpful analysis for the early detection of ASD.

scholarly journals Giant ankyrin-B mediates transduction of axon guidance and collateral branch pruning factor sema 3A

eLife ◽  
2021 ◽  
Vol 10 ◽  
Author(s):  
Blake A Creighton ◽  
Simone Afriyie ◽  
Deepa Ajit ◽  
Cristine R Casingal ◽  
Kayleigh M Voos ◽  
...  
Keyword(s):  
Brain Connectivity ◽  
Autism Spectrum ◽  
Axon Collateral ◽  
Collateral Branch ◽  
Cellular Assays ◽  
Behavioral Abnormalities ◽  
Neuropilin 1 ◽  
Branch Formation ◽  
Ankyrin B

Variants in the high confident autism spectrum disorder (ASD) gene ANK2 target both ubiquitously expressed 220 kDa ankyrin-B and neurospecific 440 kDa ankyrin-B (AnkB440) isoforms. Previous work showed that knock-in mice expressing an ASD-linked Ank2 variant yielding a truncated AnkB440 product exhibit ectopic brain connectivity and behavioral abnormalities. Expression of this variant or loss of AnkB440 caused axonal hyperbranching in vitro, which implicated AnkB440 microtubule bundling activity in suppressing collateral branch formation. Leveraging multiple mouse models, cellular assays, and live microscopy, we show that AnkB440 also modulates axon collateral branching stochastically by reducing the number of F-actin-rich branch initiation points. Additionally, we show that AnkB440 enables growth cone (GC) collapse in response to chemorepellent factor semaphorin 3 A (Sema 3 A) by stabilizing its receptor complex L1 cell adhesion molecule/neuropilin-1. ASD-linked ANK2 variants failed to rescue Sema 3A-induced GC collapse. We propose that impaired response to repellent cues due to AnkB440 deficits leads to axonal targeting and branch pruning defects and may contribute to the pathogenicity of ANK2 variants.

scholarly journals Structurally constrained effective brain connectivity

2021 ◽  
Author(s):  
Alessandro Crimi
Keyword(s):  
Community Detection ◽  
Autoregressive Model ◽  
Brain Connectivity ◽  
Effective Connectivity ◽  
Structural Connectivity ◽  
Ground Truth ◽  
Autism Spectrum ◽  
Case Control ◽  
Functional Dependencies ◽  
The Brain

The relationship between structure and function is of interest in many research fields involving the study of complex biological processes. In neuroscience in particular, the fusion of structural and functional data can help to understand the underlying principles of the operational networks in the brain. To address this issue, this paper proposes a constrained autoregressive model leading to a representation of effective connectivity that can be used to better understand how the structure modulates the function. Or simply, it can be used to find novel biomarkers characterizing groups of subjects. In practice, an initial structural connectivity representation is re-weighted to explain the functional co-activations. This is obtained by minimizing the reconstruction error of an autoregressive model constrained by the structural connectivity prior. The model has been designed to also include indirect connections, allowing to split direct and indirect components in the functional connectivity, and it can be used with raw and deconvoluted BOLD signal.The derived representation of dependencies was compared to the well known dynamic causal model, giving results closer to known ground-truth. Further evaluation of the proposed effective network was performed on two typical tasks. In a first experiment the direct functional dependencies were tested on a community detection problem, where the brain was partitioned using the effective networks across multiple subjects. In a second experiment the model was validated in a case-control task, which aimed at differentiating healthy subjects from individuals with autism spectrum disorder. Results showed that using effective connectivity leads to clusters better describing the functional interactions in the community detection task, while maintaining the original structural organization, and obtaining a better discrimination in the case-control classification task.

scholarly journals Hemispheric Coherence in ASD with and without Comorbid ADHD and Anxiety

2016 ◽  
Vol 2016 ◽  
pp. 1-12 ◽  
Author(s):  
A. Saunders ◽  
I. J. Kirk ◽  
K. E. Waldie
Keyword(s):  
Developmental Disorders ◽  
Primary Motor Cortex ◽  
Brain Connectivity ◽  
Occipital Lobe ◽  
Autism Spectrum ◽  
Adhd Group ◽  
Comorbid Conditions ◽  
Resting State Functional Connectivity ◽  
Comorbid Adhd ◽  
The Brain

There is a growing body of evidence suggesting that altered brain connectivity may be a defining feature of disorders such as autism spectrum disorder (ASD), anxiety, and ADHD. This study investigated whether resting state functional connectivity, measured by 128-channel EEG oscillation coherence, differs between developmental disorders. Analyses were conducted separately on groups with and without comorbid conditions. Analyses revealed increased coherence across central electrodes over the primary motor cortex and decreased coherence in the frontal lobe networks in those with ASD compared to neurotypical controls. There was increased coherence in occipital lobe networks in the ADHD group compared to other groups. Symptoms of generalised anxiety were positively correlated with both frontal-occipital intrahemispheric (alpha only) coherence and occipital interhemispheric coherence (alpha, approaching theta band). The patterns of coherence in the ASD pure group were different when comorbid conditions were included in the analyses, suggesting that aberrant coherence in the frontal and central areas of the brain is specifically associated with ASD. Our findings support the idea that comorbid conditions are additive, rather than being symptoms of the same disorder.

scholarly journals Giant ankyrin-B mediates transduction of axon guidance and collateral branch pruning factor Sema 3A

2021 ◽  
Author(s):  
Damaris N Lorenzo ◽  
Blake A Creighton ◽  
Deepa Ajit ◽  
Simone Afriyie ◽  
Julia C Bay
Keyword(s):  
Brain Connectivity ◽  
Autism Spectrum ◽  
Axonal Guidance ◽  
Axon Collateral ◽  
Collateral Branch ◽  
Behavioral Abnormalities ◽  
Neuropilin 1 ◽  
Branch Formation ◽  
Ankyrin B

Variants in the high confident autism spectrum disorder gene ANK2 target both ubiquitously expressed 220-kDa ankyrin- B and neurospecific 440-kDa ankyrin-B (AnkB440) isoforms. Previous work showed that knock-in mice expressing an ASD linked Ank2 variant yielding a truncated AnkB440 product exhibit ectopic brain connectivity and behavioral abnormalities. Expression of this variant or loss of AnkB440 caused axonal hyperbranching in vitro, which implicated AnkB440 microtubule bundling activity in suppressing collateral branch formation. Leveraging multiple mouse models, cellular assays, and live microscopy, we show that AnkB440 also modulates axon collateral branching stochastically by reducing the number of F-actin-rich branch initiation points. Additionally, we show that AnkB440 enables growth cone (GC) collapse in response to chemorepellent factor semaphorin 3A (Sema 3A) by stabilizing its receptor complex L1 cell adhesion molecule/neuropilin-1. ASD-linked ANK2 variants failed to rescue Sema 3A-induced GC collapse. We propose that impaired response to repellent cues due to AnkB440 deficits leads to axonal guidance and branch pruning defects and may contribute to the pathogenicity of ANK2 variants.

The effects of probiotics and prebiotics on gastrointestinal and behavioural symptoms in autism spectrum disorder

2021 ◽  
Vol 16 ◽  
Author(s):  
José Guevara-Gonzaléz ◽  
José Guevara-Campos ◽  
Lucía González ◽  
Omar Cauli
Keyword(s):  
Gut Microbiota ◽  
Autism Spectrum ◽  
Current Evidence ◽  
Unknown Etiology ◽  
Behavioural Symptoms ◽  
Beneficial Effects ◽  
Behavioral Abnormalities ◽  
Spectrum Disorders ◽  
Different Strains ◽  
The Brain

Background: Autism spectrum disorders (ASDs) are a group of prevalent neuropsychiatric disorders. They present a complex and unknown etiology, which in most cases includes significant peripheral alterations outside the brain such as in the composition of gut microbiota. Because the gut microbiota is involved in modulating the gut–brain axis, several studies have suggested that the microbiome in the gut can modify metabolites which are able to cross the blood–brain barrier and modulate brain function. Methods: we reviewed the current evidence regarding microbiota alterations in patients with ASD and the effects of the administration of probiotics and prebiotics in these patients, both in terms of gastrointestinal and behavioural symptoms. Results: Administration of a probiotic formulation containing different strains of Lactobacillus (L. acidophilus, L. rhamnosus, and others) and Bifidobacteria had beneficial effects upon these aforementioned symptoms and their use is recommended in a subgroup of ASD patients that present gastrointestinal disturbances, Nonetheless, the types of gastrointestinal disturbances that most benefit from such interventions remains to be elucidated in order to personalize the medical approaches. Conclusion: Recent clinical studies have shown that probiotic treatments can regulate the gut microbiota and may result in improvements in some behavioral abnormalities associated with ASD. Trials using prebiotic fibers or synbiotics preparations are still lacking and necessary in order to deep in such therapeutic strategies in ASD with comorbid gastrointestinal disrturbances

scholarly journals Evaluating Functional Connectivity Alterations in Autism Spectrum Disorder Using Network-Based Statistics

Diagnostics ◽  
2018 ◽  
Vol 8 (3) ◽  
pp. 51 ◽  
Author(s):  
Aitana Pascual-Belda ◽  
Antonio Díaz-Parra ◽  
David Moratal
Keyword(s):  
Autism Spectrum Disorder ◽  
Brain Connectivity ◽  
Brain Networks ◽  
Autism Spectrum ◽  
Spectrum Disorder ◽  
Typical Development ◽  
Functional Brain ◽  
Functional Brain Networks ◽  
Management Functions ◽  
The Brain

The study of resting-state functional brain networks is a powerful tool to understand the neurological bases of a variety of disorders such as Autism Spectrum Disorder (ASD). In this work, we have studied the differences in functional brain connectivity between a group of 74 ASD subjects and a group of 82 typical-development (TD) subjects using functional magnetic resonance imaging (fMRI). We have used a network approach whereby the brain is divided into discrete regions or nodes that interact with each other through connections or edges. Functional brain networks were estimated using the Pearson’s correlation coefficient and compared by means of the Network-Based Statistic (NBS) method. The obtained results reveal a combination of both overconnectivity and underconnectivity, with the presence of networks in which the connectivity levels differ significantly between ASD and TD groups. The alterations mainly affect the temporal and frontal lobe, as well as the limbic system, especially those regions related with social interaction and emotion management functions. These results are concordant with the clinical profile of the disorder and can contribute to the elucidation of its neurological basis, encouraging the development of new clinical approaches.

scholarly journals Brain connectivity at different time-scales measured with EEG

2005 ◽  
Vol 360 (1457) ◽  
pp. 1015-1024 ◽  
Author(s):  
T Koenig ◽  
D Studer ◽  
D Hubl ◽  
L Melie ◽  
W.K Strik
Keyword(s):  
Frequency Domain ◽  
Brain Connectivity ◽  
Time Domain Analysis ◽  
Domain Analysis ◽  
Brain Regions ◽  
Frequency Domain Analysis ◽  
Functional Magnetic Resonance ◽  
Eeg Signals ◽  
Electroencephalogram Eeg ◽  
The Brain

We present an overview of different methods for decomposing a multichannel spontaneous electroencephalogram (EEG) into sets of temporal patterns and topographic distributions. All of the methods presented here consider the scalp electric field as the basic analysis entity in space. In time, the resolution of the methods is between milliseconds (time-domain analysis), subseconds (time- and frequency-domain analysis) and seconds (frequency-domain analysis). For any of these methods, we show that large parts of the data can be explained by a small number of topographic distributions. Physically, this implies that the brain regions that generated one of those topographies must have been active with a common phase. If several brain regions are producing EEG signals at the same time and frequency, they have a strong tendency to do this in a synchronized mode. This view is illustrated by several examples (including combined EEG and functional magnetic resonance imaging (fMRI)) and a selective review of the literature. The findings are discussed in terms of short-lasting binding between different brain regions through synchronized oscillations, which could constitute a mechanism to form transient, functional neurocognitive networks.

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