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Author: Lisa Elena Mash
Publisher:
ISBN:
Category :
Languages : en
Pages : 143
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Book Description
Autism spectrum disorder (ASD) is a behaviorally diagnosed neurodevelopmental condition that is associated with atypical functional connectivity (FC). However, no consistent biomarkers have been identified. Most studies to date have focused on static FC, and relatively little is known about time-varying properties of FC. This three-paper dissertation aimed to better characterize brain networks in ASD by evaluating: 1) transient connectivity states, 2) BOLD lag structure, and 3) associations between hemodynamic and electrophysiological measures of brain function. Study 1 (Mash et al., 2019) used sliding window analysis to examine FC variability and describe transient connectivity in children and adolescents (ages 6-18) with ASD (n=62) and their typically developing (TD) peers (n=57). Across all regions, the ASD group showed FC overconnectivity and hypervariability, on average. Distinct patterns of FC group differences were found in two transient states, but not in static FC analyses. Study 2 (Mash, et al., under review) explored resting-state and task-related BOLD lag structure in adolescents and young adults (ages 12-21) with ASD (n=28) and typical development (n=22). Lag patterns did not significantly differ between groups, with common 'early' and 'late' regions emerging in both groups. However, lag structure was associated with both task condition and vascular supply, suggesting a combination of neural and vascular contributions to BOLD latency. Study 3 (Mash et al., 2020) characterized relationships between separately acquired resting-state fMRI and EEG activity in a sample of children and adolescents (ages 6-18) with ASD and typical development (EEG-only: n=36 per group; fMRI-only: n=66 ASD, 57 TD; EEG-fMRI: n=17 per group). Reduced EEG alpha power, increased BOLD activity in right temporal regions, and widespread thalamocortical BOLD overconnectivity were observed in the ASD group. Multilevel modeling (with brain regions nested within individuals) revealed mostly positive relationships between EEG alpha power and regional BOLD activity in typical development, which were not observed in ASD. Overall, findings suggest that in comparison to conventional static FC studies, dynamic and multimodal analyses reveal more complex FC and activity patterns that may distinguish ASD from typical development.
Author: Lisa Elena Mash
Publisher:
ISBN:
Category :
Languages : en
Pages : 143
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Book Description
Autism spectrum disorder (ASD) is a behaviorally diagnosed neurodevelopmental condition that is associated with atypical functional connectivity (FC). However, no consistent biomarkers have been identified. Most studies to date have focused on static FC, and relatively little is known about time-varying properties of FC. This three-paper dissertation aimed to better characterize brain networks in ASD by evaluating: 1) transient connectivity states, 2) BOLD lag structure, and 3) associations between hemodynamic and electrophysiological measures of brain function. Study 1 (Mash et al., 2019) used sliding window analysis to examine FC variability and describe transient connectivity in children and adolescents (ages 6-18) with ASD (n=62) and their typically developing (TD) peers (n=57). Across all regions, the ASD group showed FC overconnectivity and hypervariability, on average. Distinct patterns of FC group differences were found in two transient states, but not in static FC analyses. Study 2 (Mash, et al., under review) explored resting-state and task-related BOLD lag structure in adolescents and young adults (ages 12-21) with ASD (n=28) and typical development (n=22). Lag patterns did not significantly differ between groups, with common 'early' and 'late' regions emerging in both groups. However, lag structure was associated with both task condition and vascular supply, suggesting a combination of neural and vascular contributions to BOLD latency. Study 3 (Mash et al., 2020) characterized relationships between separately acquired resting-state fMRI and EEG activity in a sample of children and adolescents (ages 6-18) with ASD and typical development (EEG-only: n=36 per group; fMRI-only: n=66 ASD, 57 TD; EEG-fMRI: n=17 per group). Reduced EEG alpha power, increased BOLD activity in right temporal regions, and widespread thalamocortical BOLD overconnectivity were observed in the ASD group. Multilevel modeling (with brain regions nested within individuals) revealed mostly positive relationships between EEG alpha power and regional BOLD activity in typical development, which were not observed in ASD. Overall, findings suggest that in comparison to conventional static FC studies, dynamic and multimodal analyses reveal more complex FC and activity patterns that may distinguish ASD from typical development.
Author: Rajesh K. Kana
Publisher: Frontiers E-books
ISBN: 2889192822
Category : Autism
Languages : en
Pages : 265
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Book Description
The brain's ability to process information crucially relies on connectivity. Understanding how the brain processes complex information and how such abilities are disrupted in individuals with neuropsychological disorders will require an improved understanding of brain connectivity. Autism is an intriguingly complex neurodevelopmental disorder with multidimensional symptoms and cognitive characteristics. A biological origin for autism spectrum disorders (ASD) had been proposed even in the earliest published accounts (Kanner, 1943; Asperger, 1944). Despite decades of research, a focal neurobiological marker for autism has been elusive. Nevertheless, disruptions in interregional and functional and anatomical connectivity have been a hallmark of neural functioning in ASD. Theoretical accounts of connectivity perceive ASD as a cognitive and neurobiological disorder associated with altered functioning of integrative circuitry. Neuroimaging studies have reported disruptions in functional connectivity (synchronization of activated brain areas) during cognitive tasks and during task-free resting states. While these insights are valuable, they do not address the time-lagged causality and directionality of such correlations. Despite the general promise of the connectivity account of ASD, inconsistencies and methodological differences among studies call for more thorough investigations. A comprehensive neurological account of ASD should incorporate functional, effective, and anatomical connectivity measures and test the diagnostic utility of such measures. In addition, questions pertaining to how cognitive and behavioral intervention can target connection abnormalities in ASD should be addressed. This research topic of the Frontiers in Human Neuroscience addresses “Brain Connectivity in Autism” primarily from cognitive neuroscience and neuroimaging perspectives.
Author:
Publisher:
ISBN:
Category : Electronic books
Languages : en
Pages : 48
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Book Description
There is evidence of abnormal organization of functional brain networks in Autism spectrum disorders (ASDs); however, findings have been mixed, with reports of both increased and decreased functional connectivity (FC) between and within networks. The present study sought to investigate if children and adolescents with ASDs have increased network FC variability and atypical network segregation and integration, compared to TD peers. Archival functional and anatomical magnetic resonance imaging data was utilized from 91 children and adolescents with ASDs and 71 age-matched TD controls. To capture a broad range of functional domains, six neurotypical networks were selected: default mode network (DMN), central executive network (CEN), salience network (SN), motor network (MOT), visual network (VIN), and mirror neuron system (MNS). Within-network (WN) and outside-network (ON) masks were then created. Seed-based whole-brain functional connectivity analyses were conducted for each network node; the resulting correlations were Fisher r-to-z transformed. An index of network segregation and integration (NSI) was calculated for each participant and WN, ON, and NSI were compared between groups. Additionally, inter-subject spatial similarity correlations were performed both within and between groups, to assess network spatial variability. Group comparisons of WN, ON, and NSI yielded one significant difference: CEN WN connectivity was significantly greater in the ASD group. Step one of the spatial similarity analyses revealed that within group similarity was comparable between the ASD and TD groups for all comparisons except DMN ON, which was significantly decreased in the ASD group. Step two demonstrated that participants in the ASD group were significantly less similar to TD participants for DMN ON, SN ON, MOT ON, and MNS ON connectivity. The final step of the analysis demonstrated that ASD participants were, on average, more spatially similar to other ASD participants than to TD participants. The results indicated that the pattern of spatial connectivity observed within the ASD group was distinct but comparable to the pattern of spatial connectivity observed in the TD group and it was not influenced by differences in strength of network connectivity, suggesting that spatial similarity in the ASD group can be attributed to abnormal network integration and segregation.
Author: Adonay Nunes Sastre
Publisher:
ISBN:
Category :
Languages : en
Pages : 175
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Book Description
Sensation, perception, cognition and behavior depend on complex neural processes carried by the coordinated function of brain structures. This coordination is achieved through oscillatory activity and synchronization, and the main pathways can be captured with resting-state activity. Structural alterations might affect the functional coordination with other brain structures, and a structure-function approach can provide a better understanding of the underlying neural mechanism that characterizes human populations. This thesis will study altered structure-function relationships in Autism Spectrum Disorder and in children born preterm at school age. Functional activity is assessed with MEG or fMRI resting-state data and structural characteristics with MRI. Both populations present brain oscillatory and structural alterations related to the thalamic-cortical system. Recent evidence indicates that the development of brain networks connectivity is altered in ASD and in very preterm born children. Evidence remains scant, however, regarding the relationship between atypical brain network connectivity and altered structure-function relationships in these groups. In ASD, there is contradictory evidence on the nature of such alterations with some studies suggesting increased or decreased functional connectivity involving particular structural areas. In very preterm children, evidence regarding the overall nature of structure-function network alterations remains scarce. Both populations present structural alterations and atypical oscillatory activity, and this research will investigate how structure-function relationships in brain networks are altered in ASD and in very preterm children and their association with developmental difficulties. Specifically, in ASD it will be assessed the functional brain networks spatial maps variability and atypical structural developmental trajectories of cortical thickness, and in preterm, atypical oscillatory activity and synchrony, and altered thalamic structural measures.
Author: Manuel F. Casanova
Publisher: Springer Science & Business Media
ISBN: 1461468434
Category : Medical
Languages : en
Pages : 399
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Book Description
Data compiled by the Center for Disease Control and Prevention indicates an alarming and continuing increase in the prevalence of autism. Despite intensive research during the last few decades, autism remains a behavioral defined syndrome wherein diagnostic criteria lack in construct validity. And, contrary to other conditions like diabetes and hypertension, there are no biomarkers for autism. However, new imaging methods are changing the way we think about autism, bringing us closer to a falsifiable definition for the condition, identifying affected individuals earlier in life, and recognizing different subtypes of autism. The imaging modalities discussed in this book emphasize the power of new technology to uncover important clues about the condition with the hope of developing effective interventions. Imaging the Brain in Autism was created to examine autism from a unique perspective that would emphasize results from different imaging technologies. These techniques show brain abnormalities in a significant percentage of patients, abnormalities that translate into aberrant functioning and significant clinical symptomatology. It is our hope that this newfound understanding will make the field work collaborative and provide a path that minimizes technical impediments.
Author: Dewen Hu
Publisher: Springer
ISBN: 9789813295254
Category : Medical
Languages : en
Pages : 0
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Book Description
This book presents recent advances in pattern analysis of the human connectome. The human connectome, measured by magnetic resonance imaging at the macroscale, provides a comprehensive description of how brain regions are connected. Based on machine learning methods, multiviarate pattern analysis can directly decode psychological or cognitive states from brain connectivity patterns. Although there are a number of works with chapters on conventional human connectome encoding (brain-mapping), there are few resources on human connectome decoding (brain-reading). Focusing mainly on advances made over the past decade in the field of manifold learning, sparse coding, multi-task learning, and deep learning of the human connectome and applications, this book helps students and researchers gain an overall picture of pattern analysis of the human connectome. It also offers valuable insights for clinicians involved in the clinical diagnosis and treatment evaluation of neuropsychiatric disorders.
Author: Amanda E. Wagner
Publisher:
ISBN:
Category :
Languages : en
Pages : 122
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Book Description
Autism spectrum disorder (ASD) is a heterogeneous neurodevelopmental disorder. There have been increased efforts to identify meaningful subtypes of ASD based on a variety of measures (e.g., behavioral symptoms, genetic information, etc.). Elucidation of homogenous subtypes may lead to clearer understanding of underlying brain functioning and etiology of ASD. A recent exploratory study aimed to determine whether neuropsychological test data could be used to parse a group of individuals with high-functioning ASD into homogenous "subtypes" based on unique neurocognitive profiles (Wagner, 2014). Results of that study were promising and suggested the emergence of 3 clusters. This subset of individuals with ASD was successfully parsed into smaller more homogenous subgroups based on unique neurocognitive profiles driven by performance on measures of reasoning, receptive language, and learning/memory. Thus, corresponding brain regions were selected for further study in order to explore potential underlying differences in brain functioning across identified clusters. Resting state functional connectivity magnetic resonance imaging (rs-fcMRI) is an emerging neuroimaging tool used to examine functional correlations among spatially distinct brain regions. Previous rs-fcMRI studies examining individuals with ASD have found evidence for altered connectivity; however, results have been inconsistent. Inconsistencies may be related to the heterogeneous nature of ASD and underlying differences in potential neurocognitive subtypes within ASD samples. The current study aimed to extend preliminary research by comparing patterns of functional connectivity of frontal brain regions, Wernicke's area, and hippocampal regions across previously identified clusters to examine potential differences in underlying brain function. Results indicated The ASD subgroup with above average reasoning and language skills had increased frontal functional connectivity in comparison to other ASD subjects and controls, as well as increased posterior superior temporal gyrus connectivity in comparison to other ASD subjects. The ASD subgroup with below average learning and memory had decreased hippocampal functional connectivity in comparison to controls. However, when ASD subgroups were combined, there were no differences in functional connectivity between ASD and controls. Thus, ASD may be related to unique alterations in functional connectivity networks, however meaningful subgroup differences are easily masked by sample heterogeneity. Identification of neurocognitive profiles may provide diagnostic utility both within the spectrum and between ASD and other disorders. Diagnostic clarification in the form of a "neurocognitive subtype" could provide useful information about cognitive strengths and weaknesses and directions for treatment and intervention planning. Further delineation of the ASD spectrum, including variations in cognitive profiles and related underlying brain networks, may reveal important differences in underlying etiology and response to treatment.
Author: MohammadMehdi Kafashan
Publisher:
ISBN:
Category : Electronic dissertations
Languages : en
Pages : 215
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Book Description
The brain is inherently a dynamical system whose networks interact at multiple spatial and temporal scales. Understanding the functional role of these dynamic interactions is a fundamental question in neuroscience. In this research, we approach this question through the development of new methods for characterizing brain dynamics from real data and new theories for linking dynamics to function. We perform our study at two scales: macro (at the level of brain regions) and micro (at the level of individual neurons). In the first part of this dissertation, we develop methods to identify the underlying dynamics at macro-scale that govern brain networks during states of health and disease in humans. First, we establish an optimization framework to actively probe connections in brain networks when the underlying network dynamics are changing over time. Then, we extend this framework to develop a data-driven approach for analyzing neurophysiological recordings without active stimulation, to describe the spatiotemporal structure of neural activity at different timescales. The overall goal is to detect how the dynamics of brain networks may change within and between particular cognitive states. We present the efficacy of this approach in characterizing spatiotemporal motifs of correlated neural activity during the transition from wakefulness to general anesthesia in functional magnetic resonance imaging (fMRI) data. Moreover, we demonstrate how such an approach can be utilized to construct an automatic classifier for detecting different levels of coma in electroencephalogram (EEG) data. In the second part, we study how ongoing function can constraint dynamics at micro-scale in recurrent neural networks, with particular application to sensory systems. Specifically, we develop theoretical conditions in a linear recurrent network in the presence of both disturbance and noise for exact and stable recovery of dynamic sparse stimuli applied to the network. We show how network dynamics can affect the decoding performance in such systems. Moreover, we formulate the problem of efficient encoding of an afferent input and its history in a nonlinear recurrent network. We show that a linear neural network architecture with a thresholding activation function is emergent if we assume that neurons optimize their activity based on a particular cost function. Such an architecture can enable the production of lightweight, history-sensitive encoding schemes.
Author: Marcel Adam Just
Publisher: Psychology Press
ISBN: 1848728662
Category : Medical
Languages : en
Pages : 266
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Book Description
The volume covers several perspectives on autism which bring together the most recent scientific views of the nature of this disorder. A number of themes organize major developments and emerging areas in autism. The book is essential for reseachers and practitioners who require a state-of-the-art resource on autism.
Author: Mikhail I. Rabinovich
Publisher: MIT Press
ISBN: 0262549905
Category : Medical
Languages : en
Pages : 371
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Book Description
Experimental and theoretical approaches to global brain dynamics that draw on the latest research in the field. The consideration of time or dynamics is fundamental for all aspects of mental activity—perception, cognition, and emotion—because the main feature of brain activity is the continuous change of the underlying brain states even in a constant environment. The application of nonlinear dynamics to the study of brain activity began to flourish in the 1990s when combined with empirical observations from modern morphological and physiological observations. This book offers perspectives on brain dynamics that draw on the latest advances in research in the field. It includes contributions from both theoreticians and experimentalists, offering an eclectic treatment of fundamental issues. Topics addressed range from experimental and computational approaches to transient brain dynamics to the free-energy principle as a global brain theory. The book concludes with a short but rigorous guide to modern nonlinear dynamics and their application to neural dynamics.
