Reorganization of resting-state brain network functional connectivity across human brain developmental stages

[Display omitted] •fMRI BOLD time series signals can be used to group the four average developmental phases of a healthy human brain across the lifespan.•Resting-state functional connectivity reorganizes as the human brain developmental stages progress.•As the human brain goes through distinct devel...

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Veröffentlicht in:Brain research 2023-02, Vol.1800, p.148196-148196, Article 148196
Hauptverfasser: Singh, Prerna, Kumar Gandhi, Tapan, kumar, Lalan
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Kumar Gandhi, Tapan
kumar, Lalan
description [Display omitted] •fMRI BOLD time series signals can be used to group the four average developmental phases of a healthy human brain across the lifespan.•Resting-state functional connectivity reorganizes as the human brain developmental stages progress.•As the human brain goes through distinct developmental phases, six key Dosenbasch networks exhibit varying patterns of mean connectivity.•Clear separations of the Dosenbasch ROI clusters can be visualized using the t-SNE algorithm. Cognitive brain aging can either be healthy or degenerative in nature. Multiple alterations occur in brain networks with healthy aging. Much of this has yet to be investigated. This study seeks to understand the typical healthy human brain’s developmental stages using a publicly available dataset from the human connectome project. As the human brain’s developmental stage varies, we also intend to identify a pattern of reorganization in the resting state functional connectivity of several brain networks. The results are specifically presented based on the resting state BOLD signals of 1096 healthy volunteers between the age group of 7–89 years. The k-means clustering method has been used to determine the various human brain developmental stages. Using the t-SNE technique, the clusters are visually separated. BrainNet Viewer is used to study the changes in resting state functional connectivity of the entire brain as the human brain developmental stages vary. The age-related pattern of change in the resting state functional connectivity of six Dosenbasch brain networks that were grouped using the k-means elbow approach has been additionally presented. For performance evaluation, three metrics of brain network connection including network segregation, between network connectivity, and within-network connectivity are used. As the age cohort changes, a consistent pattern in the variance of these connection indices is seen for different Dosenbasch brain networks. Thus, the study’s findings suggest that healthy aging causes a functional reorganization of the resting state brain network connections.
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The age-related pattern of change in the resting state functional connectivity of six Dosenbasch brain networks that were grouped using the k-means elbow approach has been additionally presented. For performance evaluation, three metrics of brain network connection including network segregation, between network connectivity, and within-network connectivity are used. As the age cohort changes, a consistent pattern in the variance of these connection indices is seen for different Dosenbasch brain networks. 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Cognitive brain aging can either be healthy or degenerative in nature. Multiple alterations occur in brain networks with healthy aging. Much of this has yet to be investigated. This study seeks to understand the typical healthy human brain’s developmental stages using a publicly available dataset from the human connectome project. As the human brain’s developmental stage varies, we also intend to identify a pattern of reorganization in the resting state functional connectivity of several brain networks. The results are specifically presented based on the resting state BOLD signals of 1096 healthy volunteers between the age group of 7–89 years. The k-means clustering method has been used to determine the various human brain developmental stages. Using the t-SNE technique, the clusters are visually separated. BrainNet Viewer is used to study the changes in resting state functional connectivity of the entire brain as the human brain developmental stages vary. The age-related pattern of change in the resting state functional connectivity of six Dosenbasch brain networks that were grouped using the k-means elbow approach has been additionally presented. For performance evaluation, three metrics of brain network connection including network segregation, between network connectivity, and within-network connectivity are used. As the age cohort changes, a consistent pattern in the variance of these connection indices is seen for different Dosenbasch brain networks. 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subjects Adolescent
Adult
Aged
Aged, 80 and over
Aging
Brain
Brain Mapping - methods
Child
Cluster Analysis
Clustering
Connectome
Degenerative
Functional connectivity
Humans
Magnetic Resonance Imaging - methods
Middle Aged
Nerve Net - diagnostic imaging
Neural Pathways
Young Adult
title Reorganization of resting-state brain network functional connectivity across human brain developmental stages
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