Directionality of large-scale resting-state brain networks during eyes open and eyes closed conditions

Frontiers in Human Neuroscience
Delong ZhangRuiwang Huang

Abstract

The present study examined directional connections in the brain among resting-state networks (RSNs) when the participant had their eyes open (EO) or had their eyes closed (EC). The resting-state fMRI data were collected from 20 healthy participants (9 males, 20.17 ± 2.74 years) under the EO and EC states. Independent component analysis (ICA) was applied to identify the separated RSNs (i.e., the primary/high-level visual, primary sensory-motor, ventral motor, salience/dorsal attention, and anterior/posterior default-mode networks), and the Gaussian Bayesian network (BN) learning approach was then used to explore the conditional dependencies among these RSNs. The network-to-network directional connections related to EO and EC were depicted, and a support vector machine (SVM) was further employed to identify the directional connection patterns that could effectively discriminate between the two states. The results indicated that the connections among RSNs are directionally connected within a BN during the EO and EC states. The directional connections from the salience network (SN) to the anterior/posterior default-mode networks and the high-level to primary-level visual network were the obvious characteristics of both the EO and E...Continue Reading

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Citations

Nov 26, 2015·Clinical Neurophysiology : Official Journal of the International Federation of Clinical Neurophysiology·Francesca MiragliaPaolo Maria Rossini
Jun 28, 2015·Progress in Neuro-psychopharmacology & Biological Psychiatry·Je-Yeon YunJun Soo Kwon
Jun 19, 2018·Network Neuroscience·William Hedley ThompsonPeter Fransson
Nov 29, 2016·Frontiers in Neuroscience·José M SoaresNuno Sousa
Jan 13, 2021·Cognitive, Affective & Behavioral Neuroscience·Víctor CostumeroCésar Ávila

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Methods Mentioned

BETA
PCA

Software Mentioned

SPM8
GeneRalized
LIBSVM
Bayesian Net Toolbox ( BNT )
GIFT
Matlab
REST
fMRI Toolbox
Group ICA
DAGLearn

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