Literature DB >> 30287299

A dynamic system of brain networks revealed by fast transient EEG fluctuations and their fMRI correlates.

B Hunyadi1, M W Woolrich2, A J Quinn2, D Vidaurre2, M De Vos3.   

Abstract

Resting state brain activity has become a significant area of investigation in human neuroimaging. An important approach for understanding the dynamics of neuronal activity in the resting state is to use complementary imaging modalities. Electrophysiological recordings can access fast temporal dynamics, while functional magnetic resonance imaging (fMRI) studies reveal detailed spatial patterns. However, the relationship between these two measures is not fully established. In this study, we used simultaneously recorded electroencephalography (EEG) and fMRI, along with Hidden Markov Modelling, to investigate how network dynamics at fast sub-second time-scales, accessible with EEG, link to the slower time-scales and higher spatial detail of fMRI. We found that the fMRI correlates of fast transient EEG dynamic networks show highly reproducible spatial patterns, and that their spatial organization exhibits strong similarity with traditional fMRI resting state networks maps. This further demonstrates the potential of electrophysiology as a tool for understanding the fast network dynamics that underlie fMRI resting state networks.
Copyright © 2018 Elsevier Inc. All rights reserved.

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Year:  2018        PMID: 30287299     DOI: 10.1016/j.neuroimage.2018.09.082

Source DB:  PubMed          Journal:  Neuroimage        ISSN: 1053-8119            Impact factor:   6.556


  13 in total

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2.  A survey of brain network analysis by electroencephalographic signals.

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Journal:  Cogn Neurodyn       Date:  2021-06-14       Impact factor: 5.082

3.  Connectomics of human electrophysiology.

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Journal:  Neuroimage       Date:  2021-12-12       Impact factor: 6.556

4.  Inferring Brain State Dynamics Underlying Naturalistic Stimuli Evoked Emotion Changes With dHA-HMM.

Authors:  Chenhao Tan; Xin Liu; Gaoyan Zhang
Journal:  Neuroinformatics       Date:  2022-03-04

5.  Transient spectral events in resting state MEG predict individual task responses.

Authors:  R Becker; D Vidaurre; A J Quinn; R G Abeysuriya; O Parker Jones; S Jbabdi; M W Woolrich
Journal:  Neuroimage       Date:  2020-04-07       Impact factor: 6.556

6.  Multimodal EEG-fMRI: advancing insight into large-scale human brain dynamics.

Authors:  Catie Chang; Jingyuan E Chen
Journal:  Curr Opin Biomed Eng       Date:  2021-03-15

7.  Dissecting beta-state changes during timed movement preparation in Parkinson's disease.

Authors:  Simone G Heideman; Andrew J Quinn; Mark W Woolrich; Freek van Ede; Anna C Nobre
Journal:  Prog Neurobiol       Date:  2019-11-25       Impact factor: 11.685

8.  Dynamics of Neural Microstates in the VTA-Striatal-Prefrontal Loop during Novelty Exploration in the Rat.

Authors:  Ashutosh Mishra; Nader Marzban; Michael X Cohen; Bernhard Englitz
Journal:  J Neurosci       Date:  2021-06-30       Impact factor: 6.167

9.  Determination of Dynamic Brain Connectivity via Spectral Analysis.

Authors:  Peter A Robinson; James A Henderson; Natasha C Gabay; Kevin M Aquino; Tara Babaie-Janvier; Xiao Gao
Journal:  Front Hum Neurosci       Date:  2021-07-16       Impact factor: 3.169

Review 10.  Intrinsic connectome organization across temporal scales: New insights from cross-modal approaches.

Authors:  Sepideh Sadaghiani; Jonathan Wirsich
Journal:  Netw Neurosci       Date:  2020-02-01
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