A Novel Hidden Markov Approach to Studying Dynamic Functional Connectivity States in Human Neuroimaging-Reference-Cited by-同舟云学术

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A Novel Hidden Markov Approach to Studying Dynamic Functional Connectivity States in Human Neuroimaging

Published:2023-04-01 Issue:3 Volume:13 Page:154-163
ISSN:2158-0014
Container-title:Brain Connectivity
language:en
Short-container-title:Brain Connectivity

Author:

Hussain Sana¹^ORCID,Langley Jason²^ORCID,Seitz Aaron R.³^ORCID,Hu Xiaoping P.¹²^ORCID,Peters Megan A.K.¹⁴^ORCID

Affiliation:

1. Department of Bioengineering, University of California, Riverside, Riverside, California, USA.

2. Center for Advanced Neuroimaging, University of California, Riverside, Riverside, California, USA.

3. Department of Psychology, University of California, Riverside, Riverside, California, USA.

4. Department of Cognitive Sciences, University of California, Irvine, Irvine, California, USA.

Publisher

Mary Ann Liebert Inc

Subject

General Neuroscience

Link

https://www.liebertpub.com/doi/pdf/10.1089/brain.2022.0031

Reference29 articles.

1. Fast transient networks in spontaneous human brain activity

2. Investigations into resting-state connectivity using independent component analysis

3. Spatiotemporal Modeling of Brain Dynamics Using Resting-State Functional Magnetic Resonance Imaging with Gaussian Hidden Markov Model

4. Instantaneous and causal connectivity in resting state brain networks derived from functional MRI data

5. Unsupervised Learning of Functional Network Dynamics in Resting State fMRI

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1. Studying time-resolved functional connectivity via communication theory: on the complementary nature of phase synchronization and sliding window Pearson correlation;2024-06-13

2. A predictor-informed multi-subject bayesian approach for dynamic functional connectivity;PLOS ONE;2024-05-16

3. Dynamic transient brain states in preschoolers mirror parental report of behavior and emotion regulation;2024-01-22

4. Locus coeruleus integrity predicts ease of attaining and maintaining neural states of high attentiveness;Brain Research Bulletin;2023-10

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