Dynamical Complexity Fingerprints of Occupation-Dependent Brain Functional Networks in Professional Seafarers

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Abstract

The complexity derived from resting-state functional magnetic resonance imaging (rs-fMRI) data has been applied for exploring cognitive states and occupational neuroplasticity. However, there is little information about the influence of occupational factors on dynamic complexity and topological properties of the connectivity networks. In this paper, we proposed a novel dynamical brain complexity analysis (DBCA) framework to explore the changes in dynamical complexity of brain activity at the voxel level and complexity topology for professional seafarers caused by long-term working experience. The proposed DBCA is made up of dynamical brain entropy mapping analysis and complex network analysis based on brain entropy sequences, which generate the dynamical complexity of local brain areas and the topological complexity across brain areas, respectively. First, the transient complexity of voxel-wise brain map was calculated; compared with non-seafarers, seafarers showed decreased dynamic entropy values in the cerebellum and increased values in the left fusiform gyrus (BA20). Further, the complex network analysis based on brain entropy sequences revealed small-worldness in terms of topological complexity in both seafarers and non-seafarers, indicating that it is an inherent attribute of human the brain. In addition, seafarers showed a higher average path length and lower average clustering coefficient than non-seafarers, suggesting that the information processing ability is reduced in seafarers. Moreover, the reduction in efficiency of seafarers suggests that they have a less efficient processing network. To sum up, the proposed DBCA is effective for exploring the dynamic complexity changes in voxel-wise activity and region-wise connectivity, showing that occupational experience can reshape seafarers’ dynamic brain complexity fingerprints.

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Most cited references 82

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Author and article information

Contributors

Hongjie Yan: URI : http://loop.frontiersin.org/people/214145/overview

Huijun Wu: URI : http://loop.frontiersin.org/people/498540/overview

Yanyan Chen: URI : http://loop.frontiersin.org/people/1650257/overview

Yang Yang: URI : http://loop.frontiersin.org/people/933116/overview

Min Xu: URI : http://loop.frontiersin.org/people/317760/overview

Weiming Zeng: URI : http://loop.frontiersin.org/people/576792/overview

Chunqi Chang: URI : http://loop.frontiersin.org/people/417155/overview

Nizhuan Wang: URI : http://loop.frontiersin.org/people/52218/overview

Journal

Journal ID (nlm-ta): Front Neurosci

Journal ID (iso-abbrev): Front Neurosci

Journal ID (publisher-id): Front. Neurosci.

Title: Frontiers in Neuroscience

Publisher: Frontiers Media S.A.

ISSN (Print): 1662-4548

ISSN (Electronic): 1662-453X

Publication date (Electronic): 18 March 2022

Publication date Collection: 2022

Volume: 16

Electronic Location Identifier: 830808

Affiliations

[1] ¹Department of Neurology, Affiliated Lianyungang Hospital of Xuzhou Medical University , Lianyungang, China

[2] ²School of Biomedical Engineering, Health Science Center, Shenzhen University , Shenzhen, China

[3] ³Key Laboratory of Behavioral Science, Center for Brain Science and Learning Difficulties, Institute of Psychology, Chinese Academy of Sciences , Beijing, China

[4] ⁴Center for Brain Disorders and Cognitive Science, Shenzhen University , Shenzhen, China

[5] ⁵Lab of Digital Image and Intelligent Computation, Shanghai Maritime University , Shanghai, China

[6] ⁶School of Pharmacy, Health Science Center, Shenzhen University , Shenzhen, China

[7] ⁷Peng Cheng Laboratory , Shenzhen, China

[8] ⁸School of Biomedical Engineering, ShanghaiTech University , Shanghai, China

Author notes

Edited by: Albert Yang, National Yang Ming Chiao Tung University, Taiwan

Reviewed by: Shimin Cai, University of Electronic Science and Technology of China, China; Fabio Baselice, University of Naples Parthenope, Italy

*Correspondence: Nizhuan Wang, wangnizhuan1120@ 123456gmail.com

Chunqi Chang, cqchang@ 123456szu.edu.cn

^†These authors have contributed equally to this work

This article was submitted to Brain Imaging Methods, a section of the journal Frontiers in Neuroscience

Article

DOI: 10.3389/fnins.2022.830808

PMC ID: 8973415

PubMed ID: 35368265

SO-VID: d1bba68a-2cf5-4ae1-8cca-3ce0caa01e38

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This is an open-access article distributed under the terms of the Creative Commons Attribution License (CC BY). The use, distribution or reproduction in other forums is permitted, provided the original author(s) and the copyright owner(s) are credited and that the original publication in this journal is cited, in accordance with accepted academic practice. No use, distribution or reproduction is permitted which does not comply with these terms.

History

Date received : 07 December 2021

Date accepted : 24 January 2022

Page count

Figures: 8, Tables: 9, Equations: 7, References: 82, Pages: 14, Words: 8940

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Dynamical Complexity Fingerprints of Occupation-Dependent Brain Functional Networks in Professional Seafarers

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Most cited references 82

Automated anatomical labeling of activations in SPM using a macroscopic anatomical parcellation of the MNI MRI single-subject brain.

Collective dynamics of 'small-world' networks.

Complex network measures of brain connectivity: uses and interpretations.

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