Diurnal variations of resting-state fMRI data: A graph-based analysis

被引:0
|
作者
Farahani, Farzad, V [1 ,2 ]
Karwowski, Waldemar [2 ]
D'Esposito, Mark [3 ,4 ]
Betzel, Richard F. [5 ]
Douglas, Pamela K. [6 ,7 ]
Sobczak, Anna Maria [8 ]
Bohaterewicz, Bartosz [8 ,9 ]
Marek, Tadeusz [8 ]
Fafrowicz, Magdalena [8 ,10 ]
机构
[1] Johns Hopkins Univ, Dept Biostat, Baltimore, MD 21205 USA
[2] Univ Cent Florida, Dept Ind Engn & Management Syst, Computat Neuroergon Lab, Orlando, FL 32816 USA
[3] Univ Calif Berkeley, Helen Wills Neurosci Inst, Berkeley, CA 94720 USA
[4] Univ Calif Berkeley, Dept Psychol, 3210 Tolman Hall, Berkeley, CA 94720 USA
[5] Indiana Univ, Dept Psychol & Brain Sci, Bloomington, IN USA
[6] Univ Cent Florida, Inst Simulat & Training, Orlando, FL 32816 USA
[7] Univ Calif Los Angeles, Dept Psychiat & Biobehav Sci, Los Angeles, CA 90024 USA
[8] Jagiellonian Univ, Inst Appl Psychol, Dept Cognit Neurosci & Neuroergon, Krakow, Poland
[9] Univ Social Sci & Humanities, Inst Psychol, Dept Psychol Individual Differences Psychol Diag, Warsaw, Poland
[10] Jagiellonian Univ, Malopolska Ctr Biotechnol, Krakow, Poland
关键词
Functional connectivity; Resting-state fMRI; Graph theory; Network analysis; Circadian rhythm; Chronotype; Brain networks; DEFAULT-MODE NETWORK; FUNCTIONAL CONNECTIVITY; CIRCADIAN-RHYTHMS; PERMUTATION TESTS; BRAIN RESPONSES; WORKING-MEMORY; SLEEP; TIME; ATTENTION; TASK;
D O I
暂无
中图分类号
Q189 [神经科学];
学科分类号
071006 ;
摘要
Circadian rhythms (lasting approximately 24 h) control and entrain various physiological processes, ranging from neural activity and hormone secretion to sleep cycles and eating habits. Several studies have shown that time of day (TOD) is associated with human cognition and brain functions. In this study, utilizing a chronotype-based paradigm, we applied a graph theory approach on resting-state functional MRI (rs-fMRI) data to compare wholebrain functional network topology between morning and evening sessions and between morning-type (MT) and evening-type (ET) participants. Sixty-two individuals (31 MT and 31 ET) underwent two fMRI sessions, approximately 1 hour (morning) and 10 h (evening) after their wake-up time, according to their declared habitual sleep-wake pattern on a regular working day. In the global analysis, the findings revealed the effect of TOD on functional connectivity (FC) patterns, including increased small-worldness, assortativity, and synchronization across the day. However, we identified no significant differences based on chronotype categories. The study of the modular structure of the brain at mesoscale showed that functional networks tended to be more integrated with one another in the evening session than in the morning session. Local/regional changes were affected by both factors (i.e., TOD and chronotype), mostly in areas associated with somatomotor, attention, frontoparietal, and default networks. Furthermore, connectivity and hub analyses revealed that the somatomotor, ventral attention, and visual networks covered the most highly connected areas in the morning and evening sessions: the latter two were more active in the morning sessions, and the first was identified as being more active in the evening. Finally, we performed a correlation analysis to determine whether global and nodal measures were associated with subjective assessments across participants. Collectively, these findings contribute to an increased understanding of diurnal fluctuations in resting brain activity and highlight the role of TOD in future studies on brain function and the design of fMRI experiments.
引用
收藏
页数:25
相关论文
共 50 条
  • [1] Graph-based network analysis of resting-state functional MRI
    Wang, Jinhui
    Zuo, Xinian
    He, Yong
    [J]. FRONTIERS IN SYSTEMS NEUROSCIENCE, 2010, 4
  • [2] Graph-based network analysis of resting-state fMRI: test-retest reliability of binarized and weighted networks
    Xiang, Jie
    Xue, Jiayue
    Guo, Hao
    Li, Dandan
    Cui, Xiaohong
    Niu, Yan
    Yan, Ting
    Cao, Rui
    Ma, Yao
    Yang, Yanli
    Wang, Bin
    [J]. BRAIN IMAGING AND BEHAVIOR, 2020, 14 (05) : 1361 - 1372
  • [3] Graph-based network analysis of resting-state fMRI: test-retest reliability of binarized and weighted networks
    Jie Xiang
    Jiayue Xue
    Hao Guo
    Dandan Li
    Xiaohong Cui
    Yan Niu
    Ting Yan
    Rui Cao
    Yao Ma
    Yanli Yang
    Bin Wang
    [J]. Brain Imaging and Behavior, 2020, 14 : 1361 - 1372
  • [4] A method for independent component graph analysis of resting-state fMRI
    de Paula, Demetrius Ribeiro
    Ziegler, Erik
    Abeyasinghe, Pubuditha M.
    Das, Tushar K.
    Cavaliere, Carlo
    Aiello, Marco
    Heine, Lizette
    di Perri, Carol
    Demertzi, Athena
    Noirhomme, Quentin
    Charland-Verville, Vanessa
    Vanhaudenhuyse, Audrey
    Stender, Johan
    Gomez, Francisco
    Tshibanda, Jean-Flory L.
    Laureys, Steven
    Owen, Adrian M.
    Soddu, Andrea
    [J]. BRAIN AND BEHAVIOR, 2017, 7 (03):
  • [5] Classification of Resting-State fMRI Datasets Based on Graph Kernels
    Zhou, Yu
    Mei, Xue
    Li, Weiwei
    Huang, Jin
    [J]. 2017 2ND INTERNATIONAL CONFERENCE ON IMAGE, VISION AND COMPUTING (ICIVC 2017), 2017, : 665 - 669
  • [6] A multiscale analysis of the temporal characteristics of resting-state fMRI data
    Park, Cheolwoo
    Lazar, Nicole A.
    Ahn, Jeongyoun
    Sornborger, Andrew
    [J]. JOURNAL OF NEUROSCIENCE METHODS, 2010, 193 (02) : 334 - 342
  • [7] Over-Complete Analysis for Resting-State fMRI Data
    Ge, Ruiyang
    Yao, Li
    Zhang, Hang
    Wu, Xia
    Long, Zhiying
    [J]. ADVANCES IN COGNITIVE NEURODYNAMICS (V), 2016, : 317 - 323
  • [8] Advances and pitfalls in the analysis and interpretation of resting-state FMRI data
    Cole, David M.
    Smith, Stephen M.
    Beckmann, Christian F.
    [J]. FRONTIERS IN SYSTEMS NEUROSCIENCE, 2010, 4
  • [9] Functional Evolving Patterns of Cortical Networks in Progression of Alzheimer's Disease: A Graph-Based Resting-State fMRI Study
    Li, Wei
    Wen, Wen
    Chen, Xi
    Ni, BingJie
    Lin, Xuefeng
    Fan, Wenliang
    [J]. NEURAL PLASTICITY, 2020, 2020
  • [10] Abnormal Functional Resting-State Networks in ADHD: Graph Theory and Pattern Recognition Analysis of fMRI Data
    Siqueira, Anderson dos Santos
    Biazoli Junior, Claudinei Eduardo
    Comfort, William Edgar
    Rohde, Luis Augusto
    Sato, Joao Ricardo
    [J]. BIOMED RESEARCH INTERNATIONAL, 2014, 2014