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

Farzad V Farahani; Waldemar Karwowski; Mark D'Esposito; Richard F Betzel; Pamela K Douglas; Anna Maria Sobczak; Bartosz Bohaterewicz; Tadeusz Marek; Magdalena Fafrowicz

doi:10.1016/j.neuroimage.2022.119246

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

Neuroimage. 2022 Aug 1:256:119246. doi: 10.1016/j.neuroimage.2022.119246. Epub 2022 Apr 25.

Authors

Farzad V Farahani¹, Waldemar Karwowski², Mark D'Esposito³, Richard F Betzel⁴, Pamela K Douglas⁵, Anna Maria Sobczak⁶, Bartosz Bohaterewicz⁷, Tadeusz Marek⁶, Magdalena Fafrowicz⁸

Affiliations

¹ Department of Biostatistics, Johns Hopkins University, Baltimore, MD, USA; Computational Neuroergonomics Laboratory, Department of Industrial Engineering and Management Systems, University of Central Florida, Orlando, FL, USA. Electronic address: ffaraha2@jhu.edu.
² Computational Neuroergonomics Laboratory, Department of Industrial Engineering and Management Systems, University of Central Florida, Orlando, FL, USA.
³ Helen Wills Neuroscience Institute, University of California, Berkeley, CA, USA; Department of Psychology, University of California, Berkeley, CA, USA.
⁴ Department of Psychological and Brain Sciences, Indiana University, Bloomington, IN, USA.
⁵ Institute for Simulation and Training, University of Central Florida, Orlando, FL, USA; Department of Psychiatry and Biobehavioral Sciences, University of California, Los Angeles, Los Angeles, CA, USA.
⁶ Department of Cognitive Neuroscience and Neuroergonomics, Institute of Applied Psychology, Jagiellonian University, Krakow, Poland.
⁷ Department of Cognitive Neuroscience and Neuroergonomics, Institute of Applied Psychology, Jagiellonian University, Krakow, Poland; Department of Psychology of Individual Differences, Psychological Diagnosis, and Psychometrics, Institute of Psychology, University of Social Sciences and Humanities, Warsaw, Poland.
⁸ Department of Cognitive Neuroscience and Neuroergonomics, Institute of Applied Psychology, Jagiellonian University, Krakow, Poland; Malopolska Centre of Biotechnology, Jagiellonian University, Krakow, Poland. Electronic address: magda.fafrowicz@uj.edu.pl.

Abstract

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 whole-brain 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.

Keywords: Brain networks; Chronotype; Circadian rhythm; Functional connectivity; Graph theory; Network analysis; Resting-state fMRI.

Publication types

Research Support, Non-U.S. Gov't

MeSH terms

Brain Mapping
Circadian Rhythm* / physiology
Humans
Magnetic Resonance Imaging*
Rest / physiology
Sleep / physiology

Grants and funding

K01 MH110645/MH/NIMH NIH HHS/United States