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Circadian and Homeostatic Modulation of Functional Connectivity and Regional Cerebral Blood Flow in Humans under Normal Entrained Conditions
Author(s) -
Duncan J. Hodkinson,
Owen O’Daly,
Patricia A. Zunszain,
Carmine M. Pariante,
Vitaly Lazurenko,
Fernando Zelaya,
Matthew A. Howard,
Steven Williams
Publication year - 2014
Publication title -
journal of cerebral blood flow and metabolism
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 2.167
H-Index - 193
eISSN - 1559-7016
pISSN - 0271-678X
DOI - 10.1038/jcbfm.2014.109
Subject(s) - circadian rhythm , neuroscience , resting state fmri , functional magnetic resonance imaging , default mode network , cerebral blood flow , homeostasis , psychology , human brain , neuroimaging , anterior cingulate cortex , medicine , endocrinology , biology , cognition
Diurnal rhythms have been observed in human behaviors as diverse as sleep, olfaction, and learning. Despite its potential impact, time of day is rarely considered when brain responses are studied by neuroimaging techniques. To address this issue, we explicitly examined the effects of circadian and homeostatic regulation on functional connectivity (FC) and regional cerebral blood flow (rCBF) in healthy human volunteers, using whole-brain resting-state functional magnetic resonance imaging (rs-fMRI) and arterial spin labeling (ASL). In common with many circadian studies, we collected salivary cortisol to represent the normal circadian activity and functioning of the hypothalamic-pituitary-adrenal (HPA) axis. Intriguingly, the changes in FC and rCBF we observed indicated fundamental decreases in the functional integration of the default mode network (DMN) moving from morning to afternoon. Within the anterior cingulate cortex (ACC), our results indicate that morning cortisol levels are negatively correlated with rCBF. We hypothesize that the homeostatic mechanisms of the HPA axis has a role in modulating the functional integrity of the DMN (specifically, the ACC), and for the purposes of using fMRI as a tool to measure changes in disease processes or in response to treatment, we demonstrate that time of the day is important when interpreting resting-state data.

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