Circadian phenotype impacts the brain’s resting-state functional connectivity, attentional performance, and sleepiness

Abstract

Introduction Functional connectivity (FC) of the human brain’s intrinsically connected networks underpins cognitive functioning and disruptions of FC are associated with sleep and neurological disorders. However, there is limited research on the impact of circadian phenotype and time of day on FC. Study Objectives The aim of this study was to investigate resting-state FC of the default mode network (DMN) in Early and Late circadian phenotypes over a socially constrained day. Methods Thirty-eight healthy individuals (14 male, 22.7 ± 4.2 years) categorized as Early ( n = 16) or Late ( n = 22) using the Munich ChronoType Questionnaire took part. Following a 2-week baseline of actigraphy coupled with saliva samples for melatonin and cortisol rhythms, participants underwent testing at 14:00 hours, 20:00 hours, and 08:00 hours the following morning. Testing consisted of resting-state functional magnetic resonance imaging (fMRI), a structural T1 scan, attentional cognitive performance tasks, and self-reported daytime sleepiness. Seed-based FC analysis from the medial prefrontal and posterior cingulate cortices of the DMN was performed, compared between groups and linked with behavioral data. Results Fundamental differences in the DMN were observed between Early and Late circadian phenotypes. Resting-state FC of the DMN predicted individual differences in attention and subjective ratings of sleepiness. Conclusion Differences in FC of the DMN may underlie the compromised attentional performance and increased sleepiness commonly associated with Late types when they conform to a societally constrained day that does not match their intrinsic circadian phenotype.

Chronotype and Social Jetlag - a (self-)critical review

“…The MCTQ-chronotype and its assessment of sleep phase have been validated against biochemical biomarkers, such as dim-light melatonin onset (DLMO) [18,[40][41][42] and cortisol [42], and objective behavioral measures of circadian phase (activity acrophase, and sleep behavior from logs or actimetry) [18,43,44]. They are all significantly correlated with MSFsc as one would expect if they are all valid biomarkers for phase of entrainment (the system state) and thus vary more of less together.…”

Diurnal Preference and Grey Matter Volume in a Large Population of Older Adults: Data from the UK Biobank

“…Converging lines of evidence point to the precuneus as a key neural substrate for diurnal preference and chronotype. Recent resting-state FMRI studies have reported reduced precuneal functional connectivity in young adult late-type individuals as compared to morning-types [18,19] and structural MRI studies -again in younger adults -have demonstrated greater grey matter volume in the same region [28,29]. More generally, task-based FMRI studies indicate a role for the precuneus in a range of paradigms including social processing.…”

“…The functional and structural substrates of diurnal preference and chronotype are poorly understood, largely due to the paucity of studies exploring these questions. Functional Magnetic Resonance Imaging (FMRI) studies of circadian typology have reported effects of chronotype/diurnal preference on attention [10,11], language comprehension [12], inhibition [13], working memory [14], reward processing [15,16], emotional processing [17] and resting connectivity [18,19] -although see Fafrowicz [20] who reported no effect of diurnal preference on resting-state connectivity as measured by ALFF (Amplitude of Low Frequency Fluctuations -an index of total power within a predefined frequency range [20]). Interpretation of the above findings is limited due to the relatively small number of studies and, to date, lack of replication.…”

Validation of the Portuguese Variant of the Munich Chronotype Questionnaire (MCTQPT)

“…The MCTQ has been applied in many different countries: Japan ( Kitamura et al, 2014 ); Korea ( Suh et al, 2018 ); Brazil ( Miguel et al, 2014 ; Pilz et al, 2018b ); and several European countries: Poland ( Jankowski, 2015 ), Germany ( Roenneberg et al, 2003 ; Kuhnle, 2006 ), Italy ( Ghotbi et al, 2019 ), and Netherlands ( Zavada et al, 2005 ). The MCTQ has been compared with the MEQ ( Zavada et al, 2005 ; Kitamura et al, 2014 ; Miguel et al, 2014 ; Suh et al, 2018 ) and has been validated against DLMO ( Kitamura et al, 2014 ; Kantermann et al, 2015 ; Facer-Childs et al, 2019 ), cortisol ( Facer-Childs et al, 2019 ), and actimetry, for extreme chronotypes ( Facer-Childs et al, 2019 ), for young adults ( Santisteban et al, 2018 ), for communities with different levels of urbanization ( Pilz et al, 2018b ), and for shift workers ( Juda et al, 2013b ). Recently, an ultrashort version (μMCTQ) has been created and validated against DLMO and actimetry ( Ghotbi et al, 2019 ).…”