Time of day dependent longitudinal changes in resting-state fMRI - Vaisvilaite, Liucija; Andersson, Micael; Salami, Alireza; Specht, Karsten (Frontiers in Neurology, 2023)
Longitudinal studies have become more common in the past years due to their superiority over cross-sectional samples. In the light of the ongoing replication crisis, the factors that may introduce variability in resting-state networks has been widely debated. This publication aimed to address the potential sources of variability, namely time of day, sex and age, in longitudinal within individual resting-state fMRI data. DCM was used to analyze fMRI time-series, extracting EC connectivity measures and parameters that define the BOLD signal. In addition, a two-way ANOVA was used to assess the change in EC and parameters that define the BOLD signal between data collection waves. The results indicate that time of day and gender have significant model evidence for the parameters that define the BOLD signal, but not EC. From the ANOVA analysis, findings indicate that there was significant change in 2 nodes of the DMN and their connections with the fronto-parietal network. Overall, these findings suggest that in addition to age and gender, which is commonly accounted for in the fMRI data collection, studies should note time of day, possibly treating as a covariate in longitudinal samples.