Abstract

Resting-state functional connectivity (FC) has become a major functional magnetic resonance imaging method to study network organization of human brains. There has been recent interest in the temporal fluctuations of FC calculated using short time windows ("dynamic FC") because this method could provide information inaccessible with conventional "static" FC, which is typically calculated using the entire scan lasting several tens of minutes. Although multiple studies have revealed considerable temporal fluctuations in FC, it is still unclear whether the fluctuations of FC measured in hemodynamics reflect the dynamics of underlying neural activity. We addressed this question using simultaneous imaging of neuronal calcium and hemodynamic signals in mice and found coordinated temporal dynamics of calcium FC and hemodynamic FC measured in the same short time windows. Moreover, we found that variation in transient neuronal coactivation patterns was significantly related to temporal fluctuations of sliding window FC in hemodynamics. Finally, we show that the observed dynamics of FC cannot be fully accounted for by simulated data assuming stationary FC. These results provide evidence for the neuronal origin of dynamic FC and further suggest that information relevant to FC is condensed in temporally sparse events that can be extracted using a small number of time points.

Highlights

  • Resting-state functional connectivity (FC) uses temporal correlation of spontaneous neuronal activity to assess network organization of brain regions in a non-invasive manner (Fox and Raichle 2007)

  • Consistent with the idea that variability in hemodynamic FC arises from underlying neuronal activity, we found close matches between dynamic” FC (dFC) of calcium and hemodynamics

  • We used simultaneous imaging of calcium and hemodynamic signals to show that temporal fluctuations in hemodynamic FC calculated in a short time window closely follow that of calcium FC, suggesting the neuronal origin of dFC

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Summary

Introduction

Resting-state functional connectivity (FC) uses temporal correlation of spontaneous neuronal activity to assess network organization of brain regions in a non-invasive manner (Fox and Raichle 2007). In contrast to the traditional analysis of “static” FC, the temporal fluctuation of FC across short time windows is increasingly recognized as a useful aspect of FC (Allen et al 2014; Hutchison et al 2013; Zalesky et al 2014) Such “dynamic” FC (dFC) calculated using short time windows could provide information that is inaccessible with static FC about the functional network organizations of healthy and diseased brains (Calhoun et al 2014; Preti et al 2016) [We note that the term “dynamics” refers to the non-stationarity of FC obtained with the sliding window analyses and does not refer to a process that is not invariant to temporal reordering of the samples (Liégeois et al 2017)]. The presence of temporal fluctuations in FC has informed theoreticians on how to constrain realistic models of brain networks (Deco et al 2013; Hansen et al 2015; Messé et al 2014)

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