Can sliding-window correlations reveal dynamic functional connectivity in resting-state fMRI?

During the last several years, the focus of research on resting-state functional magnetic resonance imaging (fMRI) has shifted from the analysis of functional connectivity averaged over the duration of scanning sessions to the analysis of changes of functional connectivity within sessions. Although several studies have reported the presence of dynamic functional connectivity (dFC), statistical assessment of the results is not always carried out in a sound way and, in some studies, is even omitted. In this study, we explain why appropriate statistical tests are needed to detect dFC, we describe how they can be carried out and how to assess the performance of dFC measures, and we illustrate the methodology using spontaneous blood-oxygen level-dependent (BOLD) fMRI recordings of macaque monkeys under general anesthesia and in human subjects under resting-state conditions. We mainly focus on sliding-window correlations since these are most widely used in assessing dFC, but also consider a recently proposed non-linear measure. The simulations and methodology, however, are general and can be applied to any measure. The results are twofold. First, through simulations, we show that in typical resting-state sessions of 10 min, it is almost impossible to detect dFC using sliding-window correlations. This prediction is validated by both the macaque and the human data: in none of the individual recording sessions was evidence for dFC found. Second, detection power can be considerably increased by session- or subject-averaging of the measures. In doing so, we found that most of the functional connections are in fact dynamic. With this study, we hope to raise awareness of the statistical pitfalls in the assessment of dFC and how they can be avoided by using appropriate statistical methods.

Functional connectivity and oscillatory neuronal activity in the resting human brain.

Perceptions, thoughts, emotions and actions emerge from interactions between neuronal assemblies distributed across the brain rather than from local computations in restricted brain areas. Indeed, the operation of every cognitive act requires the integration of distributed activity, as implemented through long-range neuronal communication via a network of structural connections. Functional interactions in the brain are very often studied in subjects at rest, since the resting state is a privileged condition in which brain activity is unbiased by any specific goal-directed task. Early resting state studies showed that electrophysiological oscillatory activity in specific frequency bands supports synchronization processes related to long-range neuronal communication. In turn, experimental evidence from neuroimaging studies revealed that the human brain is organized into multiple large-scale networks of regions showing correlated hemodynamic activity. Multimodal studies have begun to disclose relationships between functional connectivity, as revealed by hemodynamic signals, and underlying electrophysiological processes. Furthermore, functional connectivity studies directly based on electrophysiological signals have recently revealed fundamental information regarding long-range neuronal communication at behaviorally relevant time-scales. The integration of different lines of evidence from hemodynamic and electrophysiological studies suggests that rapid changes of synchronized oscillatory activity in distributed brain networks is relevant for the ongoing maintenance and modulation of the task representations that form the basis of our cognitive flexibility.