Can fMRI functional connectivity index dynamic neural communication?

In order to continuously respond to a changing environment and support self-generating cognition and behaviour, neural communication must be highly flexible and dynamic at the same time than hierarchically organized. While whole-brain fMRI measures have revealed robust yet changing patterns of statistical dependencies between regions, it is not clear whether these statistical patterns --referred to as functional connectivity-- can reflect dynamic large-scale communication in a way that is relevant to human cognition. For functional connectivity to reflect cognition, and therefore actual communication, we propose three necessary conditions: it must span sufficient temporal complexity to support the needs of cognition while still being highly organized so that the system behaves reliably; it must be able to adapt to the current behavioural context; it must exhibit fluctuations at timescales that are compatible with the timescales of cognition. To obtain reliable estimations of time-varying functional connectivity, we developed principal components of connectivity analysis (PCCA), an approach based on applying principal component analysis on multiple runs of a time-varying functional connectivity model. We use PCCA to show that functional connectivity follows low-yet multi-dimensional trajectories that can be reliably measured, and that these trajectories meet the aforementioned criteria. These analyses suggest that these trajectories might index certain aspects of communication between neural populations and support moment-to-moment cognition. Significance StatementfMRI functional connectivity is one of the most widely used metrics in neuroimaging research in both theoretical research and clinical applications. However, this work suffers from a lack of context because we still do not fully understand what fMRI functional connectivity can or cannot reflect biologically and behaviourally. In particular, can it reflect between-region neuronal communication? We develop methods to reliably quantify temporal trajectories of functional connectivity and investigate the nature of these trajectories across different experimental conditions. Using these methods, we demonstrate that functional connectivity exhibits reliable changes that are context-dependent, reflect cognitive complexity, and bear a relationship with cognitive abilities. These conditions show that fMRI functional connectivity could reflect changes in between-region communication above and beyond non-neural factors.