Differential contributions of static and time-varying functional connectivity to human behavior.

Adam Eichenbaum,Ioannis Pappas,Jessica R Cohen,Mark D'Esposito,Daniel Lurie

doi:10.1162/netn_a_00172

Abstract

Measures of human brain functional connectivity acquired during the resting-state track critical aspects of behavior. Recently, fluctuations in resting-state functional connectivity patterns—typically averaged across in traditional analyses—have been considered for their potential neuroscientific relevance. There exists a lack of research on the differences between traditional “static” measures of functional connectivity and newly considered “time-varying” measures as they relate to human behavior. Using functional magnetic resonance imagining (fMRI) data collected at rest, and a battery of behavioral measures collected outside the scanner, we determined the degree to which each modality captures aspects of personality and cognitive ability. Measures of time-varying functional connectivity were derived by fitting a hidden Markov model. To determine behavioral relationships, static and time-varying connectivity measures were submitted separately to canonical correlation analysis. A single relationship between static functional connectivity and behavior existed, defined by measures of personality and stable behavioral features. However, two relationships were found when using time-varying measures. The first relationship was similar to the static case. The second relationship was unique, defined by measures reflecting trialwise behavioral variability. Our findings suggest that time-varying measures of functional connectivity are capable of capturing unique aspects of behavior to which static measures are insensitive.

Highlights

Measuring spontaneous activity in the human brain during a task-free “resting state” has become common as this activity has been revealed to be spatially and temporally organized (Biswal et al, 1995)
The current report takes a data-driven approach to characterize how time-varying patterns of human brain functional connectivity differ from traditional static measures in their ability to track aspects of personality and cognitive ability
We determine that time-varying patterns of functional connectivity track similar aspects of behavior as do static measures, and unique behavioral qualities as well, those that reflect behavioral variability

Summary

Introduction

Measuring spontaneous activity in the human brain during a task-free “resting state” has become common as this activity has been revealed to be spatially and temporally organized (Biswal et al, 1995). These patterns of resting-state functional connectivity (rsFC) are sensitive to numerous aspects of behavior measured outside the scanner, including cognitive performance (Stevens et al, 2012; Chan et al, 2014), age (Chan et al, 2014), and the extent of cognitive impairments (Alexander-Bloch et al, 2010; Rudie et al, 2013). There is recent evidence that fluctuations of task-based FC track aspects of cognitive control (Khambhati et al, 2018) and attention (Sadaghiani et al, 2015), suggesting that flexible network reconfiguration indexes trial-by-trial performance

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Discussion

Conclusion