Predicting Task and Subject Differences with Functional Connectivity and BOLD Variability

TL;DR

This study demonstrates that both functional connectivity and BOLD variability can reliably predict individual subjects and tasks across years, offering new insights into brain activity patterns.

Contribution

It introduces BOLD Variability as a novel, interpretable measure for predicting subject and task identity, complementing traditional functional connectivity analysis.

Findings

Both FC and BV predict subject and task identity across years.

BV is reduced during cognitive tasks compared to rest.

Subject differences dominate changes in BV and FC.

Abstract

Previous research has found that functional connectivity (FC) can accurately predict the identity of a subject performing a task and the type of task being performed. We replicate these results using a large dataset collected at the OSU Center for Cognitive and Behavioral Brain Imaging. We also introduce a novel perspective on task and subject identity prediction: BOLD Variability (BV). Conceptually, BV is a region-specific measure based on the variance within each brain region. BV is simple to compute, interpret, and visualize. We show that both FC and BV are predictive of task and subject, even across scanning sessions separated by multiple years. Subject differences rather than task differences account for the majority of changes in BV and FC. Similar to results in FC, we show that BV is reduced during cognitive tasks relative to rest.