Temporal meta-states are associated with differential patterns of dynamic connectivity, network topology and attention

TL;DR

This study reveals that neural activity fluctuates over long periods, with distinct states linked to changes in brain network topology and attention, emphasizing the importance of longitudinal analysis in understanding brain dynamics.

Contribution

The paper identifies and characterizes two distinct temporal neural states over 18 months, linking them to network topology and attention, and replicates findings in an independent dataset.

Findings

Two neural states fluctuate over 18 months.

Distinct states are associated with changes in global efficiency.

States correlate with self-reported attention levels.

Abstract

Little is currently known about the coordination of neural activity over longitudinal time-scales and how these changes relate to behavior. To investigate this issue, we used resting-state fMRI data from a single individual to identify the presence of two distinct temporal states that fluctuated over the course of 18 months. We then demonstrated that these temporal states were associated with distinct neural dynamics within individual scanning sessions. In addition, the temporal states were also related to significant alterations in global efficiency, as well as differences in self-reported attention. These patterns were replicated in a separate longitudinal dataset, providing further supportive evidence for the presence of fluctuations in functional network topology over time. Together, our results underscore the importance of longitudinal phenotyping in cognitive neuroscience.