Stability of Brain Functional Network During Working Memory Using Structural Balance Theory

TL;DR

This study uses Structural Balance Theory to analyze fMRI brain networks during working memory tasks, revealing increased stability and balanced triads in the network compared to resting state, highlighting the brain's integrated response.

Contribution

It introduces a novel application of Structural Balance Theory to brain network analysis during working memory, demonstrating increased stability through balanced triads during task performance.

Findings

Number of balanced triads increased during working memory

Network stability improved with more balanced triads

Changes in activity synchronization between key brain regions

Abstract

Working memory plays a crucial role in various aspects of human life. Therefore, it has been an area of interest in different research studies, especially neuroscience. The neuroscientists investigating working memory have primarily emphasized the brain's functional modularity. At the same time, a holistic perspective is still required to investigate the brain as an integrated and unified system. We hypothesized that the brain should shift towards a more stable state during working memory than the resting state. Therefore, based on the Structural Balance Theory (SBT), we aimed to address this process. To achieve this, we examined triadic associations in signed fMRI networks in healthy individuals using the N-back as the working memory task. We demonstrated that the number of balanced triads increased during the working memory task compared to the resting state, while the opposite is true for imbalanced triads. The increase of balanced triads forced the network to a more stable state with a lower balance energy level. The increase of balanced triads was crucially related to changes in anti-synchrony to synchronous activities between the Temporal Cortex, the Prefrontal Cortex, and the Parietal Cortex, which are known to be involved in various aspects of working memory, during the working memory process. We hope these findings pave the way to a better understanding the working memory process.