Brain and Cognitive Reserve: Translation via Network Control Theory

TL;DR

This paper explores how network control theory can be applied to large-scale brain networks to better understand cognitive resilience and neuroplasticity, potentially guiding new interventions for brain health.

Contribution

It introduces a theoretical framework using network control theory to investigate brain resilience and neuroplasticity at the network level.

Findings

Network control theory offers new insights into brain resilience mechanisms.

Application to the human connectome can inform translational interventions.

Provides a theoretical basis for understanding neuroplasticity in large-scale networks.

Abstract

Traditional approaches to understanding the brain's resilience to neuropathology have identified neurophysiological variables, often described as brain or cognitive 'reserve,' associated with better outcomes. However, mechanisms of function and resilience in large-scale brain networks remain poorly understood. Dynamic network theory may provide a basis for substantive advances in understanding functional resilience in the human brain. In this perspective, we describe recent theoretical approaches from network control theory as a framework for investigating network level mechanisms underlying cognitive function and the dynamics of neuroplasticity in the human brain. We describe the theoretical opportunities offered by the application of network control theory at the level of the human connectome to understand cognitive resilience and inform translational intervention.