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Roy H. Hamilton

Publications and source records attributed to Roy H. Hamilton.

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Network Controllability in the IFG Relates to Controlled Language Variability and Susceptibility to TMS

In language production, humans are confronted with considerable word selection demands. Often, we must select a word from among similar, acceptable, and competing alternative words in order to construct a sentence that conveys an intended meaning. In recent years, the left inferior frontal gyrus (LIFG) has been identified as critical to this ability. Despite a recent emphasis on network approaches to understanding language, how the LIFG interacts with the brain's complex networks to facilitate controlled language performance remains unknown. Here, we take a novel approach to understand word selection as a network control process in the brain. Using an anatomical brain network derived from high-resolution diffusion spectrum imaging (DSI), we computed network controllability underlying the site of transcranial magnetic stimulation in the LIFG between administrations of two word selection tasks. We find that a statistic that quantifies the LIFG's theoretically predicted control of difficult-to-reach states explains vulnerability to TMS in language tasks that vary in response (cognitive control) demands: open-response (word generation) vs. closed-response (number naming) tasks. Moreover, we find that a statistic that quantifies the LIFG's theoretically predicted control of communication across modules in the human connectome explains TMS-induced changes in open-response language task performance only. These findings establish a link between network controllability, cognitive function, and TMS effects.

q-bio.NC

Brain and Cognitive Reserve: Translation via Network Control Theory

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.

q-bio.NC