Mapping how local perturbations influence systems-level brain dynamics
Abstract The human brain exhibits a distinct spatiotemporal organization that supports brain function and can be manipulated via local brain stimulation. Such perturbations to local cortical dynamics are globally integrated by distinct neural systems. However, it remains unclear how local changes in neural activity affect large-scale system dynamics. Here, we briefly review empirical and computational studies addressing how localized perturbations affect brain activity. We then systematically analyze a model of large-scale brain dynamics, assessing how localized changes in brain activity at the different sites affect whole-brain dynamics. We find that local stimulation induces changes in brain activity that can be summarized by relatively smooth tuning curves, which relate a region's effectiveness as a stimulation site to its position within the cortical hierarchy. Our results also support the notion that brain hubs, operating in a slower regime, are more resilient to focal perturbations and critically contribute to maintain stability in global brain dynamics. In contrast, perturbations of peripheral regions, characterized by faster activity, have greater impact on functional connectivity. As a parallel with this region-level result, we also find that peripheral systems such as the visual and sensorimotor networks were more affected by local perturbations than high-level systems such as the cingulo-opercular network. Our findings highlight the importance of a periphery-to-core hierarchy to determine the effect of local stimulation on the brain network. This study also provides novel resources to orient empirical work aiming at manipulating functional connectivity using non-invasive brain stimulation. Highlights We review empirical and computational work on network effects of local stimulation. We model whole-brain activity incorporating a hierarchy of timescales. The network effects of local perturbations follow a tuning curve linked to anatomy. Local perturbation on peripheral regions or networks has greater impact. Results highlight the importance of core-periphery axis in shaping brain dynamics.
Connectivity . Connectomics . Functional magnetic resonance imaging (fMRI) . Hubs . Brain networks . Transcranial magnetic stimulation (TMS) . Brain simulation . Computational modeling . Kuramoto model . Core-periphery axis.
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- DOI : http://dx.doi.org/10.1016/j.neuroimage.2017.01.057
- Elsevier : 저널 > 논문
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