Macroscale traveling waves evoked by single-pulse stimulation of the human brain

Campbell, Justin M.; Davis, Tyler; Anderson, Daria Nesterovich; Arain, Amir; Inman, Cory S.; Smith, Elliot H.; Rolston, John D.

doi:10.1101/2023.03.27.534002

Cited by 1 publication

(1 citation statement)

References 78 publications

(99 reference statements)

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“…Notably, we found a correlation of 0.23 between OI and FC (Supplementary Figure 9), that is close to what has been previously reported by comparing cortico-cortical evoked potentials (CCEPs) with FC [95]. Moreover, it has been proposed that at least a subset of CCEPs propagate as traveling waves [96]. Together, these works, and our findings suggest that, first, correlation-based measures such as FC capture the propagation of information in brain networks to a limited extent, and second an approach combining CMs with traveling waves could provide biophysical mechanisms for simple signal propagation models based on broadcasting regime such as communicability.…”

Section: Broadcasting As An Optimal Signaling Strategysupporting

confidence: 90%

A General Framework for Characterizing Optimal Communication in Brain Networks

Fakhar,

Hadaeghi,

Seguin

et al. 2024

Preprint

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Communication in brain networks is the foundation of cognitive function and behavior. A multitude of evolutionary pressures, including the minimization of metabolic costs while maximizing communication efficiency, contribute to shaping the structure and dynamics of these networks. However, how communication efficiency is characterized depends on the assumed model of communication dynamics. Traditional models include shortest path signaling, random walker navigation, broadcasting, and diffusive processes. Yet, a general and model-agnostic framework for characterizing optimal neural communication remains to be established.Our study addresses this challenge by assigning communication efficiency through game theory, based on a combination of structural data from human cortical networks with computational models of brain dynamics. We quantified the exact influence exerted by each brain node over every other node using an exhaustive multi-site virtual lesioning scheme, creating optimal influence maps for various models of brain dynamics. These descriptions show how communication patterns unfold in the given brain network if regions maximize their influence over one another. By comparing these influence maps with a large variety of brain communication models, we found that optimal communication most closely resembles a broadcasting model in which regions leverage multiple parallel channels for information dissemination. Moreover, we show that the most influential regions within the cortex are formed by its rich-club. These regions exploit their topological vantage point by broadcasting across numerous pathways, thereby significantly enhancing their effective reach even when the anatomical connections are weak.Our work provides a rigorous and versatile framework for characterizing optimal communication across brain networks and reveals the most influential brain regions and the topological features underlying their optimal communication.

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Section: Broadcasting As An Optimal Signaling Strategysupporting

confidence: 90%