Genetic and Neuroanatomical Support for Functional Brain Network Dynamics in Epilepsy

TL;DR

This study demonstrates that seizure-related brain network dynamics in epilepsy can be predicted from anatomical, connectivity, and genetic data, revealing conserved and individual-specific features that influence seizure propagation.

Contribution

It introduces a model linking large-scale brain networks, genetics, and seizure dynamics, highlighting conserved and individual-specific factors in epilepsy.

Findings

Seizure dynamics are predicted by anatomy, white matter, and gene expression.

White matter features better predict ictal than preictal states.

Individual-specific architecture influences seizure patterns.

Abstract

Focal epilepsy is a devastating neurological disorder that affects an overwhelming number of patients worldwide, many of whom prove resistant to medication. The efficacy of current innovative technologies for the treatment of these patients has been stalled by the lack of accurate and effective methods to fuse multimodal neuroimaging data to map anatomical targets driving seizure dynamics. Here we propose a parsimonious model that explains how large-scale anatomical networks and shared genetic constraints shape inter-regional communication in focal epilepsy. In extensive ECoG recordings acquired from a group of patients with medically refractory focal-onset epilepsy, we find that ictal and preictal functional brain network dynamics can be accurately predicted from features of brain anatomy and geometry, patterns of white matter connectivity, and constraints complicit in patterns of gene coexpression, all of which are conserved across healthy adult populations. Moreover, we uncover evidence that markers of non-conserved architecture, potentially driven by idiosyncratic pathology of single subjects, are most prevalent in high frequency ictal dynamics and low frequency preictal dynamics. Finally, we find that ictal dynamics are better predicted by white matter features and more poorly predicted by geometry and genetic constraints than preictal dynamics, suggesting that the functional brain network dynamics manifest in seizures rely on - and may directly propagate along - underlying white matter structure that is largely conserved across humans. Broadly, our work offers insights into the generic architectural principles of the human brain that impact seizure dynamics, and could be extended to further our understanding, models, and predictions of subject-level pathology and response to intervention.