Biology subjects

Revell, A. Y.

Publications and source records attributed to Revell, A. Y..

3 recordsLinked to original sources

bioRxiv2022

A Taxonomy of Seizure Spread Patterns, Speed of Spread, and Associations With Structural Connectivity

Although seizure detection algorithms are widely used to localize seizure onset on intracranial EEG in epilepsy patients, relatively few studies focus on seizure activity beyond the seizure onset zone to direct treatment of surgical patients with epilepsy. To address this gap, we develop and compare fully automated deep learning algorithms to detect seizure activity on single channels, effectively quantifying spread when deployed across multiple channels. Across 275 seizures in 71 patients, we discover that the extent of seizure spread across the brain and the timing of seizure spread between temporal lobe regions is associated with both surgical outcomes and the brains structural connectivity between temporal lobes. Finally, we uncover a hierarchical structure of seizure spread patterns highlighting the relationship between clusters of seizures. Collectively, these findings underscore the broad utility in quantifying seizure activity past seizure onset to identify novel mechanisms of seizure evolution and its relationship to potential seizure freedom.

neuroscience↗

bioRxiv2021

White Matter Signals Reflect Information Transmission Between Brain Regions During Seizures

White matter supports critical brain functions such as learning and memory, modulates the distribution of action potentials, and transmits neural information between brain regions. Notably, neuronal cell bodies exist in deeper white matter tissue, neurotransmitter vesicles are released directly in white matter, and white matter blood-oxygenation level dependent (BOLD) signals are detectable across a range of different tasks--all appearing to reflect a dynamic, active tissue from which recorded signals can reveal meaningful information about the brain. Yet, the signals within white matter have largely been ignored. Here, we elucidate the properties of white matter signals using intracranial EEG in a bipolar montage. We show that such signals capture the communication between brain regions and differentiate pathophysiologies of epilepsy. In direct contradiction to past assumptions that white matter functional signals provide little value, we show that white matter recordings can elucidate brain function and pathophysiology. Broadly, white matter functional recordings acquired through implantable devices may provide a wealth of currently untapped knowledge about the neurobiology of disease.

neuroscience↗

bioRxiv2021

A Framework for Brain Atlases: Lessons from seizure Dynamics

Brain maps, or atlases, are essential tools for studying brain function and organization. The abundance of available atlases used across the neuroscience literature, however, creates an implicit challenge that may alter the hypotheses and predictions we make about neurological function and pathophysiology. Here, we demonstrate how parcellation scale, shape, anatomical coverage, and other atlas features may impact our prediction of the brains function from its underlying structure. We show how network topology, structure-function correlation (SFC), and the power to test specific hypotheses about epilepsy pathophysiology may change as a result of atlas choice and atlas features. Through the lens of our disease system, we propose a general framework and algorithm for atlas selection. This framework aims to maximize the descriptive, explanatory, and predictive validity of an atlas. Broadly, our framework strives to provide empirical guidance to neuroscience research utilizing the various atlases published over the last century.

neuroscience↗