Network signatures define consciousness state during focal seizures

Author:

Doss Derek J.123ORCID,Johnson Graham W.123ORCID,Makhoul Ghassan S.123ORCID,Rashingkar Rohan V.24ORCID,Shless Jared S.24ORCID,Bibro Camden E.24ORCID,Paulo Danika L.4ORCID,Gummadavelli Abhijeet4ORCID,Ball Tyler J.4,Reddy Shilpa B.5ORCID,Naftel Robert P.4ORCID,Haas Kevin F.6,Dawant Benoit M.12347ORCID,Constantinidis Christos189ORCID,Williams Roberson Shawniqua16ORCID,Bick Sarah K.14ORCID,Morgan Victoria L.12346ORCID,Englot Dario J.12346ORCID

Affiliation:

1. Department of Biomedical Engineering Vanderbilt University Nashville Tennessee USA

2. Vanderbilt University Institute of Imaging Science, Vanderbilt University Medical Center Nashville Tennessee USA

3. Vanderbilt Institute for Surgery and Engineering Nashville Tennessee USA

4. Department of Neurological Surgery Vanderbilt University Medical Center Nashville Tennessee USA

5. Department of Pediatrics Vanderbilt Children's Hospital Nashville Tennessee USA

6. Department of Neurology Vanderbilt University Medical Center Nashville Tennessee USA

7. Department of Radiology and Radiological Sciences Vanderbilt University Medical Center Nashville Tennessee USA

8. Vanderbilt Brain Institute Vanderbilt University Nashville Tennessee USA

9. Department of Ophthalmology and Visual Sciences Vanderbilt University Nashville Tennessee USA

Abstract

AbstractObjectiveEpilepsy is a common neurological disorder affecting 1% of the global population. Loss of consciousness in focal impaired awareness seizures (FIASs) and focal‐to‐bilateral tonic–clonic seizures (FBTCSs) can be devastating, but the mechanisms are not well understood. Although ictal activity and interictal connectivity changes have been noted, the network states of focal aware seizures (FASs), FIASs, and FBTCSs have not been thoroughly evaluated with network measures ictally.MethodsWe obtained electrographic data from 74 patients with stereoelectroencephalography (SEEG). Sliding window band power, functional connectivity, and segregation were computed on preictal, ictal, and postictal data. Five‐minute epochs of wake, rapid eye movement sleep, and deep sleep were also extracted. Connectivity of subcortical arousal structures was analyzed in a cohort of patients with both SEEG and functional magnetic resonance imaging (fMRI). Given that custom neuromodulation of seizures is predicated on detection of seizure type, a convolutional neural network was used to classify seizure types.ResultsWe found that in the frontoparietal association cortex, an area associated with consciousness, both consciousness‐impairing seizures (FIASs and FBTCSs) and deep sleep had increases in slow wave delta (1–4 Hz) band power. However, when network measures were employed, we found that only FIASs and deep sleep exhibited an increase in delta segregation and a decrease in gamma segregation. Furthermore, we found that only patients with FIASs had reduced subcortical‐to‐neocortical functional connectivity with fMRI versus controls. Finally, our deep learning network demonstrated an area under the curve of .75 for detecting consciousness‐impairing seizures.SignificanceThis study provides novel insights into ictal network measures in FASs, FIASs, and FBTCSs. Importantly, although both FIASs and FBTCSs result in loss of consciousness, our results suggest that ictal network changes in FIASs uniquely resemble those that occur during deep sleep. Our results may inform novel neuromodulation strategies for preservation of consciousness in epilepsy.

Funder

National Institute of Biomedical Imaging and Bioengineering

National Institute of General Medical Sciences

National Institute of Neurological Disorders and Stroke

Publisher

Wiley

Reference45 articles.

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