Sleep–wake states change the interictal localization of candidate epileptic source generators

Author:

McLeod Graham A1ORCID,Abbasian Parandoush23,Toutant Darion4,Ghassemi Amirhossein4,Duke Tyler4,Rycyk Conrad4,Serletis Demitre56,Moussavi Zahra4,Ng Marcus C47

Affiliation:

1. Department of Clinical Neurosciences, University of Calgary , Calgary, AB , Canada

2. Medical Physics, Department of Physics and Astronomy, University of Manitoba , Winnipeg, MB , Canada

3. CancerCare Manitoba Research Institute , Winnipeg, MB , Canada

4. Biomedical Engineering, University of Manitoba , Winnipeg, MB , Canada

5. Charles Shor Epilepsy Center, Cleveland Clinic , Cleveland, OH , USA

6. Department of Neurosurgery, Cleveland Clinic Foundation , Cleveland, OH , USA

7. Section of Neurology, University of Manitoba , Winnipeg, MB , Canada

Abstract

Abstract Study Objectives To compare estimated epileptic source localizations from 5 sleep–wake states (SWS): wakefulness (W), rapid eye movement sleep (REM), and non-REM 1-3. Methods Electrical source localization (sLORETA) of interictal spikes from different SWS on surface EEG from the epilepsy monitoring unit at spike peak and take-off, with results mapped to individual brain models for 75% of patients. Concordance was defined as source localization voxels shared between 2 and 5 SWS, and discordance as those unique to 1 SWS against 1–4 other SWS. Results 563 spikes from 16 prospectively recruited focal epilepsy patients across 161 day-nights. SWS exerted significant differences at spike peak but not take-off. Source localization size did not vary between SWS. REM localizations were smaller in multifocal than unifocal patients (28.8% vs. 54.4%, p = .0091). All five SWS contributed about 45% of their localizations to converge onto 17.0 ± 15.5% voxels. Against any one other SWS, REM was least concordant (54.4% vs. 66.9%, p = .0006) and most discordant (39.3% vs. 29.6%, p = .0008). REM also yielded the most unique localizations (20.0% vs. 8.6%, p = .0059). Conclusions REM was best suited to identify candidate epileptic sources. sLORETA proposes a model in which an “omni-concordant core” of source localizations shared by all five SWS is surrounded by a “penumbra” of source localizations shared by some but not all SWS. Uniquely, REM spares this core to “move” source voxels from the penumbra to unique cortex not localized by other SWS. This may reflect differential intra-spike propagation in REM, which may account for its reported superior localizing abilities.

Funder

Canadian Institutes of Health Research

Mathematics of Information Technology and Complex Systems Accelerate

Health Sciences Centre Foundation

Publisher

Oxford University Press (OUP)

Subject

Physiology (medical),Neurology (clinical)

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