Network signatures define consciousness state during focal seizures

Area of Science:

• Neuroscience
• Epileptology
• Computational Neuroscience

Background:

• Epilepsy affects 1% of the global population, with loss of consciousness in focal impaired awareness seizures (FIASs) and focal-to-bilateral tonic-clonic seizures (FBTCSs) being particularly debilitating.
• The underlying network mechanisms causing loss of consciousness during seizures are not fully understood.
• Previous studies noted ictal activity and interictal connectivity changes, but ictal network states across different seizure types remain unevaluated.

Purpose of the Study:

• To investigate and compare the ictal network states of focal aware seizures (FASs), FIASs, and FBTCSs using advanced network measures.
• To explore the relationship between brain network dynamics during seizures and states of consciousness.
• To develop a deep learning model for classifying consciousness-impairing seizures.

Main Methods:

• Stereoelectroencephalography (SEEG) data from 74 epilepsy patients were analyzed.
• Sliding window band power, functional connectivity, and segregation were computed for preictal, ictal, and postictal periods.
• Subcortical-to-neocortical connectivity was assessed using SEEG and fMRI, and a convolutional neural network was employed for seizure type classification.

Main Results:

• Consciousness-impairing seizures (FIASs, FBTCSs) and deep sleep showed increased delta band power in the frontoparietal cortex.
• FIASs and deep sleep uniquely exhibited increased delta and decreased gamma segregation.
• Patients with FIASs displayed reduced subcortical-to-neocortical functional connectivity compared to controls.
• A deep learning network achieved an AUC of 0.75 for detecting consciousness-impairing seizures.

Conclusions:

• This study reveals distinct ictal network dynamics across different focal epilepsy seizure types.
• Ictal network changes in FIASs closely mirror those observed during natural deep sleep, differentiating them from FBTCSs.
• These findings offer potential for developing novel neuromodulation strategies to preserve consciousness in epilepsy patients.