Dynamic directed interictal connectivity in left and right temporal lobe epilepsy

Area of Science:

• Neuroscience
• Epileptology
• Brain Network Analysis

Background:

• Epileptic activity involves widespread brain networks, not just single sources.
• These networks contribute to interictal brain dysfunction.
• Understanding dynamic connectivity is crucial for characterizing epilepsy subtypes.

Purpose of the Study:

• To investigate fast-varying network behavior during interictal spikes in right temporal lobe epilepsy (RTLE) and left temporal lobe epilepsy (LTLE).
• To analyze whole-brain scale directed connectivity patterns.
• To correlate connectivity findings with neuropsychological impairments.

Main Methods:

• High-density electroencephalography (EEG) and individual head models were used to estimate source activity in 82 cortical regions of interest (ROIs).
• Multivariate, time-varying, and frequency-resolved Granger-causal modeling (weighted Partial Directed Coherence) was applied to source signals.
• Nonparametric statistical tests compared spike and baseline epochs; connectivity results were compared between RTLE and LTLE and with neuropsychological data.

Main Results:

• Ipsilateral anterior temporal structures were identified as key drivers in both RTLE and LTLE, aligning with invasive epileptogenic zone findings.
• Increased outflow from key drivers was observed before spikes; ipsilateral and contralateral drivers varied between RTLE and LTLE.
• RTLE exhibited a more prominent ipsilateral-to-contralateral connectivity pattern than LTLE, with RTLE patients showing cognitive deficits linked to contralateral dysfunction.

Conclusions:

• Distinct time-varying connectivity patterns in RTLE and LTLE indicate they are not symmetrical epilepsy entities.
• The identified key driver region's outflow correlated with invasive validation of the epileptogenic zone.
• Dynamic connectivity characterization can elucidate cognitive deficits and aid in surgical management decisions for epilepsy patients.