Thalamic stimulation induced changes in network connectivity and excitability in epilepsy
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Objective
The effects of deep brain stimulation (DBS) manifest across multiple timescales, spanning seconds to months, and involve direct electrical effects, neuroplasticity, and network reorganization. In epilepsy, the delayed impact of DBS on seizures presents challenges for optimization. Single-pulse stimulation and resulting brain stimulation evoked potentials (BSEPs) provide a means to assess effective connectivity and network excitability. This study integrates BSEPs and short trials of DBS during stereoelectroencephalography (sEEG) to map seizure network engagement, modulate network dynamics, and monitor excitability and interictal abnormalities, for biomarker informed neuromodulation.
Methods
Ten individuals with drug resistant epilepsy undergoing clinical sEEG were enrolled in this retrospective cohort study of epilepsy neuromodulation biomarkers. Each patient underwent a trial of high frequency (145 Hz) thalamic DBS. BSEPs were acquired before and after DBS trials. Baseline BSEP amplitude assessed seizure network engagement, and modulation of amplitude (pre vs. post DBS) assessed change in network excitability. Interictal epileptiform discharges were tracked by an automated classifier.
Results:
Baseline BSEPs delineated distinct patterns of network engagement between thalamic subfields, with maximal frontotemporal engagement achieved with stimulation of the anterior nucleus of the thalamus-ventral anterior nucleus junction. DBS delivered for >1.5 hours reduced BSEP amplitudes compared to baseline, and the degree of modulation correlated with baseline connectivity strength. Shorter DBS trials did not induce reliable BSEP amplitude suppression, but did immediately suppress interictal epileptiform discharge rates in well-connected seizure networks.
Interpretation
BSEPs and trials of DBS during sEEG provide novel network biomarkers to evaluate the modulation of large-scale networks across multiple timescales, advancing biomarker informed neuromodulation.
