Detecting high-frequency oscillations in real time during epilepsy surgery with neuromorphic hardware validated to predict postoperative seizure outcome.

The optimal detection parameters yielded Spearman R = .71 between channelwise HFO rates detected by the proposed spiking neural network detection and those previously detected by the Spectrum Detector in the training dataset.

During a live surgery, the detector analyzed incoming intraoperative electrocorticography during acquisition, HFOs were successfully captured, and HFO feedback was available within 1 min after completion of the recording period.

SIGNIFICANCE: Our automatic detector was easily transferred between centers and anesthesia protocols.