An electronic neuromorphic system for real-time detection of High Frequency Oscillations (HFOs) in intracranial EEG

Abstract

In this work, we present a neuromorphic system that combines for the first time a neural recording headstage with a signal-to-spike conversion circuit and a multi-core spiking neural network (SNN) architecture on the same die for recording, processing, and detecting High Frequency Oscillations (HFO), which are biomarkers for the epileptogenic zone. The device was fabricated using a standard 0.18$\mu$m CMOS technology node and has a total area of 99mm${}^2$. We demonstrate its application to HFO detection in the iEEG recorded from 9 patients with temporal lobe epilepsy who subsequently underwent epilepsy surgery. The total average power consumption of the chip during the detection task was 614.3$\mu$W. We show how the neuromorphic system can reliably detect HFOs: the system predicts postsurgical seizure outcome with state-of-the-art accuracy, specificity and sensitivity (78%, 100%, and 33% respectively). This is the first feasibility study towards identifying relevant features in intracranial human data in real-time, on-chip, using event-based processors and spiking neural networks. By providing "neuromorphic intelligence" to neural recording circuits the approach proposed will pave the way for the development of systems that can detect HFO areas directly in the operation room and improve the seizure outcome of epilepsy surgery.

arXiv comment16 pages. A short video describing the rationale underlying the study can be viewed on https://youtu.be/NuAA91fdmaM

References in corpus (8)

• Memory and information processing in neuromorphic systems
• A scalable multi-core architecture with heterogeneous memory structures for Dynamic Neuromorphic Asynchronous Processors (DYNAPs)
• Neuromorphic electronic circuits for building autonomous cognitive systems
• Hardware Implementation of Deep Network Accelerators Towards Healthcare and Biomedical Applications
• Real-time ultra-low power ECG anomaly detection using an event-driven neuromorphic processor
• A recipe for creating ideal hybrid memristive-CMOS neuromorphic computing systems
• Ultra-Low-Power FDSOI Neural Circuits for Extreme-Edge Neuromorphic Intelligence
• A neuromorphic systems approach to in-memory computing with non-ideal memristive devices: From mitigation to exploitation

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