An electronic neuromorphic system for real-time detection of high frequency oscillations (HFO) in intracranial EEG.
TLDR
In this article, the authors presented a neuromorphic system that combines a neural recording headstage with a spiking neural network (SNN) processing core on the same die for processing intracranial EEG (iEEG) from epilepsy patients for the detection of high frequency oscillations (HFO), which are a biomarker for epileptogenic brain tissue.Abstract:
The analysis of biomedical signals for clinical studies and therapeutic applications can benefit from embedded devices that can process these signals locally and in real-time An example is the analysis of intracranial EEG (iEEG) from epilepsy patients for the detection of High Frequency Oscillations (HFO), which are a biomarker for epileptogenic brain tissue Mixed-signal neuromorphic circuits offer the possibility of building compact and low-power neural network processing systems that can analyze data on-line in real-time Here we present a neuromorphic system that combines a neural recording headstage with a spiking neural network (SNN) processing core on the same die for processing iEEG, and show how it can reliably detect HFO, thereby achieving state-of-the-art accuracy, sensitivity, and specificity This is a first feasibility study towards identifying relevant features in iEEG in real-time using mixed-signal neuromorphic computing technologiesread more
Citations
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Neural interface systems with on-device computing: machine learning and neuromorphic architectures.
Jerald Yoo,Mahsa Shoaran +1 more
TL;DR: In this article, the authors reviewed the recent development of the "on-chip" machine learning and neuromorphic architectures, which is one of the key puzzles in devising next-generation clinically viable neural interface systems.
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A review of non-cognitive applications for neuromorphic computing
James B. Aimone,Prasanna Date,G. A. Fonseca Guerra,Kathleen E. Hamilton,Kyle G. Henke,Bill Kay,Garrett T. Kenyon,Shruti R. Kulkarni,Susan M. Mniszewski,Maryam Parsa,Sumedh R. Risbud,Catherine D. Schuman,William Severa,J. Darby Smith +13 more
TL;DR: The current state-of-the-art for non-cognitive applications on neuromorphic computers, including simple computational kernels for composition, graph algorithms, constrained optimization, and signal processing are reviewed.
Journal ArticleDOI
Generative Models of Brain Dynamics
Mahta Ramezanian-Panahi,German Abrevaya,Jean-Christophe Gagnon-Audet,Vikram Voleti,Irina Rish,Guillaume Dumas +5 more
TL;DR: This review article presents several hybrid generative models from recent literature in scientific machine learning, which can be efficiently deployed to yield interpretable models of neural dynamics.
Journal ArticleDOI
Blinded study: prospectively defined high-frequency oscillations predict seizure outcome in individual patients.
Vasileios Dimakopoulos,Pierre Mégevand,Ece Boran,Shahan Momjian,Margitta Seeck,Serge Vulliemoz,Johannes Sarnthein +6 more
TL;DR: In this article, an automated, prospective definition of clinically relevant high-frequency oscillations in intracranial EEG from Montreal and tested it in recordings from Zurich was developed and validated using an automated procedure to delineate the clinically relevant area in each individual patient of an independently recorded dataset.
Journal ArticleDOI
A neuromorphic spiking neural network detects epileptic high frequency oscillations in the scalp EEG
TL;DR: In this paper , a custom spike neural network (SNN) was designed to detect events of interest (EoI) in the 80-250 Hz ripple band and reject artifacts in the 500-900 Hz band.
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