An electronic neuromorphic system for real-time detection of high frequency oscillations (HFO) in intracranial EEG

A major challenge across a variety of fields is how to process the vast quantities of data produced by sensors without large computation resources. Here, the authors present a neuromorphic chip which can detect a relevant signature of epileptogenic tissue from intracranial recordings in patients.

Bibliographic Details
Main Authors: Mohammadali Sharifshazileh, Karla Burelo, Johannes Sarnthein, Giacomo Indiveri
Format: Article
Language:English
Published: Nature Publishing Group 2021-05-01
Series:Nature Communications
Online Access:https://doi.org/10.1038/s41467-021-23342-2
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spelling doaj-a3cfb68b64334917b81d3f7c9301c80a2021-05-30T11:15:18ZengNature Publishing GroupNature Communications2041-17232021-05-0112111410.1038/s41467-021-23342-2An electronic neuromorphic system for real-time detection of high frequency oscillations (HFO) in intracranial EEGMohammadali Sharifshazileh0Karla Burelo1Johannes Sarnthein2Giacomo Indiveri3Institute of Neuroinformatics, University of Zurich and ETH ZurichInstitute of Neuroinformatics, University of Zurich and ETH ZurichDepartment of Neurosurgery, University Hospital Zurich, University of ZurichInstitute of Neuroinformatics, University of Zurich and ETH ZurichA major challenge across a variety of fields is how to process the vast quantities of data produced by sensors without large computation resources. Here, the authors present a neuromorphic chip which can detect a relevant signature of epileptogenic tissue from intracranial recordings in patients.https://doi.org/10.1038/s41467-021-23342-2
collection DOAJ
language English
format Article
sources DOAJ
author Mohammadali Sharifshazileh
Karla Burelo
Johannes Sarnthein
Giacomo Indiveri
spellingShingle Mohammadali Sharifshazileh
Karla Burelo
Johannes Sarnthein
Giacomo Indiveri
An electronic neuromorphic system for real-time detection of high frequency oscillations (HFO) in intracranial EEG
Nature Communications
author_facet Mohammadali Sharifshazileh
Karla Burelo
Johannes Sarnthein
Giacomo Indiveri
author_sort Mohammadali Sharifshazileh
title An electronic neuromorphic system for real-time detection of high frequency oscillations (HFO) in intracranial EEG
title_short An electronic neuromorphic system for real-time detection of high frequency oscillations (HFO) in intracranial EEG
title_full An electronic neuromorphic system for real-time detection of high frequency oscillations (HFO) in intracranial EEG
title_fullStr An electronic neuromorphic system for real-time detection of high frequency oscillations (HFO) in intracranial EEG
title_full_unstemmed An electronic neuromorphic system for real-time detection of high frequency oscillations (HFO) in intracranial EEG
title_sort electronic neuromorphic system for real-time detection of high frequency oscillations (hfo) in intracranial eeg
publisher Nature Publishing Group
series Nature Communications
issn 2041-1723
publishDate 2021-05-01
description A major challenge across a variety of fields is how to process the vast quantities of data produced by sensors without large computation resources. Here, the authors present a neuromorphic chip which can detect a relevant signature of epileptogenic tissue from intracranial recordings in patients.
url https://doi.org/10.1038/s41467-021-23342-2
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