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.
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2021-05-01
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Series: | Nature Communications |
Online Access: | https://doi.org/10.1038/s41467-021-23342-2 |
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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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