Removing Noise from Extracellular Neural Recordings Using Fully Convolutional Denoising Autoencoders

Extracellular recordings are severely contaminated by a considerable amount of noise sources, rendering the denoising process an extremely challenging task that should be tackled for efficient spike sorting. To this end, we propose an end-to-end deep learning approach to the problem, utilizing a Ful...

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Bibliographic Details

Published in:	2021 43rd Annual International Conference of the IEEE Engineering in Medicine and Biology Society (EMBC) Vol. 2021; pp. 890 - 893
Main Authors:	Kechris, Christodoulos, Delitzas, Alexandros, Matsoukas, Vasileios, Petrantonakis, Panagiotis C.
Format:	Conference Proceeding Journal Article
Language:	English
Published:	United States IEEE 01.11.2021
Subjects:	Brain modeling Cell Movement Convolution Discrete wavelet transforms Extracellular Neural Networks, Computer Noise Noise measurement Noise reduction Protein Transport Signal-To-Noise Ratio Task analysis
ISSN:	2694-0604, 2694-0604
Online Access:	Get full text
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