Discovering optimal features for neuron-type identification from extracellular recordings

Discovering optimal features for neuron-type identification from extracellular recordings

Advancements in multichannel recordings of single-unit activity (SUA) in vivo present an opportunity to discover novel features of spatially-varying extracellularly-recorded action potentials (EAPs) that are useful for identifying neuron-types. Traditional approaches to classifying neuron-types ofte...

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Bibliographic Details
Main Authors: Vergil R. Haynes, Yi Zhou, Sharon M. Crook
Format: Article
Language:English
Published: Frontiers Media S.A. 2024-02-01
Series:Frontiers in Neuroinformatics
Subjects:
extracellular action potentials
machine learning
neuron-type prediction
simulated EAP
neuron models
Online Access:https://www.frontiersin.org/articles/10.3389/fninf.2024.1303993/full

Internet

https://www.frontiersin.org/articles/10.3389/fninf.2024.1303993/full

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