Scalable and accurate method for neuronal ensemble detection in spiking neural networks

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dc.contributor.authorHerzog, Rubén
dc.contributor.authorMorales, Arturo
dc.contributor.authorMora, Soraya
dc.contributor.authorAraya, Joaquín
dc.contributor.authorEscobar, María-José
dc.contributor.authorPalacios, Adrian G.
dc.contributor.authorCofré, Rodrigo
dc.date.accessioned2022-11-30T02:46:26Z
dc.date.available2022-11-30T02:46:26Z
dc.date.issued2021
dc.description.abstractWe propose a novel, scalable, and accurate method for detecting neuronal ensembles from a population of spiking neurons. Our approach offers a simple yet powerful tool to study ensemble activity. It relies on clustering synchronous population activity (population vectors), allows the participation of neurons in different ensembles, has few parameters to tune and is computationally efficient. To validate the performance and generality of our method, we generated synthetic data, where we found that our method accurately detects neuronal ensembles for a wide range of simulation parameters. We found that our method outperforms current alternative methodologies. We used spike trains of retinal ganglion cells obtained from multi-electrode array recordings under a simple ON-OFF light stimulus to test our method. We found a consistent stimuli-evoked ensemble activity intermingled with spontaneously active ensembles and irregular activity. Our results suggest that the early visual system activity could be organized in distinguishable functional ensembles. We provide a Graphic User Interface, which facilitates the use of our method by the scientific community.en_ES
dc.facultadFacultad de Cienciasen_ES
dc.file.nameHerzo_Sca2021.pdf
dc.identifier.citationHerzog R, Morales A, Mora S, Araya J, Escobar M-J, Palacios AG, et al. (2021) Scalable and accurate method for neuronal ensemble detection in spiking neural networks. PLoS ONE 16(7): e0251647. https://doi.org/10.1371/journal. pone.0251647en_ES
dc.identifier.doihttps://doi.org/10.1371/journal.pone.0251647
dc.identifier.urihttp://repositoriobibliotecas.uv.cl/handle/uvscl/7372
dc.languageen
dc.publisherPlos
dc.rightsCopyright: © 2021 Herzog et al. This is an open access article distributed under the terms of the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original author and source are credited.
dc.sourcePlos One
dc.subjectNEURONSen_ES
dc.subjectRETINAL GANGLION CELLSen_ES
dc.subjectPRINCIPAL COMPONENT ANALYSISen_ES
dc.subjectNEURONAL TUNINGen_ES
dc.subjectACTION POTENTIALSen_ES
dc.subjectPROBABILITY DENSITYen_ES
dc.subjectALGORITHMSen_ES
dc.subjectVISIONen_ES
dc.titleScalable and accurate method for neuronal ensemble detection in spiking neural networks
dc.typeArticulo
uv.departamentoCentro Interdisciplinario de Neurociencia de Valparaiso

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