Partial information decomposition reveals that synergistic neural integration is greater downstream of recurrent information flow in organotypic cortical cultures.

The directionality of network information flow dictates how networks process information. A central component of information processing in both biological and artificial neural networks is their ability to perform synergistic integration-a type of computation. We established previously that synergis...

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Autores principales:	Samantha P Sherrill, Nicholas M Timme, John M Beggs, Ehren L Newman
Formato:	article
Lenguaje:	EN
Publicado:	Public Library of Science (PLoS) 2021
Materias:	Biology (General) QH301-705.5
Acceso en línea:	https://doaj.org/article/e3b7e366579b44e48b67202091c819c6
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spelling	oai:doaj.org-article:e3b7e366579b44e48b67202091c819c62021-12-02T19:57:24ZPartial information decomposition reveals that synergistic neural integration is greater downstream of recurrent information flow in organotypic cortical cultures.1553-734X1553-735810.1371/journal.pcbi.1009196https://doaj.org/article/e3b7e366579b44e48b67202091c819c62021-07-01T00:00:00Zhttps://doi.org/10.1371/journal.pcbi.1009196https://doaj.org/toc/1553-734Xhttps://doaj.org/toc/1553-7358The directionality of network information flow dictates how networks process information. A central component of information processing in both biological and artificial neural networks is their ability to perform synergistic integration-a type of computation. We established previously that synergistic integration varies directly with the strength of feedforward information flow. However, the relationships between both recurrent and feedback information flow and synergistic integration remain unknown. To address this, we analyzed the spiking activity of hundreds of neurons in organotypic cultures of mouse cortex. We asked how empirically observed synergistic integration-determined from partial information decomposition-varied with local functional network structure that was categorized into motifs with varying recurrent and feedback information flow. We found that synergistic integration was elevated in motifs with greater recurrent information flow beyond that expected from the local feedforward information flow. Feedback information flow was interrelated with feedforward information flow and was associated with decreased synergistic integration. Our results indicate that synergistic integration is distinctly influenced by the directionality of local information flow.Samantha P SherrillNicholas M TimmeJohn M BeggsEhren L NewmanPublic Library of Science (PLoS)articleBiology (General)QH301-705.5ENPLoS Computational Biology, Vol 17, Iss 7, p e1009196 (2021)
institution	DOAJ
collection	DOAJ
language	EN
topic	Biology (General) QH301-705.5
spellingShingle	Biology (General) QH301-705.5 Samantha P Sherrill Nicholas M Timme John M Beggs Ehren L Newman Partial information decomposition reveals that synergistic neural integration is greater downstream of recurrent information flow in organotypic cortical cultures.
description	The directionality of network information flow dictates how networks process information. A central component of information processing in both biological and artificial neural networks is their ability to perform synergistic integration-a type of computation. We established previously that synergistic integration varies directly with the strength of feedforward information flow. However, the relationships between both recurrent and feedback information flow and synergistic integration remain unknown. To address this, we analyzed the spiking activity of hundreds of neurons in organotypic cultures of mouse cortex. We asked how empirically observed synergistic integration-determined from partial information decomposition-varied with local functional network structure that was categorized into motifs with varying recurrent and feedback information flow. We found that synergistic integration was elevated in motifs with greater recurrent information flow beyond that expected from the local feedforward information flow. Feedback information flow was interrelated with feedforward information flow and was associated with decreased synergistic integration. Our results indicate that synergistic integration is distinctly influenced by the directionality of local information flow.
format	article
author	Samantha P Sherrill Nicholas M Timme John M Beggs Ehren L Newman
author_facet	Samantha P Sherrill Nicholas M Timme John M Beggs Ehren L Newman
author_sort	Samantha P Sherrill
title	Partial information decomposition reveals that synergistic neural integration is greater downstream of recurrent information flow in organotypic cortical cultures.
title_short	Partial information decomposition reveals that synergistic neural integration is greater downstream of recurrent information flow in organotypic cortical cultures.
title_full	Partial information decomposition reveals that synergistic neural integration is greater downstream of recurrent information flow in organotypic cortical cultures.
title_fullStr	Partial information decomposition reveals that synergistic neural integration is greater downstream of recurrent information flow in organotypic cortical cultures.
title_full_unstemmed	Partial information decomposition reveals that synergistic neural integration is greater downstream of recurrent information flow in organotypic cortical cultures.
title_sort	partial information decomposition reveals that synergistic neural integration is greater downstream of recurrent information flow in organotypic cortical cultures.
publisher	Public Library of Science (PLoS)
publishDate	2021
url	https://doaj.org/article/e3b7e366579b44e48b67202091c819c6
work_keys_str_mv	AT samanthapsherrill partialinformationdecompositionrevealsthatsynergisticneuralintegrationisgreaterdownstreamofrecurrentinformationflowinorganotypiccorticalcultures AT nicholasmtimme partialinformationdecompositionrevealsthatsynergisticneuralintegrationisgreaterdownstreamofrecurrentinformationflowinorganotypiccorticalcultures AT johnmbeggs partialinformationdecompositionrevealsthatsynergisticneuralintegrationisgreaterdownstreamofrecurrentinformationflowinorganotypiccorticalcultures AT ehrenlnewman partialinformationdecompositionrevealsthatsynergisticneuralintegrationisgreaterdownstreamofrecurrentinformationflowinorganotypiccorticalcultures
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Partial information decomposition reveals that synergistic neural integration is greater downstream of recurrent information flow in organotypic cortical cultures.

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