Agent-based modeling of the central amygdala and pain using cell-type specific physiological parameters.

The amygdala is a brain area involved in emotional regulation and pain. Over the course of the last 20 years, multiple researchers have studied sensory and motor connections within the amygdala in trying to understand the ultimate role of this structure in pain perception and descending control of p...

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Autores principales:	Rachael Miller Neilan, Gabrielle Majetic, Mauricio Gil-Silva, Anisha P Adke, Yarimar Carrasquillo, Benedict J Kolber
Formato:	article
Lenguaje:	EN
Publicado:	Public Library of Science (PLoS) 2021
Materias:	Biology (General) QH301-705.5
Acceso en línea:	https://doaj.org/article/61ff53f23f314d5faef5327955c98d51
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spelling	oai:doaj.org-article:61ff53f23f314d5faef5327955c98d512021-11-25T05:40:37ZAgent-based modeling of the central amygdala and pain using cell-type specific physiological parameters.1553-734X1553-735810.1371/journal.pcbi.1009097https://doaj.org/article/61ff53f23f314d5faef5327955c98d512021-06-01T00:00:00Zhttps://doi.org/10.1371/journal.pcbi.1009097https://doaj.org/toc/1553-734Xhttps://doaj.org/toc/1553-7358The amygdala is a brain area involved in emotional regulation and pain. Over the course of the last 20 years, multiple researchers have studied sensory and motor connections within the amygdala in trying to understand the ultimate role of this structure in pain perception and descending control of pain. A number of investigators have been using cell-type specific manipulations to probe the underlying circuitry of the amygdala. As data have accumulated in this research space, we recognized a critical need for a single framework to integrate these data and evaluate emergent system-level responses. In this manuscript, we present an agent-based computational model of two distinct inhibitory neuron populations in the amygdala, those that express protein kinase C delta (PKCδ) and those that express somatostatin (SOM). We utilized a network of neural links to simulate connectivity and the transmission of inhibitory signals between neurons. Type-specific parameters describing the response of these neurons to noxious stimuli were estimated from published physiological and immunological data as well as our own wet-lab experiments. The model outputs an abstract measure of pain, which is calculated in terms of the cumulative pro-nociceptive and anti-nociceptive activity across neurons in both hemispheres of the amygdala. Results demonstrate the ability of the model to produce changes in pain that are consistent with published studies and highlight the importance of several model parameters. In particular, we found that the relative proportion of PKCδ and SOM neurons within each hemisphere is a key parameter in predicting pain and we explored model predictions for three possible values of this parameter. We compared model predictions of pain to data from our earlier behavioral studies and found areas of similarity as well as distinctions between the data sets. These differences, in particular, suggest a number of wet-lab experiments that could be done in the future.Rachael Miller NeilanGabrielle MajeticMauricio Gil-SilvaAnisha P AdkeYarimar CarrasquilloBenedict J KolberPublic Library of Science (PLoS)articleBiology (General)QH301-705.5ENPLoS Computational Biology, Vol 17, Iss 6, p e1009097 (2021)
institution	DOAJ
collection	DOAJ
language	EN
topic	Biology (General) QH301-705.5
spellingShingle	Biology (General) QH301-705.5 Rachael Miller Neilan Gabrielle Majetic Mauricio Gil-Silva Anisha P Adke Yarimar Carrasquillo Benedict J Kolber Agent-based modeling of the central amygdala and pain using cell-type specific physiological parameters.
description	The amygdala is a brain area involved in emotional regulation and pain. Over the course of the last 20 years, multiple researchers have studied sensory and motor connections within the amygdala in trying to understand the ultimate role of this structure in pain perception and descending control of pain. A number of investigators have been using cell-type specific manipulations to probe the underlying circuitry of the amygdala. As data have accumulated in this research space, we recognized a critical need for a single framework to integrate these data and evaluate emergent system-level responses. In this manuscript, we present an agent-based computational model of two distinct inhibitory neuron populations in the amygdala, those that express protein kinase C delta (PKCδ) and those that express somatostatin (SOM). We utilized a network of neural links to simulate connectivity and the transmission of inhibitory signals between neurons. Type-specific parameters describing the response of these neurons to noxious stimuli were estimated from published physiological and immunological data as well as our own wet-lab experiments. The model outputs an abstract measure of pain, which is calculated in terms of the cumulative pro-nociceptive and anti-nociceptive activity across neurons in both hemispheres of the amygdala. Results demonstrate the ability of the model to produce changes in pain that are consistent with published studies and highlight the importance of several model parameters. In particular, we found that the relative proportion of PKCδ and SOM neurons within each hemisphere is a key parameter in predicting pain and we explored model predictions for three possible values of this parameter. We compared model predictions of pain to data from our earlier behavioral studies and found areas of similarity as well as distinctions between the data sets. These differences, in particular, suggest a number of wet-lab experiments that could be done in the future.
format	article
author	Rachael Miller Neilan Gabrielle Majetic Mauricio Gil-Silva Anisha P Adke Yarimar Carrasquillo Benedict J Kolber
author_facet	Rachael Miller Neilan Gabrielle Majetic Mauricio Gil-Silva Anisha P Adke Yarimar Carrasquillo Benedict J Kolber
author_sort	Rachael Miller Neilan
title	Agent-based modeling of the central amygdala and pain using cell-type specific physiological parameters.
title_short	Agent-based modeling of the central amygdala and pain using cell-type specific physiological parameters.
title_full	Agent-based modeling of the central amygdala and pain using cell-type specific physiological parameters.
title_fullStr	Agent-based modeling of the central amygdala and pain using cell-type specific physiological parameters.
title_full_unstemmed	Agent-based modeling of the central amygdala and pain using cell-type specific physiological parameters.
title_sort	agent-based modeling of the central amygdala and pain using cell-type specific physiological parameters.
publisher	Public Library of Science (PLoS)
publishDate	2021
url	https://doaj.org/article/61ff53f23f314d5faef5327955c98d51
work_keys_str_mv	AT rachaelmillerneilan agentbasedmodelingofthecentralamygdalaandpainusingcelltypespecificphysiologicalparameters AT gabriellemajetic agentbasedmodelingofthecentralamygdalaandpainusingcelltypespecificphysiologicalparameters AT mauriciogilsilva agentbasedmodelingofthecentralamygdalaandpainusingcelltypespecificphysiologicalparameters AT anishapadke agentbasedmodelingofthecentralamygdalaandpainusingcelltypespecificphysiologicalparameters AT yarimarcarrasquillo agentbasedmodelingofthecentralamygdalaandpainusingcelltypespecificphysiologicalparameters AT benedictjkolber agentbasedmodelingofthecentralamygdalaandpainusingcelltypespecificphysiologicalparameters
_version_	1718414519646027776

Agent-based modeling of the central amygdala and pain using cell-type specific physiological parameters.

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