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Large-scale biophysically detailed model of somatosensory thalamocortical circuits in NetPyNE

The primary somatosensory cortex (S1) of mammals is critically important in the perception of touch and related sensorimotor behaviors. In 2015, the Blue Brain Project (BBP) developed a groundbreaking rat S1 microcircuit simulation with over 31,000 neurons with 207 morpho-electrical neuron types, an...

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Autores principales: Borges, Fernando S., Moreira, Joao V. S., Takarabe, Lavinia M., Lytton, William W., Dura-Bernal, Salvador
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Frontiers Media S.A. 2022
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9536213/
https://www.ncbi.nlm.nih.gov/pubmed/36213546
http://dx.doi.org/10.3389/fninf.2022.884245
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author Borges, Fernando S.
Moreira, Joao V. S.
Takarabe, Lavinia M.
Lytton, William W.
Dura-Bernal, Salvador
author_facet Borges, Fernando S.
Moreira, Joao V. S.
Takarabe, Lavinia M.
Lytton, William W.
Dura-Bernal, Salvador
author_sort Borges, Fernando S.
collection PubMed
description The primary somatosensory cortex (S1) of mammals is critically important in the perception of touch and related sensorimotor behaviors. In 2015, the Blue Brain Project (BBP) developed a groundbreaking rat S1 microcircuit simulation with over 31,000 neurons with 207 morpho-electrical neuron types, and 37 million synapses, incorporating anatomical and physiological information from a wide range of experimental studies. We have implemented this highly detailed and complex S1 model in NetPyNE, using the data available in the Neocortical Microcircuit Collaboration Portal. NetPyNE provides a Python high-level interface to NEURON and allows defining complicated multiscale models using an intuitive declarative standardized language. It also facilitates running parallel simulations, automates the optimization and exploration of parameters using supercomputers, and provides a wide range of built-in analysis functions. This will make the S1 model more accessible and simpler to scale, modify and extend in order to explore research questions or interconnect to other existing models. Despite some implementation differences, the NetPyNE model preserved the original cell morphologies, electrophysiological responses and spatial distribution for all 207 cell types; and the connectivity properties of all 1941 pathways, including synaptic dynamics and short-term plasticity (STP). The NetPyNE S1 simulations produced reasonable physiological firing rates and activity patterns across all populations. When STP was included, the network generated a 1 Hz oscillation comparable to the original model in vitro-like state. By then reducing the extracellular calcium concentration, the model reproduced the original S1 in vivo-like states with asynchronous activity. These results validate the original study using a new modeling tool. Simulated local field potentials (LFPs) exhibited realistic oscillatory patterns and features, including distance- and frequency-dependent attenuation. The model was extended by adding thalamic circuits, including 6 distinct thalamic populations with intrathalamic, thalamocortical (TC) and corticothalamic connectivity derived from experimental data. The thalamic model reproduced single known cell and circuit-level dynamics, including burst and tonic firing modes and oscillatory patterns, providing a more realistic input to cortex and enabling study of TC interactions. Overall, our work provides a widely accessible, data-driven and biophysically-detailed model of the somatosensory TC circuits that can be employed as a community tool for researchers to study neural dynamics, function and disease.
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spelling pubmed-95362132022-10-07 Large-scale biophysically detailed model of somatosensory thalamocortical circuits in NetPyNE Borges, Fernando S. Moreira, Joao V. S. Takarabe, Lavinia M. Lytton, William W. Dura-Bernal, Salvador Front Neuroinform Neuroscience The primary somatosensory cortex (S1) of mammals is critically important in the perception of touch and related sensorimotor behaviors. In 2015, the Blue Brain Project (BBP) developed a groundbreaking rat S1 microcircuit simulation with over 31,000 neurons with 207 morpho-electrical neuron types, and 37 million synapses, incorporating anatomical and physiological information from a wide range of experimental studies. We have implemented this highly detailed and complex S1 model in NetPyNE, using the data available in the Neocortical Microcircuit Collaboration Portal. NetPyNE provides a Python high-level interface to NEURON and allows defining complicated multiscale models using an intuitive declarative standardized language. It also facilitates running parallel simulations, automates the optimization and exploration of parameters using supercomputers, and provides a wide range of built-in analysis functions. This will make the S1 model more accessible and simpler to scale, modify and extend in order to explore research questions or interconnect to other existing models. Despite some implementation differences, the NetPyNE model preserved the original cell morphologies, electrophysiological responses and spatial distribution for all 207 cell types; and the connectivity properties of all 1941 pathways, including synaptic dynamics and short-term plasticity (STP). The NetPyNE S1 simulations produced reasonable physiological firing rates and activity patterns across all populations. When STP was included, the network generated a 1 Hz oscillation comparable to the original model in vitro-like state. By then reducing the extracellular calcium concentration, the model reproduced the original S1 in vivo-like states with asynchronous activity. These results validate the original study using a new modeling tool. Simulated local field potentials (LFPs) exhibited realistic oscillatory patterns and features, including distance- and frequency-dependent attenuation. The model was extended by adding thalamic circuits, including 6 distinct thalamic populations with intrathalamic, thalamocortical (TC) and corticothalamic connectivity derived from experimental data. The thalamic model reproduced single known cell and circuit-level dynamics, including burst and tonic firing modes and oscillatory patterns, providing a more realistic input to cortex and enabling study of TC interactions. Overall, our work provides a widely accessible, data-driven and biophysically-detailed model of the somatosensory TC circuits that can be employed as a community tool for researchers to study neural dynamics, function and disease. Frontiers Media S.A. 2022-09-22 /pmc/articles/PMC9536213/ /pubmed/36213546 http://dx.doi.org/10.3389/fninf.2022.884245 Text en Copyright © 2022 Borges, Moreira, Takarabe, Lytton and Dura-Bernal. https://creativecommons.org/licenses/by/4.0/This is an open-access article distributed under the terms of the Creative Commons Attribution License (CC BY). The use, distribution or reproduction in other forums is permitted, provided the original author(s) and the copyright owner(s) are credited and that the original publication in this journal is cited, in accordance with accepted academic practice. No use, distribution or reproduction is permitted which does not comply with these terms.
spellingShingle Neuroscience
Borges, Fernando S.
Moreira, Joao V. S.
Takarabe, Lavinia M.
Lytton, William W.
Dura-Bernal, Salvador
Large-scale biophysically detailed model of somatosensory thalamocortical circuits in NetPyNE
title Large-scale biophysically detailed model of somatosensory thalamocortical circuits in NetPyNE
title_full Large-scale biophysically detailed model of somatosensory thalamocortical circuits in NetPyNE
title_fullStr Large-scale biophysically detailed model of somatosensory thalamocortical circuits in NetPyNE
title_full_unstemmed Large-scale biophysically detailed model of somatosensory thalamocortical circuits in NetPyNE
title_short Large-scale biophysically detailed model of somatosensory thalamocortical circuits in NetPyNE
title_sort large-scale biophysically detailed model of somatosensory thalamocortical circuits in netpyne
topic Neuroscience
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9536213/
https://www.ncbi.nlm.nih.gov/pubmed/36213546
http://dx.doi.org/10.3389/fninf.2022.884245
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