The influence of synaptic weight distribution on neuronal population dynamics.

The manner in which different distributions of synaptic weights onto cortical neurons shape their spiking activity remains open. To characterize a homogeneous neuronal population, we use the master equation for generalized leaky integrate-and-fire neurons with shot-noise synapses. We develop fast se...

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Autores principales:	Ramakrishnan Iyer, Vilas Menon, Michael Buice, Christof Koch, Stefan Mihalas
Formato:	article
Lenguaje:	EN
Publicado:	Public Library of Science (PLoS) 2013
Materias:	Biology (General) QH301-705.5
Acceso en línea:	https://doaj.org/article/7804ba7fc2c44fadb56d3609e4765000
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spelling	oai:doaj.org-article:7804ba7fc2c44fadb56d3609e47650002021-11-18T05:53:29ZThe influence of synaptic weight distribution on neuronal population dynamics.1553-734X1553-735810.1371/journal.pcbi.1003248https://doaj.org/article/7804ba7fc2c44fadb56d3609e47650002013-10-01T00:00:00Zhttps://www.ncbi.nlm.nih.gov/pmc/articles/pmid/24204219/?tool=EBIhttps://doaj.org/toc/1553-734Xhttps://doaj.org/toc/1553-7358The manner in which different distributions of synaptic weights onto cortical neurons shape their spiking activity remains open. To characterize a homogeneous neuronal population, we use the master equation for generalized leaky integrate-and-fire neurons with shot-noise synapses. We develop fast semi-analytic numerical methods to solve this equation for either current or conductance synapses, with and without synaptic depression. We show that its solutions match simulations of equivalent neuronal networks better than those of the Fokker-Planck equation and we compute bounds on the network response to non-instantaneous synapses. We apply these methods to study different synaptic weight distributions in feed-forward networks. We characterize the synaptic amplitude distributions using a set of measures, called tail weight numbers, designed to quantify the preponderance of very strong synapses. Even if synaptic amplitude distributions are equated for both the total current and average synaptic weight, distributions with sparse but strong synapses produce higher responses for small inputs, leading to a larger operating range. Furthermore, despite their small number, such synapses enable the network to respond faster and with more stability in the face of external fluctuations.Ramakrishnan IyerVilas MenonMichael BuiceChristof KochStefan MihalasPublic Library of Science (PLoS)articleBiology (General)QH301-705.5ENPLoS Computational Biology, Vol 9, Iss 10, p e1003248 (2013)
institution	DOAJ
collection	DOAJ
language	EN
topic	Biology (General) QH301-705.5
spellingShingle	Biology (General) QH301-705.5 Ramakrishnan Iyer Vilas Menon Michael Buice Christof Koch Stefan Mihalas The influence of synaptic weight distribution on neuronal population dynamics.
description	The manner in which different distributions of synaptic weights onto cortical neurons shape their spiking activity remains open. To characterize a homogeneous neuronal population, we use the master equation for generalized leaky integrate-and-fire neurons with shot-noise synapses. We develop fast semi-analytic numerical methods to solve this equation for either current or conductance synapses, with and without synaptic depression. We show that its solutions match simulations of equivalent neuronal networks better than those of the Fokker-Planck equation and we compute bounds on the network response to non-instantaneous synapses. We apply these methods to study different synaptic weight distributions in feed-forward networks. We characterize the synaptic amplitude distributions using a set of measures, called tail weight numbers, designed to quantify the preponderance of very strong synapses. Even if synaptic amplitude distributions are equated for both the total current and average synaptic weight, distributions with sparse but strong synapses produce higher responses for small inputs, leading to a larger operating range. Furthermore, despite their small number, such synapses enable the network to respond faster and with more stability in the face of external fluctuations.
format	article
author	Ramakrishnan Iyer Vilas Menon Michael Buice Christof Koch Stefan Mihalas
author_facet	Ramakrishnan Iyer Vilas Menon Michael Buice Christof Koch Stefan Mihalas
author_sort	Ramakrishnan Iyer
title	The influence of synaptic weight distribution on neuronal population dynamics.
title_short	The influence of synaptic weight distribution on neuronal population dynamics.
title_full	The influence of synaptic weight distribution on neuronal population dynamics.
title_fullStr	The influence of synaptic weight distribution on neuronal population dynamics.
title_full_unstemmed	The influence of synaptic weight distribution on neuronal population dynamics.
title_sort	influence of synaptic weight distribution on neuronal population dynamics.
publisher	Public Library of Science (PLoS)
publishDate	2013
url	https://doaj.org/article/7804ba7fc2c44fadb56d3609e4765000
work_keys_str_mv	AT ramakrishnaniyer theinfluenceofsynapticweightdistributiononneuronalpopulationdynamics AT vilasmenon theinfluenceofsynapticweightdistributiononneuronalpopulationdynamics AT michaelbuice theinfluenceofsynapticweightdistributiononneuronalpopulationdynamics AT christofkoch theinfluenceofsynapticweightdistributiononneuronalpopulationdynamics AT stefanmihalas theinfluenceofsynapticweightdistributiononneuronalpopulationdynamics AT ramakrishnaniyer influenceofsynapticweightdistributiononneuronalpopulationdynamics AT vilasmenon influenceofsynapticweightdistributiononneuronalpopulationdynamics AT michaelbuice influenceofsynapticweightdistributiononneuronalpopulationdynamics AT christofkoch influenceofsynapticweightdistributiononneuronalpopulationdynamics AT stefanmihalas influenceofsynapticweightdistributiononneuronalpopulationdynamics
_version_	1718424674280407040

The influence of synaptic weight distribution on neuronal population dynamics.

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