Exact firing time statistics of neurons driven by discrete inhibitory noise
Abstract Neurons in the intact brain receive a continuous and irregular synaptic bombardment from excitatory and inhibitory pre- synaptic neurons, which determines the firing activity of the stimulated neuron. In order to investigate the influence of inhibitory stimulation on the firing time statist...
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Nature Portfolio
2017
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oai:doaj.org-article:6d77eb69e75847ef952f4c6e4a5df36d2021-12-02T16:07:58ZExact firing time statistics of neurons driven by discrete inhibitory noise10.1038/s41598-017-01658-82045-2322https://doaj.org/article/6d77eb69e75847ef952f4c6e4a5df36d2017-05-01T00:00:00Zhttps://doi.org/10.1038/s41598-017-01658-8https://doaj.org/toc/2045-2322Abstract Neurons in the intact brain receive a continuous and irregular synaptic bombardment from excitatory and inhibitory pre- synaptic neurons, which determines the firing activity of the stimulated neuron. In order to investigate the influence of inhibitory stimulation on the firing time statistics, we consider Leaky Integrate-and-Fire neurons subject to inhibitory instantaneous post- synaptic potentials. In particular, we report exact results for the firing rate, the coefficient of variation and the spike train spectrum for various synaptic weight distributions. Our results are not limited to stimulations of infinitesimal amplitude, but they apply as well to finite amplitude post-synaptic potentials, thus being able to capture the effect of rare and large spikes. The developed methods are able to reproduce also the average firing properties of heterogeneous neuronal populations.Simona OlmiDavid Angulo-GarciaAlberto ImparatoAlessandro TorciniNature PortfolioarticleMedicineRScienceQENScientific Reports, Vol 7, Iss 1, Pp 1-15 (2017) |
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Medicine R Science Q Simona Olmi David Angulo-Garcia Alberto Imparato Alessandro Torcini Exact firing time statistics of neurons driven by discrete inhibitory noise |
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Abstract Neurons in the intact brain receive a continuous and irregular synaptic bombardment from excitatory and inhibitory pre- synaptic neurons, which determines the firing activity of the stimulated neuron. In order to investigate the influence of inhibitory stimulation on the firing time statistics, we consider Leaky Integrate-and-Fire neurons subject to inhibitory instantaneous post- synaptic potentials. In particular, we report exact results for the firing rate, the coefficient of variation and the spike train spectrum for various synaptic weight distributions. Our results are not limited to stimulations of infinitesimal amplitude, but they apply as well to finite amplitude post-synaptic potentials, thus being able to capture the effect of rare and large spikes. The developed methods are able to reproduce also the average firing properties of heterogeneous neuronal populations. |
format |
article |
author |
Simona Olmi David Angulo-Garcia Alberto Imparato Alessandro Torcini |
author_facet |
Simona Olmi David Angulo-Garcia Alberto Imparato Alessandro Torcini |
author_sort |
Simona Olmi |
title |
Exact firing time statistics of neurons driven by discrete inhibitory noise |
title_short |
Exact firing time statistics of neurons driven by discrete inhibitory noise |
title_full |
Exact firing time statistics of neurons driven by discrete inhibitory noise |
title_fullStr |
Exact firing time statistics of neurons driven by discrete inhibitory noise |
title_full_unstemmed |
Exact firing time statistics of neurons driven by discrete inhibitory noise |
title_sort |
exact firing time statistics of neurons driven by discrete inhibitory noise |
publisher |
Nature Portfolio |
publishDate |
2017 |
url |
https://doaj.org/article/6d77eb69e75847ef952f4c6e4a5df36d |
work_keys_str_mv |
AT simonaolmi exactfiringtimestatisticsofneuronsdrivenbydiscreteinhibitorynoise AT davidangulogarcia exactfiringtimestatisticsofneuronsdrivenbydiscreteinhibitorynoise AT albertoimparato exactfiringtimestatisticsofneuronsdrivenbydiscreteinhibitorynoise AT alessandrotorcini exactfiringtimestatisticsofneuronsdrivenbydiscreteinhibitorynoise |
_version_ |
1718384662651338752 |