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Transient Responses to Rapid Changes in Mean and Variance in Spiking Models
The mean input and variance of the total synaptic input to a neuron can vary independently, suggesting two distinct information channels. Here we examine the impact of rapidly varying signals, delivered via these two information conduits, on the temporal dynamics of neuronal firing rate responses. W...
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Formato: | Texto |
Lenguaje: | English |
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Public Library of Science
2008
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Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC2582948/ https://www.ncbi.nlm.nih.gov/pubmed/19023442 http://dx.doi.org/10.1371/journal.pone.0003786 |
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author | Khorsand, Peyman Chance, Frances |
author_facet | Khorsand, Peyman Chance, Frances |
author_sort | Khorsand, Peyman |
collection | PubMed |
description | The mean input and variance of the total synaptic input to a neuron can vary independently, suggesting two distinct information channels. Here we examine the impact of rapidly varying signals, delivered via these two information conduits, on the temporal dynamics of neuronal firing rate responses. We examine the responses of model neurons to step functions in either the mean or the variance of the input current. Our results show that the temporal dynamics governing response onset depends on the choice of model. Specifically, the existence of a hard threshold introduces an instantaneous component into the response onset of a leaky-integrate-and-fire model that is not present in other models studied here. Other response features, for example a decaying oscillatory approach to a new steady-state firing rate, appear to be more universal among neuronal models. The decay time constant of this approach is a power-law function of noise magnitude over a wide range of input parameters. Understanding how specific model properties underlie these response features is important for understanding how neurons will respond to rapidly varying signals, as the temporal dynamics of the response onset and response decay to new steady-state determine what range of signal frequencies a population of neurons can respond to and faithfully encode. |
format | Text |
id | pubmed-2582948 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2008 |
publisher | Public Library of Science |
record_format | MEDLINE/PubMed |
spelling | pubmed-25829482008-11-21 Transient Responses to Rapid Changes in Mean and Variance in Spiking Models Khorsand, Peyman Chance, Frances PLoS One Research Article The mean input and variance of the total synaptic input to a neuron can vary independently, suggesting two distinct information channels. Here we examine the impact of rapidly varying signals, delivered via these two information conduits, on the temporal dynamics of neuronal firing rate responses. We examine the responses of model neurons to step functions in either the mean or the variance of the input current. Our results show that the temporal dynamics governing response onset depends on the choice of model. Specifically, the existence of a hard threshold introduces an instantaneous component into the response onset of a leaky-integrate-and-fire model that is not present in other models studied here. Other response features, for example a decaying oscillatory approach to a new steady-state firing rate, appear to be more universal among neuronal models. The decay time constant of this approach is a power-law function of noise magnitude over a wide range of input parameters. Understanding how specific model properties underlie these response features is important for understanding how neurons will respond to rapidly varying signals, as the temporal dynamics of the response onset and response decay to new steady-state determine what range of signal frequencies a population of neurons can respond to and faithfully encode. Public Library of Science 2008-11-21 /pmc/articles/PMC2582948/ /pubmed/19023442 http://dx.doi.org/10.1371/journal.pone.0003786 Text en Khorsand et al. http://creativecommons.org/licenses/by/4.0/ This is an open-access article distributed under the terms of the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original author and source are properly credited. |
spellingShingle | Research Article Khorsand, Peyman Chance, Frances Transient Responses to Rapid Changes in Mean and Variance in Spiking Models |
title | Transient Responses to Rapid Changes in Mean and Variance in Spiking Models |
title_full | Transient Responses to Rapid Changes in Mean and Variance in Spiking Models |
title_fullStr | Transient Responses to Rapid Changes in Mean and Variance in Spiking Models |
title_full_unstemmed | Transient Responses to Rapid Changes in Mean and Variance in Spiking Models |
title_short | Transient Responses to Rapid Changes in Mean and Variance in Spiking Models |
title_sort | transient responses to rapid changes in mean and variance in spiking models |
topic | Research Article |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC2582948/ https://www.ncbi.nlm.nih.gov/pubmed/19023442 http://dx.doi.org/10.1371/journal.pone.0003786 |
work_keys_str_mv | AT khorsandpeyman transientresponsestorapidchangesinmeanandvarianceinspikingmodels AT chancefrances transientresponsestorapidchangesinmeanandvarianceinspikingmodels |