Fluctuation scaling in neural spike trains
Fluctuation scaling has been observed universally in a wide variety of phenomena. In time series that describe sequences of events, fluctuation scaling is expressed as power function relationships between the mean and variance of either inter-event intervals or counting statistics, depending on meas...
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AIMS Press
2015-12-01
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Online Access: | https://www.aimspress.com/article/doi/10.3934/mbe.2016006 |
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author | Shinsuke Koyama Ryota Kobayashi |
author_facet | Shinsuke Koyama Ryota Kobayashi |
author_sort | Shinsuke Koyama |
collection | DOAJ |
description | Fluctuation scaling has been observed universally in a wide variety of phenomena. In time series that describe sequences of events, fluctuation scaling is expressed as power function relationships between the mean and variance of either inter-event intervals or counting statistics, depending on measurement variables. In this article, fluctuation scaling has been formulated for a series of events in which scaling laws in the inter-event intervals and counting statistics were related. We have considered the first-passage time of an Ornstein-Uhlenbeck process and used a conductance-based neuron model with excitatory and inhibitory synaptic inputs to demonstrate the emergence of fluctuation scaling with various exponents, depending on the input regimes and the ratio between excitation and inhibition. Furthermore, we have discussed the possible implication of these results in the context of neural coding. |
format | Article |
id | doaj-art-6ca27e22bb904354944906c4c539022d |
institution | Kabale University |
issn | 1551-0018 |
language | English |
publishDate | 2015-12-01 |
publisher | AIMS Press |
record_format | Article |
series | Mathematical Biosciences and Engineering |
spelling | doaj-art-6ca27e22bb904354944906c4c539022d2025-01-24T02:35:23ZengAIMS PressMathematical Biosciences and Engineering1551-00182015-12-0113353755010.3934/mbe.2016006Fluctuation scaling in neural spike trainsShinsuke Koyama0Ryota Kobayashi1Department of Statistical Modeling, The Institute of Statistical Mathematics, 10-3 Midoricho, Tachikawa, TokyoPrinciples of Informatics Research Division, National Institute of Informatics, 2-1-2 Hitotsubashi, Chiyoda-ku, TokyoFluctuation scaling has been observed universally in a wide variety of phenomena. In time series that describe sequences of events, fluctuation scaling is expressed as power function relationships between the mean and variance of either inter-event intervals or counting statistics, depending on measurement variables. In this article, fluctuation scaling has been formulated for a series of events in which scaling laws in the inter-event intervals and counting statistics were related. We have considered the first-passage time of an Ornstein-Uhlenbeck process and used a conductance-based neuron model with excitatory and inhibitory synaptic inputs to demonstrate the emergence of fluctuation scaling with various exponents, depending on the input regimes and the ratio between excitation and inhibition. Furthermore, we have discussed the possible implication of these results in the context of neural coding.https://www.aimspress.com/article/doi/10.3934/mbe.2016006single neuron models.first-passage timeornstein-uhlenbeck processspike train statisticsneural coding |
spellingShingle | Shinsuke Koyama Ryota Kobayashi Fluctuation scaling in neural spike trains Mathematical Biosciences and Engineering single neuron models. first-passage time ornstein-uhlenbeck process spike train statistics neural coding |
title | Fluctuation scaling in neural spike trains |
title_full | Fluctuation scaling in neural spike trains |
title_fullStr | Fluctuation scaling in neural spike trains |
title_full_unstemmed | Fluctuation scaling in neural spike trains |
title_short | Fluctuation scaling in neural spike trains |
title_sort | fluctuation scaling in neural spike trains |
topic | single neuron models. first-passage time ornstein-uhlenbeck process spike train statistics neural coding |
url | https://www.aimspress.com/article/doi/10.3934/mbe.2016006 |
work_keys_str_mv | AT shinsukekoyama fluctuationscalinginneuralspiketrains AT ryotakobayashi fluctuationscalinginneuralspiketrains |