Efficient information transfer by Poisson neurons

Recently, it has been suggested that certain neurons with Poissonianspiking statistics may communicate by discontinuously switchingbetween two levels of firing intensity. Such a situation resembles inmany ways the optimal information transmission protocol for thecontinuous-time Poisson channel known...

Full description

Saved in:
Bibliographic Details
Main Authors: Lubomir Kostal, Shigeru Shinomoto
Format: Article
Language:English
Published: AIMS Press 2015-12-01
Series:Mathematical Biosciences and Engineering
Subjects:
Online Access:https://www.aimspress.com/article/doi/10.3934/mbe.2016004
Tags: Add Tag
No Tags, Be the first to tag this record!
_version_ 1832590133244723200
author Lubomir Kostal
Shigeru Shinomoto
author_facet Lubomir Kostal
Shigeru Shinomoto
author_sort Lubomir Kostal
collection DOAJ
description Recently, it has been suggested that certain neurons with Poissonianspiking statistics may communicate by discontinuously switchingbetween two levels of firing intensity. Such a situation resembles inmany ways the optimal information transmission protocol for thecontinuous-time Poisson channel known from information theory. In thiscontribution we employ the classical information-theoretic results toanalyze the efficiency of such a transmission from differentperspectives, emphasising the neurobiological viewpoint. We addressboth the ultimate limits, in terms of the information capacity undermetabolic cost constraints, and the achievable bounds on performanceat rates below capacity with fixed decoding error probability. Indoing so we discuss optimal values of experimentally measurablequantities that can be compared with the actual neuronal recordings ina future effort.
format Article
id doaj-art-9a4b31f2b1c14a759d6b763a79069ae6
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-9a4b31f2b1c14a759d6b763a79069ae62025-01-24T02:35:23ZengAIMS PressMathematical Biosciences and Engineering1551-00182015-12-0113350952010.3934/mbe.2016004Efficient information transfer by Poisson neuronsLubomir Kostal0Shigeru Shinomoto1Institute of Physiology of the Czech Academy of Sciences, Videnska 1083, 14220 Prague 4Department of Physics, Graduate School of Science, Kyoto University, Sakyo-ku, Kyoto 606-8502Recently, it has been suggested that certain neurons with Poissonianspiking statistics may communicate by discontinuously switchingbetween two levels of firing intensity. Such a situation resembles inmany ways the optimal information transmission protocol for thecontinuous-time Poisson channel known from information theory. In thiscontribution we employ the classical information-theoretic results toanalyze the efficiency of such a transmission from differentperspectives, emphasising the neurobiological viewpoint. We addressboth the ultimate limits, in terms of the information capacity undermetabolic cost constraints, and the achievable bounds on performanceat rates below capacity with fixed decoding error probability. Indoing so we discuss optimal values of experimentally measurablequantities that can be compared with the actual neuronal recordings ina future effort.https://www.aimspress.com/article/doi/10.3934/mbe.2016004poisson neuroninformation capacitymetabolic costdecoding error.
spellingShingle Lubomir Kostal
Shigeru Shinomoto
Efficient information transfer by Poisson neurons
Mathematical Biosciences and Engineering
poisson neuron
information capacity
metabolic cost
decoding error.
title Efficient information transfer by Poisson neurons
title_full Efficient information transfer by Poisson neurons
title_fullStr Efficient information transfer by Poisson neurons
title_full_unstemmed Efficient information transfer by Poisson neurons
title_short Efficient information transfer by Poisson neurons
title_sort efficient information transfer by poisson neurons
topic poisson neuron
information capacity
metabolic cost
decoding error.
url https://www.aimspress.com/article/doi/10.3934/mbe.2016004
work_keys_str_mv AT lubomirkostal efficientinformationtransferbypoissonneurons
AT shigerushinomoto efficientinformationtransferbypoissonneurons