Encoding of spatio-temporal input characteristics by a CA1 pyramidal neuron model.

The in vivo activity of CA1 pyramidal neurons alternates between regular spiking and bursting, but how these changes affect information processing remains unclear. Using a detailed CA1 pyramidal neuron model, we investigate how timing and spatial arrangement variations in synaptic inputs to the dist...

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Autores principales:	Eleftheria Kyriaki Pissadaki, Kyriaki Sidiropoulou, Martin Reczko, Panayiota Poirazi
Formato:	article
Lenguaje:	EN
Publicado:	Public Library of Science (PLoS) 2010
Materias:	Biology (General) QH301-705.5
Acceso en línea:	https://doaj.org/article/5e7d4bb26ae54a6babffa294beb3e6dd
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spelling	oai:doaj.org-article:5e7d4bb26ae54a6babffa294beb3e6dd2021-11-18T05:50:49ZEncoding of spatio-temporal input characteristics by a CA1 pyramidal neuron model.1553-734X1553-735810.1371/journal.pcbi.1001038https://doaj.org/article/5e7d4bb26ae54a6babffa294beb3e6dd2010-12-01T00:00:00Zhttps://www.ncbi.nlm.nih.gov/pmc/articles/pmid/21187899/?tool=EBIhttps://doaj.org/toc/1553-734Xhttps://doaj.org/toc/1553-7358The in vivo activity of CA1 pyramidal neurons alternates between regular spiking and bursting, but how these changes affect information processing remains unclear. Using a detailed CA1 pyramidal neuron model, we investigate how timing and spatial arrangement variations in synaptic inputs to the distal and proximal dendritic layers influence the information content of model responses. We find that the temporal delay between activation of the two layers acts as a switch between excitability modes: short delays induce bursting while long delays decrease firing. For long delays, the average firing frequency of the model response discriminates spatially clustered from diffused inputs to the distal dendritic tree. For short delays, the onset latency and inter-spike-interval succession of model responses can accurately classify input signals as temporally close or distant and spatially clustered or diffused across different stimulation protocols. These findings suggest that a CA1 pyramidal neuron may be capable of encoding and transmitting presynaptic spatiotemporal information about the activity of the entorhinal cortex-hippocampal network to higher brain regions via the selective use of either a temporal or a rate code.Eleftheria Kyriaki PissadakiKyriaki SidiropoulouMartin ReczkoPanayiota PoiraziPublic Library of Science (PLoS)articleBiology (General)QH301-705.5ENPLoS Computational Biology, Vol 6, Iss 12, p e1001038 (2010)
institution	DOAJ
collection	DOAJ
language	EN
topic	Biology (General) QH301-705.5
spellingShingle	Biology (General) QH301-705.5 Eleftheria Kyriaki Pissadaki Kyriaki Sidiropoulou Martin Reczko Panayiota Poirazi Encoding of spatio-temporal input characteristics by a CA1 pyramidal neuron model.
description	The in vivo activity of CA1 pyramidal neurons alternates between regular spiking and bursting, but how these changes affect information processing remains unclear. Using a detailed CA1 pyramidal neuron model, we investigate how timing and spatial arrangement variations in synaptic inputs to the distal and proximal dendritic layers influence the information content of model responses. We find that the temporal delay between activation of the two layers acts as a switch between excitability modes: short delays induce bursting while long delays decrease firing. For long delays, the average firing frequency of the model response discriminates spatially clustered from diffused inputs to the distal dendritic tree. For short delays, the onset latency and inter-spike-interval succession of model responses can accurately classify input signals as temporally close or distant and spatially clustered or diffused across different stimulation protocols. These findings suggest that a CA1 pyramidal neuron may be capable of encoding and transmitting presynaptic spatiotemporal information about the activity of the entorhinal cortex-hippocampal network to higher brain regions via the selective use of either a temporal or a rate code.
format	article
author	Eleftheria Kyriaki Pissadaki Kyriaki Sidiropoulou Martin Reczko Panayiota Poirazi
author_facet	Eleftheria Kyriaki Pissadaki Kyriaki Sidiropoulou Martin Reczko Panayiota Poirazi
author_sort	Eleftheria Kyriaki Pissadaki
title	Encoding of spatio-temporal input characteristics by a CA1 pyramidal neuron model.
title_short	Encoding of spatio-temporal input characteristics by a CA1 pyramidal neuron model.
title_full	Encoding of spatio-temporal input characteristics by a CA1 pyramidal neuron model.
title_fullStr	Encoding of spatio-temporal input characteristics by a CA1 pyramidal neuron model.
title_full_unstemmed	Encoding of spatio-temporal input characteristics by a CA1 pyramidal neuron model.
title_sort	encoding of spatio-temporal input characteristics by a ca1 pyramidal neuron model.
publisher	Public Library of Science (PLoS)
publishDate	2010
url	https://doaj.org/article/5e7d4bb26ae54a6babffa294beb3e6dd
work_keys_str_mv	AT eleftheriakyriakipissadaki encodingofspatiotemporalinputcharacteristicsbyaca1pyramidalneuronmodel AT kyriakisidiropoulou encodingofspatiotemporalinputcharacteristicsbyaca1pyramidalneuronmodel AT martinreczko encodingofspatiotemporalinputcharacteristicsbyaca1pyramidalneuronmodel AT panayiotapoirazi encodingofspatiotemporalinputcharacteristicsbyaca1pyramidalneuronmodel
_version_	1718424788278444032

Encoding of spatio-temporal input characteristics by a CA1 pyramidal neuron model.

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