Phasic firing in vasopressin cells: understanding its functional significance through computational models.

Vasopressin neurons, responding to input generated by osmotic pressure, use an intrinsic mechanism to shift from slow irregular firing to a distinct phasic pattern, consisting of long bursts and silences lasting tens of seconds. With increased input, bursts lengthen, eventually shifting to continuou...

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Autores principales:	Duncan J MacGregor, Gareth Leng
Formato:	article
Lenguaje:	EN
Publicado:	Public Library of Science (PLoS) 2012
Materias:	Biology (General) QH301-705.5
Acceso en línea:	https://doaj.org/article/08843f262b4e48cb85a1700f49af4014
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spelling	oai:doaj.org-article:08843f262b4e48cb85a1700f49af40142021-11-18T05:52:46ZPhasic firing in vasopressin cells: understanding its functional significance through computational models.1553-734X1553-735810.1371/journal.pcbi.1002740https://doaj.org/article/08843f262b4e48cb85a1700f49af40142012-01-01T00:00:00Zhttps://www.ncbi.nlm.nih.gov/pmc/articles/pmid/23093929/pdf/?tool=EBIhttps://doaj.org/toc/1553-734Xhttps://doaj.org/toc/1553-7358Vasopressin neurons, responding to input generated by osmotic pressure, use an intrinsic mechanism to shift from slow irregular firing to a distinct phasic pattern, consisting of long bursts and silences lasting tens of seconds. With increased input, bursts lengthen, eventually shifting to continuous firing. The phasic activity remains asynchronous across the cells and is not reflected in the population output signal. Here we have used a computational vasopressin neuron model to investigate the functional significance of the phasic firing pattern. We generated a concise model of the synaptic input driven spike firing mechanism that gives a close quantitative match to vasopressin neuron spike activity recorded in vivo, tested against endogenous activity and experimental interventions. The integrate-and-fire based model provides a simple physiological explanation of the phasic firing mechanism involving an activity-dependent slow depolarising afterpotential (DAP) generated by a calcium-inactivated potassium leak current. This is modulated by the slower, opposing, action of activity-dependent dendritic dynorphin release, which inactivates the DAP, the opposing effects generating successive periods of bursting and silence. Model cells are not spontaneously active, but fire when perturbed by random perturbations mimicking synaptic input. We constructed one population of such phasic neurons, and another population of similar cells but which lacked the ability to fire phasically. We then studied how these two populations differed in the way that they encoded changes in afferent inputs. By comparison with the non-phasic population, the phasic population responds linearly to increases in tonic synaptic input. Non-phasic cells respond to transient elevations in synaptic input in a way that strongly depends on background activity levels, phasic cells in a way that is independent of background levels, and show a similar strong linearization of the response. These findings show large differences in information coding between the populations, and apparent functional advantages of asynchronous phasic firing.Duncan J MacGregorGareth LengPublic Library of Science (PLoS)articleBiology (General)QH301-705.5ENPLoS Computational Biology, Vol 8, Iss 10, p e1002740 (2012)
institution	DOAJ
collection	DOAJ
language	EN
topic	Biology (General) QH301-705.5
spellingShingle	Biology (General) QH301-705.5 Duncan J MacGregor Gareth Leng Phasic firing in vasopressin cells: understanding its functional significance through computational models.
description	Vasopressin neurons, responding to input generated by osmotic pressure, use an intrinsic mechanism to shift from slow irregular firing to a distinct phasic pattern, consisting of long bursts and silences lasting tens of seconds. With increased input, bursts lengthen, eventually shifting to continuous firing. The phasic activity remains asynchronous across the cells and is not reflected in the population output signal. Here we have used a computational vasopressin neuron model to investigate the functional significance of the phasic firing pattern. We generated a concise model of the synaptic input driven spike firing mechanism that gives a close quantitative match to vasopressin neuron spike activity recorded in vivo, tested against endogenous activity and experimental interventions. The integrate-and-fire based model provides a simple physiological explanation of the phasic firing mechanism involving an activity-dependent slow depolarising afterpotential (DAP) generated by a calcium-inactivated potassium leak current. This is modulated by the slower, opposing, action of activity-dependent dendritic dynorphin release, which inactivates the DAP, the opposing effects generating successive periods of bursting and silence. Model cells are not spontaneously active, but fire when perturbed by random perturbations mimicking synaptic input. We constructed one population of such phasic neurons, and another population of similar cells but which lacked the ability to fire phasically. We then studied how these two populations differed in the way that they encoded changes in afferent inputs. By comparison with the non-phasic population, the phasic population responds linearly to increases in tonic synaptic input. Non-phasic cells respond to transient elevations in synaptic input in a way that strongly depends on background activity levels, phasic cells in a way that is independent of background levels, and show a similar strong linearization of the response. These findings show large differences in information coding between the populations, and apparent functional advantages of asynchronous phasic firing.
format	article
author	Duncan J MacGregor Gareth Leng
author_facet	Duncan J MacGregor Gareth Leng
author_sort	Duncan J MacGregor
title	Phasic firing in vasopressin cells: understanding its functional significance through computational models.
title_short	Phasic firing in vasopressin cells: understanding its functional significance through computational models.
title_full	Phasic firing in vasopressin cells: understanding its functional significance through computational models.
title_fullStr	Phasic firing in vasopressin cells: understanding its functional significance through computational models.
title_full_unstemmed	Phasic firing in vasopressin cells: understanding its functional significance through computational models.
title_sort	phasic firing in vasopressin cells: understanding its functional significance through computational models.
publisher	Public Library of Science (PLoS)
publishDate	2012
url	https://doaj.org/article/08843f262b4e48cb85a1700f49af4014
work_keys_str_mv	AT duncanjmacgregor phasicfiringinvasopressincellsunderstandingitsfunctionalsignificancethroughcomputationalmodels AT garethleng phasicfiringinvasopressincellsunderstandingitsfunctionalsignificancethroughcomputationalmodels
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Phasic firing in vasopressin cells: understanding its functional significance through computational models.

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