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ABSTRACT: This a model from the article: This model was taken from the CellML repository and automatically converted to SBML. This model originates from BioModels Database: A Database of Annotated Published Models (http://www.ebi.ac.uk/biomodels/). It is copyright (c) 2005-2011 The BioModels.net Team. In summary, you are entitled to use this encoded model in absolutely any manner you deem suitable, verbatim, or with modification, alone or embedded it in a larger context, redistribute it, commercially or not, in a restricted way or not..
Role for G protein Gbetagamma isoform specificity in synaptic signal processing:a computational study.
Bertram R, Arnot MI, Zamponi GW. J Neurophysiol 2002 May;87(5):2612-23 11976397 ,
Abstract:
Computational modeling is used to investigate the functional impact of Gprotein-mediated presynaptic autoinhibition on synaptic filtering properties. Itis demonstrated that this form of autoinhibition, which is relieved bydepolarization, acts as a high-pass filter. This contrasts with vesicledepletion, which acts as a low-pass filter. Model parameters are adjusted toreproduce kinetic slowing data from different Gbetagamma dimeric isoforms, whichproduce different degrees of slowing. With these sets of parameter values, wedemonstrate that the range of frequencies filtered out by the autoinhibitionvaries greatly depending on the Gbetagamma isoform activated by theautoreceptors. It is shown that G protein autoinhibition can enhance the spatialcontrast between a spatially distributed high-frequency signal and surroundinglow-frequency noise, providing an alternate mechanism to lateral inhibition. Itis also shown that autoinhibition can increase the fidelity of coincidencedetection by increasing the signal-to-noise ratio in the postsynaptic cell. Thefilter cut, the input frequency below which signals are filtered, depends onseveral biophysical parameters in addition to those related to Gbetagammabinding and unbinding. By varying one such parameter, the rate at whichtransmitter unbinds from autoreceptors, we show that the filter cut can beadjusted up or down for several of the Gbetagamma isoforms. This allows forgreat synapse-to-synapse variability in the distinction between signal andnoise.
The original model was: Bertram R, Arnot MI, Zamponi GW. (2002) - version=1.0
The original CellML model was created by:
Catherine Lloyd
c.lloyd@auckland.ac.nz
The University of Auckland
To the extent possible under law, all copyright and related or neighbouring rights to this encoded model have been dedicated to the public domain worldwide. Please refer to CC0 Public Domain Dedication for more information.
To cite BioModels Database, please use: Li C, Donizelli M, Rodriguez N, Dharuri H, Endler L, Chelliah V, Li L, He E, Henry A, Stefan MI, Snoep JL, Hucka M, Le Novère N, Laibe C (2010) BioModels Database: An enhanced, curated and annotated resource for published quantitative kinetic models. BMC Syst Biol., 4:92.
ORGANISM(S): Homo sapiens
SUBMITTER: Camille Laibe
PROVIDER: MODEL1006230024 | biostudies-other |
SECONDARY ACCESSION(S): 11976397
REPOSITORIES: biostudies-other

Journal of neurophysiology 20020501 5
Computational modeling is used to investigate the functional impact of G protein-mediated presynaptic autoinhibition on synaptic filtering properties. It is demonstrated that this form of autoinhibition, which is relieved by depolarization, acts as a high-pass filter. This contrasts with vesicle depletion, which acts as a low-pass filter. Model parameters are adjusted to reproduce kinetic slowing data from different Gbetagamma dimeric isoforms, which produce different degrees of slowing. With th ...[more]