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Dynamic I-V curves are reliable predictors of naturalistic pyramidal-neuron voltage traces
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Badel, Laurent, Lefort, Sandrine, Brette, Romain, Petersen, Carl, Gerstner, Wulfram and Richardson, Magnus J. E. (2008) Dynamic I-V curves are reliable predictors of naturalistic pyramidal-neuron voltage traces. Journal of Neurophysiology, Vol.99 (No.2). pp. 656-666. doi:10.1152/jn.01107.2007 ISSN 0022-3077.
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Official URL: http://dx.doi.org/10.1152/jn.01107.2007
Abstract
Neuronal response properties are typically probed by intracellular measurements of current-voltage (I-V) relationships during application of current or voltage steps. Here we demonstrate the measurement of a novel I-V curve measured while the neuron exhibits a fluctuating voltage and emits spikes. This dynamic I-V curve requires only a few tens of seconds of experimental time and so lends itself readily to the rapid classification of cell type, quantification of heterogeneities in cell populations, and generation of reduced analytical models. We apply this technique to layer-5 pyramidal cells and show that their dynamic I-V curve comprises linear and exponential components, providing experimental evidence for a recently proposed theoretical model. The approach also allows us to determine the change of neuronal response properties after a spike, millisecond by millisecond, so that postspike refractoriness of pyramidal cells can be quantified. Observations of I-V curves during and in absence of refractoriness are cast into a model that is used to predict both the subthreshold response and spiking activity of the neuron to novel stimuli. The predictions of the resulting model are in excellent agreement with experimental data and close to the intrinsic neuronal reproducibility to repeated stimuli.
Item Type: | Journal Article | ||||
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Subjects: | R Medicine > RC Internal medicine > RC0321 Neuroscience. Biological psychiatry. Neuropsychiatry Q Science > QP Physiology |
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Divisions: | Faculty of Science, Engineering and Medicine > Research Centres > Warwick Systems Biology Centre | ||||
Library of Congress Subject Headings (LCSH): | Neurons, Neural networks (Neurobiology), Neural circuitry, Nervous system -- Mathematical model, Neural networks (Computer science) | ||||
Journal or Publication Title: | Journal of Neurophysiology | ||||
Publisher: | American Physiological Society | ||||
ISSN: | 0022-3077 | ||||
Official Date: | February 2008 | ||||
Dates: |
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Volume: | Vol.99 | ||||
Number: | No.2 | ||||
Number of Pages: | 11 | ||||
Page Range: | pp. 656-666 | ||||
DOI: | 10.1152/jn.01107.2007 | ||||
Status: | Peer Reviewed | ||||
Publication Status: | Published | ||||
Access rights to Published version: | Restricted or Subscription Access | ||||
Funder: | Schweizerischer Nationalfonds zur Förderung der Wissenschaftlichen Forschung [Swiss National Science Foundation] (SNSF), France. Agence nationale de la recherche (ANR), European Union (EU) | ||||
Grant number: | HR-CORTEX (ANR) |
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