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J Neurophysiol (December 5, 2007). doi:10.1152/jn.01107.2007
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Submitted on October 5, 2007
Accepted on December 3, 2007

Dynamic I-V curves are reliable predictors of naturalistic pyramidal-neuron voltage traces

Laurent Badel1, Sandrine Lefort2, Romain Brette3, Carl C. H. Petersen2, Wulfram Gerstner1, and Magnus J E Richardson4*

1 School of Computer and Communications Sciences and Brain-Mind Institute, Ecole Polytechnique Federale de Lausanne, Switzerland
2 Brain-Mind Institute, Ecole Polytechnique Federale de Lausanne, Lausanne, Switzerland
3 Departement d'Informatique, Ecole Normale Superieure, Paris, France
4 Warwick Systems Biology Centre, University of Warwick, Coventry, United Kingdom; , United Kingdom

* To whom correspondence should be addressed. E-mail: magnus.richardson{at}warwick.ac.uk.

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 to the 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 post-spike refractoriness of pyramidal cells can be quantified. Observations of I-V curves during and in absence of refractoriness are cast into a model which 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.




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[Abstract] [Full Text] [PDF]




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