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Predicting spike timing of neocortical pyramidal neurons by simple threshold models

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Abstract

Neurons generate spikes reliably with millisecond precision if driven by a fluctuating current—is it then possible to predict the spike timing knowing the input? We determined parameters of an adapting threshold model using data recorded in vitro from 24 layer 5 pyramidal neurons from rat somatosensory cortex, stimulated intracellularly by a fluctuating current simulating synaptic bombardment in vivo. The model generates output spikes whenever the membrane voltage (a filtered version of the input current) reaches a dynamic threshold. We find that for input currents with large fluctuation amplitude, up to 75% of the spike times can be predicted with a precision of ±2 ms. Some of the intrinsic neuronal unreliability can be accounted for by a noisy threshold mechanism. Our results suggest that, under random current injection into the soma, (i) neuronal behavior in the subthreshold regime can be well approximated by a simple linear filter; and (ii) most of the nonlinearities are captured by a simple threshold process.

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Authors and Affiliations

  1. Ecol Polytechnique Federale de Lausanne (EPFL), School of Computer and Communication Sciences and Brain Mind Institute, Station 15, CH-1015, Lausanne, Switzerland

    Renaud Jolivet & Wulfram Gerstner

  2. University of Bern, Institute of Physiology, CH-3012, Bern, Switzerland

    Alexander Rauch & Hans-Rudolf Lüscher

  3. Max Planck Institute for Biological Cybernetics, D-72012, Tübingen, Germany

    Alexander Rauch

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  1. Renaud Jolivet
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  2. Alexander Rauch
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  3. Hans-Rudolf Lüscher
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  4. Wulfram Gerstner
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Correspondence to Renaud Jolivet.

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Jolivet, R., Rauch, A., Lüscher, HR. et al. Predicting spike timing of neocortical pyramidal neurons by simple threshold models. J Comput Neurosci 21, 35–49 (2006). https://doi.org/10.1007/s10827-006-7074-5

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