Journal of Computational Neuroscience

, Volume 21, Issue 1, pp 35–49 | Cite as

Predicting spike timing of neocortical pyramidal neurons by simple threshold models

  • Renaud JolivetEmail author
  • Alexander Rauch
  • Hans-Rudolf Lüscher
  • Wulfram Gerstner


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.


Spike Response Model Stochastic input Adapting threshold Spike-timing reliability Predicting spike timing. 


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Copyright information

© Springer Science + Business Media, LLC 2006

Authors and Affiliations

  • Renaud Jolivet
    • 1
    Email author
  • Alexander Rauch
    • 2
    • 3
  • Hans-Rudolf Lüscher
    • 2
  • Wulfram Gerstner
    • 1
  1. 1.Ecol Polytechnique Federale de Lausanne (EPFL), School of Computer and Communication Sciences and Brain Mind InstituteLausanneSwitzerland
  2. 2.University of Bern, Institute of PhysiologyBernSwitzerland
  3. 3.Max Planck Institute for Biological CyberneticsTübingenGermany

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