Spike generation estimated from stationary spike trains in a variety of neurons in vivo

Anton Spanne, Pontus Geborek, Fredrik Bengtsson, Henrik Jörntell

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Abstract

To any model of brain function, the variability of neuronal spike firing is a problem that needs to be taken into account. Whereas the synaptic integration can be described in terms of the original Hodgkin-Huxley (H-H) formulations of conductance-based electrical signaling, the transformation of the resulting membrane potential into patterns of spike output is subjected to stochasticity that may not be captured with standard single neuron H-H models. The dynamics of the spike output is dependent on the normal background synaptic noise present in vivo, but the neuronal spike firing variability in vivo is not well studied. In the present study, we made long-term whole cell patch clamp recordings of stationary spike firing states across a range of membrane potentials from a variety of subcortical neurons in the non-anesthetized, decerebrated state in vivo. Based on the data, we formulated a simple, phenomenological model of the properties of the spike generation in each neuron that accurately captured the stationary spike firing statistics across all membrane potentials. The model consists of a parametric relationship between the mean and standard deviation of the inter-spike intervals, where the parameter is linearly related to the injected current over the membrane. This enabled it to generate accurate approximations of spike firing also under inhomogeneous conditions with input that varies over time. The parameters describing the spike firing statistics for different neuron types overlapped extensively, suggesting that the spike generation had similar properties across neurons.
Original languageEnglish
Article number199
JournalFrontiers in Cellular Neuroscience
Volume8
DOIs
Publication statusPublished - 2014

Subject classification (UKÄ)

  • Neurosciences

Keywords

  • spike firing statistics
  • stochasticity
  • spinal interneurons
  • purkinje
  • cells
  • golgi cells
  • molecular layer interneurons
  • synaptic integration
  • whole cell recordings in vivo

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