Firing-rate response of a neuron receiving excitatory and inhibitory synaptic shot noise.

The synaptic coupling between neurons in neocortical networks is sufficiently strong so that relatively few synchronous synaptic pulses are required to bring a neuron from rest to the spiking threshold. However, such finite-amplitude effects of fluctuating synaptic drive are missed in the standard diffusion approximation. Here exact solutions for the firing-rate response to modulated presynaptic rates are derived for a neuron receiving additive excitatory and inhibitory synaptic shot noise with exponential amplitude distributions. The shot-noise description of the neuronal response to synaptic dynamics is shown to be richer and qualitatively distinct from that predicted by the diffusion approximation. It is also demonstrated how the framework developed here can be generalized to multiplicative shot noise so as to better capture effects of the inhibitory reversal potential.

[1]  R. Stein A THEORETICAL ANALYSIS OF NEURONAL VARIABILITY. , 1965, Biophysical journal.

[2]  J. Doob Stochastic processes , 1953 .

[3]  Martin Jacobsen,et al.  Exit times for a class of piecewise exponential Markov processes with two-sided jumps , 2007 .

[4]  J Rinzel,et al.  A theoretical basis for large coefficient of variation and bimodality in neuronal interspike interval distributions. , 1983, Journal of theoretical biology.

[5]  Wulfram Gerstner,et al.  Synaptic Shot Noise and Conductance Fluctuations Affect the Membrane Voltage with Equal Significance , 2005, Neural Computation.

[6]  Benjamin Lindner,et al.  Method to calculate the moments of the membrane voltage in a model neuron driven by multiplicative filtered shot noise. , 2008, Physical review. E, Statistical, nonlinear, and soft matter physics.

[7]  Stefan Rotter,et al.  Higher-Order Statistics of Input Ensembles and the Response of Simple Model Neurons , 2003, Neural Computation.

[8]  D. Hansel,et al.  How Spike Generation Mechanisms Determine the Neuronal Response to Fluctuating Inputs , 2003, The Journal of Neuroscience.

[9]  M. DeWeese,et al.  Non-Gaussian Membrane Potential Dynamics Imply Sparse, Synchronous Activity in Auditory Cortex , 2006, The Journal of Neuroscience.

[10]  M. J. Richardson,et al.  Firing-rate response of linear and nonlinear integrate-and-fire neurons to modulated current-based and conductance-based synaptic drive. , 2007, Physical review. E, Statistical, nonlinear, and soft matter physics.

[11]  Nicolas Brunel,et al.  Fast Global Oscillations in Networks of Integrate-and-Fire Neurons with Low Firing Rates , 1999, Neural Computation.

[12]  C. Stevens,et al.  Input synchrony and the irregular firing of cortical neurons , 1998, Nature Neuroscience.

[13]  Alan Bain,et al.  What is a Stochastic Process , 1942 .

[14]  Bruce W. Knight,et al.  Dynamics of Encoding in a Population of Neurons , 1972, The Journal of general physiology.

[15]  L Schimansky-Geier,et al.  Transmission of noise coded versus additive signals through a neuronal ensemble. , 2001, Physical review letters.

[16]  Moritz Helias,et al.  Equilibrium and response properties of the integrate-and-fi re neuron in discrete time , 2022 .

[17]  Maurizio Mattia,et al.  Diverse population-bursting modes of adapting spiking neurons. , 2007, Physical review letters.

[18]  W. Gerstner,et al.  Dynamic I-V curves are reliable predictors of naturalistic pyramidal-neuron voltage traces. , 2008, Journal of neurophysiology.

[19]  L. Ricciardi,et al.  Diffusion Processes and Related Topics in Biology. , 1978 .

[20]  H. Markram,et al.  Physiology and anatomy of synaptic connections between thick tufted pyramidal neurones in the developing rat neocortex. , 1997, The Journal of physiology.

[21]  Lawrence Sirovich,et al.  The Approach of a Neuron Population Firing Rate to a New Equilibrium: An Exact Theoretical Result , 2000, Neural Computation.

[22]  J. Hammersley,et al.  Diffusion Processes and Related Topics in Biology , 1977 .

[23]  Andrew G. Glen,et al.  APPL , 2001 .