Publication

Noise and the PSTH response to current transients II. Integrate-and-fire model with slow recovery and application to motoneuron data

Wulfram Gerstner
2001
Journal Articles

Abstract

A generalized version of the integrate-and-fire model is presented that qualitatively reproduces firing rates and membrane trajectories of motoneurons. The description is based on the spike-response model and includes 3 different time constants: the passive membrane time constant, a recovery time of the input conductance after each spike, and a time constant of the spike afterpotential. The effect of stochastic background input on the peristimulus time histogram (P STH) response to spike input is calculated analytically. Model results are compared with the experimental data of Poliakov et al. (1996). The linearized theory shows that the PSTH response to an input spike is proportional to a filtered version of the postsynaptic potential generated by the input spike. The shape of the filter depends on the background activity. The full nonlinear theory is in close agreement with simulated PSTH data.

Official source

https://infoscience.epfl.ch/entities/publication/a9459adb-cd71-4399-921e-7ab68192d05c

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Wulfram Gerstner
2001
Journal Articles

Abstract

Official source

https://infoscience.epfl.ch/entities/publication/a9459adb-cd71-4399-921e-7ab68192d05c

About this result

Related concepts (32)

Biological neuron model

Biological neuron models, also known as a spiking neuron models, are mathematical descriptions of the properties of certain cells in the nervous system that generate sharp electrical potentials across their cell membrane, roughly one millisecond in duration, called action potentials or spikes (Fig. 2). Since spikes are transmitted along the axon and synapses from the sending neuron to many other neurons, spiking neurons are considered to be a major information processing unit of the nervous system.

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Neural coding (or neural representation) is a neuroscience field concerned with characterising the hypothetical relationship between the stimulus and the individual or ensemble neuronal responses and the relationship among the electrical activity of the neurons in the ensemble. Based on the theory that sensory and other information is represented in the brain by networks of neurons, it is thought that neurons can encode both digital and analog information.

Related publications (2)

Noise and the PSTH response to current transients II. Integrate-and-fire model with slow recovery and application to motoneuron data

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