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Biological Cybernetics

, Volume 103, Issue 2, pp 151–165

First Online: 27 April 2010Received: 20 January 2010Accepted: 01 April 2010

Abstract

In the past decades, many studies have focussed on the relation between the input and output of neurons with the aim to understand information processing by neurons. A particular aspect of neuronal information, which has not received much attention so far, concerns the problem of information transfer when a neuron or a population of neurons receives input from two or more populations of neurons, in particular when these populations of neurons carry different types of information. The aim of the present study is to investigate the responses of neurons to multiple inputs modulated in the gamma frequency range. By a combination of theoretical approaches and computer simulations, we test the hypothesis that enhanced modulation of synchronized excitatory neuronal activity in the gamma frequency range provides an advantage over a less synchronized input for various types of neurons. The results of this study show that the spike output of various types of neurons i.e. the leaky integrate and fire neuron, the quadratic integrate and fire neuron and the Hodgkin–Huxley HH neuron and that of excitatory–inhibitory coupled pairs of neurons, like the Pyramidal Interneuronal Network Gamma PING model, is highly phase-locked to the larger of two gamma-modulated input signals. This implies that the neuron selectively responds to the input with the larger gamma modulation if the amplitude of the gamma modulation exceeds that of the other signals by a certain amount. In that case, the output of the neuron is entrained by one of multiple inputs and that other inputs are not represented in the output. This mechanism for selective information transmission is enhanced for short membrane time constants of the neuron.

KeywordsSynchronization Gamma oscillations Phase locking Stimulus selection  Download to read the full article text



Author: Stan Gielen - Martin Krupa - Magteld Zeitler

Source: https://link.springer.com/



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