| Autor: |
Pakdaman, K., Alvarez, F., Segundo, J.P., Diez-Martínez, O., Vibert, J.-F. |
| Zdroj: |
International Journal of Modelling and Simulation; January 2002, Vol. 22 Issue: 4 p260-269, 10p |
| Abstrakt: |
AbstractRecurrent excitatory circuits and the positive feedback they imply are assigned important roles in a variety of tasks in living organisms. Such networks do not exhibit saturated behaviour in the sense of extremely fast rates and/or insensitivity to input variations, as artificial systems with positive feedback generally do- It is therefore important to identify how intrinsic neuronal properties prevent saturation. The simplest circuit where this can be investigated is formed by a single neuron that excites itself directly, and was analyzed experimentally by Diez-Martmez and Segundo (1983) using the pacemaker neuron of the crayfish stretch receptor organ. They showed that the system remained sensitive to variations in the input and suggested that neuronal adaptation along rapid successive firing played an important role in this. We tested this hypothesis by modelling the same system. In a previous publication, using four neuron models of increasing complexity, we showed that for a fixed constant input and several transmission delays, providing adaptation was implemented, the model displayed dynamics reminiscent of the experimental data. In this publication, we extend previous investigations by estimating, for a fixed delay, a transfer function of the system defined as the relationship between the constant input and the mean firing rate of the model. We show that when adaptation is implemented saturation occurs only at larger inputs and/or larger EPSPs. Our study is therefore compatible with the hypothesis that neuronal adaptation may be important in preventing saturation. |
| Databáze: |
Supplemental Index |
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