![]() ![]() Channel inactivation rate depends on recent neural activity, which in turn depends through modulations of the neural response function on the fraction of active channels. The model neuron here presented is composed of an ensemble of ion channels that can wander in a large pool of degenerate inactive states and thus exhibits multiple-time-scale dynamics at the molecular level. All these effects have been observed experimentally and are not explained by current single-neuron models. The model neuron exhibits history-dependent multiple-time-scale dynamics in several effects: first, after stimulation, the recovery time scale is related to the stimulation duration by a power-law scaling second, temporal patterns of neural activity in response to ongoing stimulation are modulated over time finally, the characteristic time scale for adaptation after a step change in stimulus depends on the duration of the preceding stimulus. Here, we construct a model that captures some features of the connection between these two levels of organization. How the temporally complex channel kinetics gives rise to dynamical properties of the neuron is not well understood. ![]() At the level of the single neuron, several microscopic mechanisms, including ion channel kinetics, can support multiple-time-scale dynamics. Such dynamics can provide powerful means for computation and memory. History-dependent characteristic time scales in dynamics have been observed at several levels of organization in neural systems. ![]()
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