A Simple Model of Non-Spiking Neurons
Résumé
Due to the ubiquity of spiking neurons in neuronal processes, various simple spiking neuron models have been proposed as an alternative to conductance-based models (a.k.a. Hodgkin-Huxley type models), known to be computationally expensive and difficult to treat mathematically. However, to the best of our knowledge, there is no equivalent in the literature of a simple and lightweight model for describing the voltage behavior of non-spiking neurons, which also are ubiquitous in a large variety of nervous tissues in both vertebrate and invertebrate species, and play a central role in information processing. This paper proposes a simple model that reproduces the experimental qualitative behavior of known types of non-spiking neurons. The proposed model, which differs fundamentally from classic simple spiking models unable to characterize non-spiking dynamics due to their intrinsic structure, is derived from the bifurcation study of conductance-based models of non-spiking neurons. Since such neurons display a high sensitivity to noise, the model aims at capturing the experimental distribution of single neuron responses rather than perfectly replicating a single given experimental voltage trace. We show that such a model: (i) can be used as a building block for realistic simulations of large non-spiking neuronal networks, and (ii) is endowed with generalization capabilities, granted by design.
Origine : Fichiers produits par l'(les) auteur(s)