Do biological synapses perform probabilistic computations?

Autor(es)

Pelaez, Javier Ropero ; Andina, Diego

• Tipo de documento: Artigo Científico
• Fonte: Neurocomputing; v. 114, p. 8-pg., 2013-08-19.

Resumo

In this paper, the presynaptic rule, a classical model of synaptic reinforcement, is revisited. It is shown that this model is capable of reproducing recently discovered properties of biological synapses such as synaptic directionality, and metaplasticity of the long-term potentiation threshold. With slight modifications, the presynaptic model also reproduces metaplasticity of the long-term depression threshold and Artola, Brocher and Singer's experimental model. Two asymptotically equivalent approaches were adopted for this analysis, one with firing rates and another with conditional probabilities. Although both approximations are consistent with biological properties, the results obtained by the probabilistic approach are qualitatively closer to biological experimental results. (C) 2013 Elsevier B.V. All rights reserved. (AU)

• Processo FAPESP: 03/08804-0 - Modelo computacional da dinâmica sub-cortical em resposta a estímulos aversivos
• Beneficiário: Francisco Javier Ropero Pelaez
• Modalidade de apoio: Bolsas no Brasil - Pós-Doutorado