Effects of refractory periods in the dynamics of a diluted neural network

F.A. TAMARIT; D.A. STARIOLO; S.A. CANNAS; PABLO SERRA

PHYSICAL REVIEW E

AMER PHYSICAL SOC

Lugar: New York; Año: 1996 vol. 53 p. 5146 - 5152

1539-3755

We propose a stochastic dynamics for a neural network which accounts for the effects of the refractoryperiods ~absolute and relative! in the dynamics of a single neuron. The dynamics can be solved analytically inan extremely diluted network. We found a very rich scenario that presents retrieval phases and a perioddoubling route to chaos in the attractors of the overlap order parameter. Our model incorporates some char-acteristics that make it biologically appealing, such as asymmetric synaptic efficacies, dilution of the synapticmatrix, absolute and relative refractory periods, complex retrieval dynamics, and low levels of activity in theretrieval regime.