Abstract
We study a strongly diluted neural network with nonmonotonic neurons and adapting synapses, whose dynamics can be analytically calculated. Dynamics reduction is observed for low connectivity: the network has no chaotic attractors in the stationary regime. For high connectivity chaos is not completely removed. We present some evidence that the dynamics reduction occurs, in the high connectivity case, when the synaptic correlations become relevant.
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