Abstract
Experimental evidence shows that certain types of visual information processing, such as face recognition, may be extremely rapid: in a few tens of milliseconds a neuron may yield most of the information about a visual stimulus that can ever be extracted from the response of that neuron. These data might be taken to indicate that there is insufficient time for recurrent or feedback processing. However, a novel analytical method allows the analysis of the dynamics of an associative memory network of integrate-and-fire neurons, laterally connected through realistically modelled synapses. The analysis, supported by preliminary simulations, indicates that the network may retrieve information from memory over a time determined mainly by excitatory synaptic conductance time constants, that is in times in the order of tens of milliseconds. The results thus show that the dynamics of recurrent processing is sufficiently rapid for it to contribute to processing within the short times observed in neurophysiological experiments.
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