This study is an attempt to answer the question - what kind of spiking neural networks could efficiently transform rate-coded input signal into tempo- rally coded form - specific activity of neuronal groups with strictly fixed temporal delays between spikes emitted by different neurons in every group. Since theo- retical approach to the solution of this problem appears to be very hard or impos- sible the network configurations performing this task efficiently were found by means of genetic algorithm. Exploration of their structure showed that while excitatory neurons form the groups with stereotypical firing patterns, the inhibi- tory neurons of the network make these patterns specific for different rate-coded stimuli and, thus, play the key role in conversion of rate-coded input signal to temporal code.
['Mikhail V. Kiselev']
Conversion from Rate Code to Temporal Code - Crucial Role of Inhibition