Modeling neural spatiotemporal behavior

We study some aspects of the dynamic neural filter (DNF), a recurrent network that produces spatiotemporal sequences in reaction to sets of constant inputs. The biological motivation for this study came from the observation of spatiotemporal patterns in the locust antennal lobe. Some of the aspects of these results can be reformulated and characterized by the DNF. Studying deterministic dynamics we find differences between low and high numbers of neurons. For low numbers there exists clear correlation between distances in input space and edit distances of spatiotemporal sequences. For large numbers of neurons we observe divergence between close-by spatiotemporal sequences. Nonetheless neuronal correlations survive for small changes in input space.