Signal Processing With Temporal Sequences in Olfactory Systems

Abstract

The olfactory system is a very efficient biological setup capable of odor information processing with neural signals. The nature of neural signals restricts the information representation to multidimensional temporal sequences of spikes. The information is contained in the interspike intervals within each individual neural signal and interspike intervals between multiple signals. A mechanism of interactions between random excitations evoked by odorants in the olfactory receptors of the epithelium and deterministic operation of the olfactory bulb is proposed in this paper. Inverse Frobenius-Perron models of the bulb's temporal sequences are fitted to the interspike distributions of temporally modulated receptor signals. Ultimately, such pattern matching results in ability to recognize odors and offer a hypothetic model for signal processing occurring in the primary stage of the olfactory system.