MODELING THE SENSORY COMPUTATIONS OF OLFACTORY BULB SYSTEM

摘要

The olfactory system is close to the periphery of the brain. It is phylogenetically very old and occupies a large part of it. We conjecture that understanding the olfactory system can be instrumental in the research and modeling of the human brain. The purpose of this study is to simulate the dynamic behavior of the olfactory bulb in a biologically plausible way. Our model consists of an array of coupled nonlinear oscillators. The input of the model consists of a vector, representing background activity of the sensory neurons, the odor input and gaussian noise. The odor input varies in time according to the sniff cycle. Odors evoke oscillatory activity in populations of excitatory and inhibitory cells of the proposed architecture with feedforward and feedback connections between them, and the system exhibits odor-specific adaptation. The model is able to reduce noise, allowing the pattern to emerge from incomplete and noisy input. The simulations show that it is capable to solve the odor detection, recognition and segmentation problems.