Computational models of the olfactory system aim to understand how the system works and make predictions about how it responds to different odor stimuli. One such model is the "odor-identity model," which uses a set of "odor-identity vectors" to represent the unique activation pattern of each odor molecule across all receptors.
The odor-identity model also includes populations of "MCs" and "GCs," which represent the mitral cells and granule cells in the olfactory bulb, respectively. These cells are responsible for processing and refining the information from the olfactory epithelium, and for separating the odor information into different channels.
By simulating the activity of the MCs and GCs in response to different odor stimuli, the odor-identity model can make predictions about how the olfactory system processes and recognizes different odors.