English: Fig. 1 The model’s architecture – Ambros-Ingerson et al.’s model uses two networks, bulb and cortex. Within the bulb, there are 400 simulated excitatory mitral cells, each projecting sparsely and non-topographically to the cortex via the (biologically inspired) Lateral Olfactory Tract. These 400 Mitral cells are divided into patches of 40 cells, each receiving an input from a peripheral receptor axon. The number of active Mitral cells in a patch represents the intensity of a given cue. Simulated inhibitory granule cells serve to normalize the output of the bulb (in biology, this is believed to occur via dendro-dendritic contacts with Mitral cells) such that the bulbar output to the cortex is relatively constant across cues and intensities. Inhibitory granule cells also receive randomly organized excitatory feedback from the cortex, which is composed of 1000 excitatory layer II cells. These are grouped into patches of 20 cells, and connected to each other in a feedforward fashion either directly or via local inhibitory neurons, creating a competitive soft winner-take-all response to bulbar input in each patch. Connections are learnt via correlational, Hebbian-type rules. Both learning and anatomy of the model are based on reported anatomical and physiological data.