Abstract.
This paper proposes temporal-to-spatial dynamic mapping inspired by neural dynamics of the olfactory cortex. In our model the temporal structure of olfactory-bulb patterns is mapped to the spatial dynamics of the ensemble of cortical neurons. This mapping is based on the following biological mechanism: while anterior part of piriform cortex can be excited by the afferent input alone, the posterior areas require both afferent and association signals, which are temporally correlated in a specific way. One of the functional types of the neurons in our model corresponds to the cortical spatial dynamics and encodes odor components, and another represents temporal activity of association-fiber signals, which, we suggest, may be relevant to the encoding of odor concentrations. The temporal-to-spatial mapping and distributed representation of the model enable simultaneous rough cluster classification and fine recognition of patterns within a cluster as parts of the same dynamic process. The model is able to extract and segment the components of complex odor patterns which are spatiotemporal sequences of neural activity.
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Received: 16 October 2001 / Accepted in revised form: 7 February 2002
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Lysetskiy, M., Lozowski, A. & Zurada, J. Temporal-to-spatial dynamic mapping, flexible recognition, and temporal correlations in an olfactory cortex model. Biol Cybern 87, 58–67 (2002). https://doi.org/10.1007/s00422-002-0319-0
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DOI: https://doi.org/10.1007/s00422-002-0319-0