Odor space and olfactory processing: Collective algorithms and neural implementation
AUTOR(ES)
Hopfield, J. J.
FONTE
The National Academy of Sciences
RESUMO
Several basic olfactory tasks must be solved by highly olfactory animals, including background suppression, multiple object separation, mixture separation, and source identification. The large number N of classes of olfactory receptor cells—hundreds or thousands—permits the use of computational strategies and algorithms that would not be effective in a stimulus space of low dimension. A model of the patterns of olfactory receptor responses, based on the broad distribution of olfactory thresholds, is constructed. Representing one odor from the viewpoint of another then allows a common description of the most important basic problems and shows how to solve them when N is large. One possible biological implementation of these algorithms uses action potential timing and adaptation as the “hardware” features that are responsible for effective neural computation.
ACESSO AO ARTIGO
http://www.pubmedcentral.nih.gov/articlerender.fcgi?artid=22963Documentos Relacionados
- Chemical implementation and thermodynamics of collective neural networks.
- Odor-induced increases in c-fos mRNA expression reveal an anatomical "unit" for odor processing in olfactory bulb.
- Food processing: principles and applications
- Odor-induced phosphorylation of olfactory cilia proteins.
- Image processing: some challenging problems.