title: Odor space and olfactory processing: collective algorithms and neural implementation.
abstract: 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.
authors.affiliation: Department of Molecular Biology, Princeton University, Princeton NJ 08544-1014, USA. hopfield@princeton.edu
authors.forename: J J
authors.initials: JJ
authors.lastname: Hopfield
mesh_terms: D000465:Algorithms; D009812:Odorants; D009833:Olfactory Pathways / Q000502:physiology*; D012903:Smell / Q000502:physiology*