Literature DB >> 1862075

Olfactory computation and object perception.

J J Hopfield1.   

Abstract

Animals that are primarily dependent on olfaction must obtain a description of the spatial location and the individual odor quality of environmental odor sources through olfaction alone. The variable nature of turbulent air flow makes such a remote sensing problem solvable if the animal can make use of the information conveyed by the fluctuation with time of the mixture of odor sources. Behavioral evidence suggests that such analysis takes place. An adaptive network can solve the essential problem, isolating the quality and intensity of the components within a mixture of several individual unknown odor sources. The network structure is an idealization of olfactory bulb circuitry. The dynamics of synapse change is essential to the computation. The synaptic variables themselves contain information needed by higher processing centers. The use of the same axons to convey intensity information and quality information requires time-coding of information. Covariation defines an individual odor source (object), and this may have a parallel in vision.

Mesh:

Year:  1991        PMID: 1862075      PMCID: PMC52105          DOI: 10.1073/pnas.88.15.6462

Source DB:  PubMed          Journal:  Proc Natl Acad Sci U S A        ISSN: 0027-8424            Impact factor:   11.205


  6 in total

1.  Olfactory Basis of Homing Behavior in the Giant Garden Slug, Limax maximus.

Authors:  A Gelperin
Journal:  Proc Natl Acad Sci U S A       Date:  1974-03       Impact factor: 11.205

Review 2.  Contributions of topography and parallel processing to odor coding in the vertebrate olfactory pathway.

Authors:  J S Kauer
Journal:  Trends Neurosci       Date:  1991-02       Impact factor: 13.837

3.  Olfactory recognition: a simple memory system.

Authors:  P Brennan; H Kaba; E B Keverne
Journal:  Science       Date:  1990-11-30       Impact factor: 47.728

4.  Oscillatory responses in cat visual cortex exhibit inter-columnar synchronization which reflects global stimulus properties.

Authors:  C M Gray; P König; A K Engel; W Singer
Journal:  Nature       Date:  1989-03-23       Impact factor: 49.962

5.  The gradient-sensing mechanism in bacterial chemotaxis.

Authors:  R M Macnab; D E Koshland
Journal:  Proc Natl Acad Sci U S A       Date:  1972-09       Impact factor: 11.205

6.  Temporal stimulation of chemotaxis in Escherichia coli.

Authors:  D A Brown; H C Berg
Journal:  Proc Natl Acad Sci U S A       Date:  1974-04       Impact factor: 11.205

  6 in total
  37 in total

1.  Stochastic fractal behavior in concentration fluctuation and fluorescence correlation spectroscopy.

Authors:  H Qian; G M Raymond; J B Bassingthwaighte
Journal:  Biophys Chem       Date:  1999-07-19       Impact factor: 2.352

2.  Sensory segmentation with coupled neural oscillators.

Authors:  C von der Malsburg; J Buhmann
Journal:  Biol Cybern       Date:  1992       Impact factor: 2.086

3.  Regulation of tentacle length in snails by odor concentration.

Authors:  E S Nikitin; I S Zakharov; P M Balaban
Journal:  Neurosci Behav Physiol       Date:  2006-01

4.  Nonequilibrium landscape theory of neural networks.

Authors:  Han Yan; Lei Zhao; Liang Hu; Xidi Wang; Erkang Wang; Jin Wang
Journal:  Proc Natl Acad Sci U S A       Date:  2013-10-21       Impact factor: 11.205

Review 5.  Central processing of natural odor mixtures in insects.

Authors:  Hong Lei; Neil Vickers
Journal:  J Chem Ecol       Date:  2008-06-25       Impact factor: 2.626

6.  Associative memory and segmentation in an oscillatory neural model of the olfactory bulb.

Authors:  O Hendin; D Horn; M V Tsodyks
Journal:  J Comput Neurosci       Date:  1998-05       Impact factor: 1.621

7.  Transforming neural computations and representing time.

Authors:  J J Hopfield
Journal:  Proc Natl Acad Sci U S A       Date:  1996-12-24       Impact factor: 11.205

8.  The role of inhibition in an associative memory model of the olfactory bulb.

Authors:  O Hendin; D Horn; M V Tsodyks
Journal:  J Comput Neurosci       Date:  1997-04       Impact factor: 1.621

9.  Olfactory bulb coding of odors, mixtures and sniffs is a linear sum of odor time profiles.

Authors:  Priyanka Gupta; Dinu F Albeanu; Upinder S Bhalla
Journal:  Nat Neurosci       Date:  2015-01-12       Impact factor: 24.884

10.  A probabilistic approach to demixing odors.

Authors:  Agnieszka Grabska-Barwińska; Simon Barthelmé; Jeff Beck; Zachary F Mainen; Alexandre Pouget; Peter E Latham
Journal:  Nat Neurosci       Date:  2016-12-05       Impact factor: 24.884

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