Literature DB >> 3233263

Principles of odor coding and a neural network for odor discrimination.

D Schild1.   

Abstract

A concept of olfactory coding is proposed. It describes the stimulus responses of all receptor cells by the use of vector spaces. The morphological convergence pattern between receptor cells and glomeruli is given in the same vector space as the receptor cell activities. The overall input of a glomerulus follows as the scalar product of the receptor cell activity vector and the vector of the glomerulus' convergence pattern. The proposed coding concept shows how the network of the olfactory bulb succeeds in discriminating odors with high selectivity. It is concluded that sets of mitral cells coding similar odors work very much in the way of mutually inhibited matched filters. This solves one main problem both in olfaction as well as real-time odor detection by an artificial nose, i.e., how the fairly low degree of selectivity of receptor cells or sensors is overcome by the neural network following the receptor stage. The formal description of olfactory coding suggests that quality perception which is invariant under concentration shifts is accomplished by an associative memory in the olfactory bulb.

Mesh:

Year:  1988        PMID: 3233263      PMCID: PMC1330413          DOI: 10.1016/S0006-3495(88)83038-8

Source DB:  PubMed          Journal:  Biophys J        ISSN: 0006-3495            Impact factor:   4.033


  62 in total

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Journal:  Brain Res       Date:  1970-10-13       Impact factor: 3.252

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Authors:  J T Davies
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  16 in total

1.  An olfactory sensory neuron line, odora, properly targets olfactory proteins and responds to odorants.

Authors:  J R Murrell; D D Hunter
Journal:  J Neurosci       Date:  1999-10-01       Impact factor: 6.167

2.  Significance of glomerular compartmentalization for olfactory coding.

Authors:  D Schild; H Riedel
Journal:  Biophys J       Date:  1992-03       Impact factor: 4.033

3.  Detecting synfire chain activity using massively parallel spike train recording.

Authors:  Sven Schrader; Sonja Grün; Markus Diesmann; George L Gerstein
Journal:  J Neurophysiol       Date:  2008-07-16       Impact factor: 2.714

4.  Investigation of the role of interneurons and their modulation by centrifugal fibers in a neural model of the olfactory bulb.

Authors:  C Linster; R Gervais
Journal:  J Comput Neurosci       Date:  1996-09       Impact factor: 1.621

5.  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

6.  A model of cholinergic modulation in olfactory bulb and piriform cortex.

Authors:  Licurgo de Almeida; Marco Idiart; Christiane Linster
Journal:  J Neurophysiol       Date:  2012-12-05       Impact factor: 2.714

7.  Probability model for molecular recognition in biological receptor repertoires: significance to the olfactory system.

Authors:  D Lancet; E Sadovsky; E Seidemann
Journal:  Proc Natl Acad Sci U S A       Date:  1993-04-15       Impact factor: 11.205

8.  Dynamics of the olfactory bulb: bifurcations, learning, and memory.

Authors:  P Erdi; T Gröbler; G Barna; K Kaski
Journal:  Biol Cybern       Date:  1993       Impact factor: 2.086

9.  Assessment and discrimination of odor stimuli in rat olfactory bulb by dynamic functional MRI.

Authors:  F Xu; I Kida; F Hyder; R G Shulman
Journal:  Proc Natl Acad Sci U S A       Date:  2000-09-12       Impact factor: 11.205

Review 10.  Brain-computer symbiosis.

Authors:  Gerwin Schalk
Journal:  J Neural Eng       Date:  2008-01-17       Impact factor: 5.379

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