Document Detail

A computational system for simulating and analyzing arrays of biological and artificial chemical sensors.
MedLine Citation:
PMID:  11923188     Owner:  NLM     Status:  MEDLINE    
We have designed an approach for modeling olfactory pathways by which one can explore how the properties of individual receptors affect the information coding capacity of an entire system. The effect of receptor tuning breadth on system performance was explored explicitly. We presented model sensory arrays with sets of stimuli randomly and uniformly distributed in an "olfactory space". Arrays of uniformly sized model receptors responding to 25-35% of the stimuli gave the best performance as measured by the ability to capture the most information about the stimulus set. Arrays of variably sized model receptors that were both more broadly and more narrowly tuned than this optimum could, however, perform better than uniform arrays. This method and the results obtained using it suggest a framework for considering the growing body of evidence on the functional properties of individual olfactory receptor and relay neurons from a systems coding perspective.
Tarik K Alkasab; Joel White; John S Kauer
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Publication Detail:
Type:  Journal Article; Research Support, U.S. Gov't, Non-P.H.S.; Research Support, U.S. Gov't, P.H.S.    
Journal Detail:
Title:  Chemical senses     Volume:  27     ISSN:  0379-864X     ISO Abbreviation:  Chem. Senses     Publication Date:  2002 Mar 
Date Detail:
Created Date:  2002-03-29     Completed Date:  2002-09-11     Revised Date:  2006-11-15    
Medline Journal Info:
Nlm Unique ID:  8217190     Medline TA:  Chem Senses     Country:  England    
Other Details:
Languages:  eng     Pagination:  261-75     Citation Subset:  IM    
Department of Neuroscience, Tufts University School of Medicine, Boston, MA 02111, USA.
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MeSH Terms
Biosensing Techniques
Computational Biology*

From MEDLINE®/PubMed®, a database of the U.S. National Library of Medicine

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