A computational system for simulating and analyzing arrays of biological and artificial chemical sensors.
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.
Alkasab
Tarik K
TK
Department of Neuroscience, Tufts University School of Medicine, Boston, MA 02111, USA.
White
Joel
J
Kauer
John S
JS
D015374:Biosensing Techniques; D019295:Computational Biology; D009812:Odorants