Techniques for temporal detection of neural sensitivity to external stimulation
Entity
UAM. Departamento de Ingeniería InformáticaPublisher
Springer-VerlagDate
2009-04-01Citation
10.1007/s00422-009-0297-6
Biological Cybernetics 100.4, (2009): 289-297
ISSN
0340-1200 (print); 1432-0770 (online)DOI
10.1007/s00422-009-0297-6Funded by
This work was supported by the Spanish Government projects TIN 2007-65989 and Network CAM S-SEM-0255-2006.Project
Comunidad de Madrid. S2006/SEM-0255/OLFACTOSENSEEditor's Version
http://dx.doi.org/10.1007/s00422-009-0297-6Subjects
Bayes test; Fisher test; Likelihood ratio test; Neural coding; Neural response; Olfaction; Sensitivity; Statistical testing; InformáticaNote
The final publication is available at Springer via http://dx.doi.org/10.1007/s00422-009-0297-6Rights
© The Author(s) 2009Abstract
We propose a simple measure of neural sensitivity for characterizing stimulus coding. Sensitivity is defined as the fraction of neurons that show positive responses to n stimuli out of a total of N. To determine a positive response, we propose two methods: Fisherian statistical testing and a data-driven Bayesian approach to determine the response probability of a neuron. The latter is non-parametric, data-driven, and captures a lower bound for the probability of neural responses to sensory stimulation. Both methods are compared with a standard test that assumes normal probability distributions. We applied the sensitivity estimation based on the proposed method to experimental data recorded from the mushroom body (MB) of locusts. We show that there is a broad range of sensitivity that the MB response sweeps during odor stimulation. The neurons are initially tuned to specific odors, but tend to demonstrate a generalist behavior towards the end of the stimulus period, meaning that the emphasis shifts from discrimination to feature learning.
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Google Scholar:Rodríguez Ortiz, Francisco Borja
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Huerta, Ramón
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