Techniques for temporal detection of neural sensitivity to external stimulation
EntityUAM. Departamento de Ingeniería Informática
10.1007/s00422-009-0297-6Biological Cybernetics 100.4, (2009): 289-297
ISSN0340-1200 (print); 1432-0770 (online)
Funded byThis work was supported by the Spanish Government projects TIN 2007-65989 and Network CAM S-SEM-0255-2006.
ProjectComunidad de Madrid. S2006/SEM-0255/OLFACTOSENSE
SubjectsBayes test; Fisher test; Likelihood ratio test; Neural coding; Neural response; Olfaction; Sensitivity; Statistical testing; Informática
NoteThe final publication is available at Springer via http://dx.doi.org/10.1007/s00422-009-0297-6
Rights© The Author(s) 2009
Esta obra está bajo una Licencia Creative Commons Atribución 4.0 Internacional.
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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