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@inproceedings{726361, author = {Lánský, Petr and Pokora, Ondřej and Rospars, JeanandPierre}, address = {Berlin / Heidelberg}, booktitle = {Advances in Brain, Vision, and Artificial Intelligence, Lecture Notes in Computer Science 4729}, keywords = {neuronal coding}, howpublished = {tištěná verze "print"}, language = {eng}, location = {Berlin / Heidelberg}, isbn = {978-3-540-75554-8}, pages = {338-349}, publisher = {Springer}, title = {Stimulus-Response Curves in Sensory Neurons: How to Find the Stimulus Measurable with the Highest Precision}, url = {http://dx.doi.org/10.1007/978-3-540-75555-5_32}, year = {2007} }
TY - JOUR ID - 726361 AU - Lánský, Petr - Pokora, Ondřej - Rospars, Jean-Pierre PY - 2007 TI - Stimulus-Response Curves in Sensory Neurons: How to Find the Stimulus Measurable with the Highest Precision PB - Springer CY - Berlin / Heidelberg SN - 9783540755548 KW - neuronal coding UR - http://dx.doi.org/10.1007/978-3-540-75555-5_32 N2 - To study sensory neurons, the neuron response is plotted versus stimulus level. The aim of the present contribution is to determine how well two different levels of the incoming stimulation can be distinguished on the basis of their evoked responses. Two generic models of response function are presented and studied under the influence of noise. We show that the most suitable signal, from the point of view of its identification, is not unique. To obtain the best identification we propose to use measures based on Fisher information. For these measures, we show that the most identifiable signal may differ from that derived when the noise is neglected. ER -
LÁNSKÝ, Petr, Ondřej POKORA and Jean-Pierre ROSPARS. Stimulus-Response Curves in Sensory Neurons: How to Find the Stimulus Measurable with the Highest Precision. In \textit{Advances in Brain, Vision, and Artificial Intelligence, Lecture Notes in Computer Science 4729}. Berlin / Heidelberg: Springer, 2007, p.~338-349. ISBN~978-3-540-75554-8.
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