Stimulus-Response Curves in Sensory Neurons: How to Find the Stimulus Measurable with the Highest Precision

  • Petr Lansky
  • Ondřej Pokora
  • Jean-Pierre Rospars
Part of the Lecture Notes in Computer Science book series (LNCS, volume 4729)


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 in these noisy cases 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.


Transfer Function Sensory Neuron Stimulus Intensity Optimality Criterion Fisher Information 
These keywords were added by machine and not by the authors. This process is experimental and the keywords may be updated as the learning algorithm improves.


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Copyright information

© Springer-Verlag Berlin Heidelberg 2007

Authors and Affiliations

  • Petr Lansky
    • 1
  • Ondřej Pokora
    • 1
    • 2
  • Jean-Pierre Rospars
    • 3
  1. 1.Institute of Physiology, Academy of Sciences of Czech Republic, Videnska 1083, 142 20 Prague 4Czech Republic
  2. 2.Department of Mathematics and Statistics, Faculty of Science, Masaryk University, Janackovo namesti 2a, 602 00 BrnoCzech Republic
  3. 3.UMR 1272 UMPC–INRA–AgroParisTech “Physiologie de l’Insecte Signalisation et Communication”, INRA, 78026 Versailles CedexFrance

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