Detection of stimuli from multi-neuron activity: Empirical study and theoretical implications

Nir Nossenson*, Ari Magal, Hagit Messer

*Corresponding author for this work

Research output: Contribution to journalArticlepeer-review

Abstract

We report on detection results obtained in 20 experiments in which the presence of an external auditory stimulus had to be detected from observing electrophysiological multi-unit activity in the brain stem of rats. The performance of the optimal Gaussian-signal-in-Gaussian-noise (model-based) detector is compared to that of the energy detector which is widely used in electrophysiology as well as in many other disciplines with similar signal characteristics. It is shown that the optimal model based detector is indeed superior, but the performance gap in favor of the optimal detector is substantial mainly in very low probabilities of false alarm errors. The performance of the energy detector is close to optimum in moderate and high probabilities of false alarm error. Furthermore, the energy detector is shown to be more resilient to isolated and short, yet intense disturbances. We discuss a conjecture inspired by the model underlying the optimal detector and the empirical results, that the neural tissue itself executes a modified energy detection scheme, and we review experimental results from the literature that allegedly support this conjecture.

Original languageEnglish
Pages (from-to)822-837
Number of pages16
JournalNeurocomputing
Volume174
DOIs
StatePublished - 22 Jan 2016

Keywords

  • Decision making
  • Electrophysiology
  • Gaussian signal in gaussian noise
  • Glutamate uptake rate
  • Multi unit activity
  • Stimulus detection

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