Contrast saturation in a neuronally-based model of elementary motion detection

Zuley Rivera-Alvidrez, Charles M. Higgins

Research output: Contribution to journalArticle

5 Scopus citations

Abstract

The Hassenstein-Reichardt (HR) correlation model is commonly used to model elementary motion detection in the fly. Recently, a neuronally-based computational model was proposed which, unlike the HR model, is based on identified neurons. The response of both models increases as the square of contrast, although the response of insect neurons saturates at high contrasts. We introduce a saturating nonlinearity into the neuronally-based model in order to produce contrast saturation and discuss the neuronal implications of these elements. Furthermore, we show that features of the contrast sensitivity of movement-detecting neurons are predicted by the modified model.

Original languageEnglish (US)
Pages (from-to)173-179
Number of pages7
JournalNeurocomputing
Volume65-66
Issue numberSPEC. ISS.
DOIs
StatePublished - Jun 1 2005

Keywords

  • Contrast saturation
  • Contrast sensitivity functions
  • Elementary motion detection
  • Fly
  • Neuronally-based model
  • Vision

ASJC Scopus subject areas

  • Computer Science Applications
  • Cognitive Neuroscience
  • Artificial Intelligence

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