Stochastic Correlative Firing for Figure-Ground Segregation

Biol Cybern. 2005 Mar;92(3):192-8. doi: 10.1007/s00422-005-0544-4. Epub 2005 Mar 5.

Abstract

Segregation of sensory inputs into separate objects is a central aspect of perception and arises in all sensory modalities. The figure-ground segregation problem requires identifying an object of interest in a complex scene, in many cases given binaural auditory or binocular visual observations. The computations required for visual and auditory figure-ground segregation share many common features and can be cast within a unified framework. Sensory perception can be viewed as a problem of optimizing information transmission. Here we suggest a stochastic correlative firing mechanism and an associative learning rule for figure-ground segregation in several classic sensory perception tasks, including the cocktail party problem in binaural hearing, binocular fusion of stereo images, and Gestalt grouping in motion perception.

Publication types

  • Research Support, Non-U.S. Gov't

MeSH terms

  • Acoustic Stimulation
  • Action Potentials / physiology
  • Afferent Pathways / physiology*
  • Animals
  • Auditory Perception / physiology
  • Brain / physiology*
  • Contrast Sensitivity / physiology
  • Functional Laterality / physiology
  • Humans
  • Learning / physiology
  • Models, Neurological
  • Motion Perception / physiology
  • Neurons / physiology
  • Pattern Recognition, Visual / physiology
  • Perception / physiology*
  • Photic Stimulation
  • Sensory Thresholds / physiology
  • Sound Localization / physiology
  • Stochastic Processes
  • Vision, Binocular / physiology