Stochastic correlative firing for figure-ground segregation

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.

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Correspondence to Zhe Chen.

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Chen, Z. Stochastic correlative firing for figure-ground segregation. Biol Cybern 92, 192–198 (2005). https://doi.org/10.1007/s00422-005-0544-4

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Keywords

  • Sensory Modality
  • Associative Learning
  • Learning Rule
  • Sensory Perception
  • Unify Framework