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Stochastic correlative firing for figure-ground segregation

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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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References

  • J-M Alonso WM Usrey RC Reid (1996) ArticleTitlePrecisely correlated firing in cells of the lateral geniculate nucleus Nature 383 815–819

    Google Scholar 

  • SM Anstis (1980) ArticleTitleThe perception of apparent movement Phil Trans R Soc Lond B290 153–168

    Google Scholar 

  • M Arbib (Eds) (1995) The handbook of brain theory and neural networks MIT Press Cambridge, MA

    Google Scholar 

  • JJ Atick (1992) ArticleTitleCan information theory provide an ecological theory of sensory processing Network 3 213–251 Occurrence Handle10.1088/0954-898X/3/2/009

    Article  Google Scholar 

  • DH Ballard GE Hinton TJ Sejnowski (1983) ArticleTitleParallel visual computation Nature 306 21–26

    Google Scholar 

  • S Becker GE Hinton (1992) ArticleTitleA self-organizing neural network that discovers surfaces in random-dot stereograms Nature 355 161–163

    Google Scholar 

  • AJ Bell TJ Sejnowski (1995) ArticleTitleAn information-maximization approach to blind separation and blind deconvolution Neural Comput 7 1129–1159

    Google Scholar 

  • BS Blais N Intrator H Shouval LN Cooper (1998) ArticleTitleReceptive field formation in natural scene environments: comparison of single cell learning rules Neural Comput 10 1797–1813

    Google Scholar 

  • AS Bregman (1990) Auditory scene analysis MIT Press Cambridge, MA

    Google Scholar 

  • GD Brown S Yamada TJ Sejnowski (2001) ArticleTitleIndependent component analysis at the neural cocktail party Trends Neurosci 24 54–63

    Google Scholar 

  • Chen Z, Haykin S (2004) Figure-ground segregation in sensory perception using a stochastic correlative learning rule. Technical Report, Adaptive Systems Lab, McMaster University, Hamilton, Canada

  • EC Cherry (1953) ArticleTitleSome experiments on the recognition of speech, with one and two ears J Acoust Soc Am 25 975–979

    Google Scholar 

  • JE Cook (1991) ArticleTitleCorrelated activity in the CNS: a role on every timescale? Trends Neurosci 14 397–401

    Google Scholar 

  • JJ Eggermont (1990) The correlative brain Springer Berlin Heidelberg New York

    Google Scholar 

  • DJ Field (1994) ArticleTitleWhat is the goal of sensory coding? Neural Comput 6 559–601

    Google Scholar 

  • S Geman D Geman (1984) ArticleTitleStochastic relaxation, Gibbs distributions, and the Bayesian restoration of images IEEE Trans Pattern Anal Mach Intell 6 721–741 Occurrence Handle0573.62030

    MATH  Google Scholar 

  • S Grossberg E Mingolla (1985) ArticleTitleNeural dynamics of perceptual grouping: textures, boundaries and emergent segmentations Percept Psychophys 38 141–171

    Google Scholar 

  • E Harth E Tzanakou (1974) ArticleTitleAlopex: a stochastic method for determining visual receptive fields Vision Res 14 1475–1482

    Google Scholar 

  • E Harth KP Unnikrishnan AS Pandya (1987) ArticleTitleThe inversion of sensory processing by feedback pathways: a model of visual cognitive functions Science 237 184–187

    Google Scholar 

  • S Haykin Z Chen S Becker (2004) ArticleTitleStochastic correlative learning algorithms IEEE Trans Signal Process 52 2200–2209

    Google Scholar 

  • DO Hebb (1949) The organization of behavior Wiley New York

    Google Scholar 

  • A Hyvärinen J Karhunen E Oja (2001) Independent component analysis Wiley New York

    Google Scholar 

  • B Julesz (1971) Foundations of cyclopean perception University of Chicago Press Chicago

    Google Scholar 

  • S Kirkpatrick CG Gelatt MP Vecchi (1983) ArticleTitleOptimization by simulated annealing Science 220 671–680 Occurrence Handle85f:90091

    MathSciNet  Google Scholar 

  • P König AK Engel (1995) ArticleTitleCorrelated firing in sensory-motor systems Curr Opin Neurobiol 5 511–519

    Google Scholar 

  • M Livingstone D Hubel (1988) ArticleTitleSegregation of form, color, movement, and depth: anatomy, physiology, and perception Science 240 740–749

    Google Scholar 

  • S Makeig T-P Jung AJ Bell D Ghahremani TJ Sejnowski (1997) ArticleTitleBlind separation of auditory event-related brain response into independent components Proc Natl Acad Sci USA 94 10979–10984

    Google Scholar 

  • D Marr T Poggio (1976) ArticleTitleCooperative computation of stereo disparity Science 194 283–287

    Google Scholar 

  • D Marr T Poggio (1979) ArticleTitleA computational theory of human stereo vision Proc R Soc Lond B 204 301–328

    Google Scholar 

  • KD Miller (1990) NoChapterTitle MA Gluck DE Rumelhart (Eds) Neuroscience and connectionist theory Erlbaum Hillsdale, NJ 267–353

    Google Scholar 

  • BA Olshausen DJ Field (1996) ArticleTitleEmergence of simple-cell receptive field properties by learning a sparse code for natural images Nature 381 607–609

    Google Scholar 

  • RP Rao (1999) ArticleTitleAn optimal estimation approach to visual perception and learning Vision Res 39 1963–1989

    Google Scholar 

  • W Singer (1993) ArticleTitleSynchronization of cortical activity and its putative role in information processing and learning Annu Rev Physiol 55 349–374 Occurrence Handle10.1146/annurev.ph.55.030193.002025 Occurrence Handle1:STN:280:ByyB387htV0%3D Occurrence Handle8466179

    Article  CAS  PubMed  Google Scholar 

  • O Sporns G Tononi GM Edelman (1991) ArticleTitleModeling perceptual grouping and figure-ground segregation by means of active reentrant connections Proc Natl Acad Sci USA 88 129–133

    Google Scholar 

  • E Tzanakou (2000) Supervised and unsupervised pattern recognition CRC Press Roca Raton, FL

    Google Scholar 

  • E Tzanakou R Michalak E Harth (1979) ArticleTitleThe Alopex process: visual receptive fields by response feedback Biol Cybern 35 161–174

    Google Scholar 

  • S Ullman (1979) The interpretation of visual motion MIT Press Cambridge, MA

    Google Scholar 

  • KP Unnikrishnan KP Venugopal (1994) ArticleTitleAlopex: a correlation-based learning algorithm for feedforward and recurrent neural networks Neural Comput 6 469–490

    Google Scholar 

  • Verri A, Straforini M, Torre V (1992) Computational aspects of motion perception in natural and artificial vision systems. Phil Trans R Soc Lond B pp 429–443

  • C Malsburg Particlevon der W Schneider (1986) ArticleTitleA neural cocktail-party processor Biol Cybern 54 29–40

    Google Scholar 

  • C Malsburg Particlevon der (1999) ArticleTitleThe what and why of binding: the modeler’s perspective Neuron 24 95–104

    Google Scholar 

  • AL Yuille NM Grzywacz (1988) ArticleTitleA computational theory for the perception of coherent visual motion Nature 335 71–74

    Google Scholar 

Download references

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Authors and Affiliations

  1. Adaptive Systems Lab, McMaster University, Hamilton, Canada, L8S 4K1

    Zhe Chen

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  1. Zhe Chen
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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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  • DOI: https://doi.org/10.1007/s00422-005-0544-4

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