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Skeleton Model for the Neurodynamics of Visual Action Representations

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Artificial Neural Networks and Machine Learning – ICANN 2014 (ICANN 2014)

Part of the book series: Lecture Notes in Computer Science ((LNTCS,volume 8681))

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Abstract

The visual recognition of body motion in the primate brain requires the temporal integration of information over complex patterns, potentially exploiting recurrent neural networks consisting of shape- and optic-flow-selective neurons. The paper presents a mathematically simple neurodynamical model that approximates the mean-field dynamics of such networks. It is based on a two-dimensional neural field with appropriate lateral interaction kernel and an adaptation process for the individual neurons. The model accounts for a number of, so far not modeled, observations in the recognition of body motion, including perceptual multi-stability and the weakness of repetition suppression, as observed in single-cell recordings for the repeated presentation of action stimuli. In addition, the model predicts novel effects in the perceptual organization of action stimuli.

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References

  1. Blake, R., Shiffrar, M.: Perception of human motion. Annu. Rev. Psychol. 58, 47–73 (2007)

    Article  Google Scholar 

  2. Giese, M.A., Poggio, T.: Neural mechanisms for the recognition of biological movements. Nat. Rev. Neurosci. 4(3), 179–192 (2003)

    Article  Google Scholar 

  3. Barraclough, N.E., Keith, R.H., Xiao, D., Oram, M.W., Perrett, D.: Visual adaptation to goal-directed hand actions. J. Cogn. Neurosci. 21(9), 1806–1820 (2009)

    Article  Google Scholar 

  4. Singer, J.M., Sheinberg, D.: Temporal cortex neurons encode articulated actions as slow sequences of integrated poses. J. Neurosci. 30(8), 3133–3145 (2010)

    Article  Google Scholar 

  5. Vangeneugden, J., De Mazière, P.A., Van Hulle, M.M., Jaeggli, T., Van Gool, L., Vogels, R.: Distinct mechanisms for coding of visual actions in macaque temporal cortex. J. Neurosci. 31(2), 385–401 (2011)

    Article  Google Scholar 

  6. Caggiano, V., Fogassi, L., Rizzolatti, G., Pomper, J.K., Thier, P., Giese, M.A., Casile, A.: View-based encoding of actions in mirror neurons of area f5 in macaque premotor cortex. Curr. Biol. 21(2), 144–148 (2011)

    Article  Google Scholar 

  7. Dekeyser, M., Verfaillie, K.: Bistability and biasing effects in the perception of ambiguous point-light walkers. Perception 33(5), 547–560 (2004)

    Article  Google Scholar 

  8. Leopold, D.A., Logothetis, N.: Multistable phenomena: changing views in perception. Trends. Cogn. Sci. 3(7), 254–264 (1999)

    Article  Google Scholar 

  9. Grill-Spector, K., Henson, R., Martin, A.: Repetition and the brain: Neural models of stimulus-specific effects. Trends. Cogn. Sci. 10(1), 14–23 (2006)

    Article  Google Scholar 

  10. Caggiano, V., Pomper, J.K., Fleischer, F., Fogassi, L., Giese, M., Thier, P.: Mirror neurons in monkey area F5 do not adapt to the observation of repeated actions. Nat. Commun. 4, 1433 (2013)

    Article  Google Scholar 

  11. Kilner, J.M., Kraskov, A., Lemon, R.: Do monkey F5 mirror neurons show changes in firing rate during repeated observation of natural actions? J. Neurophysiol. 111(6), 1214–1226 (2013)

    Article  Google Scholar 

  12. De Baene, W., Vogels, R.: Effects of adaptation on the stimulus selectivity of macaque inferior temporal spiking activity and local field potentials. Cereb. Cortex. 20(9), 2145–2165 (2010)

    Article  Google Scholar 

  13. Marr, D., Vaina, L.: Representation and recognition of the movements of shapes. Proc. R. Soc. Lond. B Biol. Sci. 214(1197), 501–524 (1982)

    Article  Google Scholar 

  14. Jhuang, H., Garrote, E., Mutch, J., Yu, X., Khilnani, V., Poggio, T., Steele, A.D., Serre, T.: Automated home-cage behavioural phenotyping of mice. Nat. Commun. 1, 68 (2010)

    Article  Google Scholar 

  15. Kawamoto, A.H., Anderson, J.A.: A neural network model of multi-stable perception. Acta. Psy. 59, 35–65 (1985)

    Article  Google Scholar 

  16. Kelso, J.A.S.: Dynamic Patterns. MIT Press, Cambridge (1995)

    Google Scholar 

  17. Giese, M.A.: Dynamic Neural Field Theory for Motion Perception. Kluwer Academic Publishers, Dordrecht (1998)

    Google Scholar 

  18. Gigante, G., Mattia, M., Braun, J., Del Giudice, P.: Bistable perception modeled as competing stochastic integrations at two levels. Comput. Biol. 5(7), e1000430 (2009)

    Google Scholar 

  19. Amari, S.: Dynamics of pattern formation in lateral-inhibition type neural fields. Biol. Cybern. 27(2), 77–87 (1977)

    Article  MATH  MathSciNet  Google Scholar 

  20. Xie, X., Giese, M.: Nonlinear dynamics of direction-selective recurrent neural media. Phys. Rev. E. Stat. Nonlin. Soft. Matter. Phys. 65(5 Pt 1), 51904 (2002)

    Article  MathSciNet  Google Scholar 

  21. Cohen, M.R., Kohn, A.: Measuring and interpreting neuronal correlations. Nat. Neurosci. 14(7), 811–819 (2011)

    Article  Google Scholar 

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Authors and Affiliations

  1. Section Computational Sensomotorics, Dept. of Cognitive Neurology CIN & HIH, University Clinic Tübingen, Otfried-Müller-Str. 25, 72076, Tübingen, Germany

    Martin A. Giese

Authors
  1. Martin A. Giese
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Editors and Affiliations

  1. Department of Informatics, University of Hamburg, Vogt-Kölln-Straße 30, 22527, Hamburg, Germany

    Stefan Wermter , Cornelius Weber  & Sven Magg ,  & 

  2. Department of Informatics, Nicolaus Compernicus University, ul. Grudziądzka 5, 87-100, Torun, Poland

    Włodzisław Duch

  3. Department of Modern Languages, University of Helsinki, P.O. Box 24, 00014, Helsinki, Finland

    Timo Honkela

  4. Institute of Information and Communication Technologies, Bulgarian Academy of Sciences, Acad. G. Bonchev str. bl. 25A, 1113, Sofia, Bulgaria

    Petia Koprinkova-Hristova

  5. Institute of Neural Information Processing, University of Ulm, 89069, Oberer Eselsberg, Ulm, Germany

    Günther Palm

  6. Department of Information Systems, Quartier UNIL-Dorigny, Bâtiment Internef, University of Lausanne, 1015, Lausanne, Switzerland

    Alessandro E. P. Villa

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Giese, M.A. (2014). Skeleton Model for the Neurodynamics of Visual Action Representations. In: Wermter, S., et al. Artificial Neural Networks and Machine Learning – ICANN 2014. ICANN 2014. Lecture Notes in Computer Science, vol 8681. Springer, Cham. https://doi.org/10.1007/978-3-319-11179-7_89

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  • DOI: https://doi.org/10.1007/978-3-319-11179-7_89

  • Publisher Name: Springer, Cham

  • Print ISBN: 978-3-319-11178-0

  • Online ISBN: 978-3-319-11179-7

  • eBook Packages: Computer ScienceComputer Science (R0)

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