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Using Computational Models of Object Recognition to Investigate Representational Change Through Development

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Book cover Representation and Reality in Humans, Other Living Organisms and Intelligent Machines

Part of the book series: Studies in Applied Philosophy, Epistemology and Rational Ethics ((SAPERE,volume 28))

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Abstract

Empirical research on mental representation is challenging because internal representations are not available to direct observation. This chapter will show how empirical results from developmental studies, and insights from computational modelling of those results, can be combined with existing research on adults. So together all these research perspectives can provide convergent evidence for how visual representations mediate object recognition. Recent experimental studies have shown that development towards adult performance levels in configural processing in object recognition is delayed through middle childhood. Whilst part-changes to animal and artefact stimuli are processed with similar to adult levels of accuracy from 7 years of age, relative size changes to stimuli result in a significant decrease in relative performance for participants aged between 7 and 10. Two sets of computational experiments were run using the JIM3 artificial neural network with adult and ‘immature’ versions to simulate these results. One set progressively decreased the number of neurons involved in the representation of view-independent metric relations within multi-geon objects. A second set of computational experiments involved decreasing the number of neurons that represent view-dependent (non-relational) object attributes in JIM3’s surface map. The simulation results which show the best qualitative match to empirical data occurred when artificial neurons representing metric-precision relations were entirely eliminated. These results therefore provide further evidence for the late development of relational processing in object recognition and suggest that children in middle childhood may recognise objects without forming structural description representations.

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References

  1. Abecassis, M., Sera, M.D., Yonas, A., Schwade, J.: What’s in a shape? children represent shape variability differently than adults when naming objects. J. Exp. Child Psychol. 78, 213–239 (2001)

    Article  Google Scholar 

  2. Barenholtz, E., Tarr, M.J.: Reconsidering the role of structure in vision. In: Markman, A., Ross, B. (eds.) The Psychology of Learning and Motivation, vol. 47. Elsevier, Amsterdam (2006)

    Google Scholar 

  3. Barenholtz, E., Tarr, M.J.: Visual judgment of similarity across shape transformations: evidence for a compositional model of articulated objects. Acta Psychol. 128, 331–338 (2008)

    Article  Google Scholar 

  4. Biederman, I.: Recognition by components: a theory of human image understanding. Psychol. Rev. 94, 115–147 (1987)

    Article  Google Scholar 

  5. Biederman, I., Bar, M.: One shot viewpoint invariance in matching novel objects. Vis. Res. 39, 2885–2889 (1999)

    Article  Google Scholar 

  6. Biederman, I., Gerhardstein, P.C.: Recognising depth rotated objects: evidence and conditions for three-dimensional viewpoint invariance. J. Exp. Psychol. Hum. Percept. Perform. 19, 1162–1182 (1993)

    Article  Google Scholar 

  7. Biederman, I., Gerhardstein, P.C.: Viewpoint dependent mechanisms in visual object recognition: reply to Tarr and Bulthoff. J. Exp. Psychol. Hum. Percept. Perform. 21, 1506–1514 (1995)

    Article  Google Scholar 

  8. Bulthoff, H.H., Edelman, S.: Psychophysical support for a two-dimensional view interpolation theory of object recognition. Proc. Natl. Acad. Sci. U.S.A. 89, 60–64 (1992)

    Article  Google Scholar 

  9. Davidoff, J., Roberson, D.: A theory of the discovery and predication of relational concepts. J. Exp. Child Psychol. 85, 217–234 (2002)

    Article  Google Scholar 

  10. Davidoff, J., Warrington, E.K.: The bare bones of object recognition: implications from a case of object recognition impairment. Neuropsychologia 26, 279–292 (1999)

    Article  Google Scholar 

  11. Davidoff, J., Warrington, E.K.: A particular difficulty in discriminating between mirror images. Neuropsychologia 39, 1022–1036 (2001)

    Article  Google Scholar 

  12. Doumas, L., Holyoak, K., Hummel, J.: The problems of using associations to carry binding information. Behav. Brain Sci. 29, 74–75 (2006)

    Article  Google Scholar 

  13. Doumas, L., Hummel, J., Sandhofer, C.: A theory of the discovery and predication of relational concepts. Psychol. Rev. 115, 1–43 (2008)

    Article  Google Scholar 

  14. Flavell, J.H.: First discussant’s comment: what is memory development the development of? Hum. Dev. 14, 272–278 (1971)

    Article  Google Scholar 

  15. Foster, D., Gilson, S.: Recognizing novel three-dimensional objects by summing signals from parts and views. Proc. R. Soc. Lond. B 269, 1939–1947 (2002)

    Article  Google Scholar 

  16. Goodale, M.A., Milner, A.D.: Separate visual pathways for perception and action. Trends Neurosci. 15(1), 20–25 (1992)

    Article  Google Scholar 

  17. Hayward, W.: After the viewpoint debate: where next in object recognition. Trends Cogn. Sci. 7, 425–427 (2003)

    Article  Google Scholar 

  18. Hayward, W., Tarr, M.: Testing conditions for view point invariance in object recognition. J. Exp. Psychol. Hum. Percept. Perform. 23, 1511–1521 (1997)

    Article  Google Scholar 

  19. Heinke, D., Humphreys, G.W.: Attention, spatial representation and visual neglect: simulating emergent attention and spatial memory in the selective attention for identification model (SAIM). Psychol. Rev. 110, 29–87 (2003)

    Article  Google Scholar 

  20. Hummel, J.: Where view-based theories of human object recognition break down: the role of structure in human shape perception. In: Dietrich, E., Markman, A. (eds.) Cognitive Dynamics: Conceptual Change in Humans and Machines, pp. 157–185. Lawrence Erlbaum (2000)

    Google Scholar 

  21. Hummel, J.: Complementary solutions to the binding problem in vision: implications for shape perception and object recognition. Vis. Cogn. 8, 489–517 (2001)

    Article  Google Scholar 

  22. Hummel, J., Biederman, I.: Dynamic binding in a neural network for shape recognition. Psychol. Rev. 99, 480–517 (1992)

    Article  Google Scholar 

  23. Hummel, J., Stankiewicz, B.J.B.J.: Categorical relations in shape perception. Spat. Vis. 10, 201–236 (1996)

    Article  Google Scholar 

  24. Juttner, M., Muller, A., Rentschler, I.: A developmental dissociation of view-dependent and view-invariant object recognition in adolescence. Behav. Brain Res. 175, 420–424 (2006)

    Article  Google Scholar 

  25. Juttner, M., Petters, D., Wakui, E., Davidoff, J.: Late development of metric part-relational processing in object recognition. J. Exp. Psychol. Hum. Percept. Perform. 40, 1718–1734 (2014)

    Article  Google Scholar 

  26. Juttner, M., Wakui, E., Petters, D., Kaur, S., Davidoff, J.: Developmental trajectories for part-based and configural object recognition in adolescence. Dev. Psychol. 49(1), 161–176 (2013)

    Article  Google Scholar 

  27. Leek, E.C., Reppa, I., Arguin, M.: The structure of three-dimensional object representations in human vision: evidence from whole-part matching. J. Exp. Psychol. Hum. Percept. Perform. 31, 668–684 (2005)

    Article  Google Scholar 

  28. Logan, G.D.: Spatial attention and the apprehension of spatial relations. J. Exp. Psychol. Hum. Percept. Perform. 20, 1015–1036 (1994)

    Article  Google Scholar 

  29. Marr, D., Nishihara, H.K.: Representation and recognition of the spatial organization of three-dimensional shapes. Proc. R. Soc. Lond. B 200, 269–294 (1978)

    Article  Google Scholar 

  30. Olshausen, B., Anderson, C., Van Essen, D.: A neurobiological model of visual attention and invariant pattern recognition based on dynamic routing of information. J. Neurosci. 57, 4700–4719 (1993)

    Article  Google Scholar 

  31. Poggio, T., Edelman, S.: A network that learns to recognize three-dimensional objects. Nature 343, 263–266 (1990)

    Article  Google Scholar 

  32. Rentschler, I., Juttner, M., Osman, E., Mller, A., Caelli, T.: Development of configural 3D object recognition. Behav. Brain Res. 149, 107–111 (2004)

    Article  Google Scholar 

  33. Stankiewicz, B.: Empirical evidence for independent dimensions in the visual representation of three-dimensional shape. J. Exp. Psychol. Hum. Percept. Perform. 28, 913–932 (2002)

    Article  Google Scholar 

  34. Stankiewicz, B.J., Hummel, J.: Automatic priming for translation- and scale-invariant representations of object shape. Vis. Cogn. 6, 719–739 (2002)

    Article  Google Scholar 

  35. Stankiewicz, B.J., Hummel, J., Cooper, J.E.: The role of attention in priming for left-right reflections of object images: evidence for a dual representation s of object shape. J. Exp. Psychol. Hum. Percept. Perform. 24, 732–744 (1998)

    Article  Google Scholar 

  36. Sutherland, N.S.: Outlines of a theory of visual pattern recognition in animals and man. Proc. R. Soc. Lond. B 171, 95–103 (1968)

    Article  Google Scholar 

  37. Tarr, M., Bulthoff, H.: Is human object recognition better described by geon-structure-descriptions or by multiple views? J. Exp. Psychol. Hum. Percept. Perform. 21, 1494–1505 (1995)

    Article  Google Scholar 

  38. Tarr, M., Pinker, S.: Mental rotation and orientation dependence in shape recognition. Cogn. Psychol. 21, 233–282 (1989)

    Article  Google Scholar 

  39. Thoma, V., Davidoff, J.: Object recognition: attention and dual routes. In: Osaka, I., Rentschler, I., Biederman, I. (eds.) Object Recognition, Attention and Action

    Google Scholar 

  40. Thoma, V., Henson, R.N.: Object representations in ventral and dorsal visual streams: fMRI repetition effects depend on attention and part-whole configuration. Neuroimage 57, 513–525 (2011)

    Article  Google Scholar 

  41. Thomai, V., Davidoff, J.: Priming of depth-rotated objects depends on attention and part changes. Exp. Psychol. 53, 31–47 (2006)

    Article  Google Scholar 

  42. Thomai, V., Davidoff, J., Hummel, J.: Priming of plane-rotated objects depends on attention and view familiarity. Vis. Cogn. 15, 179–210 (2007)

    Article  Google Scholar 

  43. Thomai, V., Hummel, J., Davidoff, J.: Evidence for holistic representations of ignored images and analytic representations of attended images. J. Exp. Psychol. Hum. Percept. Perform. 30, 257–267 (2004)

    Article  Google Scholar 

  44. Triesman, A.M., Gelade, G.: A feature-integration theory of attention. Cogn. Psychol. 12, 97–136 (1980)

    Article  Google Scholar 

  45. Ullman, S.: Object representations in ventral and dorsal visual streams: fMRI repetition effects depend on attention and part-whole configuration. Cognition 32, 193–254 (1989)

    Article  Google Scholar 

  46. Ullman, S.: Three-dimensional object recognition based on the combination of views. Cognition 67, 21–44 (1998)

    Article  Google Scholar 

  47. van der Velde, F., de Kamps, M.: Neural blackboard architectures of combinatorial structures in cognition. Behav. Brain Sci. 29, 37–108 (2006)

    Google Scholar 

  48. Wolfe, J.M., Cave, K.R., Franzel, S.L.: Guided search: an alternative to the feature integration model for visual search. J. Exp. Psychol. Hum. Percept. Perform. 15, 419–433 (1989)

    Article  Google Scholar 

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Author information

Authors and Affiliations

  1. Birmingham City University, Birmingham, UK

    Dean Petters

  2. University of Illinios at Urbana-Champaign, Champaign, USA

    John Hummel

  3. University of Aston, Birmingham, UK

    Martin Jüttner

  4. University of East London, London, UK

    Elley Wakui

  5. Goldsmiths College, London, UK

    Jules Davidoff

Authors
  1. Dean Petters
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  2. John Hummel
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  3. Martin Jüttner
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  4. Elley Wakui
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  5. Jules Davidoff
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Corresponding author

Correspondence to Dean Petters .

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Editors and Affiliations

  1. Gothenburg, Sweden

    Gordana Dodig-Crnkovic

  2. Faculty of Philosophy, Pontifical Lateran University, Vatican City, Italy

    Raffaela Giovagnoli

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Petters, D., Hummel, J., Jüttner, M., Wakui, E., Davidoff, J. (2017). Using Computational Models of Object Recognition to Investigate Representational Change Through Development. In: Dodig-Crnkovic, G., Giovagnoli, R. (eds) Representation and Reality in Humans, Other Living Organisms and Intelligent Machines. Studies in Applied Philosophy, Epistemology and Rational Ethics, vol 28. Springer, Cham. https://doi.org/10.1007/978-3-319-43784-2_8

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  • DOI: https://doi.org/10.1007/978-3-319-43784-2_8

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  • Publisher Name: Springer, Cham

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