The Neural Dynamics of Visual Processing in Monkey Extrastriate Cortex: A Comparison between Univariate and Multivariate Techniques

  • Maxime Cauchoix
  • Ali Bilgin Arslan
  • Denis Fize
  • Thomas Serre
Part of the Lecture Notes in Computer Science book series (LNCS, volume 7263)

Abstract

Understanding the brain mechanisms underlying invariant visual recognition has remained a central tenet of cognitive neuroscience. Much of our current understanding of this process is based on knowledge gained from visual areas studied individually. Previous electrophysiology studies have emphasized the role of the ventral stream of the visual cortex in shape processing and, in particular, of higher level visual areas in encoding abstract category information. Surprisingly, relatively little is known about the precise dynamics of visual processing along the ventral stream of the visual cortex. Here we recorded intracranial field potentials (IFPs) from multiple intermediate areas of the ventral stream of the visual cortex in two behaving monkeys engaged in a rapid face categorization task. Using multivariate pattern analysis (MVPA) techniques, we quantified at millisecond precision the face category information conveyed by IFPs in areas of the ventral stream. We further investigate the relationship between the selectivity and latency of individual electrodes as estimated with classical univariate vs. multivariate techniques and conclude on the similarity and differences between the two approaches.

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References

  1. 1.
    Carlson, T.A., Hogendoorn, H., Kanai, R., Mesik, J., Turret, J.: High temporal resolution decoding of object position and category. Journal of Vision 11(10), 9, 1–17 (2011)CrossRefGoogle Scholar
  2. 2.
    Crouzet, S.M., Kircher, H., Thorpe, S.J.: Fast saccades toward faces: Face detection in just 100 ms. Journal of Vision 10(4), 1–17 (2010)CrossRefGoogle Scholar
  3. 3.
    Fize, D., Cauchoix, M., Fabre-Thorpe, M.: Humans and monkeys share visual representations. Proceedings of the National Academy of Sciences of the United States of America 108(18), 7635–7640 (2011)CrossRefGoogle Scholar
  4. 4.
    Freedman, D.J., Riesenhuber, M., Poggio, T., Miller, E.K.: Categorical representation of visual stimuli in the primate prefrontal cortex. Science 291(5502), 312–316 (2001)CrossRefGoogle Scholar
  5. 5.
    Freedman, D.J., Riesenhuber, M., Poggio, T., Miller, E.K.: A comparison of primate prefrontal and inferior temporal cortices during visual categorization. The Journal of Neuroscience 23(12), 5235–5246 (2003)Google Scholar
  6. 6.
    Freiwald, W.A., Tsao, D.Y.: Functional compartmentalization and viewpoint generalization within the macaque face-processing system. Science 330(6005), 845–851 (2010)CrossRefGoogle Scholar
  7. 7.
    Girard, P., Jouffrais, C., Kirchner, C.H.: Ultra-rapid categorisation in non-human primates. Animal Cognition 11(3), 485–493 (2008)CrossRefGoogle Scholar
  8. 8.
    Hung, C.P., Kreiman, G., Poggio, T., DiCarlo, J.J.: Fast readout of object identity from macaque inferior temporal cortex. Science 310(5749), 863–866 (2005)CrossRefGoogle Scholar
  9. 9.
    Kiani, R., Esteky, H., Tanaka, K.: Differences in onset latency of macaque inferotemporal neural responses to primate and non-primate faces. Journal of Neurophysiology 94(2), 1587–1596 (2005)CrossRefGoogle Scholar
  10. 10.
    Kriegeskorte, N., Mur, M., Ruff, D.A., Kiani, R., Bodurka, J., Esteky, H., Tanaka, K., Bandettini, P.A.: Matching categorical object representations in inferior temporal cortex of man and monkey. Neuron 60(6), 1126–1141 (2008)CrossRefGoogle Scholar
  11. 11.
    Liu, H., Madsen, J.R., Agam, Y., Kreiman, G.: Timing, timing, timing: Fast decoding of object information from intracranial field potentials in human visual cortex. Neuron 62(2), 281–290 (2009)CrossRefGoogle Scholar
  12. 12.
    Logothetis, N.K., Sheinberg, D.L.: Visual object recognition. Annual Review of Neuroscience 19(1), 577–621 (1996)CrossRefGoogle Scholar
  13. 13.
    Pasupathy, A., Connor, C.E.: Population coding of shape in area V4. Nature Neuroscience 5(12), 1332–1338 (2002)CrossRefGoogle Scholar
  14. 14.
    Pinto, N., DiCarlo, J.: How far can you get with a modern face recognition test set using only simple features? In: Vision and Pattern Recognition, pp. 2591–2598 (2009)Google Scholar
  15. 15.
    Pitcher, D., Walsh, V., Duchaine, B.: The role of the occipital face area in the cortical face perception network. Experimental Brain Research 209(4), 481–493 (2011)CrossRefGoogle Scholar
  16. 16.
    Riesenhuber, M., Poggio, T.: Hierarchical models of object recognition in cortex. Nature Neuroscience 2(11), 1019–1025 (1999)CrossRefGoogle Scholar
  17. 17.
    Sigala, N., Logothetis, N.K.: Visual categorization shapes feature selectivity in the primate temporal cortex. Nature 415(6869), 318–320 (2002)CrossRefGoogle Scholar
  18. 18.
    Tanaka, K.: Inferotemporal cortex and object recognition. Annual Review of Neuroscience 19, 109–139 (1996)CrossRefGoogle Scholar
  19. 19.
    Thorpe, S., Fize, D., Marlot, C.: Speed of processing in the human visual system. Letters to Nature 381, 520–522 (1996)CrossRefGoogle Scholar
  20. 20.
    Tsuchiya, N., Kawasaki, H., Oya, H., Howard, M.A., Adolphs, R.: Decoding face information in time, frequency and space from direct intracranial recordings of the human brain. PloS One 3(12), e3892 (2008)CrossRefGoogle Scholar
  21. 21.
    Ungerleider, L.G., Bell, A.H.: Uncovering the visual ”alphabet”: advances in our understanding of object perception. Vision Research 51(7), 782–799 (2011)CrossRefGoogle Scholar

Copyright information

© Springer-Verlag Berlin Heidelberg 2012

Authors and Affiliations

  • Maxime Cauchoix
    • 1
    • 2
  • Ali Bilgin Arslan
    • 3
  • Denis Fize
    • 1
    • 2
  • Thomas Serre
    • 3
  1. 1.Faculté de médecine de PurpanCNRS, CerCoToulouseFrance
  2. 2.Université de Toulouse, UPS, CerCoToulouseFrance
  3. 3.Department of Cognitive, Linguistic and Psychological Sciences, Brown Institute for Brain ScienceBrown UniversityProvidenceUSA

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