Hostname: page-component-78c5997874-m6dg7 Total loading time: 0 Render date: 2024-11-08T14:29:50.720Z Has data issue: false hasContentIssue false
  • English
  • Français

Dissociating early and late visual processing via the Ebbinghaus illusion

Published online by Cambridge University Press:  21 November 2016

FILIPP SCHMIDT ,
ANDREAS WEBER  and
ANKE HABERKAMP
FILIPP SCHMIDT*
Affiliation:
Department of General Psychology, Justus-Liebig-University Giessen, D-35394 Giessen, Germany Department of Experimental Psychology, University of Kaiserslautern, D-67663 Kaiserslautern, Germany
ANDREAS WEBER
Affiliation:
Department of Experimental Psychology, University of Kaiserslautern, D-67663 Kaiserslautern, Germany
ANKE HABERKAMP
Affiliation:
Department of Clinical Psychology and Psychotherapy, Philipps-University Marburg, D-35032 Marburg, Germany
*
*Address correspondence to: Filipp Schmidt, Department of General Psychology, Justus-Liebig-University Giessen, Otto-Behaghel-Strasse 10F, D-35394 Giessen, Germany. E-mail: [email protected]
Get access Rights & Permissions [Opens in a new window]

Abstract

Visual perception is not instantaneous; the perceptual representation of our environment builds up over time. This can strongly affect our responses to visual stimuli. Here, we study the temporal dynamics of visual processing by analyzing the time course of priming effects induced by the well-known Ebbinghaus illusion. In slower responses, Ebbinghaus primes produce effects in accordance with their perceptual appearance. However, in fast responses, these effects are reversed. We argue that this dissociation originates from the difference between early feedforward-mediated gist of the scene processing and later feedback-mediated more elaborate processing. Indeed, our findings are well explained by the differences between low-frequency representations mediated by the fast magnocellular pathway and high-frequency representations mediated by the slower parvocellular pathway. Our results demonstrate the potentially dramatic effect of response speed on the perception of visual illusions specifically and on our actions in response to objects in our visual environment generally.

Keywords

Time courseTemporal dynamicsFeedforward processingEbbinghaus illusionVisual illusions
Type
Research Article
Information
Visual Neuroscience , Volume 33 , 2016 , E016
Copyright
Copyright © Cambridge University Press 2016 

Access options

Get access to the full version of this content by using one of the access options below. (Log in options will check for institutional or personal access. Content may require purchase if you do not have access.)

References

Bullier, J. (2001). Integrated model of visual processing. Brain Research Reviews 36, 96–107.CrossRefGoogle ScholarPubMed
Cohen, J. (1988). Statistical Power Analysis for the Behavioral Sciences. Hillsdale, NJ: Lawrence Erlbaum Associates.Google Scholar
Busch, A. & Müller, H.J. (2004). The Ebbinghaus illusion modulates visual search for size-defined targets: Evidence for preattentive processing of apparent object size. Attention, Perception, & Psychophysics 66, 475–495.Google Scholar
de Brouwer, A.J., Brenner, E., Medendorp, W.P. & Smeets, J.B.J. (2014). Time course of the effect of the Müller–Lyer illusion on saccades and perceptual judgments. Journal of Vision 14(4), 1–11.CrossRefGoogle ScholarPubMed
Eriksen, C.W. & Schultz, D.W. (1979). Information processing in visual search: A continuous flow conception and experimental results. Perception & Psychophysics 25, 249–263.Google Scholar
Fang, F., Boyaci, H., Kersten, D. & Murray, S.O. (2008). Attention-dependent representation of a size illusion in human V1. Current Biology 18, 1707–1712.Google Scholar
Foster, R.M. & Franz, V.H. (2014). Superadditivity of the Ebbinghaus and Müller–Lyer illusions depends on the method of comparison used. Perception 43, 783–795.Google Scholar
Franz, V.H. & Gegenfurtner, K.R. (2008). Grasping visual illusions: consistent data and no dissociation. Cognitive Neuropsychology 25, 920–950.CrossRefGoogle ScholarPubMed
Hegdé, J. (2008). Time course of visual perception: Coarse-to-fine processing and beyond. Progress in Neurobiology 84, 405–439.Google Scholar
Hochstein, S. & Ahissar, M. (2002). View from the top: Hierarchies and reverse hierarchies in the visual system. Neuron 36, 791–804.CrossRefGoogle ScholarPubMed
Howe, C.Q. & Purves, D. (2005). Perceiving Geometry: Geometrical Illusions Explained by Natural Scene Statistics. New York, NY: Springer Science & Business Media.Google Scholar
Hughes, H.C., Nozawa, G. & Kitterle, F. (1996). Global precedence, spatial frequency channels, and the statistics of natural images. Journal of Cognitive Neuroscience 8, 197–230.Google Scholar
Klotz, W. & Wolff, P. (1995). The effect of a masked stimulus on the response to the masking stimulus. Psychological Research 58, 92–101.Google Scholar
Lamme, V.A.F. & Roelfsema, P.R. (2000). The distinct modes of vision offered by feedforward and recurrent processing. Trends in Neurosciences 23, 571–579.Google Scholar
Legge, G.E. (1978). Sustained and transient mechanisms in human vision: Temporal and spatial properties. Vision Research 18, 69–81.CrossRefGoogle ScholarPubMed
Levine, T.R. & Hullett, C.R. (2002). Eta squared, partial eta squared, and misreporting of effect size in communication research. Human Communication Research 28, 612–625.Google Scholar
Malcolm, G.L., Nuthmann, A. & Schyns, P.G. (2014). Beyond gist strategic and incremental information accumulation for scene categorization. Psychological Science 25, 1087–1097.Google Scholar
Murray, S.O., Boyaci, H. & Kersten, D. (2006). The representation of perceived angular size in human primary visual cortex. Nature Neuroscience 9, 429–434.Google Scholar
Nowak, L.G. & Bullier, J. (1997). The timing of information transfer in the visual system. In Extrastriate Visual Cortex in Primates, Vol. 12, ed. Rockland, K.S., Kaas, J.H. & Peters, A., pp. 205–241. New York: Plenum Press.Google Scholar
Ögmen, H. & Breitmeyer, B.G. (2006). The First Half Second: Temporal Dynamics of Conscious and Unconscious Visual Processing. Cambridge, MA: MIT Press.Google Scholar
Oyama, T. & Morikawa, K. (1985). Temporal development of optical illusions. In Contemporary Psychology: Biological Processes and Theoretical Issues, ed. McGaugh, J.L., pp. 385–393. Amsterdam: North-Holland.Google Scholar
Piaget, J. (1969). The Mechanisms of Perception. London: Routledge and Kegan Paul.Google Scholar
Ratcliff, R. (1979). Group reaction time distributions and an analysis of distribution statistics. Psychological Bulletin 86, 446–461.Google Scholar
Roelfsema, P.R. (2006). Cortical algorithms for perceptual grouping. Annual Reviews in Neuroscience 29, 203–227.CrossRefGoogle ScholarPubMed
Rose, D. & Bressan, P. (2002). Going round in circles: Shape effects in the Ebbinghaus illusion. Spatial Vision 15, 191–203.Google Scholar
Schmidt, F. & Haberkamp, A. (2016). Temporal processing characteristics of the Ponzo illusion. Psychological Research 80, 273–285.Google Scholar
Schmidt, F., Haberkamp, A. & Schmidt, T. (2011a). Dos and don’ts in response priming research. Advances in Cognitive Psychology 7, 120–131.Google Scholar
Schmidt, F. & Schmidt, T. (2014). Rapid processing of closure and viewpoint-invariant symmetry: behavioral criteria for feedforward processing. Psychological Research 78, 37–54.Google Scholar
Schmidt, T., Haberkamp, A., Veltkamp, G.M., Weber, A., Seydell-Greenwald, A. & Schmidt, F. (2011b). Visual processing in rapid-chase systems: Image processing, attention, and awareness. Frontiers in Psychology 2, 169.CrossRefGoogle ScholarPubMed
Schmidt, T. & Vorberg, D. (2006). Criteria for unconscious cognition: Three types of dissociation. Perception & Psychophysics 68(3), 489–504.Google Scholar
Song, C., Schwarzkopf, D.S. & Rees, G. (2011). Interocular induction of illusory size perception. BMC Neuroscience 12(27), 1–9.Google Scholar
Sugihara, T., Qiu, F.T. & von der Heydt, R. (2011). The speed of context integration in the visual cortex. Journal of Neurophysiology 106, 374–385.Google Scholar
van Zoest, W. & Hunt, A.R. (2011). Saccadic eye movements and perceptual judgments reveal a shared visual representation that is increasingly accurate over time. Vision Research 51, 111–119.Google Scholar
van Zoest, W., Hunt, A.R. & Kingstone, A. (2010). Representations in visual cognition: It’s about time. Current Directions in Psychological Science 19, 116–120.Google Scholar
Vorberg, D., Mattler, U., Heinecke, A., Schmidt, T. & Schwarzbach, J. (2003). Different time courses for visual perception and action priming. Proceedings of the National Academy of Sciences 100, 6275–6280.Google Scholar