Hostname: page-component-8448b6f56d-42gr6 Total loading time: 0 Render date: 2024-04-16T22:25:15.630Z Has data issue: false hasContentIssue false
  • English
  • Français

S-cone signals invisible to the motion system can improve motion extraction via grouping by color

Published online by Cambridge University Press:  01 March 2009

JASNA MARTINOVIC ,
GEORG MEYER ,
MATTHIAS M. MÜLLER  and
SOPHIE M. WUERGER
JASNA MARTINOVIC
Affiliation:
School of Psychology, University of Liverpool, Liverpool, UK
GEORG MEYER
Affiliation:
School of Psychology, University of Liverpool, Liverpool, UK
MATTHIAS M. MÜLLER
Affiliation:
Institut für Psychologie I, Universität Leipzig, Leipzig, Germany
SOPHIE M. WUERGER*
Affiliation:
School of Psychology, University of Liverpool, Liverpool, UK
*
*Address correspondence and reprint requests to: Sophie M. Wuerger, School of Psychology, University of Liverpool, Eleanor Rathbone Building, Bedford Street South, Liverpool L69 7ZA, UK. E-mail: s.m.wuerger@liverpool.ac.uk
Get access Rights & Permissions [Opens in a new window]

Abstract

The purpose of this study was to test whether color–motion correlations carried by a pure color difference (S-cone component only) can be used to improve global motion extraction. We also examined the neural markers of color–motion correlation processing in event-related potentials. Color and motion information was dissociated using a two-colored random dot kinematogram, wherein coherent motion and motion noise differed from each other only in their S-cone component, with spatial and temporal parameters set so that global motion processing relied solely on a constant L-M component. Hence, when color and the local motion direction are correlated, more efficient segregation of coherent motion can only be brought about by the S-cone difference, and crucially, this S-cone component does not provide any effective input to a global motion mechanism but only changes the color appearance of the moving dots. The color contrasts (vector length in the S vs. L-M plane) of both the dots carrying coherent motion and the dots moving randomly were fixed at motion discrimination threshold to ensure equal effectiveness for motion extraction. In the behavioral experiment, participants were asked to discriminate between coherent and random motion, and d′ was determined for three different conditions: uncorrelated, uncued correlated, and cued correlated. In the electroencephalographic experiment, participants discriminated direction of motion for uncued correlated and cued correlated conditions. Color–motion correlations were found to improve performance. Cueing a specific color also modulated the N1 component of the event-related potential, with sources in visual area middle temporal. We conclude that S-cone signals “invisible” to the motion system can influence the analysis by direction-selective motion mechanisms through grouping of local motion signals by color. This grouping mechanism must precede motion processing and is likely to be under attentional control.

Keywords

S-conesMotionColorGroupingAttention
Type
Research Articles
Information
Visual Neuroscience , Volume 26 , Issue 2 , March 2009 , pp. 237 - 248
Copyright
Copyright © Cambridge University Press 2009

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

Bartels, A. & Zeki, S. (2000). The architecture of the colour centre in the human visual brain: New results and a review. European Journal of Neuroscience 12, 172–190.CrossRefGoogle ScholarPubMed
Becker, R., Ritter, P. & Villringer, A. (2008). Influence of ongoing alpha rhythm on the visual evoked potential. Neuroimage 39, 707–716.CrossRefGoogle ScholarPubMed
Blaser, E., Papathomas, T. & Vidnyanszky, Z. (2005). Binding of motion and colour is early and automatic. European Journal of Neuroscience 21, 2040–2044.CrossRefGoogle ScholarPubMed
Bosch-Bayard, J., Valdes-Sosa, P., Virues-Alba, T., Aubert-Vazquez, E., John, E.R., Harmony, T., Riera-Diaz, J. & Trujillo-Barreto, N. (2001). 3d statistical parametric mapping of eeg source spectra by means of variable resolution electromagnetic tomography (vareta). Clinical Electroencephalography 32, 47–61.CrossRefGoogle ScholarPubMed
Brainard, D. (1996). Cone contrast and opponent modulation color spaces. In Human Color Vision, ed. Kaiser, P.K. & Boynton, R.M., pp. 563–579. Washington, DC: Optical Society of America.Google Scholar
Braun, D.I., Mennie, N., Rasche, C., Schutz, A.C., Hawken, M.J. & Gegenfurtner, K.R. (2008). Smooth pursuit eye movements to isoluminant targets. Journal of Neurophysiology 100, 1287–1300.CrossRefGoogle ScholarPubMed
Corbetta, M. & Shulman, G.L. (2002). Control of goal-directed and stimulus-driven attention in the brain. Nature Reviews Neuroscience 3, 201–215.CrossRefGoogle ScholarPubMed
Croft, R.J. & Barry, R.J. (2000). Removal of ocular artifact from the EEG: A review. Neurophysiologie Clinique-Clinical Neurophysiology 30, 5–19.CrossRefGoogle ScholarPubMed
Croner, L.J. & Albright, T.D. (1997). Image segmentation enhances discrimination of motion in visual noise. Vision Research 37, 1415–1427.CrossRefGoogle ScholarPubMed
Cropper, S.J. & Wuerger, S.M. (2005). The perception of motion in chromatic stimuli. Behavioral and Cognitive Neuroscience Reviews 4, 192–217.CrossRefGoogle ScholarPubMed
Delorme, A. & Makeig, S. (2004). EEGLAB: An open source toolbox for analysis of single-trial EEG dynamics including independent component analysis. Journal of Neuroscience Methods 134, 9–21.CrossRefGoogle ScholarPubMed
Derrington, A.M., Krauskopf, J. & Lennie, P. (1984). Chromatic mechanisms in lateral geniculate nucleus of macaque. Journal of Physiology 357, 241–265.CrossRefGoogle ScholarPubMed
Eimer, M. (1993). Spatial cueing, sensory gating and selective response preparation: An ERP study of visuo-spatial orienting. Electroencephalography and Clinical Neurophysiology 88, 408–420.CrossRefGoogle ScholarPubMed
Eimer, M. (1994). “Sensory gating” as a mechanism for visuospatial orienting: Electrophysiological evidence from trial-by-trial cuing experiments. Perception & Psychophysics 55, 667–675.CrossRefGoogle ScholarPubMed
Eskew, R.T., McLellan, J. & Guilianini, F. (1999). Chromatic detection and discrimination. In Color Vision: From Genes to Perception, ed. Gegenfurtner, K. & Sharpe, L., pp. 345–368. Cambridge, UK: Cambridge University Press.Google Scholar
Evans, A.C., Collins, D.L., Mills, S.R., Brown, E.D., Kelly, R.L. & Peters, T.M. (1993). 3d statistical neuroanatomical models from 305 MRI volumes. In IEEE Nuclear Science Symposium and Medical Imaging Conference. MTP Press: London.Google Scholar
Gegenfurtner, K. (2001). Color in the cortex revisited. Nature Neuroscience 4, 339–340.CrossRefGoogle Scholar
Gegenfurtner, K.R. & Hawken, M.J. (1996). Interaction of motion and color in the visual pathways. Trends in Neurosciences 19, 394–401.CrossRefGoogle ScholarPubMed
Handy, T.C., ed. (2005). Event-Related Potentials: A Methods Handbook. Cambridge, MA: MIT Press.Google Scholar
Junghoefer, M., Elbert, T., Tucker, D.M. & Braun, C. (2000). Statistical control of artifacts in dense array EEG/MEG studies. Psychophysiology 37, 523–532.CrossRefGoogle Scholar
Kaiser, P.K. & Boyton, R.M. (1996). Human Color Vision. Washington, DC: Optical Society of America.Google Scholar
Khoe, W., Mitchell, J.F., Reynolds, J.H. & Hillyard, S.A. (2005). Exogenous attentional selection of transparent superimposed surfaces modulates early event-related potentials. Vision Research 45, 3004–3014.CrossRefGoogle ScholarPubMed
Li, H.-C.O. & Kingdom, F.A.A. (2001). Segregation by colour/luminance does not necessarily facilitate motion discrimination in noise. Perception & Psychophysics 63, 660–675.CrossRefGoogle Scholar
Logothetis, N.K., Schiller, P.H., Charles, E.R. & Hulbert, A.C. (1990). Perceptual deficits and the activity of the color-opponent and broad-band pathways at isoluminance. Science 247, 214–217.CrossRefGoogle ScholarPubMed
Lopez, M., Rodriguez, V. & Valdes-Sosa, M. (2004). Two-object attentional interference depends on attentional set. International Journal of Psychophysiology 53, 127–134.CrossRefGoogle ScholarPubMed
Lorenceau, J. & Alais, D. (2001). Form constraints in motion binding. Nature Neuroscience 4, 745–751.CrossRefGoogle ScholarPubMed
Lüschow, A. & Nothdurft, H.C. (1993). Pop-out of orientation but no pop-out of motion at isoluminance. Vision Research 33, 91–104.CrossRefGoogle ScholarPubMed
MacLeod, D.I.A. & Boynton, R.M. (1979). Chromaticity diagram showing cone excitation by stimuli of equal luminance. Journal of the Optical Society of America 69, 1183–1186.CrossRefGoogle ScholarPubMed
Macmillan, N.A. & Creelman, C.D. (1991). Detection theory: A user’s guide. New York: Cambridge University Press.Google Scholar
Michna, M.L. & Mullen, K.T. (2008). The contribution of color to global motion processing. Journal of Vision 8, 12.CrossRefGoogle ScholarPubMed
Morand, S., Thut, G., Grave de Peralta, R., Clarke, S., Khateb, A., Landis, T. & Michel, C.M. (2000). Electrophysiological evidence for fast visual processing through the human koniocellular pathway when stimuli move. Cerebral Cortex 10, 817–825.CrossRefGoogle ScholarPubMed
Moutoussis, K. & Zeki, S. (1997). Functional segregation and temporal hierarchy of the visual perceptive systems. Proceedings of the Royal Society of London B 264, 1–8.CrossRefGoogle ScholarPubMed
Movshon, J.A., Adelson, E.H., Gizzi, M.S. & Newsome, W.T. (1986). The analysis of moving visual patterns. Experimental Brain Research 11, 117–152.Google Scholar
Müller, H.J. & Rabbitt, P.M.A. (1989). Reflexive and voluntary orienting of visual attention—Time course of activation and resistance to interruption. Journal of Experimental Psychology-Human Perception and Performance 15, 315–330.CrossRefGoogle ScholarPubMed
Müller, M.M., Andersen, S., Trujillo, N.J., Valdes-Sosa, P., Malinowski, P. & Hillyard, S.A. (2006). Feature-selective attention enhances color signals in early visual areas of the human brain. Proceedings of the National Academy of Sciences of the United States of America 103, 14250–14254.CrossRefGoogle ScholarPubMed
Pinilla, T., Cobo, A., Torres, K. & Valdes-Sosa, M. (2001). Attentional shifts between surfaces: Effects on detection and early brain potentials. Vision Research 41, 1619–1630.CrossRefGoogle ScholarPubMed
Porciatti, V. & Sartucci, F. (1999). Normative data for onset VEPs to red-green and blue-yellow chromatic contrast. Clinical Neurophysiology 110, 772–781.CrossRefGoogle ScholarPubMed
Rodriguez, V. & Valdes-Sosa, M. (2006). Sensory suppression during shifts of attention between surfaces in transparent motion. Brain Research 1072, 110–118.CrossRefGoogle ScholarPubMed
Ruppertsberg, A., Wuerger, S.M. & Bertamini, M. (2003). The chromatic input to global motion perception. Visual Neuroscience 20, 421–428.CrossRefGoogle ScholarPubMed
Ruppertsberg, A., Wuerger, S.M. & Bertamini, M. (2007). When s-cones contribute to global motion perception. Visual Neuroscience 24, 1–8.CrossRefGoogle Scholar
Schütz, A.C., Braun, D.I., Kerzel, D. & Gegenfurtner, K.R. (2008). Improved visual sensitivity during smooth pursuit eye movements. Nature Neuroscience 11, 1211–1216.CrossRefGoogle ScholarPubMed
Shipp, S. & Zeki, S. (1995). Segregation and convergence of specialised pathways in macaque monkey visual cortex. Journal of Anatomy 187, 547–562.Google ScholarPubMed
Sincich, L.C. & Horton, J.C. (2005). The circuitry of V1 and V2: Integration of color, form, and motion. Annual Review of Neuroscience 28, 303–326.CrossRefGoogle ScholarPubMed
Sincich, L.C., Park, K.F., Wohlgemuth, M.J. & Horton, J.C. (2004). Bypassing V1: A direct geniculate input to area MT. Nature Neuroscience 7, 1123–1128.CrossRefGoogle ScholarPubMed
Spering, M. & Gegenfurtner, K.R. (2008). Contextual effects on motion perception and smooth pursuit eye movements. Brain Research 1225, 76–85.CrossRefGoogle ScholarPubMed
Thiele, A., Dobkins, K.R. & Albright, T.D. (1999). The contribution of color to motion processing in macaque middle temporal area. Journal of Neuroscience 19, 6571–6587.CrossRefGoogle ScholarPubMed
Tychsen, L. & Lisberger, S.G. (1986). Visual-motion processing for the initiation of smooth-pursuit eye movements in humans. Journal of Neurophysiology 56, 953–968.CrossRefGoogle ScholarPubMed
Valdes-Sosa, M., Bobes, M.A., Rodriguez, V., Acosta, Y., Perez, P., Iglesias, J. & Borrego, M. (2004). The influence of scene organisation on attention: Psychophysics and electrophysiology. In Attention and Performance xx: Functional Neuroimaging of Visual Cognition, ed. Kanwisher, N. & Duncan, J., pp. 321–344. Oxford: Oxford University Press.CrossRefGoogle Scholar
Valdes-Sosa, M., Bobes, M.A., Rodriguez, V. & Pinilla, T. (1998). Switching attention without shifting the spotlight object-based attentional modulation of brain potentials. Journal of Cognitive Neuroscience 10, 137–151.CrossRefGoogle ScholarPubMed
Vogel, E.K. & Luck, S.J. (2000). The visual N1 component is an index of a discrimination process. Psychophysiology 37, 190–203.CrossRefGoogle ScholarPubMed
Walsh, J.W.T. (1958). Photometry (3rd ed.). London: Constable & Co. Ltd.Google Scholar
Wandell, B.A., Poirson, A.B., Newsome, W.T., Baseler, H.A., Boynton, G.M., Huk, A., Gandhi, S. & Sharpe, L.T. (1999). Color signals in human motion-selective cortex. Neuron 24, 901–909.CrossRefGoogle ScholarPubMed
Watson, A.B. & Pelli, D. (1983). Quest: A Bayesian adaptive psychometric method. Perception & Psychophysics 33, 113–120.CrossRefGoogle Scholar
Wilmer, J.B. & Nakayama, K. (2007). Two distinct visual motion mechanisms for smooth pursuit: Evidence from individual differences. Neuron 54, 987–1000.CrossRefGoogle ScholarPubMed
Wolfe, J.M. (1998). Visual search. In Attention, ed. Pashler, H., pp. 13–73. London: University College London Press.Google Scholar
Worsley, K.J., Marrett, S., Neelin, P. & Evans, A.C. (1996). Searching scale space activation in pet images. Human brain mapping 4, 74–90.3.0.CO;2-M>CrossRefGoogle ScholarPubMed
Wuerger, S.M., Atkinson, P. & Cropper, S. (2005). The cone inputs to the unique-hue mechanisms. Vision Research 45, 3210.CrossRefGoogle Scholar
Wuerger, S.M. & Landy, M.S. (1993). Role of chromatic and luminance contrast in inferring structure from motion. Journal of the Optical Society of America A 10, 1363–1372.CrossRefGoogle ScholarPubMed
Wuerger, S.M., Watson, A.B. & Ahumada, A.J. (2002). Towards a spatio-chromatic standard observer for detection. In Human Vision and Electronic Imaging VII, ed. Rogowitz, B.E. & Pappas, T.N., pp. 159–172. San Jose, CA.CrossRefGoogle Scholar
Wyszecki, G. & Stiles, W.S. (2000). Color Science: Concepts and Methods, Quantitative Data and Formulae. New York: John Wiley & Sons.Google Scholar