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Specificity of brain reactions to second-order visual stimuli

Published online by Cambridge University Press:  19 May 2015

VITALY V. BABENKO  and
PAVEL N. ERMAKOV
VITALY V. BABENKO*
Affiliation:
Department of Psychology, Southern Federal University, Rostov-on-Don, Russia
PAVEL N. ERMAKOV
Affiliation:
Department of Psychology, Southern Federal University, Rostov-on-Don, Russia
*
*Address correspondence to: Vitaly V. Babenko, Department of Psychology, Southern Federal University, Nagibina 13, Rostov-on-Don, 344038, Russia. E-mail: [email protected]
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Abstract

The second-order visual mechanisms perform the operation of integrating the spatially distributed local visual information. Their organization is traditionally considered within the framework of the filter-rectify-filter model. These are the second-order filters that provide the ability to detect texture gradients. However, the question of the mechanisms' selectivity to the modulation dimension remains open. The aim of this investigation is to answer the above question by using visual evoked potentials (VEPs). Stimuli were textures consisting of staggered Gabor patches. The base texture was nonmodulated (NM). Three other textures represented the base texture which was sinusoidally modulated in different dimensions: contrast, orientation, or spatial frequency. EEG was recorded with 20 electrodes. VEPs of 500 ms duration were obtained for each of the four textures. After that, VEP to the NM texture was subtracted from VEP to each modulated texture. As a result, three different waves (d-waves) were obtained for each electrode site. Each d-wave was then averaged across all the 48 observers. The revealed d-waves have a latency of about 200 ms and, in our opinion, reflect the second-order filters reactivation through the feedback connection. The d-waves for different modulation dimensions were compared with each other in time, amplitude, topography, and localization of the sources of activity that causes the d-wave (with sLORETA). We proceeded from the assumption that the d-wave (its first component) represents functioning of the second-order visual mechanisms and activity changes at the following processing stages. It was found that the d-waves for different modulation dimensions significantly differ in all parameters. The obtained results indicate that the spatial modulations of different texture parameters caused specific changes in the brain activity, which could be evidence supporting the specificity of the second-order visual mechanisms to modulation dimension.

Keywords

VEPTextured-waveSecond-order mechanismsSpecificity
Type
Research Article
Information
Visual Neuroscience , Volume 32 , 2015 , E011
Copyright
Copyright © Cambridge University Press 2015 

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References

Albright, T.D. & Stoner, G.R. (2002). Contextual influences on visual processing. Annual Review of Neuroscience 25, 339–379.CrossRefGoogle ScholarPubMed
Babenko, V.V. (1989). A new approach to the problem of visual perception mechanisms. In Problems of Neurocybernetics, ed. Kogan, A.B., pp. 10–11. Rostov-on-Don, USSR: Rostov University Pub. (In Russian).Google Scholar
Babenko, V.V. (1990). Model of form discrimination channel. In Neuronet’90. International Symposium on Neural Networks and Neural Computing. pp. 27–29. Prague.Google Scholar
Babenko, V.V., Ermakov, P.N. & Bozhinskaya, M.A. (2010). Relationship between the spatial-frequency tuning of the first- and the second-order visual filters. Psychological Journal 31, 48–57. (In Russian).Google Scholar
Babenko, V.V. & Yavna, D.V. (2008). Specificity of the visual second-order mechanisms. Perception 37, 78–79.Google Scholar
Babenko, V., Yavna, D., Soloviev, A. & Miftakhova, M. (2011). Spatial selectivity of visual mechanisms sensitive to contrast modulation. Journal of Optical Technology 78, 771–776.CrossRefGoogle Scholar
Bach, M. & Meigen, T. (1999). Electrophysiological correlates of human texture segregation, an overview. Documenta Ophthalmologica 95, 335–347.CrossRefGoogle Scholar
Bach, M., Schmitt, C., Quenzer, T., Meigen, T. & Fahle, M. (2000). Summation of texture segregation across orientation and spatial frequency: Electrophysiological and psychophysical findings. Vision Research 40, 3559–3566.CrossRefGoogle ScholarPubMed
Baker, C. & Meese, T.S. (2014). Measuring the spatial extent of texture pooling using reverse correlation. Vision Research 97, 52–58.CrossRefGoogle ScholarPubMed
Buffalo, E.A., Fries, P., Landman, R., Liang, H. & Desimone, R. (2010). A backward progression of attentional effects in the ventral stream. Proceedings of the National Academy of Sciences of the United States of America 107, 361–365.CrossRefGoogle ScholarPubMed
Calvert, J., Manahilov, V., Simpson, W.A. & Parker, D.M. (2005). Human cortical responses to contrast modulations of visual noise. Vision Research 45, 2218–2230.CrossRefGoogle ScholarPubMed
Caputo, G. & Casco, C. (1999). A visual evoked potential correlate of global figure-ground segmentation. Vision Research 39, 1597–1610.CrossRefGoogle ScholarPubMed
Casco, C., Campana, G., Han, S. & Guzzon, D. (2009). Psychophysical and electrophysiological evidence of independent facilitation by collinearity and similarity in texture grouping and segmentation. Vision Research 49, 583–593.CrossRefGoogle ScholarPubMed
Chaudhuri, A. & Albright, T.D. (1997). Neuronal responses to edges defined by luminance vs. temporal texture in macaque area V1. Visual Neuroscience 14, 949–962.CrossRefGoogle ScholarPubMed
Chubb, C. & Landy, M.S. (1991). Orthogonal distribution analysis: A new approach to the study of texture perception. In Computational Models of Visual Processing, ed. Landy, M.S. & Movshon, J.A., pp. 291–301. Cambridge, MA: MIT Press.Google Scholar
Chubb, C. & Sperling, G. (1989). Two motion perception mechanisms revealed through distance-driven reversal of apparent motion. Proceedings of the National Academy of Sciences of the United States of America 86, 2985–2989.CrossRefGoogle ScholarPubMed
Cohen, E.H., Schnitzer, B.S., Gersch, T.M., Singh, M. & Kowler, E. (2007). The relationship between spatial pooling and attention in saccadic and perceptual tasks. Vision Research 47, 1907–1923.CrossRefGoogle ScholarPubMed
Corballis, P.M. (2003). Visuospatial processing and the right-hemisphere interpreter. Brain and Cognition 53, 171–176.CrossRefGoogle ScholarPubMed
Dakin, S.C. & Mareschal, I. (2000). Sensitivity to contrast modulation depends on carrier spatial frequency and orientation. Vision Research 40, 311–329.CrossRefGoogle ScholarPubMed
Das, A. & Gilbert, C.D. (1999). Topography of contextual modulations mediated by short-range interactions in primary visual cortex. Nature 399, 655–661.CrossRefGoogle ScholarPubMed
De Weerd, P., Sprague, J.M., Raiguel, S., Vandenbussche, E. & Orban, G.A. (1993). Effects of visual cortex lesions on orientation discrimination of illusory contours in the cat. European Journal of Neuroscience 5, 1695–1710.CrossRefGoogle ScholarPubMed
De Weerd, P., Sprague, J.M., Vandenbussche, E. & Orban, G.A. (1994). Two stages in visual texture segregation: A lesion study in the cat. Journal of Neuroscience 14, 929–948.CrossRefGoogle ScholarPubMed
De Weerd, P., Desimone, R. & Underleider, L.G. (1996). Cue-dependent deficits in grating orientation discrimination after V4 lesions in macaques. Visual Neuroscience 13, 529–538.CrossRefGoogle ScholarPubMed
Demb, J.B., Zaghloul, K. & Sterling, P. (2001). Cellular basis for the response to second-order motion cues in Y retinal ganglion cells. Neuron 32, 711–721.CrossRefGoogle ScholarPubMed
Di Lollo, V., Kawahara, J., Zuvic, S.M. & Visser, T.A. (2001). The preattentive emperor has no clothes: A dynamic redressing. The Journal of experimental Psychology. General 130, 479–492.CrossRefGoogle ScholarPubMed
Duncan, J. & Humphreys, G.W. (1989). Visual search and stimulus similarity. Psychological Review 96, 433–458.CrossRefGoogle ScholarPubMed
Ellemberg, D., Allen, H.A. & Hess, R.F. (2006). Second-order spatial frequency and orientation channels in human vision. Vision Research 46, 2798–2803.CrossRefGoogle ScholarPubMed
Ellemberg, D., Lavoie, K., Lewis, T.L., Maurer, D., Lepore, F. & Guillemot, J.P.O. (2003). Longer VEP latencies and slower reaction times to the onset of second-order motion than to the onset of first-order motion. Vision Research 43, 651–658.CrossRefGoogle Scholar
El-Shamayleh, Y. & Movshon, J.A. (2011). Neuronal responses to texture-defined form in macaque visual area V2. Journal of Neuroscience 31, 8543–8555.CrossRefGoogle ScholarPubMed
Fahle, M., Quenzer, T., Braun, C. & Spang, K. (2003). Feature-specific electrophysiological correlates of texture segregation. Vision Research 43, 7–19.CrossRefGoogle ScholarPubMed
Gable, P.A., Poole, B.D., Cook, M.S. (2013). Asymmetrical hemisphere activation enhances global-local processing. Brain and Cognition 83, 337–341.CrossRefGoogle ScholarPubMed
Gegenfurtner, K.R., Kiper, D.C. & Levitt, J.B. (1997). Functional properties of neurons in macaque area V3. Journal of Neurophysiology 77, 1906–1923.CrossRefGoogle ScholarPubMed
Ghose, G.M. & Ts’o, D.Y. (1997). Form processing modules in primate area V4. Journal of Neurophysiology 77, 2191–2196.CrossRefGoogle ScholarPubMed
Gilbert, C.D. & Wiesel, T.N. (1989). Columnar specificity of intrinsic horizontal and corticocortical connections in cat visual cortex. Journal of Neuroscience 9, 2432–2442.CrossRefGoogle ScholarPubMed
Graham, N.V. (2011). Beyond multiple pattern analyzers modeled as linear filters (as classical V1 simple cells): Useful additions of the last 25 years. Vision Research 51, 1397–1430.CrossRefGoogle ScholarPubMed
Graham, N., Beck, J. & Sutter, A. (1992). Nonlinear processes in spatial-frequency channel models of perceived texture segregation: Effects of sign and amount of contrast. Vision Research 32, 719–743.CrossRefGoogle ScholarPubMed
Grosof, D.H., Shapley, R.H. & Hawken, M.J. (1993). Macaque V1 neurons can signal "illusory" contours. Nature 365, 550–552.CrossRefGoogle ScholarPubMed
Hirsch, J.A. & Gilbert, C.D. (1991). Synaptic physiology of horizontal connections in primary visual cortex. Journal of Neuroscience 11, 1800–1809.CrossRefGoogle Scholar
Kahneman, D. & Henik, A. (1981). Perceptual organization and attention. In Perceptual Organization, ed. Kubovi, M. & Pomerantz, J., pp. 181–211. Hillsdale, NJ: Erlbaum.Google Scholar
Kapadia, M.K., Ito, M., Gilbert, C.D. & Westheimer, G. (1995). Improvement in visual sensitivity by changes in local context: Parallel studies in human observers and in V1 of alert monkeys. Neuron 15, 843–856.CrossRefGoogle ScholarPubMed
Khoe, W., Freeman, E., Woldorff, M.G. & Mangun, G.R. (2004). Electrophysiological correlates of lateral interactions in human visual cortex. Vision Research 44, 1659–1673.CrossRefGoogle ScholarPubMed
Kingdom, F.A. & Keeble, D.R. (1999). On the mechanism for scale invariance in orientation-defined textures. Vision Research 39, 1477–1489.CrossRefGoogle ScholarPubMed
Kingdom, F.A., Prins, N. & Hayes, A. (2003). Mechanism independence for texture-modulation detection is consistent with a filter-rectify-filter mechanism. Visual Neuroscience 20, 65–76.CrossRefGoogle ScholarPubMed
Kotsoni, E., Csibra, G., Mareschal, D. & Johnson, M.Y. (2007). Electrophysiological correlates of common-onset visual masking. Neuropsychologia 45, 2285–2293.CrossRefGoogle ScholarPubMed
Lamme, V.A., Van Dijk, B.W. & Spekreijse, H. (1992). Texture segregation is processed by primary visual cortex in man and monkey. Evidence from VEP experiments. Vision Research 32, 797–807.CrossRefGoogle ScholarPubMed
Lamme, V.A., Van Dijk, B.W. & Spekreijse, H. (1994). Organization of contour from motion processing in primate visual cortex. Vision Research 34, 721–735.CrossRefGoogle ScholarPubMed
Landy, M.S. & Oruc, I. (2002). Properties of second-order spatial frequency channels. Vision Research 42, 2311–2329.CrossRefGoogle ScholarPubMed
Larsson, J., Landy, M.S. & Heeger, D.J. (2006). Orientation-selective adaptation to first- and second-order patterns in human visual cortex. Journal of Neurophysiology 95, 862–881.CrossRefGoogle ScholarPubMed
Logan, G.D. & Gordon, R.D. (2001). Executive control of visual attention in dual-task situations. Psychological Review 108, 393–434.CrossRefGoogle ScholarPubMed
Luck, S.J. (2005). An Introduction to the Event-related Potential Technique. Cognitive Neuroscience. Cambridge: MIT Press.Google Scholar
Lui, L.L., Bourne, J.A. & Rosa, M.G. (2007). Spatial summation, end inhibition and side inhibition in the middle temporal visual area (MT). Journal of Neurophysiology 97, 1135–1148.CrossRefGoogle ScholarPubMed
Mathes, B. & Fahle, M. (2007). The electrophysiological correlate of contour integration is similar for color and luminance mechanisms. Psychophysiology 44, 305–322.CrossRefGoogle ScholarPubMed
Mathes, B., Trenner, D. & Fahle, M. (2006). The electrophysiological correlate of contour integration is modulated by task demands. Brain Research 1114, 98–112.CrossRefGoogle ScholarPubMed
Mehta, A.D., Ulbert, I. & Schroeder, C.E. (2000). Intermodal selective attention in monkeys. II: Physiological mechanisms of modulation. Cerebral Cortex 10, 359–370.CrossRefGoogle ScholarPubMed
Merigan, W. (1996). Basic visual capacities and shape discrimination after lesions of extrastriate area V4 in macaques. Visual Neuroscience 13, 51–60.CrossRefGoogle ScholarPubMed
Neri, P. & Levi, D.M. (2007). Temporal dynamics of figure-ground segregation in human vision. Journal of Neurophysiology 97, 951–957.CrossRefGoogle ScholarPubMed
Olavarria, J.F., De Yoe, E.A., Knierim, J.J., Fox, J.M. & Van Essen, D.C. (1992). Neural responses to visual texture patterns in middle temporal area of the macaque monkey. Journal of Neurophysiology 68, 164–181.CrossRefGoogle ScholarPubMed
Olzak, L.A. & Kramer, M. (2007). Higher-level processes in the second order system. Perception 36, 40.Google Scholar
Pascual-Marqui, R.D. (2002). Standardized low-resolution brain electromagnetic tomography (sLORETA): Technical details. Methods and Findings in Experimental and Clinical Pharmacology 24, 5–12.Google ScholarPubMed
Pengjing, X.U., Xiang, Y.E. & Yifeng, Z. (2007). Temporal response properties to second-order visual stimuli in the LGN of cats. Chinese Science Bulletin 52, 2233–2239.Google Scholar
Picton, T.W. (1992). The P300 wave of the human event-related potential. Journal of Clinical Neurophysiology 9, 456–479.CrossRefGoogle ScholarPubMed
Pisella, L., Alahyane, N., Blangero, A., Thery, F., Blanc, S. & Pelisson, D. (2011). Right-hemispheric dominance for visual remapping in humans. Philosophical Transactions of the Royal Society of London. Series B, Biological Sciences 366, 572–585.CrossRefGoogle ScholarPubMed
Polat, U., Mizobe, K., Pettet, M.W., Kasamatsu, T. & Norcia, A.M. (1998). Collinear stimuli regulate visual responses depending on cell’s contrast threshold. Nature 391, 580–584.CrossRefGoogle ScholarPubMed
Polich, J. & Kok, A. (1995). Cognitive and biological determinants of P300: An integrative review. Biological Psychology 41, 103–146.CrossRefGoogle ScholarPubMed
Prins, N., Nottingham, N.K. & Mussap, A.J. (2003). The role of local grouping and global orientation contrast in perception of orientation-modulated textures. Vision Research 43, 2315–2331.CrossRefGoogle ScholarPubMed
Ramon, M. & Rossion, B. (2012). Hemisphere-dependent holistic processing of familiar faces. Brain and Cognition 78, 7–13.Google ScholarPubMed
Reynaud, A. & Hess, R.F. (2012). Properties of spatial channels underlying the detection of orientation-modulations. Experimental Brain Research 220, 135–145.CrossRefGoogle ScholarPubMed
Rosenberg, A., Husson, T.R. & Issa, N.P. (2010). Subcortical representation of non-Fourier image features. Journal of Neuroscience 30, 1985–1993.CrossRefGoogle ScholarPubMed
Sáry, G., Vogels, R., Kovacs, G. & Orban, G.A. (1995). Responses of monkey inferior temporal neurons to luminance-, motion-, and texture-defined gratings. Journal of Neurophysiology 73, 1341–1354.CrossRefGoogle ScholarPubMed
Schofield, A.J., Ledgeway, T. & Hutchinson, C.V. (2007). Asymmetric transfer of the dynamic motion aftereffect between first- and second-order cues and among different second-order cues. Journal of Vision 7, 1.CrossRefGoogle ScholarPubMed
Schofield, A.J. & Yates, T.A. (2005). Interactions between orientation and contrast modulations suggest limited cross-cue linkage. Perception 34, 769–792.CrossRefGoogle ScholarPubMed
Straube, S., Grimsen, C. & Fahle, M. (2010). Electrophysiological correlates of figure-ground segregation directly reflect perceptual saliency. Vision Research 50, 509–521.CrossRefGoogle ScholarPubMed
Sugita, Y. (1999). Grouping of image fragments in primary visual cortex. Nature 401, 269–272.CrossRefGoogle ScholarPubMed
Sun, P. & Schofield, A.J. (2011). The efficacy of local luminance amplitude in disambiguating the origin of luminance signals depends on carrier frequency: Further evidence for the active role of second-order vision in layer decomposition. Vision Research 51, 496–507.CrossRefGoogle ScholarPubMed
Sutter, A., Beck, J. & Graham, N. (1989). Contrast and spatial variables in texture segregation: Testing a simple spatial-frequency channels model. Perception & Psychophysics 46, 312–332.CrossRefGoogle ScholarPubMed
Treisman, A. (1986). Properties, parts, and objects. In Handbook of Perception and Human Performance, ed. Boff, K.R. & Kaufman, L., pp. 1–70. New York: John Wiley & Sons.Google Scholar
Treisman, A.M. & Gelade, G. (1980). A feature-integration theory of attention. Cognitive Psychology 12, 97–136.CrossRefGoogle ScholarPubMed
Ts’o, D.Y., Gilbert, C.D. & Wiesel, T.N. (1986). Relationships between horizontal and interactions and functional architecture in cat striate cortex as revealed by cross correlation analysis. Journal of Neuroscience 8, 1160–1170.CrossRefGoogle Scholar
Victor, J.D. & Conte, M.M. (1989). Cortical interactions in texture processing: Scale and dynamics. Visual Neuroscience 2, 297–313.CrossRefGoogle ScholarPubMed
Volberg, G. (2014). Right-hemisphere specialization for contour grouping. Experimental Psychology 61, 331–339.CrossRefGoogle ScholarPubMed
Westrick, Z.M., Henry, C.A. & Landy, M.S. (2013). Inconsistent channel bandwidth estimates suggest winner-take-all nonlinearity in second-order vision. Vision Research 81, 58–68.CrossRefGoogle ScholarPubMed
Wilson, H.R. (1999). Non-Fourier cortical processes in texture, form, and motion perception. Cerebral Cortex 13, 445–477.CrossRefGoogle Scholar
Wolfe, J.M., Horowitz, T.S., Kenner, N., Hyle, M. & Vasan, N. (2004). How fast can you change your mind? The speed of top-down guidance in visual search. Vision Research 44, 1411–1426.CrossRefGoogle ScholarPubMed