Hostname: page-component-8448b6f56d-qsmjn Total loading time: 0 Render date: 2024-04-25T04:05:49.778Z Has data issue: false hasContentIssue false
  • English
  • Français

Cortical potentials reflecting motion processing in humans

Published online by Cambridge University Press:  02 June 2009

Dieter R. Patzwahl ,
Johannes M. Zanker  and
Eckart O. Altenmüller
Dieter R. Patzwahl
Affiliation:
Neurologische Universitätsklinik, Hoppe-Seyler-Str. 3, D-72076 Tübingen, Germany
Johannes M. Zanker
Affiliation:
Max-Planck-Institut für biologische Kybernetik, Spemannstr. 38, D-72076 Tübingen, Germany
Eckart O. Altenmüller
Affiliation:
Neurologische Universitätsklinik, Hoppe-Seyler-Str. 3, D-72076 Tübingen, Germany
Get access Rights & Permissions [Opens in a new window]

Abstract

Motion processing is a fundamental task of visual systems, and in the monkey cortical areas can be identified which appear to be functionally specialized for motion processing. The human visual system is expected to be organized in a similar way. A noninvasive method to study the functional organization of the visual cortex is the recording of scalp potentials generated by neural activity of the underlying cortical areas. In the present study, we recorded slow cortical potentials from normal subjects in order to investigate how motion stimuli are processed. Three classes of object motion were realized as random dot kinematograms, namely Fourier motion, drift-balanced motion, and theta motion, because they require mechanisms of increasing complexity in order to be extracted. Large-field motion and counterphase flicker were used as control stimuli. Three basic results were obtained: (1) The responses evoked by the three classes of object motion do not differ significantly in their time course and distribution of activation. (2) The distributions of cortical activation evoked by object motion, and the control stimuli are different. During object motion the maximum activation occurs over the superior parietal cortex. Large-field motion activates occipital and parietal locations to the same extent, and during counterphase flicker the activity is maximum over the occipital lobe. Thus, the parietal slow potentials are interpreted to specifically reflect the cortical processing of object motion. (3) The time course of the activation reflects changes in the spatial position of the object: the amplitude of a transient negative component (TNC) which occurs 240 ms after motion onset decreases with increasing eccentricity of motion onset. The consecutive sustained negative component (SNC), which persists until the movement stops, decreases during centrifugal and increases during centripetal object motion. These results can be understood on the basis of physiological and anatomical knowledge about the mapping of the visual field on the cortex.

Keywords

ManVisual systemMotion detectionSecondary motionSlow cortical potentials
Type
Research Articles
Information
Visual Neuroscience , Volume 11 , Issue 6 , November 1994 , pp. 1135 - 1147
Copyright
Copyright © Cambridge University Press 1994

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

Albright, T.D. (1992). Form-cue invariant motion processing in primate visual cortex. Science 255, 1141–1143.CrossRefGoogle ScholarPubMed
Andersen, R.A. (1989). Visual and eye movement functions of the posterior parietal cortex. Annual Review of Neuroscience 12, 377–403.CrossRefGoogle ScholarPubMed
Andersen, R.A., Asanuma, C. & Cowan, W.M. (1985). Collosal and prefrontal associational projecting cell populations in area 7a of the macaque monkey: A study using retrogradely transported fluorescent dyes. Journal of Comparative Neurology 232, 443–455.CrossRefGoogle Scholar
Bauer, H., Korunka, C. & Leodolder, M. (1989). Technical requirements for high-quality scalp DC recordings. Electroencephalography and clinical Neurophysiology 72, 545–547.CrossRefGoogle ScholarPubMed
Borst, A. & Egelhaaf, M. (1989). Principles of visual motion detection. Trends in Neuroscience 12, 297–306.CrossRefGoogle ScholarPubMed
Callichio, J.A. & Andreassi, J.L. (1982). Visual evoked potentials under varied velocities of continuous and discrete apparent motion. International Journal of Neuroscience 17, 169–177.CrossRefGoogle Scholar
Cavanagh, P. & Mather, G. (1989). Motion: The long and the short of it. Spatial vision 4, 103–129.Google Scholar
Chubb, C. & Sperling, G. (1988). Drift balanced random stimuli: A general basis for studying non-Fourier motion perception. Journal of the Optical Society of America A 5, 1986–2006.CrossRefGoogle ScholarPubMed
Clarke, P.G.H. (1973 a). Visual evoked potentials to changes in the motion of a patterned field. Experimental Brain Research 18, 145–155.Google ScholarPubMed
Clarke, P.G.H. (1973 b). Comparison of visual evoked potentials to stationary and to moving patterns. Experimental Brain Research 18, 156–164.Google ScholarPubMed
Corbetta, M., Miezen, F.M., Dobmeyer, S., Shulman, G.L. & Petersen, S.E. (1991). Selective and divided attention during visual discrimination of sharp, color, and speed: Functional anatomy by positron emission tomography. Journal of Neuroscience 11(8), 2383–2402.CrossRefGoogle Scholar
Cowey, A. & Rolls, E.T. (1974). Human cortical magnification factor and its relation to visual acuity. Experimental Brain Research 21, 447–454.CrossRefGoogle ScholarPubMed
Cunningham, V.J., Deiber, M.P., Frackowiak, R.S.J., Friston, K.J., Kennard, C., Lammertsma, A.A., Lueck, C.J., Romaya, J. & Zeki, S. (1990). The motion area (area V5) of human visual cortex. Journal of Physiology (London) 423, 101P.Google Scholar
Daniel, P.M. & Whitteridge, D. (1961). The representation of the visual field on the cerebral cortex of monkeys. Journal of Physiology 159, 203–221.CrossRefGoogle ScholarPubMed
Heilman, K.M., Watson, R.T., Valenstein, E. & Goldberg, M.E. (1987). In Handbook of Physiology: Higher Cortical Functions of the Brain, ed. Plum, F. & Mountcastle, V.B., 5, pp. 461–481. Washington, DC: American Physiological Society.Google Scholar
Hjorth, B. (1975). An on-line transformation of EEG scalp potentials into orthogonal source derivations. Electroencephalography and Clinical Neurophysiology 39, 526–530.CrossRefGoogle ScholarPubMed
Homan, R.W., Herman, J. & Purdy, P. (1987). Cerebral location of international 10–20 system electrode placement. Electroencephalography and Clinical Neurophysiology 66, 376–382.CrossRefGoogle ScholarPubMed
Horton, J.C. & Hoyt, W.F. (1991). The representation of the visual field in human striate cortex. Archives of Ophthalmology 109, 816–824.CrossRefGoogle ScholarPubMed
Jasper, H.H. (1958). Report of committee on methods of clinical examination in electroencephalography. Electroencephalography and Clinical Neurophysiology 10, 370–375.Google Scholar
Kuba, M. & Kubová, Z. (1992). Visual evoked potentials specific for motion onset. Documenta Ophtalmologica 80, 83–89.CrossRefGoogle ScholarPubMed
Livingstone, M.S. & Hubel, D.H. (1988). Segregation of form, color, movement, and depth: Anatomy, physiology, and perception. Science 240, 740–749.CrossRefGoogle ScholarPubMed
McCarthy, G. & Wood, C.C. (1985). Scalp distributions of eventrelated potentials: An ambiguity associated with analysis of variance models. Electroencephalography and Clinical Neurophysiology 62, 203–208.CrossRefGoogle ScholarPubMed
Merigan, W.H. & Maunsell, J.H.R. (1993). How parallel are the primate visual pathways? Annual Review in Neuroscience 16, 369–402.CrossRefGoogle ScholarPubMed
Nuñez, P. L. (1981). Electric Fields of the Brain. The Neurophysics of EEG. Oxford: Oxford University Press.Google Scholar
Pardo, J.V., Fox, P.T. & Raichle, M.E. (1991). Localization of a human system for sustained attention by positron emission tomography. Nature 349, 61–64.CrossRefGoogle ScholarPubMed
Patzwahl, D.R., Zanker, J.M. & Altenmüller, E.O. (1993). Cortical potentials in humans reflecting the direction of object motion. NeuroReport 4, 379–382.CrossRefGoogle ScholarPubMed
Ramachandran, V.S. & Anstis, S.M. (1986). The perception of apparent motion. Scientific American 256, 102–109.CrossRefGoogle Scholar
Regan, D. (1989). Orientation discrimination for objects defined by relative motion and objects defined by luminance contrast. Vision Research 29, 1389–1400.CrossRefGoogle ScholarPubMed
Reichardt, W. (1961). Autocorrelation, a principle for the evaluation of sensory information by the central nervous system. In Sensory Communication, ed. Rosenblith, W.A., pp. 303–317. Cambridge: MIT Press.Google Scholar
Reichardt, W. (1987). Evaluation of optical motion information by movement detectors. Journal of Comparative Physiology A 161, 533–547.CrossRefGoogle ScholarPubMed
Reichardt, W. & Poggio, T. (1979). Figure ground discrimination by relative movement in the visual system of the fly. Biological Cybernetics 35, 81–100.CrossRefGoogle Scholar
Rogers, B. & Graham, M. (1979). Motion parallax as an independent cue for depth perception. Perception 8, 125–134.CrossRefGoogle ScholarPubMed
Schlykowa, L., Van Dijk, B.W. & Ehrenstein, W.H. (1993). Motiononset visual-evoked potentials as a function of retinal eccentricity in man. Cognitive Brain Research 1, 169–174.CrossRefGoogle ScholarPubMed
Speckmann, E.J. & Caspers, H. (1979). Origin of Cerebral Field Potentials. Stuttgart, Germany: Thieme.Google Scholar
Speckmann, E.J. & Elger, C.E. (1993). Introduction to the neurophysiological basis of the EEG an DC potentials. In Electroencephalography, ed. Niedermeyer, E. & Lopes Da Silva, F., pp. 15–26. Baltimore, Maryland: Williams & Wilkins.Google Scholar
Spekreisje, H., Dagnelie, G., Maier, J. & Regan, D. (1985). Flicker and movement constituents of the pattern reversal Response. Vision Research 25, 1297–1304.CrossRefGoogle Scholar
Sperling, G. (1989). Three stages and two systems of visual processing. Spatial Vision 4, 183–207.CrossRefGoogle ScholarPubMed
Sperling, G. & Lu, Z.-L. (1994). Immunity to pedestrals distinguishes motion-energy from feature-tracking motion-perception mechanisms. Investigative Ophthalmology and Visual Science 35, 1390.Google Scholar
Ullman, S. (1983). The measurement of visual motion—computational considerations and some neurophysiological implications. Trends in Neuroscience 6, 177–179.CrossRefGoogle Scholar
Ungerleider, L.G. & Mishkin, M. (1982). Two cortical visual systems. In The Analysis of Visual Behaviour, ed. Ingle, D.J., Mansfield, R.J.W. & Goodale, M.S., pp. 549–586. Cambridge, Massachusetts: MIT Press.Google Scholar
Victor, J.D. & Conte, M.M. (1992). Evoked potential and psychophysical analysis of Fourier and non-Fourier motion mechanisms. Visual Neuroscience 9, 105–123.CrossRefGoogle ScholarPubMed
Wattam-Bell, J. (1991). Development of motion-specific cortical responses in infancy. Vision Research 31, 287–297.CrossRefGoogle ScholarPubMed
Zanker, J.M. (1990). Theta motion: A new psychophysical paradigm indicating two levels of visual motion processing. Naturwissenschaften 77, 243–246.CrossRefGoogle Scholar
Zanker, J.M. (1993). Theta motion: A paradoxical stimulus to explore higher order motion extraction. Vision Research 33, 553–569.CrossRefGoogle Scholar
Zanker, J.M. (1994). What is the elementary mechanism underlying secondary motion perception. Investigative Ophthalmology and Visual Science 35, 1405.Google Scholar
Zeki, S., Watson, J.D.G., Lueck, C.J., Friston, K.J., Kennard, C. & Frackowiak, R.S.J. (1991). A direct demonstration of functional specialization in human visual cortex. Journal of Neuroscience 11, 641–649.CrossRefGoogle ScholarPubMed