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Dissociation of early evoked cortical activity in perceptual grouping

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Abstract

Perceptual grouping is a multi-stage process, irreducible to a single mechanism localized anatomically or chronometrically. To understand how various grouping mechanisms interact, we combined a phenomenological report paradigm with high-density event-related potential (ERP) measurements, using a 256-channel electrode array. We varied the relative salience of competing perceptual organizations in multi-stable dot lattices and asked observers to report perceived groupings. The ability to discriminate groupings (the grouping sensitivity) was positively correlated with the amplitude of the earliest ERP peak C1 (about 60 ms after stimulus onset) over the middle occipital area. This early activity is believed to reflect spontaneous feed-forward processes preceding perceptual awareness. Grouping sensitivity was negatively correlated with the amplitude of the next peak P1 (about 110 ms), which is believed to reflect lateral and feedback interactions associated with perceptual awareness and attention. This dissociation between C1 and P1 activity implies that the recruitment of fast, spontaneous mechanisms for grouping leads to high grouping sensitivity. Observers who fail to recruit these mechanisms are trying to compensate by using later mechanisms, which depend less on stimulus properties such as proximity.

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Notes

  1. Studies of high-frequency gamma oscillations that are often associated with visual grouping concern later processes, more than 200 ms after stimulus onset (Muller et al. 1996; Tallon-Baudry et al. 1996; Keil et al. 1999; Vidal et al. 2006).

  2. It was shown that increase in stimulus luminance increases the amplitudes of each of the early ERP peaks: C1, P1, and N1 (Johannes et al. 1995). The ERP modulation in Johannes et al. study was found when luminance was changed by a factor of nearly 40. As we show below, we found that the changes in lattice aspect ratio caused changes in the amplitudes of peaks C1 and P1 in different directions on different peaks. This means that the changes in peak amplitudes in response to the manipulation of aspect ratio were not driven by the small changes in lattice luminance.

  3. In both stimulus- and response-based analyses we segmented data relative to stimulus onset.

  4. The relationship between number of single trials and amplitude of the resulted averaged ERP is not linear, so it is impossible to calculate a normalization factor.

  5. In a pilot experiment we determined the number of trials to be used in this study, to achieve a tradeoff between the statistical power needed for measuring changes in peak amplitudes, on the one hand, and the number of stimulus conditions, on the other.

  6. An alternative method of calculating attraction coefficients, using only responses a and b, produced similar values of attraction coefficients (Supplementary Table 1) and led to the same division of observers to two groups as the method presented in the text. In the alternative method L = log{[N(b) + 1/6]/[N(a) + 1/6]}. We chose the method that took into account responses c and d, because it allowed us to use a larger number of trials in the analyses of ERP.

  7. The values of mean-error plots do not exactly correspond to the values of the ERP curves, because the plotted values are averaged over groups of channels (used in the statistical analysis), whereas the ERP curves correspond each to a representative channel from the group.

  8. See Fig. S1 and accompanying text in Electronic Supplementary Material for the motivation behind this selection.

  9. The contribution of the superficial sources is especially significant for small EEG signals, such as early evoked potentials, which might be generated by a small dipole layer in the primary sensory cortex (Srinivasan 2004). Therefore, we believe that the distribution of scalp potentials in our data roughly reflects the underlying generators (within the known topographical limitations of EEG). Based on this argument, we believe we are in a position to draw conclusions about the topography of ERP components at the scale of large cortical areas.

  10. Note that our selection of the peak latency and the areas of activity were independent of the hypotheses tested in the ANOVAs. Therefore the effects within the pre-selected latencies and areas are not false positives that could arise had we selected the latencies and areas using an exhaustive search for differences between conditions across the spatiotemporal matrix of 256 channels and 125 time samples.

  11. Although low spatial frequencies deem critical for perceptual grouping, it is incorrect to assume that only low frequencies are needed for the task. Janez (1984) showed that grouping is possible with low frequencies filtered out from the stimulus. Consistent with this idea, our results indicate that a broad spectrum of spatial frequencies is used for grouping, manifested by ERP activity in left and right hemispheres, with higher activity in the right hemisphere indicating a greater role of low spatial frequencies.

References

  • Attneave F (1971) Multistability in perception. Sci Am 225:63–71

    Article  PubMed  CAS  Google Scholar 

  • Bauer R, Heinze S (2002) Contour integration in striate cortex. Classic cell responses or cooperative selection? Exp Brain Res 147:145–152

    Article  PubMed  Google Scholar 

  • Ben-Av MB, Sagi D (1995) Perceptual grouping by similarity and proximity: experimental results can be predicted by intensity autocorrelations. Vision Res 35:853–866

    Article  PubMed  CAS  Google Scholar 

  • Boeschoten MA, Kemner C, Kenemans JL, van Engeland H (2005) Time-varying differences in evoked potentials elicited by high versus low spatial frequencies: a topographical and source analysis. Clin Neurophysiol 116:1956–1966

    Article  PubMed  CAS  Google Scholar 

  • Bosking WH, Zhang Y, Schofield B, Fitzpatrick D (1997) Orientation selectivity and the arrangement of horizontal connections in tree shrew striate cortex. J Neurosci 17:2112–2127

    PubMed  CAS  Google Scholar 

  • Clark VP, Fan S, Hillyard SA (1995) Identification of early visual evoked potential generators by retinotopic and topographic analyses. Hum Brain Mapp 2:170–187

    Article  Google Scholar 

  • Di Russo F, Martinez A, Sereno MI, Pitzalis S, Hillyard SA (2002) Cortical sources of the early components of the visual evoked potential. Hum Brain Mapp 15:95–111

    Article  PubMed  Google Scholar 

  • Di Russo F, Martinez A, Hillyard SA (2003) Source analysis of event-related cortical activity during visuo-spatial attention. Cereb Cortex 13:486–499

    Article  PubMed  Google Scholar 

  • Duncan J (1984) Selective attention and the organization of visual information. J Exp Psychol Gen 113:501–517

    Article  PubMed  CAS  Google Scholar 

  • Felleman DJ, Van Essen DC (1991) Distributed hierarchical processing in the primate cerebral cortex. Cereb Cortex 1:1–47

    Article  PubMed  CAS  Google Scholar 

  • Foxe JJ, Simpson GV (2002) Flow of activation from V1 to frontal cortex in humans. A framework for defining “early” visual processing. Exp Brain Res 142:139–150

    Article  PubMed  Google Scholar 

  • Freeman E, Sagi D, Driver J (2001) Lateral interactions between targets and flankers in low-level vision depend on attention to the flankers. Nat Neurosci 4:1032–1036

    Article  PubMed  CAS  Google Scholar 

  • Gepshtein S, Kubovy M (2005) Stability and change in perception: spatial organization in temporal context. Exp Brain Res 160:487–495

    Article  PubMed  Google Scholar 

  • Ginsburg AP (1971) Psychological correlates of a model of the human visual system. IEEE Trans Aerosp Electron Syst 71-C-AES:283–290

    Google Scholar 

  • Ginsburg AP (1986) Spatial filtering and visual form perception. In: Boff KR, Kaufman L, Thomas JP (eds) Handbook of perception and human performance, vol 2, vol II. Wiley, New York, pp 1–41

    Google Scholar 

  • Han S, Song Y, Ding Y, Yund EW, Woods DL (2001) Neural substrates for visual perceptual grouping in humans. Psychophysiology 38:926–935

    Article  PubMed  CAS  Google Scholar 

  • Han S, Jiang Y, Mao L, Humphreys GW, Qin J (2005) Attentional modulation of perceptual grouping in human visual cortex: ERP studies. Hum Brain Mapp 26:199–209

    Article  PubMed  Google Scholar 

  • Hillyard SA, Teder-Salejarvi WA, Munte TF (1998) Temporal dynamics of early perceptual processing. Curr Opin Neurobiol 8:202–210

    Article  PubMed  CAS  Google Scholar 

  • Hogeboom M, van Leeuwen C (1997) Visual search strategy and perceptual organization covary with individual preference and structural complexity. Acta Psychol (Amst) 95:141–164

    Article  CAS  Google Scholar 

  • Janez L (1984) Visual grouping without low spatial frequencies. Vision Res 24:271–274

    Article  PubMed  CAS  Google Scholar 

  • Johannes S, Munte TF, Heinze HJ, Mangun GR (1995) Luminance and spatial attention effects on early visual processing. Brain Res Cogn Brain Res 2:189–205

    Article  PubMed  CAS  Google Scholar 

  • Julesz B (1991) Early vision and focal attention. Rev Mod Phys 63:735

    Article  Google Scholar 

  • Kahneman D, Henik A (1981) Perceptual organization and attention. In: Kubovy M, Pomerantz J (eds) Perceptual organization. Erlbaum, Hillsdale, pp 181–211

    Google Scholar 

  • Kapadia MK, Ito M, Gilbert CD, 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

    Article  PubMed  CAS  Google Scholar 

  • Keil A, Muller MM, Ray WJ, Gruber T, Elbert T (1999) Human gamma band activity and perception of a gestalt. J Neurosci 19:7152–7161

    PubMed  CAS  Google Scholar 

  • Kenemans JL, Kok A, Smulders FT (1993) Event-related potentials to conjunctions of spatial frequency and orientation as a function of stimulus parameters and response requirements. Electroencephalogr Clin Neurophysiol 88:51–63

    Article  PubMed  CAS  Google Scholar 

  • Kenemans JL, Baas JM, Mangun GR, Lijffijt M, Verbaten MN (2000) On the processing of spatial frequencies as revealed by evoked-potential source modeling. Clin Neurophysiol 111:1113–1123

    Article  PubMed  CAS  Google Scholar 

  • Khoe W, Freeman E, Woldorff MG, Mangun GR (2004) Electrophysiological correlates of lateral interactions in human visual cortex. Vision Res 44:1659–1673

    Article  PubMed  CAS  Google Scholar 

  • Khoe W, Freeman E, Woldorff MG, Mangun GR (2006) Interactions between attention and perceptual grouping in human visual cortex. Brain Res 1078:101–111

    Article  PubMed  CAS  Google Scholar 

  • Kitterle FL, Christman S, Hellige JB (1990) Hemispheric differences are found in the identification, but not the detection, of low versus high spatial frequencies. Percept Psychophys 48:297–306

    PubMed  CAS  Google Scholar 

  • Koffka K (1935/1963) Principles of Gestalt psychology. A Harbinger Book, Harcourt, Brace & World, Inc., New York

  • Köhler W (1947) Gestalt psychology. Liveright, New York

    Google Scholar 

  • Kovacs I (1996) Gestalten of today: early processing of visual contours and surfaces. Behav Brain Res 82:1–11

    Article  PubMed  CAS  Google Scholar 

  • Kubovy M (1994) The perceptual organization of dot lattices. Psychon Bull Rev 1:182–190

    Google Scholar 

  • Kubovy M, Holcombe AO, Wagemans J (1998) On the lawfulness of grouping by proximity. Cognit Psychol 35:71–98

    Article  PubMed  CAS  Google Scholar 

  • Lee TS, Nguyen M (2001) Dynamics of subjective contour formation in the early visual cortex. Proc Natl Acad Sci USA 98:1907–1911

    Article  PubMed  CAS  Google Scholar 

  • Leopold DA, Logothetis NK (1999) Multistable phenomena: changing views in perception. Trends Cogn Sci 3:254–264

    Article  PubMed  Google Scholar 

  • Li W, Piech V, Gilbert CD (2004) Perceptual learning and top–down influences in primary visual cortex. Nat Neurosci 7:651–657

    Article  PubMed  CAS  Google Scholar 

  • Marr D (1982) Vision: a computational investigation into the human representation and processing of visual information. W.H. Freeman and Company, New York

    Google Scholar 

  • Martinez A, Anllo-Vento L, Sereno MI, Frank LR, Buxton RB, Dubowitz DJ, Wong EC, Hinrichs H, Heinze HJ, Hillyard SA (1999) Involvement of striate and extrastriate visual cortical areas in spatial attention. Nat Neurosci 2:364–369

    Article  PubMed  CAS  Google Scholar 

  • Maxwell SE, Delaney HD (2004) Designing experiments and analyzing data. Lawrence Erlbaum Associates, Mahwah, New Jersey

    Google Scholar 

  • Muller MM, Bosch J, Elbert T, Kreiter A, Sosa MV, Sosa PV, Rockstroh B (1996) Visually induced gamma-band responses in human electroencephalographic activity—a link to animal studies. Exp Brain Res 112:96–102

    Article  PubMed  CAS  Google Scholar 

  • Murray MM, Wylie GR, Higgins BA, Javitt DC, Schroeder CE, Foxe JJ (2002) The spatiotemporal dynamics of illusory contour processing: combined high-density electrical mapping, source analysis, and functional magnetic resonance imaging. J Neurosci 22:5055–5073

    PubMed  CAS  Google Scholar 

  • Neisser U (1967) Cognitive psychology. Prentice-Hall, Englewood Cliffs

    Google Scholar 

  • Nikolaev AR, van Leeuwen C (2004) Flexibility in spatial and non-spatial feature grouping: an event-related potentials study. Brain Res Cogn Brain Res 22:13–25

    Article  PubMed  Google Scholar 

  • Palmer SE (1999) Vision science: photons to phenomenology. MIT Press, Cambridge

    Google Scholar 

  • Palmer SE, Brooks JL, Nelson R (2003) When does grouping happen? Acta Psychol (Amst) 114:311–330

    Article  Google Scholar 

  • Perrin F, Pernier J, Bertrand O, Echallier JF (1989) Spherical splines for scalp potential and current density mapping. Electroencephalogr Clin Neurophysiol 72:184–187

    Article  PubMed  CAS  Google Scholar 

  • Picton TW, Bentin S, Berg P, Donchin E, Hillyard SA, Johnson R Jr, Miller GA, Ritter W, Ruchkin DS, Rugg MD, Taylor MJ (2000) Guidelines for using human event-related potentials to study cognition: recording standards and publication criteria. Psychophysiology 37:127–152

    Article  PubMed  CAS  Google Scholar 

  • Pins D, ffytche D (2003) The neural correlates of conscious vision. Cereb Cortex 13:461–474

    Article  PubMed  Google Scholar 

  • Polat U, Sagi D (1993) Lateral interactions between spatial channels: suppression and facilitation revealed by lateral masking experiments. Vision Res 33:993–999

    Article  PubMed  CAS  Google Scholar 

  • Polat U, Sagi D (1994) The architecture of perceptual spatial interactions. Vision Res 34:73–78

    Article  PubMed  CAS  Google Scholar 

  • Polat U, Mizobe K, Pettet MW, Kasamatsu T, Norcia AM (1998) Collinear stimuli regulate visual responses depending on cell’s contrast threshold. Nature 391:580–584

    Article  PubMed  CAS  Google Scholar 

  • Proverbio AM, Esposito P, Zani A (2002) Early involvement of the temporal area in attentional selection of grating orientation: an ERP study. Brain Res Cogn Brain Res 13:139–151

    Article  PubMed  Google Scholar 

  • Rock I (1983) The logic of perception. MIT Press, a Bradford Book, Cambridge, Mass

  • Roelfsema PR (2006) Cortical algorithms for perceptual grouping. Annu Rev Neurosci 29:203–227

    Article  PubMed  CAS  Google Scholar 

  • Romani A, Callieco R, Tavazzi E, Cosi V (2003) The effects of collinearity and orientation on texture visual evoked potentials. Clin Neurophysiol 114:1021–1026

    Article  PubMed  Google Scholar 

  • Schmidt KE, Goebel R, Lowel S, Singer W (1997) The perceptual grouping criterion of colinearity is reflected by anisotropies of connections in the primary visual cortex. Eur J Neurosci 9:1083–1089

    Article  PubMed  CAS  Google Scholar 

  • Sergent J (1982) The cerebral balance of power: confrontation or cooperation? J Exp Psychol Hum Percept Perform 8:253–272

    Article  PubMed  CAS  Google Scholar 

  • Srinivasan R (2004) High-resolution EEG: theory and practice. In: Handy TC (ed) Event-related potentials: a methods handbook. MIT Press, Cambridge, pp 167–188

    Google Scholar 

  • Stins JF, van Leeuwen C (1993) Context influence on the perception of figures as conditional upon perceptual organization strategies. Percept Psychophys 53:34–42

    PubMed  CAS  Google Scholar 

  • Super H, Spekreijse H, Lamme VA (2001) Two distinct modes of sensory processing observed in monkey primary visual cortex (V1). Nat Neurosci 4:304–310

    Article  PubMed  CAS  Google Scholar 

  • Super H, van der Togt C, Spekreijse H, Lamme VA (2003) Internal state of monkey primary visual cortex (V1) predicts figure-ground perception. J Neurosci 23:3407–3414

    PubMed  CAS  Google Scholar 

  • Tallon-Baudry C, Bertrand O, Delpuech C, Pernier J (1996) Stimulus specificity of phase-locked and non-phase-locked 40 Hz visual responses in human. J Neurosci 16:4240–4249

    PubMed  CAS  Google Scholar 

  • Taylor MJ (2002) Non-spatial attentional effects on P1. Clin Neurophysiol 113:1903–1908

    Article  PubMed  Google Scholar 

  • van Leeuwen C, Buffart H, van der Vegt J (1988) Sequence influence on the organization of meaningless serial stimuli: economy after all. J Exp Psychol Hum Percept Perform 14:481–502

    Article  PubMed  Google Scholar 

  • VanRullen R, Thorpe SJ (2001) The time course of visual processing: from early perception to decision-making. J Cogn Neurosci 13:454–461

    Article  PubMed  CAS  Google Scholar 

  • Vidal JR, Chaumon M, O’Regan JK, Tallon-Baudry C (2006) Visual grouping and the focusing of attention induce gamma-band oscillations at different frequencies in human magnetoencephalogram signals. J Cogn Neurosci 18:1850–1862

    Article  PubMed  Google Scholar 

  • Watt RJ, Phillips WA (2000) The function of dynamic grouping in vision. Trends Cogn Sci 4:447–454

    Article  PubMed  Google Scholar 

  • Wertheimer M (1912) Experimentelle Studien über das Sehen von Bewegung. Z Psychol 61:161–265

    Google Scholar 

  • Wertheimer M (1923) Untersuchungen zur Lehre von der Gestalt. Psychol Forsch 4:301–350

    Article  Google Scholar 

  • Wu Y, Chen J, Han S (2005) Neural mechanisms of attentional modulation of perceptual grouping by collinearity. Neuroreport 16:567–570

    Article  PubMed  Google Scholar 

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Acknowledgments

We thank Tatiana Tyukina for technical support, and Misa Kawashima and Maiko Maeda for assistance in running the experiments.

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Authors and Affiliations

  1. Laboratory for Perceptual Dynamics, RIKEN Brain Science Institute, 2-1 Hirosawa, Wako-shi, Saitama, 351-0198, Japan

    Andrey R. Nikolaev, Sergei Gepshtein & Cees van Leeuwen

  2. Institute of Higher Nervous Activity, Butlerov str., 5a, 117485, Moscow, Russia

    Andrey R. Nikolaev

  3. Salk Institute for Biological Studies, 10010 North Torrey Pines Road, La Jolla, CA, 92037, USA

    Sergei Gepshtein

  4. Department of Psychology, University of Virginia, PO Box 400400, Charlottesville, VA, USA

    Michael Kubovy

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  1. Andrey R. Nikolaev
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  2. Sergei Gepshtein
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  3. Michael Kubovy
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Correspondence to Andrey R. Nikolaev.

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221_2007_1214_MOESM2_ESM.eps

Figure S1. A. Mean-error plots of the normalized amplitude of C1 activity for four aspect ratios (averaged across orientations) in the high-sensitivity group. B. Mean-error plots of the normalized amplitude of P1 activity for four aspect ratios (averaged across orientations) for all participants. In both panels, the amplitudes are shown for 28 channels organized into 4 chains of 7 electrodes (colored green in Fig. 3D). Numbers on the abscissa correspond to the ordinal numbers of electrodes within each chain, from left to right in the frontal plane (EPS 4772 kb)

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Nikolaev, A.R., Gepshtein, S., Kubovy, M. et al. Dissociation of early evoked cortical activity in perceptual grouping. Exp Brain Res 186, 107–122 (2008). https://doi.org/10.1007/s00221-007-1214-7

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