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BMe Research Grant |
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BME Doctoral School of Psychology
BME Department of Cognitive Science
Supervisor: Ilona Kovács; external advisor: János Geier
Understanding basic visual mechanisms through visual illusions
An introduction of the topic in a few lines
Visual illusions reveal much about the mechanisms of information processing in the visual system. Though the only contact of our visual system with the outer world is the distribution of light projected on our retinas, it builds up a chromatic, 3D model, which makes orientation and action possible. However, our visual system makes certain errors during this process: our perception is often does not follow the physical light distribution. During my research, I aim at discovering the main characteristics of basic visual mechanism by means of the systematic investigation of these “errors”, i.e. visual illusions. On the basis of the regularities of these errors, consequences can be drawn with regards to the basic mechanisms of perception. Hereby, as an alternative to physiological experiments, we can gain insight into the working mode of visual system by means of revealing the regularities of psychophysically measurable phenomena and by modeling them.
I interpret the results of my lightness and color experiments within the framework of a model simulating neural activity spreading in the visual system (Geier, 2009). Phenomena revealing the dynamics of the visual system and results with respect to binocular rivalry are interpreted within the framework of neural adaptation (e.g. Pastukhov and Braun, 2011).
A short introduction to the research facility
My research is carried out in two institutes: at the Department of Cognitive Science, Faculty of Sciences, BME, where a wide area of cognitive science is being investigated, from the perception of contours through the effects of sleep on learning to psycholinguistics. My external research institute is Stereo Vision Ltd, which conducts experimental research on the basic processes of human vision and works on computational models, applying these to the development of innovative image processing algorithms.
The introduction of the context and history of our research
Brightness illusions are classified into contrast/assimilation (Fig. 1-2.) phenomena. For contrast, the area in bright environment seems darker than the one surrounded by dark. Assimilation is the opposite.
To date, there is no unified model for these classes. Contrast is traditionally explained by lateral inhibition (Fig. 4, Baumgartner, 1960), which is not suitable for assimilation. Low level explanations try to capture these illusions by convolution models (Blakeslee & McCourt, 2004), which substitute each pixel by a weighted sum of its environment. Theorists of the filling-in approach (Cohen & Grossberg, 1984) search for the edges and fill in the enclosed areas. Others emphasize the role of interpretation (Adelson, 1993).
In normal vision, the two retinal images largely overlap; a minimal disparity permits 3D vision. To better understand, the system can be provoked by two different images projected to the retinas, the liciting binocular rivalry, in which either one of the two images or their mosaic is alternating spontaneously (which is never presented physically, thus, it is considered an illusion). This had been explained by the mutual inhibition of monocular cells (Blake, 1989), but Kovács et al. (1996) verified the role of higher visual areas. Pastukhov and Braun (2011) provided a neural adaptation-based model for the phenomenon.
Aim of the research, questions to investigate
The aim is to investigate the regularities of brightness/color perception and binocular vision by means of psychophysical experiment, and to capture both assimilation and contrast phenomena by a unified model. Further, the forms of neural adaptation are investigated by means of dynamic illusions and binocular rivalry.
Measuring different physical parameters on which illusions depend may help us provide a unified model for all known brightness/color illusions, and thus for the basic mechanisms of vision. Having a unified model is a key issue, since at the phenomenal level, seemingly opposite effects occur. However, it cannot be assumed that the nervous system, on recognizing the image, would switch from “assimilation method” to “contrast method”. It is more plausible to suppose that the same processes are used when seeing assimilation, contrast or real pictures.
The foregoing phenomena work even monocularly. However, to understand the system level it is necessary to investigate binocular vision, too. Our results are interpreted in Pastukhov and Braun’s (2011) framework, assuming neural adaptation behind bistable perceptual phenomena. We found significant differences within this framework: children alternated and adapted more quickly and showed a stronger adaptation effect than adults. The developmental curve, however, is incomplete; further investigations on adolescents seem fruitful.
Methods
Lightness/Brightness
By varying the image parameters of the illusions in my psychophysical experiments, I investigate the necessary/sufficient parameters for the particular illusion and the effects of changing each parameter. Here I use the cancellation technique, where the task of the subject is to modify the image presented on a computer screen until the illusion disappears. Hereby I measure the size of each illusion, depending on image parameters.
Clarifying the role of edges will be of utmost importance being a key issue in the model. Thus I investigate the segmenting role of edges by varying our ramped versions of the Chevreul illusion (Geier, Séra, Bernáth and Hudák, 2006; Geier and Hudák, 2011).
I will investigate the illusions related to the White effect and simultaneous contrast, such as our variant without edges (Hudák and Geier, 2009) and the circumstances under which the illusion reverses to contrast.
Color
Formerly, we modeled color illusions by independent processing in RGB channels, which was successful for the chromatic Hermann grid, Lotto’s illusion and color contrast, moreover, we had verified this model for the chromatic Hermann grid empirically (Hudák and Geier, 2007). Then we discovered that independent processing of the three channels does not always model properly the chromatic White effect and Pinna’s illusion. Now we aim at completing the model to simulate all color illusions with uniform parameters.
Binocular rivalry, adaptation
The binocular illusion is also investigated in psychophysical experiments, for which the paradigm was developed in international cooperation (Hudák, Gerván, Friedrich, Pastukhov, Braun and Kovács, 2011). Here subjects are requested to continuously point by a joystick to the image they are just seeing. Hereby the dynamics and the neural adaptational effects behind the phenomenon can be investigated in various populations.
Results already achieved
In developing a new unified model and having it accepted by the scientific community, the first step is to decisively refute the generally accepted old model. The principle of lateral inhibition is shown in Fig. 4, which is treated as identical with retinal receptive fields since 1960. A great proportion of contrast phenomena is explained in these terms in textbooks; convolution models are also based on it, and theorists assuming higher cognitive processes in brightness perception trace back assimilation phenomena to lateral inhibition as well, by supposing the involvement of grouping principles (Gilchrist, 2006).
We refuted this textbook explanation for the Hermann grid in our paper published in Perception, by curving the streets of the grid. We have also given the qualitative description of our model in that paper.
We have extended the model for chromatic Hermann grids. I presented these simulation results in my talk at ECVP, 2007.
We have also refuted the textbook explanation and all convolution models for the Chevreul illusion (Geier, Séra, Bernáth and Hudák, 2006; Geier and Hudák, 2011, Hudák and Geier, 2011.).
The computational model developed by Geier (2009; paper in prep.) is now suitable for simulating 80% of all known brightness illusions without changing its parameters. With a slight parameter change, it can simulate 95%, including those for which other theorists consider higher cognitive processes necessary.
Concerning the adaptation effect in binocular rivalry, we found significant differences between 9 and 21 year-olds in Pastukhov and Braun’s (2011) framework (Hudák, Gerván, Friedrich, Pastukhov and Braun, 2011). We found that children alternate more quickly, consistent with Kovács and Eisenberg (2005). Besides, children show quicker and stronger adaptation effect.
Neural adaptation plays an important role even when the dynamic change of the stimulus is not illusory (as in BR) but physical. When a letter is hidden in a dynamically changing random noise, subjects cannot identify it during stimulation, however, following the stimulation they see a clear afterimage of the hidden letter on the homogeneous screen. This shows that the visual system can adapt to the average of light pattern through time and obtain a coherent pattern from it (Anstis, Geier and Hudák, submitted).
Afterimages may even occur in the case of very short fixation times, which may not be attributed to adaptation, therefore we explain it in terms of a feedforward mechanism of the visual system (Geier, Séra and Hudák, 2007).
Expected impact, further research
Our results refuting the classical model have already gained international reputation (Anstis 2006, Bach & Poloschek, 2006; Hoffman, 2008; Howe & Livingstone, 2007; Lingelbach & Ehrenstein, 2004; Schiller & Carvey, 2005). The new model will probably be of great interest, since existing models can only account for a smaller proportion of illusions and have not been extended to chromatic pictures. We aim at further investigating the development of brightness/color perception and binocular rivalry. Furthermore, we plan to explore dynamic phenomena and spatial vision, and capture them by a similarly exact computational model that matches the results of our future psychophysical experiments.
My own publications, links, other references
My own publications
Book chapter
Journal papers
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Geier J, Bernath L, Hudak M, Sera L Straightness as the main factor of the Hermann grid illusion PERCEPTION 37:(5) pp. 651-665, Paper doi:10.1068/p5622. (2008) IF: 1.360, WoS link, Scopus link, 18605141, DOI: 10.1068/p5622
Independent quotes 13 Related quotes: 1 Total: 14
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Geier J, Hudak M Changing the Chevreul Illusion by a Background Luminance Ramp: Lateral Inhibition Fails at Its Traditional Stronghold - A Psychophysical Refutation PLOS ONE 6:(10) Paper e26062 (2011) IF: 4.411*, WoS link, Scopus link, DOI: 10.1371/journal.pone.0026062 WC: Biology | ||||||||||||||||||||||||||||
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M Hudak, P Gervan, B Friedrich, A Pastukhov, J Braun, I Kovacs Increased readiness for adaptation and faster alternation rates under binocular rivalry in children FRONTIERS IN HUMAN NEUROSCIENCE 5: 7 p. Paper 128. (2011) IF: 1.940*, WoS link, 22069386, DOI: 10.3389/fnhum.2011.00128 | ||||||||||||||||||||||||||||
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Anstis, S. Geier, J. and Hudák, M. (submitted), Afterimages from unseen patterns, I-PERCEPTION |
Conference abstracts in journals
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Hudak M F, Geier J Modelling with flying colours: The application of the RadGrad model to chromatic Hermann grids PERCEPTION 36: p. 173 (2007) IF: 1.617, WoS link WC: Psychology; Psychology, Experimental talk |
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Geier J, Sera L, Bernath L, Hudak M Increasing and decreasing the Chevreul illusion by a background luminance ramp PERCEPTION 35: p. 215 (2006) IF: 1.585, WoS link |
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Geier J, Sera L, Hudak M Whiter than white, blacker than black-overshot in lightness perception PERCEPTION 36: p. 80 (2007) IF: 1.617, WoS link |
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Hudak M, Geier J White effect without physical edges PERCEPTION 38: p. 51 (2009) |
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Geier J, Hudak M, Lingelbach B Two different illusory effects in the Spillmann-Levine grid PERCEPTION 39: p. 165 (2010) IF: 1.293, WoS link |
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Hudak M, Geier J, Lingelbach B Scintillation in the Spillmann-Levine grid PERCEPTION 39: p. 166 (2010) IF: 1.293, WoS link |
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Hudák Mariann, Geier János The segmenting effect of diagonal lines in the ramped Chevreul illusion In: European Conference on Visual Perception. Toulouse, France, 2011.08.28-2011.08.30. p. 202 (Perception 40 ECVP Abstract Supplement) http://www.perceptionweb.com/abstract.cgi?id=v110565
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Hungarian conference talks:
Hudák Mariann és Geier János: White-illúzió fizikai élek nélkül (in Hungarian), 15. Magyar Látás Szimpózium, December 18, 2009
Link: http://sites.google.com/site/latasszimpozium/Home/kivonatok
Füzesiné Hudák Mariann és Geier János: A RadGrad modell alkalmazása a színes Hermann-rács foltjaira. (in Hungarian), MAKOG XV. Eger, Hungary, January 19-21, 2007
Link: http://www.makog.cogpsyphy.hu/MAKOGprogram.pdf
Séra László, Bernáth László, Geier János, Füzesiné Hudák Mariann: A Chevreul illúzió változása a háttér rámpa változtatásával, avagy hogyan értelmezünk? (in Hungarian), MAKOG XV. Eger, Hungary. January 19-21, 2007
Link: http://www.makog.cogpsyphy.hu/MAKOGprogram.pdf
Hudák Mariann, Geier János: Receptív mezők, sűrű sötét erdők? (in Hungarian), 14. Magyar Látás Szimpózium, August 30, 2008, Pécs, Hungary
Link: http://kognit.edpsy.u-szeged.hu/latasszimpozium/2008/absztrakt.htm
Hungarian conference poster:
Geier János, Séra László, Hudák Mariann : A vizuális illúziók napjainkban (in Hungarian), Magyar Pszichológiai Társaság Nagygyűlése, Nyíregyháza, Hungary, 2008
OTDK paper (2nd place):
Hudák M. F. (2006), A színes Hermann rács foltjainak törvényszerűségei, OTDK dolgozat. OTDK 2007, Piliscsaba, Hungary
Other references
Adelson, E. (1993), Perceptual organization and the judgment of brightness. Science, 262 (5142), 2042–2044
Anstis, S. (2006), In honour of Lothar Spillmann - filling-in, wiggly lines, adaptation, and aftereffects, Prog. Brain Res., 155, 93-208
Bach és Poloschek (2006), Optical illusions, Advances in Clinical Neuroscience and Rehabilitation, 6(2), 20-21
Baumgartner, G. (1960), Indirekte Größenbestimmung der rezeptiven Felder der Retina beim Menschen mittels der Hermannschen Gittertauschung, Pflugers Archiv für die gesamte Physiologie, 272, 21-22
Blake, R. (1989), A neural theory of binocular rivalry. Psychol. Rev. (96), 145–167
Blakeslee, B. &. McCourt M. E. (2004), A unified theory of brightness contrast and assimilation incorporating oriented multiscale spatial filtering and contrast normalization, Vision Research, (44) 2483–2503
Cohen MA, Grossberg S. (1984), Neural dynamics of brightness perception: features, boundaries, diffusion, and resonance, Percept Psychophys., 36(5) 428-456
Geier J, (2009), A diffusion based computational model and computer simulation for the lightness illusions, Perception (38) ECVP Abstract Supplement, 95
Link: http://www.perceptionweb.com/abstract.cgi?id=v090993
Hoffmann, K. P. (2008), Faculty of 1000 Biology, 5 Aug 2008
Link: http://www.f1000biology.com/article/id/1118826/evaluation
Howe, P.,D.,L. & Livingstone, M. S. (2007), The use of the cancellation technique to quantify the Hermann grid illusion. PLoS ONE 2(2) e265
Kovacs I., Papathomas T.V., Yang M., Feher A. (1996), When the brain changes its mind: interocular grouping during binocular rivalry. Proc Nat Acad Sci U S A 93: 15508-11
Kovacs, I., and Eisenberg, M. (2005), “Human development of binocular rivalry,” inBinocular Rivalry, eds D. Alais, and R. Blake (Cambridge: MIT Press), 101–116
Lingelbach, B. és Ehrenstein, W. (2004), Neue sinusförmige Variante des Hermann-Gitters. Optikum, December 14, 2004
Link: http://www.optikum.at/modules.php?name=News&file=print&sid=319
Otazu, X., Vanrell, M., Párraga, A. (2008), Multiresolution wavelet framework models brightness induction effects, Vision Research (48) 733–751
Pastukhov, A., and Braun, J. (2011), Cumulative history quantifies the role of neural adaptation in multistable perception, J. Vis. 1, 12
Pinna, B. (1987), Un effetto di colorazione. In V. Majer, M. Maeran, and M. Santinello, Il laboratorio e la città. XXI Congresso degli Psicologi Italiani, 158
Schiller P H, Carvey C. E. (2005), The Hermann grid illusion revisited. Perception, (34) 1375- 1397
White M. (1979), A new effect of pattern on perceived lightness. Perception, 8(4), 413 – 416