DOCSLIB.ORG

Effects of Luminance Contrast on Color Spreading and Illusory Contour In

Total Page：16

File Type：pdf, Size：1020Kb

Download full-text PDF Read full-text
Effects of Luminance Contrast on Color Spreading and Illusory Contour In Perception & Psychophysics 1989, 45 (4), 427-430 Effects ofluminance contrast on color spreading and illusory contour in the neon color spreading effect TAKEO WATANABE University of Tokyo, Tokyo, Japan and TAKAOSATO ATR Auditory and Visual Perception Research Laboratories, Kyoto, Japan The present study examined whether color spreading and illusory contours in the neon color spreading effect ofEhrenstein figures are governed by different mechanisms. In the experiment, Ehrenstein figures with colored crosses inserted in the central gaps were used. There were three luminance conditions: the luminance ofthe Ehrenstein figures was lower than, the same as, or higher than the luminance ofthe background. In each condition, 16 trials (2 sets of instructions x 8 repetitions) were conducted in a random order. Subjects were required to adjust the luminance ofthe colored crosses according to one ofthe two sets ofinstruction given before each trial. One was to adjust the upper and lower thresholds in the luminance of the colored crosses such that their color was seen to spread out of the crosses. The other was to adjust the thresholds such that circular illusory contours were visible. It was found that illusory contours disappeared and the color spreading remained when the crosses and the Ehrenstein figures were in or nearly in isoluminance or when the Ehrenstein figures and the background were in isoluminance. These results suggest that color spreading and illusory contours are governed by different mechanisms. Redies and Spillmann (1981) showed that van Tuijl's vary the luminance of the inner segment, the outer seg­ (1975) neon color spreading effect occurred in the Ehren­ ments, and the background. Several studies have shown stein figures (Ehrenstein, 1941) by inserting a colored what effect this has on neon color spreading. Van Tuijl cross (an inner segment) in the central gap to adjoin the and de Weert (1979) found that the luminance of the in­ radial lines (outer segments). The neon color spreading ner segments must be between the luminance ofthe outer effect in the Ehrenstein illusion has two distinguishable segments and that ofthe background for observers to per­ phenomenal aspects: (1) The color of the inserted cross ceive the neon color spreading effect. As for the effect spreads outside its containing contours. We call this of relative luminance between the inner segments and phenomenon the spreading ofinner color. (2) This spread­ outer segments, Redies and Spillmann (1981), using the ing forms a circular area surrounded by an illusory con­ modified Ehrenstein matrix consisting only ofinterwoven tour. We call this phenomenon the formation ofthe illu­ red and green crosses, found that the neon color spread­ sory contour. ing effect disappeared when red and green crosses ap­ The question then arises as to whether different mecha­ proached each other in hue, whereas it persisted when nisms govern the spreading ofthe inner color and the for­ they approached each other in luminance. Ware (1980) mation of the illusory contour. Grossberg and Mingolla also showed that when Kanizsa's (1955) illusory triangle (Grossberg, 1987; Gossberg & Mingolla, 1985a, 1985b) was modified by inserting the inner, colored segments that have, in fact, constructed a model in which the mecha­ completed disks and outline triangles (Varin, 1971), the nism for the color spreading is different from that for the neon color effect was observed when the inner segment illusory contour formation. and the outer segments were approximately the same in Ifwe are able, experimentally, to separate the spread­ luminance. ing ofinner color from the formation ofthe illusory con­ These studies did not. however, distinguish the two tour, we can suggest that different mechanisms govern phenomena in question. Ifeither the spreading ofthe in­ these two phenomena. One possibility is to systematically ner color or the illusory contour disappears when the in­ ner segment and the outer segments are in isoluminance, that would suggest that the mechanisms underlying these This study was conducted while Takeo Watanabe was a visiting phenomena are different. research associate at ATR Auditory and Visual Perception Research Laboratories. Requests for reprints should be sent to Takao Sato, ATR As for the relative luminance between the outer seg­ Auditory and Visual Perception Research Laboratories, Seika-eho, ments and the background, Frisby and Clatworthy (1975) Soraku-gun, Kyoto 619-02, Japan. found that the illusory contour disappeared or at least was 427 Copyright 1989 Psychonomic Society. Inc. 428 WATANABE AND SATO weakened when inducing figures, such as three incom­ INNER OUTER plete disks and an incomplete triangle in Kanizsa's (1955) SEGMENT SEGMENT illusory triangle, and the background were in -~ isoluminance. In addition, the neon color spreading ef­ I-52' I 39'1 fect usually occurred when inner segments were inserted Iii in the figures, such as Kanizsa's illusory triangle and I I I Ehrenstein's figure, to induce illusory contours. There­ I I fore, it might be expected that the illusory contour will I I disappear when the outer segments and the background in the figures inducing the neon color spreading effect are in isoluminance. I I If neon color spreading persists and the illusory con­ tour disappears when the outer segments and the back­ ground are in isoluminance, it would suggest that the spreading ofinner color and the formation ofthe illusory contour are caused by different mechanisms. In this ex­ periment, we observed whether both the color spreading and the illusory contour persist or whether one of them persists and the other disappears when the inner segment and the outer segments, or the outer segments and the background, are in isoluminance. MEmOD Subjects II Two males and 1 female, ranging between 25 and 29 years of .Jl_ age, participated as subjects. All of them had normal color vision 2.6' and normal or corrected-to-normal visual acuity. Figure 1. The Ehreostein figure with the cross (the inner segment) Apparatus and Stimuli inserted in the gaps beween the four arms (the outer segments). The of the Ehrenstein figure with the cross were connected to the A computer (Masccomp) with a high-resolution cathode ray tube arms arms ofthe other Ebrenstein fIgUres with the crosses (13 x 13) and (1,152 x 910) was used. The viewing distance was 69 em. Sub­ constituted the presented stimulus. jects sat in a chair equipped with a chinrest. The presented stimulus consisted of 169 (13 x 13) Ehrenstein­ like figures whose radially arranged arms (the outer segments) were left was for increasing luminance ofthe inner segment, and the right connected to each other, and a cross (the inner segment) was in­ was for decreasing luminance of the inner segment) according to serted in the gap between the four arms in each Ehrenstein figure. instructions given before each trial. The two buttons on the small As shown in Figure 1, each arm (the outer segments) and each of box were connected to the computer. By pushing the right (or left) the two lines constituting each cross (the inner segment) subtended button for less than 1 sec, the luminance ofthe inner segment would a visual angle of39' and 52' ofare, respectively. The lines' width increase (or decrease) by one step. If subjects continued pushing subtended 2.6' ofarc. The luminance ofthe background was a con­ the right (or left) button for more than 1 sec, the luminance of the stant 29.3 cd/m'. The color of the background was light blue (x inner segment would continuously increase (or decrease). = .21, y = .36, in chromaticity). The luminance ofthe outer seg­ There were two sets ofinstructions. Instruction A was to adjust ments was varied with three luminance conditions: 43.5, 29.3, or the upper and lower thresholds of the luminance of the inner seg­ 12.7 OO/m'. The color of the outer segments was white (x = .29, ment such that the color of the inner segment (yellow) was seen y = .36, in chromaticity). The luminance ofthe inner segment could to spread out ofthe inner segment. Instruction B was to adjust the be varied by subjects over the range from .66 to 51.9 OO/m' with upper and lower thresholds ofthe luminance of the inner segment 256 steps. The color of the inner segment was yellow (approxi­ such that the spreading formed a circular area. mately x = .38, y = .52, in chromaticity). Eight trials were conducted under each of the two instructions. Four of the eight trials were for the increment sequence, and the Procedure other four for the decrement sequence. In one luminance condi­ The experiment had three luminance conditions. In Condition 1, tion, 16 trials (2 sets of instructions x 8 trials) were conducted the luminance ofthe outer segments was 12.7 cd/m'. The luminance in a random order. Thus, there were 48 trials (2 sets of instruc­ contrast between the outer segments and the background was -.4" tions x 3 luminance conditions x 8 repetitions) in an experimen­ when defined as (Los-LBo)/(Los+LBo), where Los and LBO refer tal session for each subject. to the luminance of the outer segments and of the background, During the intertrial interval (about 20 sec), the subjects were respectively. In Condition 2, the luminance ofthe outer segments asked to tum to the gray screen behind them in order not to adapt was 29.3 cd/m', and the luminance contrast between the outer seg­ to the presented colors. The experiment was conducted in a dark ments and the background was zero. In Condition 3, the luminance room after a 1O-min dark adaptation. of the outer segments was 43.5 OO/m', and the luminance contrast between the outer segments and the background was .2. The order in which the three luminance conditions occurred was randomly RESULTS AND DISCUSSION determined for each of the 3 subjects.
Load more

Recommended publications
  • Neon Colour Spreading in Three-Dimensional Illusory Objects in Humans
    Neuroscience Letters 281 (2000) 119±122 www.elsevier.com/locate/neulet Neon colour spreading in three-dimensional illusory objects in humans Marja Liinasuoa,*, Ilpo Kojob, Jukka HaÈ kkinenc, Jyrki Rovamod aInstitute of Biomedicine, Department of Physiology, P.O. Box 9, 00014 University of Helsinki, Helsinki, Finland bThe Finnish Institute of Occupational Health, Brain Work Laboratory, Topeliuksenkatu 41 a A, 00250 Helsinki, Finland cDepartment of Psychology, General Psychology Division, P.O. Box 13, 00014 University of Helsinki, Helsinki, Finland dDepartment of Optometry and Vision Sciences, University of Wales, College of Cardiff, P.O. Box 905, Cardiff CF1 3XF, UK Received 11 October 1999; received in revised form 7 January 2000; accepted 10 January 2000 Abstract We studied whether neon spreading can be induced within three-dimensional illusory triangles. Kanizsa triangles were induced by black pacman disks consisting of red sectors with curved sides. Viewing our stimuli monocularly produced two-dimensional illusory contours and surfaces as well as neon spreading in each ®gure. Triangles appeared concave or convex under stereoscopical viewing. Neon colour spreading was induced within illusory ®gures bending in three-dimensional space, suggesting that neural contour completion and surface ®lling-in interact across depth. Surpris- ingly, neon spreading was induced above the intervening surface even when the inducers were below the surface. Neon colour and illusory con®guration were preserved behind the intervening surface only when it appeared transparent. q 2000 Elsevier Science Ireland Ltd. All rights reserved. Keywords: Vision; Perception; Illusion; Three-dimensionality; Colour; Neon spreading Illusory ®gures with one to three dimensions are created zontal and vertical crossing lines so that some line elements by the neural processes of visual area V2 [15] between some are replaced by different colour or luminance, the surround- physically existing objects, known as inducers.
    [Show full text]
  • Introducing the Scintillating Starburst: Illusory Ray Patterns from Spatial Coincidence Detection
    Introducing the scintillating starburst: Illusory ray patterns from spatial coincidence detection 1 2 Michael W Karlovich ​ & Pascal Wallisch ​ ​ 1 Recursia Labs. 2 Department of Psychology, New York University Abstract Here, we introduce a novel class of visual illusion, the “Scintillating Starburst”, which features illusory scintillating rays or beams. We show empirically what combination of factors modulate how an observer experiences this kind of stimulus. We explain how the illusion arises from the interplay of known visual processes, specifically magnocellular and parvocellular dynamics and relate the effects of these ray patterns to other known visual illusions such as illusory contours. Introduction Illusions have played a key role in understanding the principles of perceptual processing (Purkinje, 1825; van Buren & Scholl, 2018), although this notion is not entirely without detractors (Braddick, 2018; Rogers, 2019). One important reason why illusions can be helpful is that they allow us to distinguish the mere sensation of physical object properties from the perceptual experience. This is perhaps clearest in the case of illusory contours. If contours are defined by a sharp change in luminance, it is hard to tell whether the observer “directly” perceives objects in the environment “as they are” or if the percept is constructed in the mind of the observer, because the output of a photometer and perceptual judgments agree (Gibson, 1978; Fodor & Pylyshyn, 1981). Conversely, illusory contours are not defined by changes in luminance, and would be invisible to a photometer, whereas human observers readily perceive them. One example of this is Kanisza’s triangle, which most observers perceive as a bright triangle occluding three black circles - as opposed to the three black pac-man-like shapes are actually defined by luminance (Kanisza, 1955).
    [Show full text]
  • Illusory Contours: a Window Onto the Neurophysiology of Constructing Perception
    Review Illusory contours: a window onto the neurophysiology of constructing perception 1,2,3 4,5 Micah M. Murray and Christoph S. Herrmann 1 The Functional Electrical Neuroimaging Laboratory, Neuropsychology and Neurorehabilitation Service, Department of Clinical Neurosciences, Centre Hospitalier Universitaire Vaudois and University of Lausanne, 1011 Lausanne, Switzerland 2 Electroencephalography Brain Mapping Core, Center for Biomedical Imaging (CIBM), 1011 Lausanne, Switzerland 3 Radiology Department, Centre Hospitalier Universitaire Vaudois and University of Lausanne, 1011 Lausanne, Switzerland 4 Experimental Psychology Laboratory, ‘Hearing4all’ Center of Excellence, European Medical School, Carl von Ossietzky University, 26111 Oldenburg, Germany 5 Neurosensory Science Research Center, Carl von Ossietzky University, 26111 Oldenburg, Germany Seeing seems effortless, despite the need to segregate Researchers are generally divided into three camps and integrate visual information that varies in quality, regarding the brain mechanisms responsible for IC per- quantity, and location. The extent to which seeing pas- ception based on the presumed role of feed-forward versus sively recapitulates the external world is challenged by feedback activity, as well as the locus of neural sensitivity phenomena such as illusory contours, an example of visual completion whereby borders are perceived de- Glossary spite their physical absence in the image. Instead, visual Binding:: (neurophysiologic) processes whereby different information is none- completion and seeing are increasingly conceived as theless coded to refer to the same object or event. Here, different information active processes, dependent on information exchange refers to spatially separated stimulus elements, such as inducers of ICs. across neural populations. How this is instantiated in the Bottom-up versus top-down processes:: bottom-up processes rely exclusively on feed-forward architectures, whereas top-down processes incorporate brain remains controversial.
    [Show full text]
  • Chapter 3. Visual Attention and Visual Awareness
    Section I. Anatomy and physiology of the human visual system. CHAPTER 3. VISUAL ATTENTION AND VISUAL AWARENESS. Rufin VanRullen1 and Christof Koch2. 1. CNRS Centre de Recherche Cerveau et Cognition 133 Route de Narbonne 31062 Toulouse Cedex (France) 2. California Institute of Technology Division of Biology and Division of Engineering and Applied Sciences MC 139-74 Pasadena CA 91125 (USA) 1 Intuitively, vision appears an overall easy process, effortless, almost automatic, and so efficient that a simple glance at a complex scene is sufficient to produce immediate awareness of its entire structure and elements. Unfortunately, much of this is a grand illusion (O’Regan & Noe, 2001). Proper manipulations will reveal that many often essential aspects of the visual scene can go purely unnoticed. For example, human subjects will often fail to notice an unexpected but quite large stimulus flashed right at the center of gaze during a psychophysical experiment (a phenomenon known as “inattentional blindness”, Mack and Rock, 1998). In more natural environments, observers can fail to notice the appearance or disappearance of a large object (Fig 3.1; Rensink et al, 1997; O’Regan et al, 1999), the change in identity of the person they are conversing with (Simons and Levin, 1998), or the passage of a gorilla in the middle of a ball game (Simons and Chabris, 1999). As a group, these visual failures are referred to as “change blindness” (Rensink, 2002). Such limitations are rarely directly experienced in real life –except as one of the main instrument of magician tricks; yet they shape much of our visual perceptions.
    [Show full text]
  • Illusory Contour Perception and Amodal Boundary Completion: Evidence of a Dissociation Following Callosotomy
    Illusory Contour Perception and Amodal Boundary Completion: Evidence of a Dissociation Following Callosotomy Paul M. Corballis and Robert Fendrich Dartmouth College Robert M. Shapley New York University Michael S. Gazzaniga Dartmouth College Abstract A fundamental problem in form perception is how the tion of illusory contours and amodal completion. Although visual system can link together spatially separated contour both cerebral hemispheres appear to be equally capable of fragments to form the percept of a unitary shape. Illusory perceiving illusory contours, amodal completion is more read- contours and amodal completion are two phenomena that ily utilized by the right hemisphere. These results suggest that demonstrate this linking process. In the present study we illusory contours may be attributable to low-level visual proc- investigate these phenomena in the divided hemispheres of esses common to both hemispheres, whereas amodal comple- two callosotomy (“split-brain”) patients. The data suggest that tion reects a higher-level, lateralized process. dissociable neural mechanisms are responsible for the genera- INTRODUCTION Figure 1a, no illusory contours are seen. In such cases, the grouping process responsible for the perception of To perceive objects in the environment as unied the rectangle has been termed “amodal completion” wholes, the visual system must often extrapolate from (Michotte, Thines, & Crabbe, 1964).1 incomplete contour or boundary information. Under cer- The relationship between amodal completion and the tain conditions
    [Show full text]
  • A Model of the Illusory Contour Formation Based on Dendritic Computation
    ARTICLE IN PRESS Neurocomputing 70 (2007) 1977–1982 www.elsevier.com/locate/neucom A model of the illusory contour formation based on dendritic computation Drazˇen DomijanÃ, Mia Sˇetic´, Domagoj Sˇvegar Department of Psychology, Faculty of Philosophy, University of Rijeka, I. Klobucˇaric´a 1, 51000 Rijeka, Croatia Available online 9 November 2006 Abstract We proposed a new model of illusory contour formation based on the properties of dendritic computation. The basic elements of the network are a single-excitatory cell with two dendritic branches and an inhibitory cell. Both dendritic branches behave as an independent linear unit with a threshold. They sum all excitatory input from the nearby collinear cells, and the inhibition from one collateral of the corresponding inhibitory cell. Furthermore, the output of dendritic branches multiplicatively interacts before it is sent to the soma. The multiplication allows the excitatory cell to be active only if both of its branches receive enough excitation to reach the threshold. Computer simulations showed that the presented model of the illusory contour formation is able to perform perceptual grouping of nonadjacent collinear elements. It shows a linear response relationship with the input magnitude because dendritic inhibition counteracts recurrent excitation. The model can explain why illusory contours are stronger with irregular placement of inducing elements rather than regular placement and why top-down influences may prevent the illusory contour formation. r 2006 Elsevier B.V. All rights reserved. Keywords: Contour integration; Dendritic computation; Illusory contours; Recurrent excitation; Top-down processing 1. Introduction graded strength or clarity of illusory contours with the relative size of inducing elements [3].
    [Show full text]
  • The Generic-Viewpoint Assumption and Illusory Contours
    Perception, 2000, volume 29, pages 303 ^ 312 DOI:10.1068/p3016 The generic-viewpoint assumption and illusory contours Marc K Albertô Vision Sciences Laboratory, Harvard University, Cambridge, MA 02114, USA Donald D Hoffman Department of Cognitive Sciences University of California at Irvine, Irvine, CA 92697, USA Received 16 February 1999, in revised form 17 August 1999 Abstract. Visual images are ambiguous. Any image, or collection of images, is consistent with an infinite number of possible scenes in the world. Yet we are generally unaware of this ambiguity. During ordinary perception we are generally aware of only one, or perhaps a few of these possibilities. Human vision evidently exploits certain constraintsöassumptions about the world and images formed of itö in order to generate its perceptions. One constraint that has been widely studied by researchers in human and machine vision is the generic-viewpoint assumption. We show that this assumption can help to explain the widely discussed fact that outlines of blobs are ineffective inducers of illusory contours. We also present a number of novel effects and report an experiment suggesting that the generic-viewpoint assumption strongly influences illusory-contour perception. 1 Introduction Illusory contours ICs) are contours seen where there are no corresponding gradients in the stimulus. Although ICs were first reported around the turn of the century, interest in this phenomenon dramatically increased after Kanizsa 1955) presented his striking demonstrations. Since then ICs have received a great deal of attention both experi- mentally and theoretically for reviews see Parks 1984; Purghe¨ and Coren 1992; Lesher 1995). Figure 1 is a typical example.
    [Show full text]
  • The Watercolor Illusion and Neon Color Spreading: a Unified Analysis of New Cases and Neural Mechanisms
    B. Pinna and S. Grossberg Vol. 22, No. 10/October 2005/J. Opt. Soc. Am. A 1 The watercolor illusion and neon color spreading: a unified analysis of new cases and neural mechanisms Baingio Pinna Facoltà di Lingue e Letterature Straniere, Università di Sassari, via Roma 151, I-07100, Sassari, Italy Stephen Grossberg Department of Cognitive and Neural Systems and Center for Adaptive Systems, Boston University, 677 Beacon Street, Boston, Massachusetts 02215 Received January 18, 2005; accepted April 14, 2005 Coloration and figural properties of neon color spreading and the watercolor illusion are studied using phe- nomenal and psychophysical observations. Coloration properties of both effects can be reduced to a common limiting condition, a nearby color transition called the two-dot limiting case, which clarifies their perceptual similarities and dissimilarities. The results are explained by the FACADE neural model of biological vision. The model proposes how local properties of color transitions activate spatial competition among nearby per- ceptual boundaries, with boundaries of lower-contrast edges weakened by competition more than boundaries of higher-contrast edges. This asymmetry induces spreading of more color across these boundaries than con- versely. The model also predicts how depth and figure–ground effects are generated in these illusions. © 2005 Optical Society of America OCIS codes: 330.0330, 330.1720, 330.4060, 330.4270, 330.5020, 330.5510, 330.7310. 1. INTRODUCTION: A CURRENT VIEW OF One timely piece of evidence was the Thorell et al.1 study, A SEMINAL DISCOVERY OF DEVALOIS which supported the early prediction that these bound- aries and surfaces are processed by the interblob and blob Russell DeValois and his colleagues discovered many streams, respectively, from V1 to V4.
    [Show full text]
  • Sparse Models for Computer Vision
    Chapter 14 Sparse models for Computer Vision BibTex entry This chapter appeared as (Perrinet, 2015): @inbook{Perrinet15sparse, Author = {Perrinet, Laurent U.}, Chapter = {Sparse models for Computer Vision}, Citeulike-Article-Id = {13514904}, Editor = {Crist{\'{o}}bal, Gabriel and Keil, Matthias S. and Perrinet, Laurent U.}, Keywords = {bicv-sparse, sanz12jnp, vacher14}, month = nov, chapter = {14}, Priority = {0}, isbn = {9783527680863}, title = {Sparse Models for Computer Vision}, DOI = {10.1002/9783527680863.ch14}, url={http://onlinelibrary.wiley.com/doi/10.1002/9783527680863.ch14/summary}, publisher = {Wiley-VCH Verlag GmbH {\&} Co. KGaA}, booktitle = {Biologically inspired computer vision}, Year = {2015} } arXiv:1701.06859v1 [cs.CV] 24 Jan 2017 1 Perrinet (2015) Sparse models doi:10.1002/9783527680863.ch14 2 Contents 14 Sparse models for Computer Vision 1 14.1 Motivation . .3 14.1.1 Efficiency and sparseness in biological representations of natural images . .3 14.1.2 Sparseness induces neural organization . .4 14.1.3 Outline: Sparse models for Computer Vision . .5 14.2 What is sparseness? Application to image patches . .6 14.2.1 Definitions of sparseness . .6 14.2.2 Learning to be sparse: the SparseNet algorithm . .8 14.2.3 Results: efficiency of different learning strategies . .9 14.3 SparseLets: a multi scale, sparse, biologically inspired representation of natural images 10 14.3.1 Motivation: architecture of the primary visual cortex . 10 14.3.2 The SparseLets framework . 12 14.3.3 Efficiency of the SparseLets framework . 14 14.4 SparseEdges: introducing prior information . 17 14.4.1 Using the prior in first-order statistics of edges . 17 14.4.2 Using the prior statistics of edge co-occurences .
    [Show full text]
  • Kanizsa Illusory Contours Appearing in the Plasmodium Pattern of Physarum Polycephalum
    ORIGINAL RESEARCH ARTICLE published: 28 February 2014 CELLULAR AND INFECTION MICROBIOLOGY doi: 10.3389/fcimb.2014.00010 Kanizsa illusory contours appearing in the plasmodium pattern of Physarum polycephalum Iori Tani 1*, Masaki Yamachiyo 1, Tomohiro Shirakawa 2 and Yukio-Pegio Gunji 1,3 1 Department of Earth and Planetary Science, Graduate School of Science, Kobe University, Kobe, Japan 2 Department of Computer Science, School of Electrical and Computer Engineering, National Defense Academy of Japan, Yokosuka, Japan 3 The Unconventional Computing Centre, University of the West England, Bristol, UK Edited by: The plasmodium of Physarum polycephalum is often used in the implementation of Kevin B. Clark, Veterans Affairs non-linear computation to solve optimization problems, and this organismal feature was Greater Los Angeles Healthcare not used in this analysis to compute perception and/or sensation in humans. In this paper, System, USA we focused on the Kanizsa illusion, which is a well-known visual illusion resulting from the Reviewed by: Jeff Jones, University of the West of differentiation-integration of the visual field, and compared the illusion with the adaptive England, UK network in the plasmodium of P.polycephalum. We demonstrated that the network pattern Werner Baumgarten, Universität mimicking the Kanizsa illusion can be produced by an asynchronous automata-fashioned Rostock, Germany model of the foraging slime mold and by the real plasmodia of P.polycephalum. Because *Correspondence: the protoplasm of the plasmodium is transported depending on both local and global Iori Tani, Department of Earth and Planetary Science, Graduate School computation, it may contain differentiation-integration processes. In this sense, we can of Science, Kobe University, Science extend the idea of perception and computation.
    [Show full text]
  • HOW DOES the CEREBRAL CORTEX WORK? Learning, Attention, and Grouping by the Laminar Circuits of Visual Cortex
    HOW DOES THE CEREBRAL CORTEX WORK? Learning, Attention, and Grouping by the Laminar Circuits of Visual Cortex Stephen Grossberg* Department of Cognitive and Neural Systems and Center for Adaptive Systems Boston University 677 Beacon Street Boston, MA 02215 April, 1998 Spatial Vision, in press To appear in the special issue on Long-Range Visual Mechanisms Technical Report CAS/CNS-97-023 Running Title: Cortical Circuits for Learning, Attention, and Grouping * Supported in part by the Defense Advanced Research Projects Agency, the National Science Foundation (NSF IRI-97-20333), and the Office of Naval Research (ONR N00014-95-1-0409 and ONR N00014-95-1-0657). S. Grossberg Acknowledgments: The author wishes to thank Robin Amos and Diana Meyers for their valuable assistance in the preparation of the manuscript. 1 S. Grossberg The organization of neocortex into layers is one of its most salient anatomical features. These layers include circuits that form functional columns in cortical maps. A major unsolved problem concerns how bottom-up, top-down, and horizontal interactions are organized within cortical layers to generate adaptive behaviors. This article models how these interactions help visual cortex to realize: (1) the binding process whereby cortex groups distributed data into coherent object representations; (2) the attentional process whereby cortex selectively processes important events; and (3) the developmental and learning processes whereby cortex shapes its circuits to match environmental constraints. New computational ideas about feedback systems suggest how neocortex develops and learns in a stable way, and why top-down attention requires converging bottom-up inputs to fully activate cortical cells, whereas perceptual groupings do not.
    [Show full text]
  • Stereoscopic Illusory Contours—Cortical Neuron Responses and Human Perception
    Stereoscopic Illusory Contours—Cortical Neuron Responses and Human Perception Barbara Heider1, Lothar Spillmann2, and Esther Peterhans3 Downloaded from http://mitprc.silverchair.com/jocn/article-pdf/14/7/1018/1757651/089892902320474472.pdf by guest on 18 May 2021 Abstract & In human perception, figure–ground segregation sug- signal such illusory contours and can be selective for certain gests that stereoscopic cues are grouped over wide areas of figure–ground directions that human observers perceive at the visual field. For example, two abutting rectangles of these contours. The results suggest that these neurons equal luminance and size are seen as a uniform surface group stereoscopic cues over distances up to 88. In addition, when presented at the same depth, but appear as two we compare these results with human perception and show surfaces separated by an illusory contour and a step in that the mean stimulus parameters required by these depth when presented with different retinal disparities. neurons also induce optimal percepts of illusory contours Here, we describe neurons in the monkey visual cortex that in human observers. & INTRODUCTION representations of such contours have been identified Illusory contours are perceived in visual scenes where in the human visual cortex by means of imaging objects occlude one another and produce overlapping techniques such as positron emission tomography images on the retina. If these objects have equal (PET) and functional magnetic resonance imaging luminance, their retinal images merge because their (fMRI). Representations have been localized early in overlapping borders lack luminance contrast. The visual visual processing, in area V2 (Larsson et al., 1999; system has developed methods to recover the segrega- ffytche & Zeki, 1996; Hirsch et al., 1995), and in higher tion of figure and ground in such situations—it gen- areas such as V3A, V4v, V7, and V8 (Mendola, Dale, erates illusory contours that complete the occluding Fischl, Liu, & Tootell, 1999).
    [Show full text]