August 30, Alternative to the Mishkin-Ungerleider model

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1 Visual Cognition August 30, 2007 2 3 Overview of Visual Cognition Visual system: mission critical Multivariate inputs, unitary experience Multiple types of vision means distributed visual network Segregating vs. parsing Visual experience reveals nature of underlying representations Theory >> data 4 Who s Coming to Dinner? Gestalt Psychology (interested in basic dimensions of perceptual organization) Cognitive Psychology (interested primarily in effects of cognitive operations on visual experience) Cognitive Neuropsychology (interested in effects of selective lesions of visual cortex on visual behavior) Electrophysiology (interested in single- and multiple-unit activity of cells in visual cortex) Cognitive science (interested in developing overall theories of visual experience and object recognition) 5 Sensation and Perception Sensation: Conscious outcome of sense organs and projection regions. ( I detect something, not necessarily conscious, and not necessarily meaningful) Perception: means by which information acquired from the environment via the sense organs is transformed (organized) into conscious experiences of objects, events, sounds, tastes, etc. ( I know, recognize, appreciate what I am sensing, and it means something to me ) 6 Three Stages of Visual Processing Reception: absorption of physical energy by receptors Transduction: translation of physical energy into electrochemical activity Coding: relationship between aspects of the physical stimulus and resultant nervous system activity 7 Basic Perceptual Phenomena You Already Know About Size and Shape Constancies: reflect mechanisms whereby perception of a distal object stays the same despite proximal changes in the perception implies storage of a structural representation Depth Cues: monocular or binocular sources of information that convey information about relative distance of objects from viewer involve cues about the structure, movement, and proximity of objects 8 9 10 Milner & Goodale: Perception-Action Model Alternative to the Mishkin-Ungerleider model 1

Dorsal: How do I interact with that object? Ventral: What is that object? Evidence: distinctions between object recognition and visual control of action; Balint s syndrome; optic ataxia 11 Perceptual Organization Two complementary issues: Organizing coherent objects and events out of segregated sensory/perceptual inputs ( binding ) Parsing the perceptual world; understanding which inputs belong together and which come from separate objects 12 Perceptual Organization Gestalt Psychology Law of Prägnanz: perceptual system organizes to the simplest and most stable shape possible from the array other laws describe how disparate perceptual elements are grouped although their laws are probably incorrect, the elementary concept of perceptual grouping is critical Inferring processes from performance 13 Examples of some of the Gestalt laws of perceptual organization: (a) the law of proximity; (b) the law of similarity; (c) the law of good continuation; and (d) the law of closure. 14 Figure Ground Segregation An ambiguous drawing which can be seen either as two faces or as a goblet 15 Principle of Good Continuation Schematic depiction of two types of displays: (a) homogeneous displays and (b) heterogeneous displays. From Spelke et al. (1993) with permission from Elsevier. 16 17 The study by Quinlan and Wilton (1998) shows that the Gestaltists de-emphasized the complexities involved when laws of grouping are in conflict. (a) Display involving a conflict between proximity and similarity; (b) display with a conflict between shape and colour; (c) a different display with a conflict between shape and colour. All adapted from Quinlan and Wilton (1998). 18 19 20 21 Gestalt Theory in the 21 st Century Basic perceptual principles have survived Contentions that such processes are necessarily very early in perception have not Proximity computation occurs after depth perception Segmentation is not just bottom-up (Vecera &Farah, 1997) 2

22 Illusions are fun. But their real value is that they reveal shed light on what is stored about object structure 23 24 25 26 27 28 Depth Perception Monocular depth cues cues that provide depth information with one eye closed pictorial cues (e.g., linear perspective) aerial perspective (differing contrast) texture gradients (decreased detail from front to back) interposition shading (production of shadows by 3-D objects) familiar size as anchor motion parallax 29 30 31 32 33 34 35 36 Depth Perception (cont d) Binocular Cues to Depth Binocular disparity: different images to each eye as a function of object closeness; basis of stereoscopic vision Binocular convergence: rotation of eyes depending on object closeness; brain receives efferent motor signals from ocular muscles and interprets distance accordingly Motion parallax: differential perception of motion (speed and direction) as a function of distance from perceiver 37 38 How are depth cues combined? 3

Additively Preferentially Multiplicatively Most data suggests additivity, though one cue may occasionally overwhelm another in certain circumstances 39 Color Vision Young-Helmholtz theory: three populations of cones Wide receptivity to wavelenth (continuous, not categorical; i.e., not just RGB detectors) Opponent-Process theory: R-G, B-Y, B-W LGN cells show activity to some wavelengths and activity to others Synthesis: Two-stage theory (Trichromatic at the level of neurons; O-P at the level of fibers and pathways) 40 41 Multiple Visual Areas (Zeki( Zeki) V1 and V2: responsive to color and form V3 and V3A: form and motion V4: color V5: motion 42 Color perception/cognition can be selectively impaired Achromatopsia: selective impairment of inferior visual cortex (V4?) Color anomia: a general visual-verbal disconnection (seen with other visualverbal disturbances) Specific color aphasia: specific inability to name colors 43 Theories of Perception Indirect perception: perception is the result of interactive processes from without and from within use of internal representations based on top-down and bottom-up processing Direct perception (Gibson): information from the visual world is sufficient to permit perception without the involvement of internal representations - focus in bottom-up processing, without the need to posit internal representations 44 Direct View (Gibson) Optic array contains all necessary visual information Layout of objects in space given by texture gradients, optic flow patterns, and affordances (implied meaning of objects) Perception involves picking up information through resonance Has had historical impact in restoring interest in the perceptual environment Has been criticized as being underspecified, and neglects role of knowledge in stimulus exploration 45 Data in Favor of Indirect View Context effects in perception: what is seen depends upon surround Effects of emotion (e.g., weapon focus) Visual illusions: idea is that general knowledge about objects is applied inappropriately to the perception of two-dimensional figures (e.g., Muller-Lyer) 4

46 47 Template Theories of Pattern Recognition Template theories: a miniature copy or template of each known pattern is stored in long-term memory straightforward template theory normalized template theory Problems not adaptable impose large storage requirements 48 49 Feature Theories of Pattern Recognition Feature theories: pat-terns consist of a set of specific features or attributes Advantages: elementary features can combine to form multiple objects Problems: context effects in perception recognition can take place when features are occluded 50 Prototype Theories of Pattern Recognition Individual instances are not stored; what is stored is an exemplar or representative element of a category Recognition based on distance between perceived item and prototype Nature of computation still relatively unknown 51 52 53 Theories of Object Recognition 54 Object Recognition: Key Questions When does one object end and another begin? (grouping/segmentation) Viewpoint independence (perception of objects as objects, regardless of view) How do we know that dogs are dogs and not cats, and how do we know the meaning of what we re seeing? (categorization) 55 More Key Issues The binding problem : if perception of a given object is distributed throughout visual areas, how does the brain combine features to produce unitary percept? Conscious vs. unconscious perception: perception of some object or object qualities may proceed pre-consciously or without effort (a general principle) 56 57 The Building Blocks of Object Recognition: Marr s s Representations Primal Sketch: 2-D representation of light intensity changes, information about edges, contours, and blobs Raw: pure light intensity changes Full: uses information to identify shapes 2 1/2-D Sketch: depth and orientation of visible surfaces, shading, texture, motion, binocular disparity; observer-centered 5

3-D Sketch: three dimensional description of objects independent of view 58 Marr-Hildreth Algorithm Attempts to account for development of primal sketch Idea of blurred repres-entations Zero-crossings identify edges within a visual image Only reliable zero-cross-ings are kept Four types of tokens: edge-segments, bars, terminations, and blobs 59 Marr & Nishihara (1978) Development of 3-D sketch based on processing of more elementary shape primitives (basic primitive is a cylinder with a major axis) Hierarchical organization of primitives Concavities important in segmenting parts This is a completely computational, not empirical, model 60 61 Biederman s RBC Theory Objects built from primitives called geons (n = 36) Viewer must decide appropriate way a visual object is to be segmented into geons Two key components of decision: locating concavity deciding which edge information remains invariant across different viewing angles (invariant properties like curvature, parallelism, etc.) 62 Biederman s Recognition-by-Components Theory Adapted from Biederman (1987) 63 Recognition-by-Components Theory Biederman (1987): five invariant properties of edges Curvature: points on a curve Parallelism: sets of points in parallel Cotermination: edges terminating at a common point Symmetry: versus asymmetry Collinearity: points sharing a common line 64 Biederman (1987). Participants were presented with degraded line drawings of objects. Recognition was much harder to achieve when parts of the contour containing concavity information were omitted than when other parts of the contour were deleted. This confirms the assumption that information about concavities is important for object recognition. Figures adapted from Biederman (1987). Biederman s view is viewpoint invariant 65 66 67 Viewpoint-dependent and Viewpoint-invariant Theories Biederman (1987) The ease of object recognition is not affected by the observer s viewpoint 6

Tarr (1995), Tarr and Bülthoff (1995, 1998) Changes in viewpoint reduce the speed and/or accuracy of object recognition Milner and Goodale (1995) Dorsal pathway makes use of viewpoint-dependent information Ventral pathway makes use of viewpoint-invariant information 68 Common Elements in Object Recognition Theories Edge coding Grouping or encoding into higher-order features Matching to a stored structural representation Access to semantic knowledge 69 Face Recognition Two general theories: Neural substrate model (module) Specialized processing model Face recognition can be selectively impaired (prosopagnosia), or can it? Global (configurational) vs. local (feature-based) processing 70 71 72 73 74 75 76 Examples of Greebles. In the top row, four different families are represented. For each family, two members of different genders are shown (e.g., Ribu is one gender and Pila is the other). The bottom row shows a new set of Greeble figures constructed on the same logic but asymmetrical in structure. Images provided courtesy of Michael J. Tarr (Brown University, Providence, RI). 77 Speed of Greeble matching as a function of stage training and difference in orientation between successive Greeble stimuli. Based on data in Gauthier and Tarr (2002). Figure shows that, although speed increases with training, Greeble identification is still viewpoint dependent 78 Face Recognition Probably involves specialized processing/visual expertise Dedicated neural substrates aren t the only answer Hybrid model: neural substrates dedicated to configural processing 79 Disorders of Object Recognition Visual Agnosia 7

Apperceptive agnosia Object recognition is impaired because of deficits in perceptual processing Associative agnosia Perceptual processes are essentially intact, but object recognition is impaired partly or mainly because of difficulties in accessing relevant knowledge about objects from memory 80 Riddoch and Humphreys (2001) A hierarchical model of object recognition and naming, specifying different component processes which, when impaired, can produce varieties of apperceptive and associative agnosia. 81 82 Structural Descriptions Structural descriptions consist of propositions which describe the nature of the components of a configuration and make explicit the spatial arrangement of these parts (Bruce & Green, 1990) Perceptual representation systems for faces, objects, etc. Evidence for separate systems: category-specific recognition defects 83 84 85 8