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The development of perceptual integration Topics in Cognitive Development, V. 3 December 2008 Zoltán Jakab Department of Cognitive Science, Budapest University of Technology and Economics Remember receptive fields How were they discovered? Stimulating the retina with a small light spot Recording from the optic nerve Stephen W. Kuffler (1913-1980) Receptive fields in the retina Stimulation Response of the of the retinal field ganglion cell All illuminated ganglion cell Center only excitatory illuminated connection from photoreceptor Periphery only ganglion cell illuminated inhibitory connection from Periphery photoreceptor Ganglion cell partially illum. ganglion cell spikes along the time axis All dark So in total darkness the response is stronger than when periphery only is illuminated! The other way around… Stimulation Response of the of the retinal field ganglion cell All illuminated ganglion cell Center only excitatory Illuminated connection from photoreceptor Periphery only ganglion cell Illuminated inhibitory connection from Periphery photoreceptor partially illum. ganglion cell All dark Receptove fields and the retina Photoreceptors in the retina connect to ganglion cells in ”bundles” with a special structure. cones rods bipolar cells (B) horizontal cells (H) amacrine cells (A) ganglion cells fibers of the optic nerve A beeső fény iránya An application of the concept: the Hermann grid We see the gray blobs at every junction except the one we fixate on An explanation Note: this story presupposes that RFs come in different sizes Bigger ones are found on the periphery; smaller ones at the fovea (BTW, that explains what?) It this the whole story? Do we see the blobs in the sinusoud version of the Hermann grid? What is the problem? The scintillating grid Receptive fields at higher levels Direction-selective cells in the primary visual cortex David Hubel & Torsten Wiesel (1960s & 70s) Stimulus OFF ON OFF Electric signal Microelectrode Tuning curve Direction of stimulus Orientation and direction selectivity in the primary visual cortex Hubel and Wiesel (1968): presented drifting oriented luminance bars and drifting luminance spots to monkeys while recording form their V1. The orientation selectivities of neighboring cells are similar – there is a systematic variation. Retinal/thalamic receptive fields are organized in more complex structures to give rise to a direction- selective V1 cell Receptive fields of different sizes Campbell and Robson (1968) Tested by sinusoidal gratings Four parameters: 1. frequency 2. amplitude 3. phase 4. orientation Images and sinusoidal gratings Add two low-freq Any 2D image can be synthetized sinusoid gratings with orientations out of a properly chosen set of 45 and 315 sinusoidal gratings We need to add up the gratings Add this one Put another way: Any 2D image can be decomposed into sinusoidal gratings – the list of such grating is the image’s spectrum. Fourier analysis Making a square-wave out of sine-waves Modulation transfer functions -- Lenses, mirrors, and other optical devices -- they change image spectra -- attenuating especially the higher frequencies. -- think of a clean vs. a greasy lens The MTF in action original intensity distribution spectrum (Fourier- anal.) of original lens transfer function image spectrum modified by Intensity distribution of the the lens Image formed by the lens How can we measure perceptual transfer functions? -- Can’t see the image directly -- Discriminative responses can help Contrast sensitivity functions Lightness, color, and CSFs The ability to resolve high- contrast patterns depends on illumination Window of visibility Chromatic CSFs They develop considerably in infancy, as color vision improves (significant improvement between 1 to 4 months) Lenses versus nervous systems Humans and other animals: CSFs are often bandpass filters Optical devices: MTFs are low-pass filters. Lenses cannot help but transmit low frequencies. Not so for nervous systems: low frequencies, like high ones, are transmitted only if some neurons selectively respond to them. Another evidence for neuronal action: increasing visual acuity Improvement is due to development of the primary visual cortex Amblyopia: loss of visual acuity due to lack of proper stimulation – the eye may be optically perfect – the visual system is affected (incurable and irreversible) Measuring CSFs: animals and infants The stuctural basis of CFSs The overall curve arises from… … selective responses of individual neurons to different spatial frequencies. -- Receptive fields of different sizes are likely part of the explanation. Evidence: Selective adaptation to different frequencies direction-selectivity (likely a product of direction-selective cells) Division of labor in the visual system Two visual (sub)systems - Primate physiology and anatomy - Human psychophysics and lesion studies The two subsystems process the same input information in different ways (David Milner and Melvyn Goodale, 1995) Separation after the primary visual cortex Earlier: ”what” and ”where” systems More recently: perception vs. action Double dissociation between the subsystems System-specific tasks Ventral system lesion: - shape perception is disrupted – shape and size-based discrimination is not possible (color perception, and color- based object discrimination may stay intact!) - verbal report on viewed shapes is severely affected - the mailing task; grasping an object - walking along a rocky path Dorsal system lesion: The opposite pattern – object representation remains Source of the pictures: Milner-Goodale: Sight Unseen) Optic ataxia (Bálint syndrome) Dorsal system lesion – conscious vision, object representation and report in language are all intact – visuomotor coordination is impaired The two pathways An example of dissociation: The Ebbinghaus illusion The central disks look different in size, although they are the same size The illusion also obtains for disk configurations of this kind. Measuring grip size The distance between the index finger and thumb Infrared markers attached to the ends of the fingers The grasping hand is NOT fooled by the illusion More illusions that behave the same way A contrasting case: Rod and frame illusion (top): no visuomotor effect (posting task) Simultaneous tilt illusion (bottom): visuomotor effect is just as strong as the perceptual one. How do we explain this? The latter illusion is likely the result of local effects in the primary visual cortex, and is passed on to both streams. Further functional differentiation within the ventral stream FFA: fusiform face area PPA parahippocampal place area LO: lateral occipital area Visual agnosia has different forms. (1) Object agnosia (2) Prosopagnosia (3) Topographic agnosia (activated by pictures of buildings and scenes; memory-based spatial orientation is one of its functions – e.g., remembering a route and prominent landmarks) Summary The action system: encodes object properties that change each moment wrt the observer. Online processing; Egocentric coordinates (the origo is the observer); Very short memory span (the past is irrelevant for current action) The perception system: encodes object identity and object properties for future cognition Object-centered descriptions Long-term memories Only the representatons in the perception system are conscious The structure of the primary visual cortex The structure of the primary visual cortex Organized in layers and columns Several types of cells Six Brodmann layers, and their later subdivisions Layers receiving innervation from LGN: 2/3 (supragra- Source: http://scien.stanford.edu/class/psych221/ nular) and 4C Cortical columns Columns are the vertical arrangement of cells from the surface to the white matter. Columns are both anatomical and functional units. Anatomical: e.g., the apical dentrites of pyramidal cells are bundled together in a small region Functional: columns of cortical cells all respond to the same stimulus feature (e.g., orientation, direction or color). Ocular dominance columns Visual signals from the ganglion cells remain segregated in the LGN, and up to V1. Within layer 4C there are abrupt shifts as to which eye drives the excitatory cells in a small region (such shifts occur within 50 microns). Ocular dominance columns in V1. Source: http://webvision.med.utah.edu/VisualCortex.html Receptive field properties Each cell in the visual cortex has a receptive field – a retinal region and the corresponding area in space – where the presentation of a stimulus causes response in the cortical cell in question. Mapping of the retina on the unfolded V1. Source: http://webvision.med.utah.edu/VisualCortex.html Orientation and direction selectivity Hubel and Wiesel (1968): presented drifting oriented luminance bars and drifting luminance spots to monkeys while recording form their V1. The orientation selectivities of neighboring cells are similar – there is a systematic variation. Source: http://webvision.med.utah.edu/VisualCortex.html Orientation-selectivity maps in the monkey brain A map of V1 orientation-selective cells coded in different colors. Smaller sortical columns are location and orientation-selective. Out of these, larger columnar structures arise which contain cells selective to different orientations at the same location (i.e., completely overlapping receptive fields with different orientation selectivities). Source: Csépe-Győri-Ragó: Általános pszichológia, 3.7., p113. Hubel and Wiesel also found binocular cells in V1 – cells that responded preferentially to input coming simultaneously from both eyes. Plus, they also found binocular-disparity-sensitive neurons: some neurons respond proportionally to the level of disparity V. Gabor patches Gabor patches are tiny pieces of sinusoidal gratings (one cycle across) They fit very well to the receptive fields of V1 orientation-selective cells – a good way to selectively stimulate these cells VI. Tests of low-level visual integration The role of integration: - Representing global patterns within local elements detected by the receptive fields - A useful side-effect: completing fragmentary stimuli A classical example by D. Marr We see circles and other geometrical figures overlapping and criss-crossing one another This figure is ambi- guous: it permits different groupings of its primitives The ambiguity creates the imp-ression of continu-ous change, or “swarming”, thereby demonstrating the active structure- seeking effort of early vision. Glass patterns The local elements are dots – they do not have orientation. Pattern is coded in the alignment of local elements. Psychological difference: it is argued that extrastriate areas are involved in recognizing Glass patterns. (3) Illusory contours (Kanizsa figures). V1, V2, and other extrastriate areas are involved in the perception of illusory contours (Kovács, 2000) The development of visual integration Newborn and infant visual performance: - Very early preference for moving stimuli - Good flicker sensitivity from 2 months on - Chromatic discrimination at 2-3 months - The onset of stereopsis around 4 months - Increasing visual acuity Local vs. integrative? Local attributes: contrast; color; motion Local processing: does not take between-receptive-fields interactions. The processing of local features takes place in V1. Motion integration: the aperture problem Retinal cells V1 cell Contour-integration cards: examining a relatively simple form of visual integration Developed by I. Kovács et al. Consists of Gabor signals Contains a contour (in this case, a closed one), arising from the collinear alignment of part of the signals The contour is embedded in noise. A key parameter for variation: avg distance of contour elements per avg distance of noise elements (Δ). The lower the delta, the more difficult it is to detect the contour If delta is greater than 1, that is a distinct cue for contour recognition. Collinear alignment is another critical feature for detection Orientation is indeed critical... It is argued that V1 is sufficient for accomplishing this sort of integra- tion. A severely agnosic patient with extensive bilateral damage to a number of extrastriate areas, but with spared V1 showed normal performance on the contour integration test. (Riddoch et al, Brain, Vol. 122, No. 3, 1999) I. Kovács, Vis. Res. 40 (2000), 1301-1310 What is the anatomical substrate of contour integration? Long-range, horizontal connections within the primary visual cortex. Top-down influences from extrastriate areas may also play a role Horizontal connections arise from axons of pyramidal cells found in the supragranular layers (Br layers 2-3) of V1* Conjecture: the network of horizontal connections that is thought to underlie contour integration … …includes connections of cells with similar orientation tuning that code for neighboring locations …the fine-tuning of such connections is due to visual input containig long contours Maturation in humans and animals Horizontal connections of a layer 3 pyramidal cell. Actual length of such axons is up to 1-2 mm. Such connections connect V1columns with similar orientation-selectivity. Source: Csépe-Győri-Ragó: Általános pszichológia, 3.7., p113. Contour integration in infants: continuity and closure Two principles of visual organization – good continuation – closure both were pointed out originally by the Gestalt psychologists Contours on the cards are continuous; they consist of collinear elements (Gabor signals) - - in addition, they may be open or closed. The perceptual significance of closure: a closed contour likely indicates a shape or a surface area. In experiments with adults, closed contours did have an advantage over open ones (Kovács&Julesz, 1993). An experiment with infants (3-4 m) Top: a contour that is easy to detect Operant conditioning for a 3-month-old; the bottom one is difficult. procedure Baseline level of kicking assessed; then came the training with reinforcement After the training, when the infant detected a contour on the cards, kicking slowed down for a while Results Infants this old did detect contours based on orientation information alone (delta less than 1)… …but their threshold was at or above Δ=0.8 (with a noise ratio greater than that, they went on kicking fast). In contrast with adults, closure made no difference Hatched bars: baseline White bars: right after training with reinforcement Dark bars: new stimuli containing contours Discussion It looks like the mechanism for detecting continuity is present at this age, however, that for detecting closure is not. Increased noise sensitivity might indicate shorter spatial range of the horizontal connections that are thought to underlie contour integration Related findings at this age: - 4-month-olds lack of interest in static occlusion displays (Kellman and Spelke) A simple occlusion display: an open and a closed contour A computer model of filtering and integration Visual processing begins with filtering the retinal image. Filtering is carried out by receptive fields of small sizes – - filters are orientation-selective (and also spatial frequency selective, but their spatial-freq-selectivity is determined by their size) The next step is interactions between the filters Infants are less sensitive to both color and luminance contrast, still, some signs of perceptual integration (filter interactions) are detectable in their case Output of a computer simulation of local filtering and filter interactions Two differences between infants and adults (i.e., at this early level of processing) more coarse-grained resolution in infants due to the predominance of lower spatial frequencies - cf. fig. c) and d) More efficient combina- tion of local filter outputs (edge definition and ownership, figure-ground segmentation, occlusion) What is the rate of maturation of early integration like? Maturation extends into childhood (5-14 yrs) Children’s lower performance is not due to their lower contrast sensitivity How do we know? Adults perform equally well on levels of stimulus contrast much lower than what children experience with the original cards Spatial range of interaction and the horizontal connections of V1 In addition to Δ, there is another parameter that may be varied on the cards avg distance of contour elements per avg distance of noise elements may stay constant while the absolute values of the two distances vary Thus we may have “sparse” cards and “dense” cards with the same deltas Any psychological significance? Yes indeed. A study with three sets of cards (sparse, intermediate, dense) – the members in the three series had matching delta values Adult performance was unaffected by the density parameter, whereas 5-6-yr-old children did worse on the sparse cards than on the other two sets. Why so? The spatial range of horizontal connections, therefore long- range interactions, may be limited in children. In fact, it is one property of neuronal connectivity how far the axons reach; another is, how finely their connections with other orientation-selective cells are tuned. Children’s visual cortex may be less developed on both counts.* The cue-specificity of integration High degree of stimulus-specificity indicates early levels of visual cortical processing. At these levels stimulus dimensions are still separable. Experiment to address this: - standard (orientation-based) contour-integration cards, and - color-based ones with identical arrangements of primitives Is there a transfer of learning from orientation to color and vice versa? Contour integration based on color vs. orientation The color-based cards had the same configuration of primitives as the orientation-based ones. Kovács et al., Proc. Natl. Acad Sci USA, 96(21) 12204-9 Tests on three consecu- tive days 4 X 2 groups: (orientation; color; orientation-to-color; color-to-orientation); (5-6 yrs; 19-35-yrs) There was improvement over three days in the O and C groups (more pronounced among children than adults); No transfer among adults (OtoC and CtoO grps) A tendency toward transfer in children Summary Both age groups improve with practice Transfer is absent in both groups What can we infer from this? The same mechanism might be responsible for orientation vs. color-based integration, but it operates on different early representations in the two cases. The processes are separate, but they are of the same kind: e.g., long-range interactions between orientation-selective cells vs. color-selective ones. This explains both lack of transfer and similar performance in the two tasks. Integration beyond contours – and beyond V1 Pictorial illusions (M-L, Ponzo, Ebbinghaus, perspective and relative size, etc.) According to preliminary data, they are weaker in children than in aduls They are absent in the newly sighted They arise in the ventral system (Milner and Goodale) An experiment (Kovács et al.) How can we measure the magnitude of a pictorial illusion? Take the Ebbinghaus one 2AFC task Solid curve: probability of ”bigger” and ”smaller” responses depending on the ratio of sizes of the two central disks, when the illusion is absent. Dashed curve: illusion introduced Method Subjects: 4-yr-old children and adults Four conditions; size of one of the central disks is varied 8 comparison sizes for each condition, 1.33 mm steps Each size was presented five times Results Solid: adults, Dashed: children There was a diffe- rence between children and adults in the upper two conditions There was a significant age-related difference in the first two conditions None in the fourth (i.e., children can reliably estimate the size ratios of the disks) Contrary to expectations, the third condition did not produce a significant difference. Remarks Children perceive more veridically in some settings Size constancy: related to contextual integration Adults are more susceptible to size- constancy-related illusions than children Information about distance is important in size-constant perception Which system is involved in size- constant perception – ventral or dorsal? Dorsal system lesions in monkeys do no affect size-constant perception Distance-dependent changes in neural responses in the ventral system. Finally: the rate of maturation of the ventral vs. dorsal system New methods are needed to assess dorsal system functions What we know: The ventral system appears to have an extended course of development Ontogenetically, there is a greater need for early availability of spatial orientation and visuomotor cordination (i.e., dorsal function) than conscious representation and long-term memories of visual impressions Anatomical and phylogenetic evidence also supports slower maturation of the ventral system.
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