Ординатура / Офтальмология / Английские материалы / Progress in Brain Research Visual Perception, Part I Fundamentals of Vision Low and Mid-Level Processes in Perception_2006

the duration of the train (Fig. 9). This depolarization is able to reach threshold and evoke a persistent firing of the PH neuron. The depolarization is apparently the result of the joint activation of EBN and of meso-pontine cholinergic axons (Igusa et al., 1980; Navarro-Lo´pez et al., 2004). Train stimuli (430 Hz) seem to be necessary in order to activate cholinergic axons (Moises et al., 1995). It has been shown that cholinergic terminals act on muscarinic M1 receptors located in the membrane of PH neurons (Navarro-Lo´pez et al., 2004), and it can be suggested that cholinergic effects on PH neurons are produced by the generation of a Ca2+-de- pendent unspecific cationic current (Klink and Alonso, 1997a, b; Haj-Dahmane and Andrade, 1999). Thus, the joint activation of glutamatergic and cholinergic receptors located in the membrane of PH neurons seems to be one of the mechanisms involved in the generation of the persistent activity necessary for eye-position signals (Navarro-Lo´pez et al., 2004).

According to unpublished data from our laboratory (Navarro-Lo´pez et al., 2005), train stimulation of the PPRF is also able to open postsynaptic NMDA receptors located in PH neurons. This effect is probably mediated by the simultaneous activation of muscarinic M1 receptors by the train. The activation of M1 receptors increases the production of inositoltriphosphate and diacylglycerol by a molecular mechanism involving a Gp-protein, coupled to the M1 receptor, which activates the phospholipase C. The increase in available diacylglycerol seems to activate endogenous protein kinase C (Fig. 10). Furthermore, it has been proposed that the activation of G-proteins coupled to certain receptors, such as muscarinic M1, is able to potentiate NMDAresponses, at least in hippocampal neurons (Marino et al., 1998; Sur et al., 2003). This potentiation can be blocked by drugs inhibiting protein kinase C (Lu et al., 1999). In turn, protein kinase C seems to enhance the activity of NMDA

receptors through different intermediate steps, including the activation of tyrosine kinases such as Src (Salter and Kalia, 2004). Thus, the final result is an activation of the NMDA receptors by the joint activation of AMPA/kainate and cholinergic receptors located on PH neurons. In fact, some preliminary results from our laboratory (Navarro-Lo´pez et al., 2005) indicate that a short-term potentiation of the PPRF synapse on PH neurons is produced after train stimulation of the same area (c, in Fig. 10). It is difficult to envisage at the moment the role that a short-term potentiation could have on oculomotor performance, but it could be related with the facilitation of the synchronous activation of PH neurons, increasing the signal-to-noise ratio (Lisman, 1997) during alertness.

Acknowledgments

We acknowledge the editorial help of Mr. R. Churchill. The authors thank the help of Dr. Agne`s Gruart in the edition of the figures. This work was supported by grant BFI2000-00939 from the Spanish Ministry of Science.

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Some diseases of the visual system result in a paradoxical situation: patients may present multiple blind regions or scotomas within their visual field, and yet be unaware of their existence, owing to the brain process of ‘‘perceptual completion’’, or ‘‘filling-in’’. Filling-in also takes place near the center of vision in normal healthy retinas, in the blind spot. In 1804, Troxler discovered that during strict visual fixation of a target, a small perimetric stimulus would quickly fade from perception and fill in with the visual texture surrounding it, so that it becomes indistinguishable from the background. This fading stimulus can be thought of as an ‘‘artificial scotoma’’. These facts suggest that

filling-in is a brain process of great importance to surface perception in normal vision as well as in clinical patients. Interestingly, filling-in is usually stronger when the artificial scotoma is presented on a dynamic noise background.

Peter De Weerd’s chapter reviews psychophysical and electrophysiological studies on filling-in of dynamic textures, and discusses the importance of both low-level factors and high-order processes such as the role of attention. Akiyoshi Kitaoka and colleagues describe how several visual illusions can be explained in terms of surface completion.

Susana Martinez-Conde

Introduction

Visual perceptual filling-in refers to the interpolation of information across a region in the visual environment in the absence of any physical evidence for that information in that region. Fillingin can be triggered under a number of different conditions, and some types of perceptual filling-in occur very fast. An example of fast, quasi-instan- taneous filling-in is the perceptual filling-in of the blind spot with the information surrounding it. Similar types of perceptual filling-in have been reported for pathological scotomas (Bender and Teuber, 1946; Sergent, 1988). Another form of fast filling-in (within 80 ms) has been observed across entopic images of vasculature (Coppola and Purves, 1996). Slower filling-in of retinal images (within a few seconds) has been reported under conditions of artificial retinal stabilization (Ratliff,

Corresponding author. Tel.: +31-43-388-4513;

Fax: +31-43-388-4125; E-mail: P.deweerd@Psychology.unimaas.nl

1958; Gerrits et al., 1966; Yarbus, 1967), and during the stabilization of peripheral images through maintained fixation (Troxler, 1804; Riggs et al., 1953). Perceptual filling-in during maintained fixation away from a figure is often referred to as the ‘Troxler effect’, and it can also be observed during fixation in the middle of a disk with boundaries sufficiently far from the fixation point. Depending on the exact stimulus conditions, the time required to achieve Troxler fading can range from a few to many seconds. It has been demonstrated for color, brightness, and (dynamic) texture (Ramachandran and Gregory, 1991; Spillmann and Kurtenbach, 1992; Ramachandran et al., 1993; Fujita, 1993; Friedman et al., 1999; Hamburger et al., 2006).

A distinction can be made between surface fill- ing-in and contour completion. Many studies have been devoted to the completion of contours, and several have investigated the neural correlates underlying contour completion (von der Heydt et al., 1984; Peterhans and von der Heydt, 1989; Grosof et al., 1993). This chapter, however, will focus on

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surface filling-in. Note that in this chapter, the terms ‘completion’ and ‘filling-in’ will be used synonymously, although some authors exclusively use the term completion in association with contours, and filling-in in association with surfaces (e.g., Grossberg, 2003a). Furthermore, there is a distinction made in the literature between modal and amodal completion. Amodal completion refers to the perception of continuity of a surface and its contours behind an object positioned in front. Modal completion refers to the perceptible (but illusory) effects of contour and surface completion when local cues suggest that one surface is in front of other surfaces or objects in the background (as in the Kanizsa square; Kanizsa, 1955). Despite differences in perceptual effects between modal and amodal completion, both types of completion also share common mechanisms (for review, see Davis and Driver, 2003). The type of filling-in studied in this chapter can be best considered as a modal type of filling-in. Finally, it is important to draw a conceptual distinction between perceptual filling-in (the illusory perception of a feature in a region where it is physically absent), and neural filling-in (the neuronal mechanism that produces the perceptual illusion).

In the last few decades, the illusion of the perceptual filling-in of surfaces has been studied extensively for several reasons. First, the perception of continuous surfaces (and contours) despite design features of the visual system that might interfere with these percepts, strongly suggests the existence of filling-in mechanisms. In this chapter, it will be argued that the perceptual filling-in processes that generate the illusory completion of backgrounds across regions physically occupied by a figure are relevant for normal surface perception. Second, given the likely existence of filling-in mechanisms, it is unavoidable to ask what might be the specific neural correlate underlying perceptual filling-in, and where in the visual system it might be found. Third, the perceptual filling-in of a figure by its background implies that the same physical stimulus can be perceived in two different ways (similar to bi-stable stimuli). This is suggestive of neural mechanisms that permit fast perceptual reorganization and that might be related to plastic mechanisms underlying other types of visual reorganization and

learning. These will be the three main topics in this chapter.

The paradigmatic example of filling-in upon which this chapter will focus is the slowest type of perceptual filling-in, in which figures presented away from the center of gaze become filled-in perceptually only after many seconds of maintained fixation. The processes underlying this type of perceptual filling-in may therefore, at first sight, be unlikely to contribute to normal surface perception, but a closer investigation suggests that the opposite may be true. Because of its focus on one type of perceptual filling-in, the chapter does not offer a complete review of the literature related to this phenomenon. Instead, the chapter provides the logic behind the work from our group on perceptual filling-in, with reference only to directly related work from other investigators.

Perceptual filling-in and the design of the visual apparatus

There are several design features of the visual system that provide reasons for suspecting the existence of a filling-in process. One such feature is the anatomical design of the retina, which interferes with the continuity of the retinal image. The retina is constructed such that light finding its way to the photoreceptors has to pass first through a mesh of ganglion cells, amacrine cells, bipolar cells, and blood vessels (Sterling, 1998). The fact that we do perceive the world in an uninterrupted continuous fashion points to the existence of interpolation mechanisms that complete the image. An even stronger example of the existence of such interpolation mechanisms is given by the perceptual filling-in of the blind spot. The blind spot is a scotoma corresponding to the place in the retina where the optic nerve leaves the eye, and where there are no photoreceptors. When one eye is closed, the blind spot might be expected to reveal itself as a ‘black hole’ in the visual image of the world. Instead, the ‘black hole’ is perceptually filled in by the surrounding background, and therefore goes unnoticed. Neural mechanisms of perceptual filling-in across the blind spot (Fiorani et al., 1992; Komatsu and Murakami, 1994; Komatsu et al., 2000), and across scotomas induced by a small

retinal lesion (Murakami et al., 1997) have been described in V1 of the monkey. The perceptual fillingin of a scotoma is experienced as instantaneous, while perceptual filling-in of figures on a background during maintained fixation of a point away from the figure takes time. Nevertheless, both types of filling-in may be related, as will be discussed in the next section. A second plausible reason to suspect the existence of filling-in processes is the fact that processing in the early visual system (retina, lateral geniculate nucleus (LGN)), and especially cortical processing in early visual areas is heavily biased toward the detection of local contrasts and boundaries (Kuffler, 1953; Hubel and Wiesel, 1959, 1962). Most neurons in the early cortical stages of the visual system are highly responsive to local contrasts in luminance or other features within their receptive field (RF), and fairly unresponsive to homogeneous stimulation in the RF. Ever since Hubel and Wiesel described the responses of neurons in the early visual areas to oriented lines, the contribution of visual cortex to the detection of boundaries and contours in the visual image has been heavily emphasized. Nevertheless, the world is visible only owing to our vivid perception of surfaces (Grossberg 1987a, b, 2003a). How could surface perception be accomplished given the scarcity of neurons that directly and efficiently code surface properties?

The locus of perceptual filling-in

Isomorphic representation of surfaces: some background

The debate on the nature of a neural correlate of perceptual filling-in, and on the locus of such a correlate in the visual system has been waged not only in the neuroscientific community, but also in philosophical circles (for review, see Pessoa et al., 1998; Pessoa and Neumann, 1998). Dennett (1991) in particular has taken the strong stance that perceptual filling-in is not associated with isomorphic neural filling-in processes in the brain. An isomorphic cortical representation of a perceptually filledin visual surface would imply a point-to-point correspondence between the distribution of neural activity in the cortex triggered by the surface and

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the spatial distribution of the surface in the visual field (Todorovic, 1987). Dennett (1991) has argued that this is unlikely, and that surfaces would be coded in the brain in analogy with the way in which digitized images are coded in graphical environments. A surface with a specific color in a digitized image will be represented by its boundaries and a single value that represents the color (symbolic coding). This would avoid the waste associated with a ‘pixel-by-pixel’ code in the brain. According to Dennett (1991), a cortical pixel-by-pixel code to represent surface features would be tantamount to creating a ‘Cartesian theatre’ in the brain that would have to be viewed by a separate conscious entity (a ‘homunculus’) in order to produce surface perception. A potential neurophysiological translation of the symbolic coding hypothesis of Dennett (1991) would be that surface features are coded in higher-order visual areas, which are also involved in high-level representations of objects, and which are not retinotopically organized (Desimone and Ungerleider, 1989; Wang et al., 1996; Biederman, 2000; Haxby et al., 2001; Kayaert et al., 2003). According to Dennett (1991), perceptual filling-in corresponds to ignoring the absence of information rather than the active interpolation of existing information across regions in the visual field where that information is absent.

Although physiological investigations of perceptual filling-in of surfaces had not been conducted at the time Dennett published his book, his resistance to the idea of an isomorphic neural interpolation process associated with perceptual filling-in was remarkable in view of the known organization of the visual system, and in view of existing studies demonstrating isomorphic neural interpolation processes during contour perception. The visual system consists of a number of hierarchical levels, wherein light that enters the retina reaches the cortex through the intermediary of a thalamic relay station (the LGN). Primary visual cortex and other early visual areas each consist of a sheet of neurons with small RFs that are organized in a retinotopic fashion. A classical RF is the region in visual space where a single, small bar stimulus can influence the firing rate of a neuron. A cortical area is retinotopically organized if neighboring points in the retinal image are represented by physically neighboring

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neurons in the cortical sheet with neighboring RFs. Placing stimuli inside a neuron’s RF often reveals multiple tuning properties, including orientation, disparity, velocity, direction, or color tuning, in various combinations (for review, see Desimone and Ungerleider, 1989). Placing stimuli outside the RF (in the RF surround) usually does not produce a change in activation, but can modulate activity to stimuli presented inside the classical RF. For example, an enhancement of neural responses has been reported in V1 neurons when a central line in the classical RF was flanked by a collinear line segment in the RF surround (Kapadia et al., 1995; Polat et al., 1998). Influences from the surround may be related in part to lateral, long-range connections, which show a bias to link neurons with similar orientation tuning properties (Gilbert and Wiesel, 1989; McGuire et al., 1991; Lund et al., 1993). In addition to a contribution of horizontal connections, feedback influences contribute to the extent and properties of the surround (Lamme, 1995; Zipser et al., 1996; Levitt and Lund, 2002; Bair et al., 2003).

The retinotopic organization of early visual cortex as well as the availability of circuitry that could propagate activity laterally along the cortical sheet suggests that isomorphic filling-in processes might indeed exist. In the domain of contour perception, it has been claimed that the above-described circuitry forms the basis for a tendency of the visual system to complete fragmentary information. For example, a line segment will be detected more readily if it is flanked by one or two collinear line segments (Dresp, 1993; Field et al., 1993; Polat and Sagi, 1994; Wehrhahn and Dresp, 1998). It is as if the visual system ‘expects’ that two aligned fragments are likely to come from a single contour. This expectation reveals itself in an enhanced capability to detect a third aligned line segment placed in the gap in-between the flanking line segments, and an enhanced physiological response to the middle line segment from neurons with RFs covering the gap. Neural activity in response to illusory contours is another striking example of the bias of the visual system to interpret fragments as belonging to a contour (von der Heydt et al., 1984). These types of ‘hypotheses’ are built into the architecture of visual circuitry, which is shaped through the statistical

regularities of visual stimulation during early development (Hirsch and Spinelli, 1971; Pettigrew and Freeman, 1973; Blakemore, 1976; Blasdel et al., 1977). Given the evidence for isomorphic neural mechanisms that interpolate contour information in retinotopically organized cortex (von der Heydt et al., 1984; Peterhans and von der Heydt, 1989), the question can be asked why such neural interpolation processes would not exist for surface properties as well.

Ramachandran (2003) has linked perceptual fill- ing-in phenomena to the philosophical idea of sensory ‘qualia’. The idea of qualia in visual perception can be related to the undeniable and vivid experience of a particular percept, and the vividness of that percept can be linked to the probability that it corresponds to physical reality. This hypothesis is compatible with the idea that the architecture of the visual system is shaped in early development to reflect statistical regularities in the visual environment (e.g., Blasdel et al., 1977). If particular configurations of local elements in a 2D display are statistically likely to be linked to real contours or (occluding) surfaces in 3D environment, the adult visual system will generate the (illusory) perception of contours and surfaces even in the absence of physical evidence for it in the display (as in the Kanizsa square; Kanizsa, 1955). The strong bias or ‘certainty’ of the visual system to interpret appropriately spaced and aligned local cues as belonging to real contours and surfaces produces illusory percepts of contours and surfaces, which could be considered as qualia. The convincing percepts (qualia) of contours or surfaces based on fragmentary information may reflect the action of isomorphic interpolation processes in retinotopically organized visual cortex. Because local elements that are not properly aligned or too widely spaced are less likely to be associated with a single contour or surface, they will not produce illusory contours or surfaces. Neural interpolation process therefore should have a limited spatial range.

Psychophysical evidence

Independent of physiological measurements, psychophysical experiments have suggested that neural

processes in retinotopic areas do contribute to some types of surface filling-in. In one such experiment (De Weerd et al., 1998), observers were instructed to fixate a red fixation spot, while a gray figure was presented away from fixation on a dynamic texture background (Fig. 1). The texture consisted of a black background densely filled with jittering white

Fig. 1. Typical stimulus used in perceptual filling-in experiments. The picture shows a single frame of a dynamic texture stimulus used by De Weerd et al. (1999) (see Fig. 2), and similar to the stimuli used in other experiments discussed in this chapter. The homogeneous region in the center was approximately equiluminous with the average luminance of the surrounding dynamic texture, and with the gray background upon which the texture was presented (23 cd/m2). The dynamic texture was a ‘movie’ made of five frames, each of which consisted of horizontal, white line segments (0.71 0.11) on a dark background, spaced 0.41 apart on average. Since the position of the line elements was randomized in each frame of the movie, playing the movie (at 20 Hz) created a stimulus with continuously jittering line elements on the dark texture background. In physiological recordings, the orientation of the bars and square hole typically were chosen to match the preferred orientation of the cell. The small white square indicates the position of the fixation point (Fix). The illustration is approximately to scale, except for the fixation spot which is exaggerated in size for clarity (and which in reality was red). In this example, the texture was 161 161 in size, square size was 41, and the eccentricity of the square’s center relative to fixation was 81.

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line segments, and the gray square (of which the size and eccentricity was varied) was equiluminant with the background. Subjects were instructed to report with a button press when the gray figure ‘disappeared’. The time required for filling-in varied from about 4 to 10 s, depending on the exact stimulus conditions (Fig. 2). At an eccentricity of 41, increases in the size of the square produced very steep increases in the time required for subjects to fill in, whereas at an eccentricity of 81, the same increases in square size produced much smaller increases in the time required for filling-in. This pattern of results suggested that cortical magnification of central vision was a critical factor determining the time required for perceptual filling-in. Because the cortical magnification of the projection of a stimulus in retinotopically organized cortex increases with decreasing eccentricity, the same increase in square size will produce much larger increases in cortical projection at the fovea than in the periphery. This parallels the psychophysical effects of eccentricity and figure size on the time required to perceive fill- ing-in. Indeed, re-plotting the time required for perceptual filling-in as a function of cortical projection size (after converting all figure sizes at all eccentricities into their cortical projection size), revealed a linear relationship between the two variables. Figure 2 shows filling-in times plotted as a function of cortical projection size in human V3, but equivalent results were obtained in V1 and V2. The reason for this equivalence is that the reduction of cortical magnification with eccentricity follows a similar function in different areas, except for a scaling factor to take account of the differences in size among those cortical areas (Sereno et al., 1995). Although the data in Fig. 2, therefore, could not pinpoint to what extent different early visual area(s) contribute differentially to perceptual filling-in, the data did establish a role for retinotopically organized cortex in the perception of filling-in. Other experiments in which a larger set of eccentricities and square sizes was used, confirmed the observations shown in Fig. 2 (De Weerd et al., 1998). Furthermore, the observation that two identical squares at identical eccentricities often filled in at different moments (De Weerd et al., 1998), fits with the idea that perceptual filling-in reflects localized interpolation mechanisms in retinotopic areas.