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Does 40-Hz Oscillation Play a Role in Visual Consciousness?
Consciousness and Cognition 8, 186–195 (1999) Article ID ccog.1999.0399, available online at http://www.idealibrary.com on
Does 40-Hz Oscillation Play a Role in Visual Consciousness? Ian Gold Institute for Advanced Studies, Australian National University
THE 40-Hz THESIS
What is the role of synchronous 40-Hz oscillation in visual awareness? The history of the problem begins with the finding (Eckhorn, 1988; Gray et al., 1989) that two neurons oscillate synchronously when a single external object stimulates their respective receptive fields. It was suggested that the temporal coordination of these neurons might be used to create a functional link among them—to bind them and thereby create the phenomenal coherence required for perception. Subsequently, Crick and Koch (1990a, 1990b) argued that there is a significant relation between the binding problem and the problem of visual consciousness and, as a result, that synchronous 40-Hz oscillations may be causally implicated in visual awareness as well as in visual binding. Indeed, the elegant results of Engel et al. in the target article in this volume seem to bear this prediction out. When an animal subject consciously sees an ambiguous stimulus moving in one direction, one observes synchronous oscillations that are correlated with that direction of motion. I will phrase the thesis of interest—which we can call the 40-Hz thesis—as follows: 40-Hz thesis. Synchronous (roughly) 40-Hz oscillations are causally implicated in visual consciousness. In this paper, I address two issues. First, I attempt to characterize the 40-Hz thesis in some detail. I then consider the nature of the available evidence for it. I argue that once the notion of binding is properly understood, it is seen to be indistinguishable, in the relevant respects, from the overarching computational problem of vision. However, if binding is computation, then every coherent percept is a product of the solution of a binding problem. And if 40-Hz oscillation is meant to be a marker both of binding and of consciousness, then the putative evidence for the role of 40-Hz in consciousness is confounded by considerations of binding. I conclude that we have as yet no satisfactory evidence that the 40-Hz thesis is true. SKETCH OF THE PROBLEMS: BINDING AND VISUAL AWARENESS
A guiding paradigm of modern neuroscience is the single neuron doctrine (Barlow, 1972, 1995). The doctrine holds that an adequate theory of perceptual function can This article is part of a special issue of this journal on Temporal Binding, with James Newman, guest co-editor. Commentary on A. K. Engel, P. Fries, P. Ko¨nig, M. Brecht, and W. Singer (1999). Temporal binding, binocular rivalry, and consciousness. Consciousness and Cognition, 8(2), 128–151. Address reprint requests to the author’s current address: McGill Vision Research Centre, Department of Ophthalmology, 687 Pine Avenue West, Room H4-14, Montreal, Quebec H3A 1A1, Canada. 186 1053-8100/99 $30.00 Copyright 1999 by Academic Press All rights of reproduction in any form reserved.
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be formulated at the cellular level rather than at a lower (e.g., molecular) or higher (e.g., cell population) level. An adequate model of the visual percept, therefore, must be formulated in terms of the activity of individual visual neurons. This has a strong consequence. Think, for example, of perceiving a parrot. When one is exposed to this stimulus, a group of visual neurons is activated. The neuron doctrine puts the burden of explaining the perceptual process on their joint activity. However, these neurons are separated in space and do not, in general, have direct physical connections to one other. At any instant, therefore, a set of disconnected neurons is responding to the parrot—to its form, color, texture, motion, and so on—but many of those neurons do not have information about the activity of the others by means of direct anatomical connections. What allows the neurons that respond to the parrot’s shape to be correlated with the neurons that respond to its color and texture and hence to produce a percept of a single object with multiple properties? That is, how are the appropriate neurons linked together so that visual perception is integrated? This is the binding problem. Spatial Solutions There are at least two possible mechanisms that could solve the binding problem by positing physical connections among visual neurons. These mechanisms can be thought of as spatial solutions to the binding problem, exploiting, as they do, spatial connections to form functional links. The first possible mechanism would be the rapid formation of anatomical connections among neurons in functionally significant ways in response to visual input. Neurons that respond to the various features of a parrot could temporarily form physical connections that would make them a functional group. If this were the case, the unity of the visual percept would be encoded by the unity of the neuronal group. The difficulty with this proposal, however, is that it is unlikely that anatomical connections can be formed and undone anywhere near as quickly as would be required by normal visual perception (Shatz, 1992). The second possible mechanism posits specialized neurons that respond to conjunctions of features. The neurons that respond to the color of the parrot and the neurons that respond to the shape of the parrot could converge by forming anatomical connections to cells that respond only to the conjunction of these features. These cells might, in turn, form connections to cells that respond to conjunctions of color, shape, and texture or distance from the perceiver. Ultimately there will be a single neuron that responds uniquely to a parrot of a particular shade of red, with a unique shape and texture at a particular distance from, and orientation to, the viewer. The virtue of this suggestion is that conjunction neurons have been found in the visual system, and it has been argued that features of objects can be gradually extracted through the progressive convergence just described (Hubel, 1988). The most striking support for this hypothesis is that neurons have been found that respond selectively to the visual presentation of faces (Gross, Rocha-Miranda, & Bender 1972), making them locations of high convergence. However, as is often noted, this proposal cannot solve the general form of the binding problem. The proposal entails that visual neurons get ever more specialized as they converge on cells that respond only to more elaborate conjunctions of features.
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These hypothetical cells have been called grandmother cells1 since by hypothesis they respond uniquely to single objects such as one’s grandmother. Indeed, since the grandmother cell hypothesis requires a single cell for every distinct recognizable stimulus, a grandmother cell actually responds to grandmother from some viewing angle, at some distance, at some moment in time (when grandmother has more wrinkles than before, for instance), and so on. Stated in this way, it becomes apparent that this proposal runs into a serious difficulty. Since grandmother cells are highly specific (grandmother-at-some-moment-at-some-distance-from-some-angle . . .), the recognition of even a single object will require a large numbers of cells to deal with the many unique views an observer may have of it. Since we are capable of seeing indefinitely many objects, there cannot be enough neurons to handle the task of recognizing all of them. It is unlikely that there could even be enough neurons to handle all of the objects we actually do see. This is sometimes called the problem of exponential explosion. A second problem arises in the context of the perception of novel stimuli. On first being exposed to a new object, one has no difficulty seeing it. This is true both of objects of familiar categories, such as faces, as well as objects of unknown categories, e.g., certain kinds of machines or abstract sculptures. In these cases there must either be a grandmother cell waiting to be activated by the stimulus, or a grandmother cell must be formed on demand. The latter case is ruled out because anatomical connections presumably cannot be formed rapidly enough. The former case, however, seems highly improbable. While there might be reason to believe that the genes encode information for the production of grandmother cells designed to respond to classes of ecologically significant stimuli (such as faces), there cannot be genetically determined cells waiting for the first exposure to every perceivable object. For these reasons, spatial solutions to the binding problem are not promising. A Brief History of Time An alternative solution has been proposed by Peter Milner (1974) and Christof von der Malsburg (von der Malsburg & Schneider 1986), who argue that neurons might form functional groups by some form of temporal correlation. The suggestion is that the neurons that respond to the different features of a parrot could be correlated in a temporal dimension; temporal correlation would signal a functional link among these neurons thereby integrating the percept. Similarly, all of the neurons that respond to the features of the tree branch on which the parrot is sitting will be temporally correlated with one another but will be temporally uncorrelated with the group of neurons responding to the parrot. An analogy is the instruments in an orchestra. The violins may be correlated in time with one another, and the oboes can be similarly correlated but may not be correlated with the violins. On this hypothesis, therefore neurons (and thus perceived features) are bound by synchronous electrophysiological activity rather than by means of physical connections. This proposal has the advantage of not requiring improbable physical changes in 1
See Barlow (1995) for a historical discussion of grandmother cells and other related types of cells.
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the brain and of allowing for the possibility of rapid coupling and uncoupling of neurons as required by the perceptual circumstances. As the eyes move around, a neuron that at one moment responds to the color of the parrot may at another moment form part of a different functional group to signal the color of a different object. A Putative Physiological Mechanism The proposal that binding occurs by means of temporal correlation has been given strong support by recent experimental data demonstrating temporal correlation among neurons—more precisely, the phase-locking of neuronal oscillation—when a binding problem is being solved (Eckhorn et al., 1988; Engel et al., 1990, 1991a, 1991b; Gray et al., 1989, 1990, 1992; Gray & Singer, 1989; Stryker, 1989; for recent reviews, see Singer, 1993, 1994). Consider the early findings of Gray et al. (1989). They found that cells in the visual cortex of the cat and monkey that are not anatomically connected will nonetheless oscillate more or less in phase—that is, produce rhythmic electrical activity in synchrony—at a frequency of around 40 cycles per second (40 Hertz) when they are responding to different parts of a single object. (The observed frequency can actually vary from 35 to 85 cycles per second). For example, maximal synchronous oscillatory activity is produced in response to a single moving bar; less synchronous oscillation is produced in response to two smaller bars moving together in the same direction; and less synchronous oscillation still is produced in response to two small bars moving in opposite directions. Gray et al. propose that these 40-Hz oscillations are the medium in which a form of temporal correlation is achieved, as a result of which the different properties of a single stimulus are linked in visual experience. Neurons that are oscillating in phase are neurons that are functionally linked. They claim therefore that synchronous oscillatory activity is a response to global stimulus properties—that is, that the oscillating neurons are responding to a single object. Many synchronous 40-Hz oscillations can be formed and distinguished as long as the various rhythms do not overlap. Suppose one set of neurons begins to oscillate at 40-Hz. A second group of neurons may also form a functional group by synchronous 40-Hz oscillation, but the two groups will not be correlated as long as their rhythmic patterns are not in phase. In the orchestra analogy, the violins and the oboes may play the same notes, but if the oboes begin to play slightly after the violins, the violins will be correlated with one another, and the oboes will be correlated with one another, but the violins will not be correlated with the oboes. All of the neurons responding to the features of the parrot will exhibit a synchronous 40-Hz oscillation, and all of the neurons responding to the tree branch will exhibit a synchronous 40-Hz oscillation, but these two oscillations will not themselves be synchronized thus distinguishing the parrot from the branch both neurally and in visual perception. The binding problem is thus solved by using time as a dimension of visual representation. Neurons that have to be grouped together are correlated by oscillatory synchrony producing visual perception of distinct objects and their properties. Binding occurs by exploiting time, rather than location, in generating a visual percept.
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Binding and Consciousness Francis Crick and Christof Koch (Crick & Koch 1990a, 1990b; Crick & Koch 1992; Koch & Crick 1994) have made 40-Hz oscillation, and its putative role in binding, the centerpiece of a sketch of a theory of visual consciousness or awareness. They propose that binding by means of synchronous 40-Hz oscillations is not only the mechanism by which the visual system constructs a coherent percept but, in addition, that synchronous oscillation is a mechanism by which visual information is introduced into conscious awareness. The full hypothesis proposed Crick and Koch crucially incorporates a notion of attention, which initiates binding by synchronous oscillation, and of short-term memory which receives the output of the binding mechanism: We suggest that one of the functions of consciousness is to present the result of various underlying computations and that this involves an attentional mechanism that temporarily binds the relevant neurons together by synchronizing their spikes in 40-Hz oscillations. These oscillations do not themselves encode additional information, except in so far as they join together some of the existing information into a coherent percept. We shall call this form of awareness working awareness. We further postulate that objects for which the binding problem has been solved are placed into working memory. (1990b, p. 272)
The sequence of events proposed by the theory is as follows. Objects in the visual field generate responses in visual cortex. Attention selects a part of the visual field, perhaps by means of a principle of saliency. When a salient location is selected, the information encoded about that location in the cortex is activated and sent to the thalamus. The thalamus can then feed back to the cortex, choose the appropriate neurons to entrain in oscillation, and bind them. The results of binding are then put into working memory. On this proposal, solving the binding problem produces not only a coherent percept but one that is accessible to visual awareness. By making synchronous oscillation a marker of awareness, Crick and Koch open up the possibility of an experimental research program to which Engel et al. have contributed. The central element of the Crick and Koch proposal is the element of attention. As I interpret their view, it runs like this. The visual system computes individual features of the visual scene such as color and shape; that is, it solves the problem of disambiguating the retinal stimulation. These individual features do not yet constitute a representation of an object, nor are they conscious. The diverse features are bound together and simultaneously made conscious by the focusing of attention. When I focus my attention on a parrot, I become aware of the object in that part of visual space whose features have already been computed. Attention thus has two aspects: it is a process that causes non-conscious information to come together (i.e., to be bound), and it causes the object thus bound to be made conscious. This suggestion apparently constitutes the initial impetus to explore the possibility that synchronous 40-Hz oscillation plays a central role both in solving the binding problem and in the problem of consciousness. INTERPRETING THE THESIS
I turn now to the question of how we should understand the 40-Hz thesis. Recall that the thesis of interest can be expressed as follows:
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40-Hz thesis. Synchronous (roughly) 40-Hz oscillations are causally implicated in visual consciousness. The phrase ‘‘causally implicated’’ is vague and must be clarified. If we adopt the view exemplified in the target article, then the 40-Hz thesis actually amounts to this: Necessary 40-Hz thesis. Synchronous (roughly) 40-Hz oscillations are causally necessary for visual consciousness. On this view, oscillations play some causal role in the production of visual consciousness but are not sufficient by themselves to produce it. This position opens up the possibility that when one finds oscillatory activity, one is not necessarily tracking visual consciousness because the other causal processes necessary for consciousness may not be present. What more can be said about the nature of this causal process? Binding and Computation It is commonplace that the global problem of vision is a computational one. The aim of vision is to compute the properties of the environment most likely to have caused the pattern of stimulation at the retina. The problem is sometimes described as one of inverse optics: optics determines the pattern of light on the retina given the physical structure of the scene before the eyes. The task of vision is to invert the optics to reconstruct that scene (Aloimonos, 1991; Poggio 1983). The global function of vision—which we may call the computational problem of vision—is the problem of determining the nature and arrangement of properties in the visual scene. Consider a simple case of looking at a red square and a blue circle. The retina is stimulated by light coming from the two objects and the computational problem is threefold: (1) to compute the three-dimensional shapes of the objects, (2) to compute the colors (i.e., the spectral reflectances) of the surfaces, and (3) to assign the reflectances to the appropriate surfaces. This is not meant to imply that the computations are carried out independently; they are not. For example, the reflectance computed will be affected by the perceived spatial arrangement of the scene (Gilchrist, 1977). The details of the computational solutions are not of concern for the present discussion. It is sufficient to say, however, that the problem for vision in this case involves assigning spatial properties and reflectance values to the scene as well as putting those values into register—that is, producing a representation of a red square and blue circle and not a colorless square with a red blob next to it, or a colorless square with a blue blob next to it, or a blue square, and so on. But, of course, the mechanism instantiating this computation is a neural mechanism. Somehow, the activity of visual neurons must carry out the three computational functions just described: they must compute the spatial arrangement of the scene, compute the reflectances of the surfaces, and put these two values into register. How, then, is the neural instantiation of the computational problem related to the binding problem? Suppose one were recording from four neurons responding to the scene. One neuron responds to a straight edge; one to a curved contour; one to red; and one to blue. If the scene is correctly perceived, the neuron responding to the straight edge must be bound to the neuron responding to the color red, and the neuron re-
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sponding to the curved contour must be bound to the neuron responding to the color blue. On the face of it, then, the binding problem looks very much like the basic computational problem of vision: in computational terms it is the problem of deciding which properties go with which others; in neural terms it is the problem of functionally binding together the appropriate neurons.2 Characterizing the binding problem as a neural description of the computational problem, however, is not entirely satisfactory. There are two more specific possible relations that might hold between computation and binding. On the first of these, some visual neurons compute the relevant features of the scene and their spatial locations. The output of this computation is then transmitted to other neurons that would be entrained in oscillation as a way of expressing the output of the computation, e.g., that the neurons responding to the square are functionally connected to the neurons responding to the red color. On this view, the first set of neurons solves the computational problem and the second set of neurons expresses that solution. Thus, one might distinguish the binding problem from the computational problem by arguing that only the first set of neurons solves the computational problem and only the second solves the binding problem. A second possibility is that the very neurons involved in the computation of the scene could oscillate as a way of expressing the output of their part of the computation and to form the relevant functional connections with other neurons participating in the computation. On this view, oscillation is an implementation (in Marr’s (1982) sense) of the computational problem, and the binding problem is nothing over and above a description of the computational problem in neural terms. Which of these options is the correct one? Recall the point made above regarding the interaction of the computation of spatial properties and reflectance properties. These two parts of the global computation of the features of the scene must interact for the computation to produce the correct result. This means that neurons responsive to spatial features of the scene and neurons responsive to reflectance features of the scene must communicate with one another in the course of carrying out their respective parts of the computation. According to the oscillation theory, however, this crosstalk is subserved by synchronous oscillations when anatomical connections are absent. Since, typically, some spatial neurons and some reflectance neurons will be anatomically disconnected, they will have to exhibit oscillatory activity to communicate. But if this is the case, then the oscillatory activity is itself part of the computation of the scene; in the absence of such oscillation, the computation cannot be successfully completed. While it is possible to posit further oscillatory activity that would express the same information as the initial group of neurons, this hypothesis is completely otiose; once the computational problem is solved—and solved in part by
2
One should not be misled into thinking that the binding problem captures only the third part of the computational problem described above, viz., the problem of putting three-dimensional contours and reflectance values into register. The binding problem operates at the level of determining which neurons responding to edges and contours go together as well as the original findings of Gray et al. (1989) demonstrate. That is, the solution to the binding problem, like the solution to the computational problem, involves disambiguating the shapes and colors of the individual objects as well as putting the colors and shapes into register.
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means of oscillations—there is no further problem to be solved and thus no further oscillations to posit. It follows, therefore, that the correct view of binding is that it is a redescription of the computational problem—a description of a functional problem in implementation terms. We have said that the correct interpretation of the thesis renders it a claim about causal necessity. Given the discussion above, we may now say something more precise: synchronous (roughly) 40-Hz oscillations implement the solution to the computational problem of vision and are also causally necessary for the output of that solution to enter awareness. EVALUATION OF THE THESIS
I turn now to the evaluation of this thesis. Given our characterization above, the thesis raises a significant problem. The data of Engel et al. putatively supporting the role of 40-Hz oscillation as necessary to visual consciousness are confounded by the fact that a conscious percept is always also a percept that is bound, where by ‘‘bound’’ one means computationally bound in the sense just described. As we have seen, the problem of binding is the computational problem redescribed in implementation terms. All percepts, therefore, must exhibit binding, and this includes conscious percepts as well. After all, if the conscious percept were not so bound, it would not deserve the name ‘‘percept.’’ If a percept is bound in this sense, however, that fact is sufficient to explain the finding of synchronous oscillation whether the percept is conscious or not. If one wanted to demonstrate the causal efficacy of synchronous oscillation to consciousness experimentally, one would have to control for the presence of binding in conscious perception. Since it remains to be seen what sense, if any, can be made of a conscious percept that is not bound, it is not clear whether the relation between binding and consciousness can in fact be disentangled experimentally. If we had a sound theoretical argument supporting the relation of 40-Hz oscillation and visual consciousness, such an argument might serve to support the claim that 40-Hz oscillation is performing two functions in the case of conscious visual perception despite the fact that these two functions have not yet been distinguished experimentally. Given, however, that the 40-Hz thesis originates in a theory about binding, and binding, as we have seen, is a ubiquitous feature of vision, we have no independent argument for the role of oscillation in consciousness and thus no conceptual way out of the experimental ambiguity. We have no reason, therefore, to interpret the data as offering support for the claim that synchronous oscillation is necessary for visual consciousness. The conservative interpretation of the data on 40-Hz oscillation and consciousness, therefore, is that synchronous oscillation has only thus far been shown to be a mechanism of binding but not of consciousness. Thus, when the authors of the target article observe coherent oscillatory activity apparently correlated with the subject’s perceived direction of motion in response to an ambiguous stimulus, it is impossible to determine whether the oscillatory activity is a marker of consciousness or merely of the binding that characterizes the disambiguated percept; certainly, the percept must be computationally disambiguated in order to support the animal’s behavior. Since
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the percept would have to be a bound percept to be a conscious percept, the behavioral evidence is opaque with respect to the question of the conscious state of the animal. In general, unless and until we can separate the problems of visual binding and visual awareness experimentally, the role, if any, of 40-Hz oscillation in consciousness will remain an open question.3 REFERENCES Aloimonos, Y., & Rosenfeld, A. (1991). Computer vision. Science 253, 1249–1254. Barlow, H. B. (1972). Single units and sensation: a neuron doctrine for perceptual psychology. Perception 1, 371–394. Barlow, H. B. (1995). The neuron doctrine in perception. In M. Gazzaniga (Ed.), The cognitive neurosciences. Cambridge: MIT. Crick, F., & Koch, C. (1990a). Some reflections on visual awareness. Cold Spring Harbor Symposia on Quantitative Biology 55, 953–962. Crick, F., & Koch, C. (1990b). Towards a neurobiological theory of consciousness. Seminars in the Neurosciences 2, 263–275. Crick, F., & Koch, C. (1992). The problem of consciousness. Scientific American 26, 153–159. Eckhorn, R., Bauer, R., Jordan, W., Brosch, M., Kruse, W., Munk, M., & Reitboeck, J. J. (1988). Coherent oscillations: a mechanism of feature linking in the visual cortex? Biological Cybernetics 60, 121– 130. Engel, A. K., Ko¨nig, P., Gray, C. M., & Singer, W. (1990). Stimulus-dependent neuronal oscillations in cat visual cortex: Inter-columnar interaction as determined by cross-correlation analysis. European Journal of Neuroscience 2, 588–606. Engel, A. K., Ko¨nig, P., Kreiter, A. K., & Singer, W. (1991a). Interhemispheric synchronization of oscillatory neuronal responses in cat visual cortex. Science 252, 1177–1179. Engel, A. K., Kreiter, A. K., Ko¨nig, P., & Singer, W. (1991b). Synchronization of oscillatory neuronal responses between striate and extrastriate visual cortical areas of the cat. Proceedings of the National Academy of Sciences USA 88, 6048–6052. Gilchrist, A. L. (1977). Perceived lightness depends on perceived spatial arrangement. Science 195, 185– 187. Gray, C. M., Engel, A. K., Ko¨nig, P., & Singer, W. (1990). Stimulus-dependent neuronal oscillations in cat visual cortex: Receptive field properties and feature dependence. European Journal of Neuroscience 2, 607–619. Gray, C. M., Engel, A. K., Ko¨nig, P., & Singer, W. (1992). Synchronization of oscillatory neuronal responses in cat striate cortex: Temporal properties. Visual Neuroscience 8, 337–347. Gray, C. M., Ko¨nig, P., Engel, A. K., & Singer, W. (1989). Oscillatory responses in cat visual cortex exhibit inter-columnar synchronization which reflects global stimulus properties. Nature 338, 334– 337. Gray, C. M., & Singer, W. (1989). Stimulus-specific neuronal oscillations in orientation columns of cat visual cortex. Proceedings of the National Academy of Science USA. 86, 1698–1702. Gross, C. G., Rocha-Miranda, C. E., & Bender, D. B. (1972). Visual properties of neurons in inferotemporal cortex of the macaque. Journal of Neurophysiology 35, 96–111. Hubel, D. H. (1988). Eye, brain, and vision. New York: Scientific American Library. Koch, C., & Crick, F. (1994). Some further ideas regarding the neuronal basis of awareness. In J. L. Davis & C. Koch (Eds.), Large-scale neuronal theories of the brain. Cambridge: MIT.
3 I am grateful to Kathleen Akins, Jakob Hohwy, and Natalie Stoljar for many helpful comments on earlier drafts of this paper.
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Marr, D. (1982). Vision. New York: Freeman. Milner, P. (1974). A model for visual shape recognition. Psychological Review 8(6), 521–535. Poggio, T., & Koch, C. (1985). Ill-posed problems in early vision: From computational theory to analogue networks. Proceedings of the Royal Society of London B 226, 303–323. Shatz, C. J. The developing brain. Scientific American 267, 60–67. Singer, W. (1993). Synchronization of cortical activity and its putative role in information processing and learning. Annual Review of Physiology 55, 349–374. Singer, W. (1994). Putative functions of temporal correlations in neocortical processing. In J. L. Davis & C. Koch (Eds.), Large-scale neuronal theories of the brain. Cambridge: MIT. Stryker, M. P. (1989). Is grandmother an oscillation? Nature 338, 297–298. von der Malsburg, C., & Schneider, W. (1986). A neural cocktail-party processor. Biological Cybernetics 54, 29–40.
Does 40-Hz Oscillation Play a Role in Visual Consciousness? Ian Gold Institute for Advanced Studies, Australian National University
THE 40-Hz THESIS
What is the role of synchronous 40-Hz oscillation in visual awareness? The history of the problem begins with the finding (Eckhorn, 1988; Gray et al., 1989) that two neurons oscillate synchronously when a single external object stimulates their respective receptive fields. It was suggested that the temporal coordination of these neurons might be used to create a functional link among them—to bind them and thereby create the phenomenal coherence required for perception. Subsequently, Crick and Koch (1990a, 1990b) argued that there is a significant relation between the binding problem and the problem of visual consciousness and, as a result, that synchronous 40-Hz oscillations may be causally implicated in visual awareness as well as in visual binding. Indeed, the elegant results of Engel et al. in the target article in this volume seem to bear this prediction out. When an animal subject consciously sees an ambiguous stimulus moving in one direction, one observes synchronous oscillations that are correlated with that direction of motion. I will phrase the thesis of interest—which we can call the 40-Hz thesis—as follows: 40-Hz thesis. Synchronous (roughly) 40-Hz oscillations are causally implicated in visual consciousness. In this paper, I address two issues. First, I attempt to characterize the 40-Hz thesis in some detail. I then consider the nature of the available evidence for it. I argue that once the notion of binding is properly understood, it is seen to be indistinguishable, in the relevant respects, from the overarching computational problem of vision. However, if binding is computation, then every coherent percept is a product of the solution of a binding problem. And if 40-Hz oscillation is meant to be a marker both of binding and of consciousness, then the putative evidence for the role of 40-Hz in consciousness is confounded by considerations of binding. I conclude that we have as yet no satisfactory evidence that the 40-Hz thesis is true. SKETCH OF THE PROBLEMS: BINDING AND VISUAL AWARENESS
A guiding paradigm of modern neuroscience is the single neuron doctrine (Barlow, 1972, 1995). The doctrine holds that an adequate theory of perceptual function can This article is part of a special issue of this journal on Temporal Binding, with James Newman, guest co-editor. Commentary on A. K. Engel, P. Fries, P. Ko¨nig, M. Brecht, and W. Singer (1999). Temporal binding, binocular rivalry, and consciousness. Consciousness and Cognition, 8(2), 128–151. Address reprint requests to the author’s current address: McGill Vision Research Centre, Department of Ophthalmology, 687 Pine Avenue West, Room H4-14, Montreal, Quebec H3A 1A1, Canada. 186 1053-8100/99 $30.00 Copyright 1999 by Academic Press All rights of reproduction in any form reserved.
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be formulated at the cellular level rather than at a lower (e.g., molecular) or higher (e.g., cell population) level. An adequate model of the visual percept, therefore, must be formulated in terms of the activity of individual visual neurons. This has a strong consequence. Think, for example, of perceiving a parrot. When one is exposed to this stimulus, a group of visual neurons is activated. The neuron doctrine puts the burden of explaining the perceptual process on their joint activity. However, these neurons are separated in space and do not, in general, have direct physical connections to one other. At any instant, therefore, a set of disconnected neurons is responding to the parrot—to its form, color, texture, motion, and so on—but many of those neurons do not have information about the activity of the others by means of direct anatomical connections. What allows the neurons that respond to the parrot’s shape to be correlated with the neurons that respond to its color and texture and hence to produce a percept of a single object with multiple properties? That is, how are the appropriate neurons linked together so that visual perception is integrated? This is the binding problem. Spatial Solutions There are at least two possible mechanisms that could solve the binding problem by positing physical connections among visual neurons. These mechanisms can be thought of as spatial solutions to the binding problem, exploiting, as they do, spatial connections to form functional links. The first possible mechanism would be the rapid formation of anatomical connections among neurons in functionally significant ways in response to visual input. Neurons that respond to the various features of a parrot could temporarily form physical connections that would make them a functional group. If this were the case, the unity of the visual percept would be encoded by the unity of the neuronal group. The difficulty with this proposal, however, is that it is unlikely that anatomical connections can be formed and undone anywhere near as quickly as would be required by normal visual perception (Shatz, 1992). The second possible mechanism posits specialized neurons that respond to conjunctions of features. The neurons that respond to the color of the parrot and the neurons that respond to the shape of the parrot could converge by forming anatomical connections to cells that respond only to the conjunction of these features. These cells might, in turn, form connections to cells that respond to conjunctions of color, shape, and texture or distance from the perceiver. Ultimately there will be a single neuron that responds uniquely to a parrot of a particular shade of red, with a unique shape and texture at a particular distance from, and orientation to, the viewer. The virtue of this suggestion is that conjunction neurons have been found in the visual system, and it has been argued that features of objects can be gradually extracted through the progressive convergence just described (Hubel, 1988). The most striking support for this hypothesis is that neurons have been found that respond selectively to the visual presentation of faces (Gross, Rocha-Miranda, & Bender 1972), making them locations of high convergence. However, as is often noted, this proposal cannot solve the general form of the binding problem. The proposal entails that visual neurons get ever more specialized as they converge on cells that respond only to more elaborate conjunctions of features.
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These hypothetical cells have been called grandmother cells1 since by hypothesis they respond uniquely to single objects such as one’s grandmother. Indeed, since the grandmother cell hypothesis requires a single cell for every distinct recognizable stimulus, a grandmother cell actually responds to grandmother from some viewing angle, at some distance, at some moment in time (when grandmother has more wrinkles than before, for instance), and so on. Stated in this way, it becomes apparent that this proposal runs into a serious difficulty. Since grandmother cells are highly specific (grandmother-at-some-moment-at-some-distance-from-some-angle . . .), the recognition of even a single object will require a large numbers of cells to deal with the many unique views an observer may have of it. Since we are capable of seeing indefinitely many objects, there cannot be enough neurons to handle the task of recognizing all of them. It is unlikely that there could even be enough neurons to handle all of the objects we actually do see. This is sometimes called the problem of exponential explosion. A second problem arises in the context of the perception of novel stimuli. On first being exposed to a new object, one has no difficulty seeing it. This is true both of objects of familiar categories, such as faces, as well as objects of unknown categories, e.g., certain kinds of machines or abstract sculptures. In these cases there must either be a grandmother cell waiting to be activated by the stimulus, or a grandmother cell must be formed on demand. The latter case is ruled out because anatomical connections presumably cannot be formed rapidly enough. The former case, however, seems highly improbable. While there might be reason to believe that the genes encode information for the production of grandmother cells designed to respond to classes of ecologically significant stimuli (such as faces), there cannot be genetically determined cells waiting for the first exposure to every perceivable object. For these reasons, spatial solutions to the binding problem are not promising. A Brief History of Time An alternative solution has been proposed by Peter Milner (1974) and Christof von der Malsburg (von der Malsburg & Schneider 1986), who argue that neurons might form functional groups by some form of temporal correlation. The suggestion is that the neurons that respond to the different features of a parrot could be correlated in a temporal dimension; temporal correlation would signal a functional link among these neurons thereby integrating the percept. Similarly, all of the neurons that respond to the features of the tree branch on which the parrot is sitting will be temporally correlated with one another but will be temporally uncorrelated with the group of neurons responding to the parrot. An analogy is the instruments in an orchestra. The violins may be correlated in time with one another, and the oboes can be similarly correlated but may not be correlated with the violins. On this hypothesis, therefore neurons (and thus perceived features) are bound by synchronous electrophysiological activity rather than by means of physical connections. This proposal has the advantage of not requiring improbable physical changes in 1
See Barlow (1995) for a historical discussion of grandmother cells and other related types of cells.
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the brain and of allowing for the possibility of rapid coupling and uncoupling of neurons as required by the perceptual circumstances. As the eyes move around, a neuron that at one moment responds to the color of the parrot may at another moment form part of a different functional group to signal the color of a different object. A Putative Physiological Mechanism The proposal that binding occurs by means of temporal correlation has been given strong support by recent experimental data demonstrating temporal correlation among neurons—more precisely, the phase-locking of neuronal oscillation—when a binding problem is being solved (Eckhorn et al., 1988; Engel et al., 1990, 1991a, 1991b; Gray et al., 1989, 1990, 1992; Gray & Singer, 1989; Stryker, 1989; for recent reviews, see Singer, 1993, 1994). Consider the early findings of Gray et al. (1989). They found that cells in the visual cortex of the cat and monkey that are not anatomically connected will nonetheless oscillate more or less in phase—that is, produce rhythmic electrical activity in synchrony—at a frequency of around 40 cycles per second (40 Hertz) when they are responding to different parts of a single object. (The observed frequency can actually vary from 35 to 85 cycles per second). For example, maximal synchronous oscillatory activity is produced in response to a single moving bar; less synchronous oscillation is produced in response to two smaller bars moving together in the same direction; and less synchronous oscillation still is produced in response to two small bars moving in opposite directions. Gray et al. propose that these 40-Hz oscillations are the medium in which a form of temporal correlation is achieved, as a result of which the different properties of a single stimulus are linked in visual experience. Neurons that are oscillating in phase are neurons that are functionally linked. They claim therefore that synchronous oscillatory activity is a response to global stimulus properties—that is, that the oscillating neurons are responding to a single object. Many synchronous 40-Hz oscillations can be formed and distinguished as long as the various rhythms do not overlap. Suppose one set of neurons begins to oscillate at 40-Hz. A second group of neurons may also form a functional group by synchronous 40-Hz oscillation, but the two groups will not be correlated as long as their rhythmic patterns are not in phase. In the orchestra analogy, the violins and the oboes may play the same notes, but if the oboes begin to play slightly after the violins, the violins will be correlated with one another, and the oboes will be correlated with one another, but the violins will not be correlated with the oboes. All of the neurons responding to the features of the parrot will exhibit a synchronous 40-Hz oscillation, and all of the neurons responding to the tree branch will exhibit a synchronous 40-Hz oscillation, but these two oscillations will not themselves be synchronized thus distinguishing the parrot from the branch both neurally and in visual perception. The binding problem is thus solved by using time as a dimension of visual representation. Neurons that have to be grouped together are correlated by oscillatory synchrony producing visual perception of distinct objects and their properties. Binding occurs by exploiting time, rather than location, in generating a visual percept.
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Binding and Consciousness Francis Crick and Christof Koch (Crick & Koch 1990a, 1990b; Crick & Koch 1992; Koch & Crick 1994) have made 40-Hz oscillation, and its putative role in binding, the centerpiece of a sketch of a theory of visual consciousness or awareness. They propose that binding by means of synchronous 40-Hz oscillations is not only the mechanism by which the visual system constructs a coherent percept but, in addition, that synchronous oscillation is a mechanism by which visual information is introduced into conscious awareness. The full hypothesis proposed Crick and Koch crucially incorporates a notion of attention, which initiates binding by synchronous oscillation, and of short-term memory which receives the output of the binding mechanism: We suggest that one of the functions of consciousness is to present the result of various underlying computations and that this involves an attentional mechanism that temporarily binds the relevant neurons together by synchronizing their spikes in 40-Hz oscillations. These oscillations do not themselves encode additional information, except in so far as they join together some of the existing information into a coherent percept. We shall call this form of awareness working awareness. We further postulate that objects for which the binding problem has been solved are placed into working memory. (1990b, p. 272)
The sequence of events proposed by the theory is as follows. Objects in the visual field generate responses in visual cortex. Attention selects a part of the visual field, perhaps by means of a principle of saliency. When a salient location is selected, the information encoded about that location in the cortex is activated and sent to the thalamus. The thalamus can then feed back to the cortex, choose the appropriate neurons to entrain in oscillation, and bind them. The results of binding are then put into working memory. On this proposal, solving the binding problem produces not only a coherent percept but one that is accessible to visual awareness. By making synchronous oscillation a marker of awareness, Crick and Koch open up the possibility of an experimental research program to which Engel et al. have contributed. The central element of the Crick and Koch proposal is the element of attention. As I interpret their view, it runs like this. The visual system computes individual features of the visual scene such as color and shape; that is, it solves the problem of disambiguating the retinal stimulation. These individual features do not yet constitute a representation of an object, nor are they conscious. The diverse features are bound together and simultaneously made conscious by the focusing of attention. When I focus my attention on a parrot, I become aware of the object in that part of visual space whose features have already been computed. Attention thus has two aspects: it is a process that causes non-conscious information to come together (i.e., to be bound), and it causes the object thus bound to be made conscious. This suggestion apparently constitutes the initial impetus to explore the possibility that synchronous 40-Hz oscillation plays a central role both in solving the binding problem and in the problem of consciousness. INTERPRETING THE THESIS
I turn now to the question of how we should understand the 40-Hz thesis. Recall that the thesis of interest can be expressed as follows:
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40-Hz thesis. Synchronous (roughly) 40-Hz oscillations are causally implicated in visual consciousness. The phrase ‘‘causally implicated’’ is vague and must be clarified. If we adopt the view exemplified in the target article, then the 40-Hz thesis actually amounts to this: Necessary 40-Hz thesis. Synchronous (roughly) 40-Hz oscillations are causally necessary for visual consciousness. On this view, oscillations play some causal role in the production of visual consciousness but are not sufficient by themselves to produce it. This position opens up the possibility that when one finds oscillatory activity, one is not necessarily tracking visual consciousness because the other causal processes necessary for consciousness may not be present. What more can be said about the nature of this causal process? Binding and Computation It is commonplace that the global problem of vision is a computational one. The aim of vision is to compute the properties of the environment most likely to have caused the pattern of stimulation at the retina. The problem is sometimes described as one of inverse optics: optics determines the pattern of light on the retina given the physical structure of the scene before the eyes. The task of vision is to invert the optics to reconstruct that scene (Aloimonos, 1991; Poggio 1983). The global function of vision—which we may call the computational problem of vision—is the problem of determining the nature and arrangement of properties in the visual scene. Consider a simple case of looking at a red square and a blue circle. The retina is stimulated by light coming from the two objects and the computational problem is threefold: (1) to compute the three-dimensional shapes of the objects, (2) to compute the colors (i.e., the spectral reflectances) of the surfaces, and (3) to assign the reflectances to the appropriate surfaces. This is not meant to imply that the computations are carried out independently; they are not. For example, the reflectance computed will be affected by the perceived spatial arrangement of the scene (Gilchrist, 1977). The details of the computational solutions are not of concern for the present discussion. It is sufficient to say, however, that the problem for vision in this case involves assigning spatial properties and reflectance values to the scene as well as putting those values into register—that is, producing a representation of a red square and blue circle and not a colorless square with a red blob next to it, or a colorless square with a blue blob next to it, or a blue square, and so on. But, of course, the mechanism instantiating this computation is a neural mechanism. Somehow, the activity of visual neurons must carry out the three computational functions just described: they must compute the spatial arrangement of the scene, compute the reflectances of the surfaces, and put these two values into register. How, then, is the neural instantiation of the computational problem related to the binding problem? Suppose one were recording from four neurons responding to the scene. One neuron responds to a straight edge; one to a curved contour; one to red; and one to blue. If the scene is correctly perceived, the neuron responding to the straight edge must be bound to the neuron responding to the color red, and the neuron re-
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sponding to the curved contour must be bound to the neuron responding to the color blue. On the face of it, then, the binding problem looks very much like the basic computational problem of vision: in computational terms it is the problem of deciding which properties go with which others; in neural terms it is the problem of functionally binding together the appropriate neurons.2 Characterizing the binding problem as a neural description of the computational problem, however, is not entirely satisfactory. There are two more specific possible relations that might hold between computation and binding. On the first of these, some visual neurons compute the relevant features of the scene and their spatial locations. The output of this computation is then transmitted to other neurons that would be entrained in oscillation as a way of expressing the output of the computation, e.g., that the neurons responding to the square are functionally connected to the neurons responding to the red color. On this view, the first set of neurons solves the computational problem and the second set of neurons expresses that solution. Thus, one might distinguish the binding problem from the computational problem by arguing that only the first set of neurons solves the computational problem and only the second solves the binding problem. A second possibility is that the very neurons involved in the computation of the scene could oscillate as a way of expressing the output of their part of the computation and to form the relevant functional connections with other neurons participating in the computation. On this view, oscillation is an implementation (in Marr’s (1982) sense) of the computational problem, and the binding problem is nothing over and above a description of the computational problem in neural terms. Which of these options is the correct one? Recall the point made above regarding the interaction of the computation of spatial properties and reflectance properties. These two parts of the global computation of the features of the scene must interact for the computation to produce the correct result. This means that neurons responsive to spatial features of the scene and neurons responsive to reflectance features of the scene must communicate with one another in the course of carrying out their respective parts of the computation. According to the oscillation theory, however, this crosstalk is subserved by synchronous oscillations when anatomical connections are absent. Since, typically, some spatial neurons and some reflectance neurons will be anatomically disconnected, they will have to exhibit oscillatory activity to communicate. But if this is the case, then the oscillatory activity is itself part of the computation of the scene; in the absence of such oscillation, the computation cannot be successfully completed. While it is possible to posit further oscillatory activity that would express the same information as the initial group of neurons, this hypothesis is completely otiose; once the computational problem is solved—and solved in part by
2
One should not be misled into thinking that the binding problem captures only the third part of the computational problem described above, viz., the problem of putting three-dimensional contours and reflectance values into register. The binding problem operates at the level of determining which neurons responding to edges and contours go together as well as the original findings of Gray et al. (1989) demonstrate. That is, the solution to the binding problem, like the solution to the computational problem, involves disambiguating the shapes and colors of the individual objects as well as putting the colors and shapes into register.
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means of oscillations—there is no further problem to be solved and thus no further oscillations to posit. It follows, therefore, that the correct view of binding is that it is a redescription of the computational problem—a description of a functional problem in implementation terms. We have said that the correct interpretation of the thesis renders it a claim about causal necessity. Given the discussion above, we may now say something more precise: synchronous (roughly) 40-Hz oscillations implement the solution to the computational problem of vision and are also causally necessary for the output of that solution to enter awareness. EVALUATION OF THE THESIS
I turn now to the evaluation of this thesis. Given our characterization above, the thesis raises a significant problem. The data of Engel et al. putatively supporting the role of 40-Hz oscillation as necessary to visual consciousness are confounded by the fact that a conscious percept is always also a percept that is bound, where by ‘‘bound’’ one means computationally bound in the sense just described. As we have seen, the problem of binding is the computational problem redescribed in implementation terms. All percepts, therefore, must exhibit binding, and this includes conscious percepts as well. After all, if the conscious percept were not so bound, it would not deserve the name ‘‘percept.’’ If a percept is bound in this sense, however, that fact is sufficient to explain the finding of synchronous oscillation whether the percept is conscious or not. If one wanted to demonstrate the causal efficacy of synchronous oscillation to consciousness experimentally, one would have to control for the presence of binding in conscious perception. Since it remains to be seen what sense, if any, can be made of a conscious percept that is not bound, it is not clear whether the relation between binding and consciousness can in fact be disentangled experimentally. If we had a sound theoretical argument supporting the relation of 40-Hz oscillation and visual consciousness, such an argument might serve to support the claim that 40-Hz oscillation is performing two functions in the case of conscious visual perception despite the fact that these two functions have not yet been distinguished experimentally. Given, however, that the 40-Hz thesis originates in a theory about binding, and binding, as we have seen, is a ubiquitous feature of vision, we have no independent argument for the role of oscillation in consciousness and thus no conceptual way out of the experimental ambiguity. We have no reason, therefore, to interpret the data as offering support for the claim that synchronous oscillation is necessary for visual consciousness. The conservative interpretation of the data on 40-Hz oscillation and consciousness, therefore, is that synchronous oscillation has only thus far been shown to be a mechanism of binding but not of consciousness. Thus, when the authors of the target article observe coherent oscillatory activity apparently correlated with the subject’s perceived direction of motion in response to an ambiguous stimulus, it is impossible to determine whether the oscillatory activity is a marker of consciousness or merely of the binding that characterizes the disambiguated percept; certainly, the percept must be computationally disambiguated in order to support the animal’s behavior. Since
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the percept would have to be a bound percept to be a conscious percept, the behavioral evidence is opaque with respect to the question of the conscious state of the animal. In general, unless and until we can separate the problems of visual binding and visual awareness experimentally, the role, if any, of 40-Hz oscillation in consciousness will remain an open question.3 REFERENCES Aloimonos, Y., & Rosenfeld, A. (1991). Computer vision. Science 253, 1249–1254. Barlow, H. B. (1972). Single units and sensation: a neuron doctrine for perceptual psychology. Perception 1, 371–394. Barlow, H. B. (1995). The neuron doctrine in perception. In M. Gazzaniga (Ed.), The cognitive neurosciences. Cambridge: MIT. Crick, F., & Koch, C. (1990a). Some reflections on visual awareness. Cold Spring Harbor Symposia on Quantitative Biology 55, 953–962. Crick, F., & Koch, C. (1990b). Towards a neurobiological theory of consciousness. Seminars in the Neurosciences 2, 263–275. Crick, F., & Koch, C. (1992). The problem of consciousness. Scientific American 26, 153–159. Eckhorn, R., Bauer, R., Jordan, W., Brosch, M., Kruse, W., Munk, M., & Reitboeck, J. J. (1988). Coherent oscillations: a mechanism of feature linking in the visual cortex? Biological Cybernetics 60, 121– 130. Engel, A. K., Ko¨nig, P., Gray, C. M., & Singer, W. (1990). Stimulus-dependent neuronal oscillations in cat visual cortex: Inter-columnar interaction as determined by cross-correlation analysis. European Journal of Neuroscience 2, 588–606. Engel, A. K., Ko¨nig, P., Kreiter, A. K., & Singer, W. (1991a). Interhemispheric synchronization of oscillatory neuronal responses in cat visual cortex. Science 252, 1177–1179. Engel, A. K., Kreiter, A. K., Ko¨nig, P., & Singer, W. (1991b). Synchronization of oscillatory neuronal responses between striate and extrastriate visual cortical areas of the cat. Proceedings of the National Academy of Sciences USA 88, 6048–6052. Gilchrist, A. L. (1977). Perceived lightness depends on perceived spatial arrangement. Science 195, 185– 187. Gray, C. M., Engel, A. K., Ko¨nig, P., & Singer, W. (1990). Stimulus-dependent neuronal oscillations in cat visual cortex: Receptive field properties and feature dependence. European Journal of Neuroscience 2, 607–619. Gray, C. M., Engel, A. K., Ko¨nig, P., & Singer, W. (1992). Synchronization of oscillatory neuronal responses in cat striate cortex: Temporal properties. Visual Neuroscience 8, 337–347. Gray, C. M., Ko¨nig, P., Engel, A. K., & Singer, W. (1989). Oscillatory responses in cat visual cortex exhibit inter-columnar synchronization which reflects global stimulus properties. Nature 338, 334– 337. Gray, C. M., & Singer, W. (1989). Stimulus-specific neuronal oscillations in orientation columns of cat visual cortex. Proceedings of the National Academy of Science USA. 86, 1698–1702. Gross, C. G., Rocha-Miranda, C. E., & Bender, D. B. (1972). Visual properties of neurons in inferotemporal cortex of the macaque. Journal of Neurophysiology 35, 96–111. Hubel, D. H. (1988). Eye, brain, and vision. New York: Scientific American Library. Koch, C., & Crick, F. (1994). Some further ideas regarding the neuronal basis of awareness. In J. L. Davis & C. Koch (Eds.), Large-scale neuronal theories of the brain. Cambridge: MIT.
3 I am grateful to Kathleen Akins, Jakob Hohwy, and Natalie Stoljar for many helpful comments on earlier drafts of this paper.
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Marr, D. (1982). Vision. New York: Freeman. Milner, P. (1974). A model for visual shape recognition. Psychological Review 8(6), 521–535. Poggio, T., & Koch, C. (1985). Ill-posed problems in early vision: From computational theory to analogue networks. Proceedings of the Royal Society of London B 226, 303–323. Shatz, C. J. The developing brain. Scientific American 267, 60–67. Singer, W. (1993). Synchronization of cortical activity and its putative role in information processing and learning. Annual Review of Physiology 55, 349–374. Singer, W. (1994). Putative functions of temporal correlations in neocortical processing. In J. L. Davis & C. Koch (Eds.), Large-scale neuronal theories of the brain. Cambridge: MIT. Stryker, M. P. (1989). Is grandmother an oscillation? Nature 338, 297–298. von der Malsburg, C., & Schneider, W. (1986). A neural cocktail-party processor. Biological Cybernetics 54, 29–40.