A Real Science of Mind
- Tyler Burge -
DEC. 19, 2010, 5:18 PM
In recent years popular science writing has bombarded us with titillating reports of discoveries of the brain’s psychological prowess. Such reports invade even introductory patter in biology and psychology. We are told that the brain — or some area of it sees, decides, reasons, knows, emotes, is altruistic/egotistical, or wants to make love. For example, a recent article reports a researcher’s “looking at love, quite literally, with the aid of an MRI machine.” One wonders whether lovemaking is to occur between two brains, or between a brain and a human being.
There are three things wrong with this talk.
First, it provides little insight into psychological phenomena. Often the discoveries amount to finding stronger activation in some area of the brain when a psychological phenomenon occurs. As if it is news that the brain is not dormant during psychological activity! The reported neuroscience is often descriptive rather than explanatory. Experiments have shown that neurobabble produces the illusion of understanding. But little of it is sufficiently detailed to aid, much less provide, psychological explanation.
The idea that the neural can replace the psychological is the same idea that led to thinking that all psychological ills can be cured with drugs.
Second, brains-in-love talk conflates levels of explanation. Neurobabble piques interest in science, but obscures how science works. Individuals see, know, and want to make love. Brains don’t. Those things are psychological — not, in any evident way, neural. Brain activity is necessary for psychological phenomena, but its relation to them is complex.
Imagine that reports of the mid-20th-century breakthroughs in biology had focused entirely on quantum mechanical interactions among elementary particles. Imagine that the reports neglected to discuss the structure or functions of DNA. Inheritance would not have been understood. The level of explanation would have been wrong. Quantum mechanics lacks a notion of function, and its relation to biology is too complex to replace biological understanding. To understand biology, one must think in biological terms.
Discussing psychology in neural terms makes a similar mistake. Explanations of neural phenomena are not themselves explanations of psychological phenomena. Some expect the neural level to replace the psychological level. This expectation is as naive as expecting a single cure for cancer. Science is almost never so simple. See John Cleese’s apt spoof of such reductionism.
The third thing wrong with neurobabble is that it has pernicious feedback effects on science itself. Too much immature science has received massive funding, on the assumption that it illuminates psychology. The idea that the neural can replace the psychological is the same idea that led to thinking that all psychological ills can be cured with drugs.
Perceptual psychology, not neuroscience, should be grabbing headlines.
Correlations between localized neural activity and specific psychological phenomena are important facts. But they merely set the stage for explanation. Being purely descriptive, they explain nothing. Some correlations do aid psychological explanation. For example, identifying neural events underlying vision constrains explanations of timing in psychological processes and has helped predict psychological effects. We will understand both the correlations and the psychology, however, only through psychological explanation.
Scientific explanation is our best guide to understanding the world. By reflecting on it, we learn better what we understand about the world.
Neurobabble’s popularity stems partly from the view that psychology’s explanations are immature compared to neuroscience. Some psychology is indeed still far from rigorous. But neurobabble misses an important fact.
A powerful, distinctively psychological science matured over the last four decades. Perceptual psychology, pre-eminently vision science, should be grabbing headlines. This science is more advanced than many biological sciences, including much neuroscience. It is the first science to explain psychological processes with mathematical rigor in distinctively psychological terms. (Generative linguistics — another relatively mature psychological science — explains psychological structures better than psychological processes.)
What are distinctively psychological terms? Psychology is distinctive in being a science of representation. The term “representation” has a generic use and a more specific use that is distinctively psychological. I start with the generic use, and will return to the distinctively psychological use. States of an organism generically represent features of the environment if they function to correlate with them. A plant or bacterium generically represents the direction of light. States involved in growth or movement functionally correlate with light’s direction.
Task-focused explanations in biology and psychology often use “represent” generically, and proceed as follows. They identify a natural task for an organism. They then measure environmental properties relevant to the task, and constraints imposed by the organism’s bio-physical make-up. Next, they determine mathematically optimal performance of the task, given the environmental properties and the organism’s constraints. Finally, they develop hypotheses and test the organism’s fulfillment of the task against optimal performance.
This approach identifies systematic correlations between organisms’ states and environmental properties. Such correlations constitute generic representation. However, task-focused explanations that use “representation” generically are not distinctively psychological. For they apply to states of plants, bacteria, and water pumps, as well as to perception and thought.
Explanation in perceptual psychology is a sub-type of task-focused explanation. What makes it distinctively psychological is that it uses notions like representational accuracy, a specific type of correlation.
The difference between functional correlation and representational accuracy is signaled by the fact that scientific explanations of light-sensitivity in plants or bacteria invoke functional correlation, but not states capable of accuracy. Talk of accuracy would be a rhetorical afterthought. States capable of accuracy are what vision science is fundamentally about.
Science of mind is one of the most important intellectual developments in the last half century. It should not be obscured by neurobabble.
Why are explanations in terms of representational accuracy needed? They explain perceptual constancies. Perceptual constancies are capacities to perceive a given environmental property under many types of stimulation. You and a bird can see a stone as the same size from 6 inches or 60 yards away, even though the size of the stone’s effect on the retina differs. You and a bee can see a surface as yellow bathed in white or red light, even though the distribution of wavelengths hitting the eye differ.
Plants and bacteria (and water-pumps) lack perceptual constancies. Responses to light by plants and bacteria are explained by reference to states determined by properties of the light stimulus — frequency, intensity, polarization — and by how and where light stimulates their surfaces.
Visual perception is getting the environment right — seeing it, representing it accurately. Standard explanations of neural patterns cannot explain vision because such explanations do not relate vision, or even neural patterns, to the environment. Task-focused explanations in terms of functional correlation do relate organisms’ states to the environment. But they remain too generic to explain visual perception.
Perceptual psychology explains how perceptual states that represent environmental properties are formed. It identifies psychological patterns that are learned, or coded into the perceptual system through eons of interaction with the environment. And it explains how stimulations cause individuals’ perceptual states via those patterns. Perceptions and illusions of depth, movement, size, shape, color, sound localization, and so on, are explained with mathematical rigor.
Perceptual psychology uses two powerful types of explanation — one, geometrical and traditional; the other, statistical and cutting-edge.
Here is a geometrical explanation of distance perception. Two angles and the length of one side determine a triangle. A point in the environment forms a triangle with the two eyes. The distance between the eyes in many animals is constant. Suppose that distance to be innately coded in the visual system. Suppose that the system has information about the angles at which the two eyes are pointing, relative to the line between the eyes. Then the distance to the point in the environment is computable. Descartes postulated this explanation in 1637. There is now rich empirical evidence to indicate that this procedure, called “convergence,” figures in perception of distance. Convergence is one of over 15 ways human vision is known to represent distance or depth.
Here is a statistical explanation of contour grouping. Contour grouping is representing which contours (including boundary contours) “go together,” for example, as belonging to the same object. Contour grouping is a step toward perception of object shape. Grouping boundary contours that belong to the same object is complicated by this fact: Objects commonly occlude other objects, obscuring boundary contours of partially occluded objects. Grouping boundaries on opposite sides of an occluder is a step towards perceiving object shape.
To determine how boundary contours should ideally be grouped, numerous digital photographs of natural scenes are collected. Hundreds of thousands of contours are extracted from the photographic images. Each pair is classified as to whether or not it corresponds to boundaries of the same object. The distances and relative orientations between paired image-contours are recorded. Given enough samples, the probability that two photographic image-contours correspond to contours on the same object can be calculated. Probabilities vary depending on distance — and orientation relations among the image-contours. So whether two image-contours correspond to boundaries of the same object depends statistically on properties of image-contours.
Human visual systems are known to record contour information. In experiments, humans are shown only image-contours in photographs, not full photographs. Their performance in judging which contours belong to the same object, given only the image-contours, closely matches the objective probabilities established from the photographs. Such tests support hypotheses about how perceptions of object shape are formed from cues regarding contour groupings.
Representation, in the specific sense, and consciousness are the two primary properties that are distinctive of psychological phenomena. Consciousness is the what-it-is-like of experience. Representation is the being-about-something in perception and thought. Consciousness is introspectively more salient. Representation is scientifically better understood.
Where does mind begin? One beginning is the emergence of representational accuracy — in arthropods. (We do not know where consciousness begins.) Rigorous science of mind begins with perception, the first distinctively psychological representation. Maturation of a science of mind is one of the most important intellectual developments in the last half century. Its momentousness should not be obscured by neurobabble that baits with psychology, but switches to brain science. Brain and psychological sciences are working toward one another. Understanding their relation depends on understanding psychology. We have a rigorous perceptual psychology. It may provide a model for further psychological explanation that will do more than display an MRI and say, “behold, love.”
Additional Reading:
Charless C. Fowlkes, David R. Martin, and Jitendra Malik, “Local Figure-Ground Cues are Valid for Natural Images,” Journal of Vision 7 (2007), 1-9.
W.S. Geisler, “Visual Perception and the Statistical Properties of Natural Scenes,” Annual Review of Psychology 59 (2008), 10.1-10.26.
David Knill, “Discriminating Planar Surface Slant from Texture: Human and Ideal Observers Compared,” Vision Research, 38 (1998), 1683-1711.
Stephen E. Palmer, Vision Science: Photons to Phenomenology (Cambridge, Mass.: MIT Press, 2002).
D. Vishwanath, A.R. Girshick, and M.S. Banks, “Why Pictures Look Right When Viewed from the Wrong Place,” Nature Neuroscience (2005), 1401-1410.
D.S. Weisberg, F.C. Keil, J. Goodstein, E. Rawson, and J.R. Gray, “The Seductive Allure of Neuroscience Explanations,” Journal of Cognitive Neuroscience 20 (2008), 470-477.
Tyler Burge is Distinguished Professor of Philosophy at U.C.L.A. He is the author of many papers on philosophy of mind and three books with Oxford University Press: “Truth, Thought, Reason: Essays on Frege,” “Foundations of Mind,” and most recently, “Origins of Objectivity, which discusses the origins of mind in perception and the success of perceptual psychology as a science.
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Out of Our Brains *****
- ANDY CLARK -
DECEMBER 12, 2010, 3:47 PM
Where is my mind?
The question — memorably posed by rock band the Pixies in their 1988 song — is one that, perhaps surprisingly, divides many of us working in the areas of philosophy of mind and cognitive science. Look at the science columns of your daily newspapers and you could be forgiven for thinking that there is no case to answer. We are all familiar with the colorful “brain blob” pictures that show just where activity (indirectly measured by blood oxygenation level) is concentrated as we attempt to solve different kinds of puzzles: blobs here for thinking of nouns, there for thinking of verbs, over there for solving ethical puzzles of a certain class, and so on, ad blobum. (In fact, the brain blob picture has seemingly been raised to the status of visual art form of late with the publication of a book of high-octane brain images. )
There is no limit, it seems, to the different tasks that elicit subtly, and sometimes not so subtly, different patterns of neural activation. Surely then, all the thinking must be going on in the brain? That, after all, is where the lights are.
As our technologies become better adapted to fit the niche provided by the biological brain, they become more like cognitive prosthetics.
But then again, maybe not. We’ve all heard the story of the drunk searching for his dropped keys under the lone streetlamp at night. When asked why he is looking there, when they could surely be anywhere on the street, he replies, “Because that’s where the light is.” Could it be the same with the blobs?
Is it possible that, sometimes at least, some of the activity that enables us to be the thinking, knowing, agents that we are occurs outside the brain?
The idea sounds outlandish at first. So let’s take a familiar kind of case as a first illustration. Most of us gesture (some of us more wildly than others) when we talk. For many years, it was assumed that this bodily action served at best some expressive purpose, perhaps one of emphasis or illustration. Psychologists and linguists such as Susan Goldin-Meadow and David McNeill have lately questioned this assumption, suspecting that the bodily motions may themselves be playing some kind of active role in our thought process. In experiments where the active use of gesture is inhibited, subjects show decreased performance on various kinds of mental tasks. Now whatever is going on in these cases, the brain is obviously deeply implicated! No one thinks that the physical handwavings are all by themselves the repositories of thoughts or reasoning. But it may be that they are contributing to the thinking and reasoning, perhaps by lessening or otherwise altering the tasks that the brain must perform, and thus helping us to move our own thinking along.
Hiroko Masuike for The New York Times“Brain Cloud (2010)” on display at the Metropolitan Museum of Art in New York as part of a show by John Baldessari.
It is noteworthy, for example, that the use of spontaneous gesture increases when we are actively thinking a problem through, rather than simply rehearsing a known solution. There may be more to so-called “handwaving” than meets the eye.
This kind of idea is currently being explored by a wave of scientists and philosophers working in the areas known as “embodied cognition” and “the extended mind.” Uniting these fields is the thought that evolution and learning don’t give a jot what resources are used to solve a problem. There is no more reason, from the perspective of evolution or learning, to favor the use of a brain-only cognitive strategy than there is to favor the use of canny (but messy, complex, hard-to-understand) combinations of brain, body and world. Brains play a major role, of course. They are the locus of great plasticity and processing power, and will be the key to almost any form of cognitive success. But spare a thought for the many resources whose task-related bursts of activity take place elsewhere, not just in the physical motions of our hands and arms while reasoning, or in the muscles of the dancer or the sports star, but even outside the biological body — in the iPhones, BlackBerrys, laptops and organizers which transform and extend the reach of bare biological processing in so many ways. These blobs of less-celebrated activity may sometimes be best seen, myself and others have argued, as bio-external elements in an extended cognitive process: one that now criss-crosses the conventional boundaries of skin and skull.
One way to see this is to ask yourself how you would categorize the same work were it found to occur “in the head” as part of the neural processing of, say, an alien species. If you’d then have no hesitation in counting the activity as genuine (though non-conscious) cognitive activity, then perhaps it is only some kind of bio-envelope prejudice that stops you counting the same work, when reliably performed outside the head, as a genuine element in your own mental processing?
Another way to approach the idea is by comparison with the use of prosthetic limbs. After a while, a good prosthetic limb functions not as a mere tool but as a non-biological bodily part. Increasingly, the form and structure of such limbs is geared to specific functions (consider the carbon-fiber running blades of the Olympic and Paralympic athlete Oscar Pistorius) and does not replicate the full form and structure of the original biological template. As our information-processing technologies improve and become better and better adapted to fit the niche provided by the biological brain, they become more like cognitive prosthetics: non-biological circuits that come to function as parts of the material underpinnings of minds like ours.
Many people I speak to are perfectly happy with the idea that an implanted piece of non-biological equipment, interfaced to the brain by some kind of directly wired connection, would count (assuming all went well) as providing material support for some of their own cognitive processing. Just as we embrace cochlear implants as genuine but non-biological elements in a sensory circuit, so we might embrace “silicon neurons” performing complex operations as elements in some future form of cognitive repair. But when the emphasis shifts from repair to extension, and from implants with wired interfacing to “explants” with wire-free communication, intuitions sometimes shift. That shift, I want to argue, is unjustified. If we can repair a cognitive function by the use of non-biological circuitry, then we can extend and alter cognitive functions that way too. And if a wired interface is acceptable, then, at least in principle, a wire-free interface (such as links your brain to your notepad, BlackBerry or iPhone) must be acceptable too. What counts is the flow and alteration of information, not the medium through which it moves.
When information flows, some of the most important unities may emerge in regimes that weave together activity in brain, body and world.
Perhaps we are moved simply by the thought that these devices (like prosthetic limbs) are detachable from the rest of the person? Ibn Sina Avicenna, a Persian philosopher-scientist who lived between 980 and 1037 A.D, wrote in the seventh volume of his epic “De Anima (Liber de anima seu sextus de naturalibus)” that “These bodily members are, as it were, no more than garments; which, because they have been attached to us for a long time, we think are us, or parts of us [and] the cause of this is the long period of adherence: we are accustomed to remove clothes and to throw them down, which we are entirely unaccustomed to do with our bodily members” (translation by R. Martin). Much the same is true, I want to say, of our own cognitive circuitry.
The fact that there is a stable biological core that we do not “remove and throw down” blinds us to the fact that minds, like bodies, are collections of parts whose deepest unity consists not in contingent matters of undetachability but in the way they (the parts) function together as effective wholes. When information flows, some of the most important unities may emerge in integrated processing regimes that weave together activity in brain, body, and world.
Such an idea is not new. Versions can be found in the work of James, Heidegger, Bateson, Merleau-Ponty, Dennett, and many others. But we seem to be entering an age in which cognitive prosthetics (which have always been around in one form or another) are displaying a kind of Cambrian explosion of new and potent forms. As the forms proliferate, and some become more entrenched, we might do well to pause and reflect on their nature and status. At the very least, minds like ours are the products not of neural processing alone but of the complex and iterated interplay between brains, bodies, and the many designer environments in which we increasingly live and work.
Please don’t get me wrong. Some of my best friends are neuroscientists and neuro-imagers (as it happens, my partner is a neuro-imager, so brain blobs are part of our daily diet). The brain is a fantastic beast, more than worthy of the massive investments we make to study it. But we — the human beings with versatile bodies living in a complex, increasingly technologized, and heavily self-structured, world — are more fantastic still. Really understanding the mind, if the theorists of embodied and extended cognition are right, will require a lot more than just understanding the brain. Or as the Pixies put it:
Where is my mind?
Way out in the water, see it swimming
[Andy Clark's response to the comments on this post can be found here: "Extended Mind Redux: A Response."]
Andy Clark is professor of logic and metaphysics in the School of Philosophy, Psychology, and Language Sciences at Edinburgh University, Scotland. He is the author of “Being There: Putting Brain, Body, and World Together Again” (MIT Press, 1997) and “Supersizing the Mind: Embodiment, Action, and Cognitive Extension” (Oxford University Press, 2008).
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