In my lab we have shown that the left cerebral hemisphere is better at encoding categorical spatial relations, which makes sense because categories are often language-based. On the other hand (hemisphere), the right hemisphere is better at encoding coordinate spatial relations. This is true in normal people, it's true when we and others have done neuroimaging, and it's true when you look at deficit sin patients who have brain lesions. We've constructed a whole raft of neural network models that showed that, in fact, if you split a model—a network—into two separate streams (one for each type of representation), it does better than if you have a single system trying to make both categorical and coordinate representations. The point is not so much that the hemispheres are different, but rather that the brain relies on two distinct ways to code spatial relations. This claim caused a mini-controversy. I'm delighted to see that in a recent issue of the Journal of Cognitive Neuroscience researchers (who I don't know) tested over a hundred people after they "turned off" one hemisphere at a time for medical reasons, and showed that with challenging tasks where you have to make categorical versus coordinate spatial relations judgments, the laterality effects I predicted worked beautifully. If it was too easy it didn't work, which also fits perfectly with our modeling and previous experiments— so it looks like this controversy has been settled (but experience has taught me that those are famous last words….).

This is really just one little corner of what I do, and ultimately is related to my imagery work. I’ve always argued that imagery has to be understood in a system that includes language-like propositional representations as well as depictive representations. I don’t think of the mind as purely imaginal. That can't be true. It's got to depend on coordinating many different types of representations that interact in intricate and interesting ways. The distinction between the two types of representations invites a further distinction between different forms of imagery, which make use of the different sorts of spatial relations. And in fact we have evidence for such a distinction. One clear conclusion from all this: "Imagery" isn't just "one thing."

Getting back to computational theorizing in psychology per se. From my perspective—and maybe I’m missing something—computational theorizing has reached a plateau. That’s not to say there isn’t progress, but it’s incremental and is currently within a paradigm that was set perhaps ten years ago. I don’t see any revolutionary work out there. Right now, the connectionists are probably the leaders in computational theorizing relevant to the brain. David Rummelhart did terrific work. Terry Sejnowski is excellent, as is Jay McClelland. These are people who have been at it for years. I don't see too much really new on the horizon.

In terms of interesting theorizing, Dan Dennett and Steve Pinker and their colleagues are trying to cash out the evolutionary psychology program. Instead of trying to think about behaviors as being the products of evolution, they are thinking about how the modular structure of information processing in the brain is a consequence of evolution. That's an interesting program. My objection is that this enterprise is not particularly empirical. Science is the process of finding things out. You've got to go out and do studies to find things out. It's very helpful to have theories as a base from which you can direct your attention to issues and questions, but then you’re got to go do the actual research.

If you asked me to explain the direction of mind science writ large, I'd say that what you’re going to see is a bridging between cognitive neuroscience—where the mind is conceived of as what the brain does—and genetics. Those are the two really hot areas right now, and there’s a giant gulf between them.

I was recently writing a introductory psychology textbook chapter on intelligence, and read a lot of behavioral genetics. I was really struck by the fact that these guys are trying to bridge the gap from genes to behavior in one fell swoop, and they’re not doing that good a job at it. They're not doing that well in linkage studies that try to connect variability in a behavior with variability in different types of alleles. Sometimes they manage 2% of the variance. It occurred to me that they’re leaving out the middle man. They want to think in terms of the model: genes —> behavior. But it would be much better to think in terms of: genes —> brain, and then brain —> behavior. Genes influence behavior and cognition via what they do to the brain. Thinking about this has gotten me very interested in genetics, but not in the sense that genetics is a blueprint. Most genes functioning in the adult brain seem to be up-regulated and down-regulated by circumstances. They turn on and off.

Here’s an example developed by Steve Hyman that can serve as a metaphor: If you want to build muscles you lift weights. If the weight is heavy enough it’s going to damage the muscles. That damage creates a chemical cascade and reaches into the nuclei of your muscle cells, and turns on genes that make proteins and build up muscle fibers. Those genes are only turned on in response to some environmental challenge. That’s why you’ve got to keep lifting heavier and heavier weights. The phrase, "No pain no gain," is literally true in this case. Interaction with the environment turns on certain genes which otherwise wouldn’t be turned on; in fact, they will be turned off if certain challenges aren’t being faced. The same is true in the brain. Growing new dendritic spines, or even replenishing neurotransmitters, is linked to genes that are being turned on and turned off in response to what the brain is doing, which in turn is responding to environmental challenges.

I'm really interested in how genes allow the brain to respond to the tasks at hand. When genes are turned on and off, this affects what neurons are doing; which then, of course, affects how blood is allocated; in turn, affecting cognition and behavior. There is a gigantic project yet to be done that will have the effect of rooting psychology in the rest of natural science. Once this is accomplished, you'll be able to go from phenomenology—things like mental imagery—to information processing—thinking about things you can model on the computer—to the brain—thinking about how a particular kind of information processing arises from this particular brain we have—down through the workings of the neurons, including the biochemistry, all the way to the biophysics and the way that genes are up-regulated and down-regulated.

This is going to happen; I have no doubt at all. When it does we’re going to have a much better understanding of human nature than is otherwise going to be possible. If you want to understand evolution, the residue of evolution is the genes. Why not study the genes if you want to understand the reasons behind the brain's organization? There are reasons we have those genes rather than other ones—that’s where the evolutionary story comes in. But my particular brain or your particular brain is the way it is not only because of the particular genes we have, but also because of the way the environment up-regulated or down-regulated those genes during development, sculpting our brains certain ways, and the ways our genes respond to environmental and endogenous challenges. All of this is empirically tractable. The tools are available, the questions are clear, and we know what sort of answers to seek. Time to get cracking!


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