I’ve recently run across three little articles that GGers should find interesting (Thx Colin).
The first features David Poeppel. He discusses some recent work by Edward Chang at UCSF who has discovered neurons that respond to “basic “phonemic features,” rather than to phonemes themselves, which are larger chunks of sound.” As David points out in his remarks, this is not news to linguists. But it is a nice example of how what we have discovered, using pretty conventional analytic methods within phono, have mapped pretty directly onto basic neuro units. So when someone asks how linguistics is relevant to the brain sciences, this is a nice case to pull out and wave about. One more thing caught my eye: the relation between brain and cognition is here executed at the level of primitives. As Chang put it, features are the “building blocks of speech and language.” It makes sense to think that the easiest bridges to the brain will be from our primitives to theirs. The reason is that once one gets by this very simple stage complexity grows rapidly and the mapping likely becomes more and more obscure. This recalls the Embick and Poeppel observations concerning the Granularity Mismatch Problem (see here for some discussion). If GG is to make contact with neuroscience (which, IMO, it had better do or risk irrelevance, or worse), it will need to find ways if breaking the complexities of grammar into simpler and simpler sub-units and primitive operations. Happily, GG has been doing this since the mid 80s when constructions were broken down into more primitive operations like ‘moe alpha.’ As all of you know, this is also the main animating conceit of the Minimalist Program. And if what we see above is indicative, this is a very good thing for it’s at the level of simple units and basic operations that we might hope to find links to the neurosciences.
Marcus continues this theme in two pieces. The first is a piece in the NYTs (here) in which Gary argues that we need to return to the idea that the brain is a kind of computer. Apparently, this idea is no longer in fashion. Gary explains why the reasons for dumping this analogy are very weak and actually counterproductive. As he points out the right question is not whether the brain is (like) a computer but what kind of computer the brain is like. This seems absolutely right. The brain is an information processing device. Thus, it computes.
Gary rebuts the standard reasons for ignoring this analogy between brains and computers. But more interesting still he provides an interesting proposal for what kind of computer the brain might be. In a paper with two colleagues (here), he suggests that the brain is very like a “FIELD programmable gate array.” What are these? Well, they
…consist of a large number of “logic block” programs that can be configured, and reconfigured, individually, to do a wide range of tasks. One logic block might do arithmetic, another signal processing, and yet another look things up in a table. The computation of the whole is a function of how the individual parts are configured. Much of the logic can be executed in parallel, much like what happens in a brain.
In the Science piece, Gary & Co propose (p. 552) that neuroscience ought to be looking not for “a single canonical circuit” but for
…a broad array of reusable computational primitives- elementary units- of processing akin to basic sets of instructions in a microprocessor- perhaps wired together in parallel…
This fits with the “basic units/operations” theme I alluded to above. Again, it is at this very basic level that we can rationally hope to make contact with the brain sciences.
One more observation: the Science piece reads a little like a minimalist manifesto for the neurosciences. Most of cognition is made up of several simple operations that link together in different ways for different ends. Thus we should expect to find the same primitives again and again across cognition. This is music to a minimalist’s ears: most knowledge of language resides in recycled basic cognitive circuits. If there is something linguistically special (and I believe that the evidence to date is that there is) then it is a pretty small addition to this basic inventory of primitives. Our job is two fold: (i) to identify that special linguistic operation and (ii) to show that all the rest of G competence can be reduced/analyzed in terms of the remaining cognitively general ones. Conceptually, this program in linguistics fits snugly with the one that Marcus & friends outline for cogneuro, and that is just great!
One really last observation: Gary & Co end their Science piece with the following inspirational peroration (my emphasis NH):
Neuroscience must develop precisely the sorts of experimental tools, detailed brian maps, and computational infrastructures that today’s brain initiatives aim to support, but also a new set of intellectual tools for understanding how, even in principle, systems might bridge from neuronal networks to symbolic cognition…
In other words, it ends in praise of research on how things could work as well as how they do work. I could not agree more, not only in neuroscience, but in linguistics as well. The obsession with the actual is often a barrier to intellectual progress. For the big questions, it is indispensible. Sadly, IMO, it is often devalued. But you already know that I think this. I find comfort in finding that I am not alone.