New technologies that are changing our concept of the nature of learning

New computer-driven technologies (e.g. PET scans, fMRI, qEEG) are revolutionizing the way in which we are able to study learning as it happens in the brain. These new technologies reveal, in ways that were unimaginable ten years ago, that learning is 1) modular, 2) distributed, 3) parallel, and 4) heterarchical. While a full explication of these observations for understanding the processes of learning is beyond the scope of this paper (see Meyer and Rose, in press) several aspects of the research can be highlighted.

These new tools and methodologies allow us to "see" the brain as it learns - by performing enormously complicated computations on subtle changes in brain activity that are then displayed as a simple "topographical" map of activity on a computer screen. The dominant impression from these computed images is how "modularized" the brain seems to be. It is immediately apparent that the brain learns, for example, about the color of an object in a different region than it learns about the shape of the same object. Moreover, it processes the word "cat" in a different region when it is presented in print than when it is presented in speech, and it uses an entirely different area to compose the word "cat" for speaking. The brain has a large number of such distributed modules that work "in parallel," each highly specialized for learning about specific aspects of the world.

The pattern of activity across different modules clearly depends on the task - different modules are active when one listens to a speech or when one listens to a symphony, for example. In a general sense there is a "signature" of activity in the brain that corresponds to the kind of task being performed. But the distribution of activity for any task also varies across individuals. Each individual reveals a particular "map" of activity - differing both in the proportions of space devoted to each of the modules, and in the composition of different modules used to accomplish the same task. The brain of an individual with perfect pitch, for example, shows a strikingly different distribution of activity from that of an individual with "normal" pitch perception, or one who is "tone deaf."

Significantly, the "map" of activity changes as the brain learns. Recent research has shown that a novice uses very different modules in the brain for the same task than does an expert. New technologies allow us to watch the brain over the course of learning, as it changes from using one set of modules to another. Surprisingly, these new techniques have also shown that the size of an individual processing module can grow (and others can shrink) with experience, even in adults.

New technologies for studying the brain are yielding an increasingly more accurate articulation of the concept of learning - revealing not one generalized learning capacity, but many different "modules" and "distributed processes" for learning within the same brain. Further, it is becoming clear that individual brains differ from each other not in a general ability (like IQ) but in many different kinds of specific abilities.