By its nature an interdisciplinary endeavor, this field straddles the borders between linguistics, neurobiology, and computer science, among others. Researchers are drawn to it from a variety of backgrounds, bringing along a variety of experimental techniques as well as widely differing theoretical perspectives.
Historically, the term neurolinguistics has been most closely associated with aphasiology, the study of linguistics deficits, and spared abilities, resulting from specific forms of brain damage. This field is considered in a separate article.
Although aphasiology is the historical core of neurolinguistics, in recent years the field has broadened considerably, as new technologies have been brought to bear on the matter. Language is a fundamental topic of interest in cognitive neuroscience, and modern brain imaging techniques have contributed greatly to a growing understanding of the anatomical organization of language functions. Such techniques include PET and fMRI, which provide high spatial resolution images of energy use in various brain regions during language processing tasks. To date, the results of these techniques have not contradicted the existing results from aphasiology. Unfortunately, these techniques do not allow for high temporal resolution of brain activity as the comprehension or production of sentences unfolds. As temporal resolution is of utmost importance in these questions, researchers also employ the gross electrophysiological techniques EEG and MEG. These provide millisecond-level resolution, but the nature of the brain mechanisms that generate the electrical signals on the scalp is not known, making them difficult to interpret. As a result, EEG and MEG are used mainly to inform theories of the cognitive/computational architecture of language, without regard to their precise neurobiological implementation. For example, one might suspect that out of three categories of words that could end a sentence, two are actually tapping into the same mechanism but the third is represented differently. Showing that these two categories elicit an identical electrophysiological response different from that of the third would support such a hypothesis.
Closely related to such research is the field of psycholinguistics, which seeks to elucidate the cognitive mechanisms of language by employing the traditional techniques of experimental psychology, including analyses of such indicators as reaction time, error rates, and eye movements.
One other important methodology in the cognitive neuroscience of language is computational modeling, which can demonstrate the (im)plausibility of specific hypotheses about the neural organization of language while generating novel predictions for further empirical research. Currently, computational modelers are collaborating increasingly with brain imagers and psychologists in coordinated, interdisciplinary programs of research. Such programs have yielded important new insights into the nature of language, as well as major language disorders that affect millions, such as stuttering and dyslexia.\n
