Research Spending & Results

• Alec P Marantz
• (212) 998-3593
• marantz@nyu.edu

• FY 2011=$207,566
• FY 2010=$206,846
• FY 2009=$198,491

• William J. Badecker
• (703) 292-5069
• wbadecke@nsf.gov

Awardee Location

Primary Place of Performance

Abstract at Time of Award

This project will investigate the comprehension of morphologically complex words, words like "knowable" that can be broken down into pieces. Linguists and psycholinguists disagree on whether all words that consist of a possibly independent stem ("know" is a verb by itself) and an identifiable suffix ("-able" generally creates adjectives from verbs) are analyzed as complex by speakers and whether all or any such words are recognized via decomposition into their parts. The issue is particularly controversial for words like "tolerable" apparently built from roots that do not appear on their own ("toler-" is also seen in "tolerate" but not elsewhere). This project uses magnetoencephalographic (MEG) brain monitoring methods to test a theory about the interaction of linguistic representations and neural computations. The theory demands that every decomposition motivated by linguistic theory is a necessary computational step in recognizing a word and that each computation maps to neural activity of a set of brain regions at particular time latencies during word recognition. For this project, subjects will read or listen to individual words and non-words, judging their word status, while the electrical activity in their brains is monitored with MEG. A novel analysis technique will be developed that correlates the brain responses of each subject for each word with continuous stimulus variables such as word frequency, suffix frequency, and the probability of having a particular suffix following a particular stem. Given sufficient numbers of subjects and stimuli, this technique can provide meaningful data about individual words and individual subjects. For example, is a word like "vulnerable", whose root "vulner-" does not appear elsewhere in English, recognized in the same way as "knowable" or "tolerable"?

The project should elucidate the connections among linguistic theory, psycholinguistic models, and brain activity while testing hypotheses about the comprehension of morphologically complex words. Since for the theories of morphology being tested, the structure of words involves the same computations and representations as the structure of sentences, support for full decomposition to the root for words like "knowable" and "tolerable" will have implications for language processing at all levels of linguistic analysis. The single trial MEG analysis techniques developed by the project should aid greatly in the diagnosis of language-impaired populations and in the evaluation of remediation. Exploiting the results and techniques of this project, future research can ask, for example, how the brain responses of an individual dyslexic or autistic subject differ from the norm along various dimensions, and if any of these responses approach group norms after intervention. Progress in understanding and treating these deficits should come from an understanding of how neural systems perform linguistic computations and store and manipulate linguistic representations.