Department of Hearing and Speech Sciences
Jared Novick is an Assistant Professor in the Department of Hearing and Speech Sciences and Associate Research Scientist at the Center for Advanced Study of Language. He received his Ph.D. in Cognitive Psychology at the University of Pennsylvania and trained as a post-doctoral fellow in Cognitive Neuroscience at MIT. Dr. Novick's research focuses on the behavioral and neurobiological interplay among language, memory, and cognitive control. In particular, his work seeks to understand the human computational systems that support the real-time interpretation and re-interpretation of sentences. He addresses this issue by using (i) eye-tracking techniques to record readers' and listeners' moment-to-moment processing decisions; (ii) neuroimaging methods to test for common brain bases of linguistic and nonlinguistic performance; and (iii) lesion-deficit analyses of neurological patients' language and cognitive abilities. Recent questions include: how does experience-induced plasticity of cognitive control (the ability to regulate thoughts and behavior) affect online language processing? What are the processing demands of being a bilingual speaker that contribute to the "bilingual advantage" in cognitive control compared to monolinguals?
- Psycholinguistics; Bilingualism; Cognitive Control; Neuroscience
One of the most striking computational properties of the human mind is its ability to interpret speech and text in real-time. As you read this sentence, you are quickly retrieving from long-term memory not only the meanings of the individual words, but also detailed grammatical knowledge about how these words lawfully combine to engender a coherent overall interpretation. Findings from language processing studies suggest that readers and listeners achieve much of this process moment-by-moment as they encounter language input (sounds, words, phrases). That is, when reading or processing speech, people do not delay interpretation until a sentence or even a single word unfolds entirely; rather, they commit to provisional analyses incrementally on the basis of accumulating evidence, rapidly consulting multiple sources of information from both the linguistic signal and the external visual environment to guide comprehension. Real-time processing is certainly efficient, obviating the need to hold in working memory low-level characterizations of the input (e.g., visual or phonological representations) for extended periods of time. However, processing language ‘on-the-fly’ comes at the cost of having to deal with temporary ambiguity, as early analyses sometimes turn out wrong when new, later-arriving input suggests a quite different interpretation. Consider for example this New York Times headline: “Google’s computer might betters translation tool.” Because “might” frequently appears as an auxiliary verb, readers may initially misunderstand that it is used here as a noun (meaning strength). The processing difficulty experienced following such misanalysis requires the deployment of cognitive resources to countermand early parsing decisions. My research seeks to understand the human computational system that supports the real-time interpretation and re-interpretation of sentences. In particular, my work has proposed that domain-general ‘cognitive control’ functions are central to people’s ability to revise initial processing commitments. Cognitive control refers to the regulation of mental activity to guide goal-directed behavior consistent with situation-specific requirements, enabling individuals to bias relevant over irrelevant representations when confronted with information-conflict during processing.