Current Projects

Dynamic Right Hemisphere Recruitment for Language

Our ability to understand linguistic function and dysfunction is contingent upon an improved understanding of how language processes are distributed in the intact brain, and how resources are allocated as a function of the ever changing demands.  This project,funded by the National Institute on Deafness and other Communication Disorders, applies TMS, fMRI, and concurrent TMS/fMRI investigations to explore a new hypothesis about the dynamic roles of the two cerebral hemispheres in normal language processes and implications for recovery of function following unilateral brain damage.  Our hypothesis in brief is that the right hemisphere (RH) becomes engaged in a variety of linguistic tasks when the processing demands of the task outstrip the resources available in the dominant left hemisphere (LH) and some of the residual processing “spills over” into RH homologues (e.g., Just & Varma, 2007; Prat, Mason, & Just, 2011).  Importantly, the spillover hypothesis predicts that RH involvement varies across tasks and individuals, as a function of the relation between cognitive and neural resources available to an individual and of the demands required to complete the task. Recovery from unilateral brain damage is likely to vary as a function of pre-injury lateralization; therefore our understanding of the factors related to individual differences in language lateralization is imperative.  One goal of this project is to obtain knowledge about the causes and correlates of individual differences in language laterality.  Another is to investigate system-level characteristics of the cortical network responsible for language processes, and how they relate to individual language lateralization and skill.  A final goal is to investigate how the language network changes as a whole in response to impaired functioning in isolated regions. This information will further our understanding of how the two hemispheres cooperate during intact language processes, and ultimately improve our understanding of deficits associated with unilateral damage and how to enhance recovery.

Bilingual Brain Training

Speaking one language is, in itself, an amazing achievement. According to some estimates, however, almost half of the world population manages to be proficient in two or moredifferent languages. Research shows that such mastering of multiple languages has profound effects an individual’s cognitive abilities, extending beyond social and communicative benefits. In fact, bilinguals outperform monolinguals in a variety of tasks that are cognitively demanding , such as those drawing on executive processes such as inhibitory control and working memory.  In other words, speaking two languages seems to “train” the brain in a manner that has effects that generalize to non-language domains.  Our current research at the CCDL is using “Dynamic Causal Modeling” of neuroimaging data, in combination with our existing understanding of the neural basis of individual differences in cognitive capabilities, to better understand the nature of the brain changes induced by bilingualism, and explain how this translates into a general cognitive benefit.

Instructions and Rule Application

Controlling one’s own actions according to predefined rules is an amazing feature of human behavior. It underlies human’s intelligence and flexibility,  makes general knowledge possible,  and enables planning. Importantly, it also makes it possible to communicate instructions (in the form of rules) using language (which is, in itself, a rule based skill). Though such rule-based behavior is central to flexible human thought, the precise neural mechanisms underlying rule acquisition, instantiation, and execution are still poorly understood. At the CCDL, we are trying to understand the process by which our brain encodes and interpret rules by using “Dynamic Causal Modeling” of neuroimaging data, and detailed computer models of the brain. We are also applying our knowledge to real-world scenarios, by devising methods that would improve how students understand mathematical rules, and using data from the brain to better understand the causes of their mistakes.
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