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Fedorenko investigates how people understand and produce language. She uses behavioral and brain imaging (fMRI, ERP, MEG) methods in healthy adults and patients with developmental and acquired brain disorders, as well as intracranial recordings and stimulation in neurosurgical patients, and, more recently, computational modeling. Fedorenko has shown that the language network is selective for language processing over diverse non-linguistic processes that have been argued to share computational demands with language; that syntactic processing is not localized to a particular region within the language network, and every brain region that responds to syntactic processing is at least as sensitive to word meanings; and that semantic composition, rather than syntactic structure building, may be the core driver of the language-selective brain regions. In ongoing work, Fedorenko is probing the time-course, effective connectivity, and causal mechanisms of language processing using intracranial recordings and stimulation; applying computational approaches, including state-of-the art decoding, and deep neural nets to develop a precise model of what the language brain regions are doing; examining non-literal (pragmatic) processing given that much of language comprehension goes beyond the literal string of words; relating inter-individual variability in neural language markers to behavior and genetics; and probing the cognitive and neural architecture of individuals with exceptional linguistic talent (e.g., “hyper-polyglots”).