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Guest Lecture

Prof. Michael T. Ullman | Evidence that language is learned in brain circuits that predate humans: Implications for typical and a typical development

It has often been claimed that humans learn language using specialized brain components that are dedicated to this uniquely human capacity. However, increasing evidence suggests that language learning depends importantly on general-purpose brain circuits that pre-existed humans. In particular, research indicates both that children learn native languages and adults learn additional languages in evolutionarily ancient circuits that are found in other vertebrates, and are used for a wide range of tasks. For example, birds rely on these circuits to remember where they stored their hidden acorns, while rats use them to follow rule-governed grooming sequences. Similarly, humans depend on these neural systems for tasks as diverse as remembering a shopping list and learning to drive. Converging evidence from multiple brain and behavioral studies suggests that humans also rely on these systems for both their lexical (word) and grammatical (rule-governed combination) abilities, in both first and second language. Newer evidence also suggests that aspects of reading and math are learned in these systems. Moreover, abnormalities in or compensation by these systems can help explain atypical language and other functions, for example in specific language impairment and dyslexia. The research has implications not only for understanding the biology and evolution of language and how it is learned, but also for how language learning can be improved, both for people learning a second language and for those with developmental and other disorders. [more]

Guest Lecture

Dr Mareike Grotheer | Separate lanes for math and reading in the white matter highways of the human brain

Math and reading skills greatly influence the socio-economic outlook of an individual. These skills have both shared (e.g. decoding of visual stimuli), as well as dissociated (e.g. quantity processing) cognitive components. Moreover, math and reading learning disabilities have a high-rate of co-occurrence, although some children have difficulties with only one skill or the other. Therefore, it is possible that math and reading have both shared and dissociated neural substrates, which are presently unknown. To address this significant gap in knowledge, we applied an innovative multi-modal approach, combining functional MRI (fMRI), diffusion MRI (dMRI), and quantitative MRI (qMRI), to identify and compare both the gray and white matter substrates of the math and reading networks. Through meticulous single-subject analyses, we showed that processing associated with math and reading occurs largely in parallel in the human brain. First, fMRI revealed that gray matter regions involved in processing math and reading are distinct, even though they neighbor in cortex. Second, dMRI showed that while the superior longitudinal (SLF) and the arcuate (AF) fascicles contribute to both math and reading networks, within these fascicles there are segregated and parallel sub-bundles of white matter tracts associated with math or reading. This organization is akin to parallel and distinct lanes in a highway. Third, qMRI measurements showed lower T1 relaxation time, which suggests a higher degree of myelination, in white matter tracts associated with reading than math. These novel findings: (i) open a new avenue of research enabling linkage of sub-bundles within fascicles to behavior and (ii) may explain both isolated and comorbid cases of math and reading disabilities, which may be associated with white matter abnormalities within sub-bundles or entire fascicles, respectively. [more]

Guest Lecture

Prof. Andreas Nieder | tba

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