Dr. Nick Turke-Browne will present.
Registration via Eventbrite.
Livestreaming via Vimeo.
Speaker: Nick Turke-Brown, Ph.D.
Professor of Psychology and Director of Wu Tsai Institute, Yale University, USA
Abstract: Adult cognitive neuroscience provides a rich account of how different brain systems give rise to diverse forms of learning and memory. However, these theories often neglect the greatest period of learning in life, during early development. A key challenge for studying this age range is the limited set of behavioral tasks and measures available. Neuroscientific techniques such as EEG and fNIRS provide another window into the infant mind, but have limited spatial resolution and lack access to deep-brain structures important for adult learning and memory. I will present our recent efforts to adapt fMRI, which helps address these limitations, for studying human infants during cognitive tasks. I will describe one of our awake infant fMRI studies in detail, addressing a mystery about how the brain supports statistical learning. We have shown in adults that the hippocampus is important for statistical learning, and statistical learning is a core building block of the infant mind, yet the hippocampus of infants is assumed to be immature (e.g., to explain infantile amnesia). This and our other fMRI studies in awake infants aim to advance understanding of the functions and plasticity of the youngest minds and brains.
Bio: Different cognitive processes like perception, attention, learning, and memory – and the underlying brain systems that support them – are often studied in isolation. This is productive and necessary, but my lab takes the complementary perspective of trying to understand how these systems interact. The hope is that this will help elucidate the constraints and functions of individual systems and also help produce a more integrated understanding of mind and brain. We use a variety of techniques, including psychophysical experiments to characterize behaviors of interest, functional magnetic resonance imaging to explore the underlying circuits and representations, case studies of patients with brain damage to provide converging evidence, and computational approaches (machine learning, graph theory, neural networks, real-time analysis) to formalize theories and generate quantitative predictions. As an example, we have worked extensively on ‘statistical learning’, the process by which humans extract regularities from sensory input. High-resolution imaging revealed that subfields of the hippocampus – typically linked to the encoding of discrete experiences – play an important role in such learning of commonalities across experiences, and computational modeling provided a theoretical explanation of the mechanism. We study a variety of other topics as well, including predictive coding, memory-guided attention, and, most recently, the development of brain function in infants and toddlers.
The Feindel Virtual Brain and Mind (VBM) Seminar Series will advance the vision of Dr. William Feindel (1918–2014), Former Director of the Neuro (1972–1984), to constantly bridge the clinical and research realms. The talks will highlight the latest advances and discoveries in neuropsychology, cognitive neuroscience, and neuroimaging.
Speakers will include scientists from across The Neuro, as well as colleagues and collaborators locally and from around the world. The series is intended to provide a virtual forum for scientists and trainees to continue to foster interdisciplinary exchanges on the mechanisms, diagnosis and treatment of brain and cognitive disorders.