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NEURAL DYNAMICS: THE NEURAL BASIS OF LEARNING AND MEMORY AND TEMPORAL PROCESSING Behavior and cognition are not the product of isolated neurons, but rather emerge from the dynamics of interconnected neurons embedded in complex recurrent networks. Significant progress has been made towards understanding cellular and synaptic properties in isolation, as well as in establishing which areas of the brain are active during specific tasks. However, elucidating how the activity of hundreds of thousands of neurons within local cortical circuits underlie computations remains an elusive and fundamental goal in neuroscience. The primary goal of my laboratory is to understand how functional computations emerge from networks of neurons. One computation we are particularly interested in is how the brain tells time. Temporal processing refers to your ability to distinguish the interval and duration of sensory stimuli, and is a fundamental component of speech and music perception. To answer these questions the main approaches in my laboratory involve: (1) In Vitro Electrophysiology: Using acute and chronic brain slices we study the spatio-temporal dynamics of cortical circuits, as well as the learning rules that allow networks to develop, organize and perform computations ??? that is, to learn. (2) Computer Simulations: Computer models are used to simulate how networks perform computations, as well as test and generate predictions in parallel with our experimental research. (3) Human Psychophysics: We also use human pyschophysical experiments to characterize learning and generalization of temporal tasks, such as interval discrimination.
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Benjamin Liu,Dean V Buonomano
bioRxiv : the preprint server for biology (2024)
Science advancesno. 18 (2024): eadk7257-eadk7257
Research Square (Research Square) (2023)
bioRxiv (Cold Spring Harbor Laboratory) (2023)
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The Journal of neuroscience : the official journal of the Society for Neuroscienceno. 45 (2023): 7565-7574
biorxiv(2022)
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