Wednesday, April 16, 2025

Grand Rounds: György Buzsáki, M.D., Ph.D.

10:30 AM to 12:00 PM

Rachel Upjohn Building Auditorium and webcast

32nd Annual Alfred Barrett Neuroscience Lecture

"Mechanisms of Memory Selection and Consolidation"

Speaker

 György Buzsáki, M.D., Ph.D. photo

György Buzsáki, M.D., Ph.D.

Biggs Professor of Neural Sciences
NYU Neuroscience Institute
New York University, Langone Medical Center

György Buzsáki is Biggs Professor of Neuroscience at New York University. His primary focus is “neural syntax”, i.e., how the numerous brain rhythms organize segmentation of neural information to support cognitive functions. He is among the top 0.1% most-cited neuroscientists, member of the National Academy of Sciences USA, Academia Europaea, Fellow of AAAS, and he sits on the editorial boards of several leading neuroscience journals, including Science and Neuron, honoris causa at Université Aix-Marseille, France, University of Pecs and University of Kaposvar, Hungary. He is a co-recipient of the 2011 Brain Prize. 

Buzsáki’s main interest is “neural syntax,” which allows segmentation of brain activity so that unlimited amount of information can be created from a limited set of elements as in human language. His general hypothesis is that the brain's numerous rhythms perpetually generates are responsible for such syntactical segmentation of neural information and communication across brain regions. He has shown that these neuronal oscillations span several orders of magnitude in time (from a few milliseconds to long seconds, supporting neuronal commands from fast motor responses to short-term memory). These individual oscillators form a hierarchical system so that the slower oscillation's phase modulates the faster one's amplitude and so on. The interleaved fast and slow rhythms, therefore, can package and concatenate neuronal messages of various lengths, akin to letters, words, and sentences of language.

Within this larger framework, his laboratory focuses on the mechanisms of memory and associated diseases, in particular how sleep affects learned events. His most influential work is the two-stage model of memory trace consolidation, identifying hippocampal sharp wave ripples (SPW-R) as a biomarker for memory transfer. Several laboratories worldwide have adopted his framework and provided supporting evidence for his model in experimental animals and human subjects. Relevant to clinical translation, hippocampal ripples and other brain rhythms (such as theta and gamma oscillations) that our laboratory has identified lend themselves to diagnosis of disease and drug discovery.

 

(Books: Rhythms of the Brain, OUP, 2006; The Brain from Inside Out, OUP 2019)

https://buzsakilab.com/wp/

Host