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Seminar: Dr Yaniv Ziv
September 5, 2018 @ 16:00 - 17:00
Stability and dynamics underlying hippocampal neural codes for long-term memory
Wednesday 5 September @ 4pm – 5pm (Sherrington Library, Sherrington Building, Department of Physiology, Anatomy and Genetics)
We are delighted to host a seminar by Dr Yaniv Ziv from the Weizmann Institute of Science, Israel. The talk will take place in the Sherrington Library, Sherrington Building, Department of Physiology, Anatomy and Genetics. Please contact Tai-Ying Lee (tai-ying.lee -at- dpag.ox.ac.uk) if you would like to arrange an individual meeting with the speaker.
After the talk, we will head to a pub for some food and drinks with the speaker. If you would like to join, RSVP to cortex.club -at- studentclubs.ox.ac.uk.
Episodic memory relies on the hippocampus, whose neurons are thought to encode information about where and when events have occurred. Whereas ample knowledge exists regarding the encoding of location, relatively little is known about the neural mechanisms that enable the encoding of the time in which events occur. We performed time-lapse imaging of thousands of neurons over weeks in the hippocampal CA1 of mice as they repeatedly visited two distinct environments. Longitudinal analysis exposed ongoing environment-independent evolution of episodic representations, despite stable place field locations and constant remapping between the two environments. These dynamics time-stamped experienced events via neuronal ensembles that had cellular composition and activity patterns unique to specific points in time. Our results suggest that days-scale hippocampal ensemble dynamics could support the formation of a mental timeline in which experienced events could be mnemonically associated or dissociated based on their temporal distance, and point to a plausible mechanism by which information about place and time can be simultaneously and independently encoded in episodic representations. I will also discuss how the stability of function may be achieved despite the ongoing continuous ensemble dynamics that we observe.