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TZID:UTC
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TZOFFSETFROM:+0000
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DTSTART:20230101T000000
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BEGIN:VEVENT
DTSTART;TZID=UTC:20240617T113000
DTEND;TZID=UTC:20240617T130000
DTSTAMP:20260513T180713
CREATED:20240613T195130Z
LAST-MODIFIED:20240613T195130Z
UID:929-1718623800-1718629200@arni-institute.org
SUMMARY:CTN: Stefano Fusi
DESCRIPTION:Title: The Geometry of Abstraction\n\nAbstract: I’ll first discuss the theoretical framework introduced in Bernardi et al. 2020\, Cell\, in which we propose a possible definition of abstract representations. I’ll go into the details of the most up-to-date  conceptual framework\, discuss the computational relevance of the representational geometry and the cross-validated measures of representational geometry that we normally use to characterize neural data in artificial and biological networks. Then I’ll apply the analytical tools to the study of human electrophysiological data (see Courellis\, H.S.\, Mixha\, J.\, Cardenas\, A.R.\, Kimmel\, D.\, Reed\, C.M.\, Valiante\, T.A.\, Salzman\, C.D.\, Mamelak\, A.N.\, Fusi\, S. and Rutishauser\, U.\, 2023. Abstract representations emerge in human hippocampal neurons during inference behavior. bioRxiv\, pp.2023-11 for more details).
URL:https://arni-institute.org/event/ctn-stefano-fusi/
LOCATION:Zuckerman Institute – L5-084\, 3227 Broadway\, New York\, NY\, United States
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