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SUMMARY:A reinforcement learning account of planning\, prospective simulat
 ion\, and hippocampal replay
DTSTART:20190328T150000
DTEND:20190328T160000
DTSTAMP:20260924T071703Z
UID:d3a90d266ef00c8e7c56e27915c65c787419e924959536cbc920de5b
CATEGORIES:Conferences - Seminars
DESCRIPTION:Dr Marcelo G. Mattar\, University of Cambridge\, UK.\nTo make 
 decisions\, we must evaluate candidate choices by accessing records of rel
 evant experiences. Yet little is known about which experiences the brain c
 onsiders or ignore during planning\, which ultimately affects choice. In t
 his talk\, I will describe my research revealing principles by which we us
 e our memories to plan and decide. First\, I will describe a normative the
 ory predicting which memories would be ideally accessed at each moment to 
 optimize future decisions. Using nonlocal “replay” of spatial location
 s in hippocampus as a window into memory access\, I will show simulations 
 of a spatial navigation task where an ideal agent accesses memories of loc
 ations sequentially\, ordered by utility: how much extra reward would be e
 arned due to better choices. This prioritization balances two desiderata: 
 the need to evaluate imminent choices\, vs. the gain from propagating newl
 y encountered information to preceding locations. In addition to explainin
 g the role of memory in planning\, this theory offers a simple explanation
  for numerous findings about place cells and unifies seemingly disparate p
 roposed functions of replay including planning\, learning\, and consolidat
 ion. I will then present an experimental framework using neuroimaging in h
 umans to predict and measure memory reactivation during planning and its e
 ffect on choice\, including techniques from machine learning and network s
 cience. Finally\, I will describe a broader research program for understan
 ding the neural mechanisms of how we plan and decide and the implications 
 for related psychiatric disorders such as rumination and craving.\n \nBio
 \nMarcelo Mattar is a Newton International Postdoctoral Fellow working at 
 University of Cambridge and Princeton University with Máté Lengyel and N
 athaniel Daw. He studies learning and decision-making using a combination 
 of theoretical and human behavioral/imaging approaches\, with a particular
  interest in reinforcement learning and Bayesian inference. He completed h
 is PhD in Psychology at the University of Pennsylvania\, where he studied 
 network theory with Danielle Bassett and visual adaptation with Geoffrey A
 guirre.\n\nVideo transmission using zoom : https://epfl.zoom.us/j/99464957
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LOCATION:SV 1717 https://plan.epfl.ch/?room==SV%201717
STATUS:CONFIRMED
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