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CATEGORIES:Computational Neuroscience
SUMMARY:Neural mechanisms of model-based planning in the r
 at - Kevin Miller\, University College London
DTSTART;TZID=Europe/London:20181120T110000
DTEND;TZID=Europe/London:20181120T120000
UID:TALK115159AThttp://talks.cam.ac.uk
URL:http://talks.cam.ac.uk/talk/index/115159
DESCRIPTION:Planning can be defined as use of an internal mode
 l\, containing knowledge about the outcomes likely
  to follow each possible action\, to guide action 
 selection. In recent work\, we adapted for rodents
  a multi-step decision task widely used to study p
 lanning in human subjects\, allowing the extensive
  experimental toolkit available for rodents to be 
 brought to bear on this problem in a new way. We f
 ound that rats adopt a strategy of model-based pla
 nning to solve this task\, and that silencing neur
 al activity in either the orbitofrontal cortex or 
 the dorsal hippocampus was sufficient to impair pl
 anning. Here\, I will describe new data from exper
 iments designed to reveal the computational role i
 n model-based cognition played by each region. In 
 the orbitofrontal cortex (OFC)\, neurons encode in
 formation about expected outcomes in a manner spec
 ifically suitable for a role in model-based learni
 ng\, but not for a role in model-based choice. Tri
 al-by-trial optogenetic inactivations of the OFC s
 imilarly reveal a pattern of impairment that is co
 nsistent with impaired learning\, but not with imp
 aired decision-making. These data suggest that the
  OFC supports model-based cognition by signaling e
 xpected outcomes to a process which updates choice
  mechanisms residing elsewhere in the brain. In th
 e dorsal hippocampus\, activity of CA1 neurons doe
 s not seem to encode information about expected ou
 tcomes\, but instead indexes the various behaviora
 l states of the task in a manner reminiscent of “p
 lace cell” coding. Sharp wave ripple events which 
 occur during the inter-trial interval show evidenc
 e of “replay”\, in which sequences of neural activ
 ity typical of task performance (occupying several
  seconds) are rapidly repeated within the span of 
 a single sharp-wave ripple (occupying severals ten
 s of milliseconds). Ongoing work seeks to test whe
 ther the content of these replay events is consist
 ent with computational theories proposing roles in
  learning\, decision-making\, or both.
LOCATION:Cambridge University Engineering Department\, CBL\
 , BE4-38 (http://learning.eng.cam.ac.uk/Public/Dir
 ections)
CONTACT:Marcelo Gomes Mattar
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