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SUMMARY:Dynamic reorganization of neuronal activity patterns in parietal c
 ortex - Laura Driscoll (Harvard University)
DTSTART:20170220T100000Z
DTEND:20170220T103000Z
UID:TALK71093@talks.cam.ac.uk
CONTACT:Daniel McNamee
DESCRIPTION:Abstract:\nThe neuronal representations of learned association
 s between sensory stimuli and behavioral actions have been studied extensi
 vely. However\, the contribution of neurons to these representations has b
 een examined almost exclusively at single snapshots in time. Therefore\, i
 t remains poorly understood if neuronal representations of learned associa
 tions are stable over timescales of days and weeks. We tracked the activit
 y of a large population of posterior parietal cortex neurons for a month a
 s mice stably performed a navigation-based decision task in virtual realit
 y. Cells had reliable relationships between their activity and task featur
 es on single days\; however\, these relationships often changed over time.
  The neurons that were most informative about key task features\, such as 
 the trial type and locations in the maze\, differed across days. Despite c
 hanges in individual cells\, the activity in the neuronal population had s
 tatistically similar properties on each day and allowed for the stable rea
 d out of task information for over a week. During learning of new behavior
 al associations\, novel activity patterns were incorporated into the same 
 neurons that participated in existing representations without affecting th
 e rate of activity changes. We propose that dynamic neuronal activity patt
 erns provide a framework to balance plasticity required for learning and s
 tability required for memory.
LOCATION:Cambridge University Engineering Department\, CBL\, BE-438 (http:
 //learning.eng.cam.ac.uk/Public/Directions)
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