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SUMMARY:Computational Neuroscience Journal Club - Yan Wu (University of Ca
 mbridge)
DTSTART:20150512T150000Z
DTEND:20150512T160000Z
UID:TALK59407@talks.cam.ac.uk
CONTACT:Guillaume Hennequin
DESCRIPTION:Yan Wu will cover:\n\n* Model-based choices involve prospectiv
 e neural activity\n* B B Doll\, K D Duncan\,	D A Simon\, D Shohamy and N D
  Daw\n* Nature Neuroscience 18\, 767–772 (2015)\n* http://www.nature.com
 /neuro/journal/v18/n5/full/nn.3981.html\n\nDecisions may arise via 'model-
 free' repetition of previously reinforced actions or by 'model-based' eval
 uation\, which is widely thought to follow from prospective anticipation o
 f action consequences using a learned map or model. While choices and neur
 al correlates of decision variables sometimes reflect knowledge of their c
 onsequences\, it remains unclear whether this actually arises from prospec
 tive evaluation. Using functional magnetic resonance imaging and a sequent
 ial reward-learning task in which paths contained decodable object categor
 ies\, we found that humans' model-based choices were associated with neura
 l signatures of future paths observed at decision time\, suggesting a pros
 pective mechanism for choice. Prospection also covaried with the degree of
  model-based influences on neural correlates of decision variables and was
  inversely related to prediction error signals thought to underlie model-f
 ree learning. These results dissociate separate mechanisms underlying mode
 l-based and model-free evaluation and support the hypothesis that model-ba
 sed influences on choices and neural decision variables result from prospe
 ction.
LOCATION:Cambridge University Engineering Department\, CBL\, BE-438 (http:
 //learning.eng.cam.ac.uk/Public/Directions)
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