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SUMMARY:Efficient coding of subjective value - Xiaolu Wang
DTSTART:20240110T140000Z
DTEND:20240110T150000Z
UID:TALK210388@talks.cam.ac.uk
CONTACT:Adam Triabhall
DESCRIPTION:This week we will discuss and debate a recent paper by Polaní
 a and colleagues\, published in Nature Neuroscience (2019).\n\nAbstract: 
 “Preference-based decisions are essential for survival\, for instance\, 
 when deciding what we should (not) eat. Despite their importance\, prefere
 nce-based decisions are surprisingly variable and can appear irrational in
  ways that have defied mechanistic explanations. Here we propose that subj
 ective valuation results from an inference process that accounts for the s
 tructure of values in the environment and that maximizes information in va
 lue representations in line with demands imposed by limited coding resourc
 es. A model of this inference process explains the variability in both sub
 jective value reports and preference-based choices\, and predicts a new pr
 eference illusion that we validate with empirical data. Interestingly\, th
 e same model explains the level of confidence associated with these report
 s. Our results imply that preference-based decisions reflect information-m
 aximizing transmission and statistically optimal decoding of subjective va
 lues by a limited-capacity system. These findings provide a unified accoun
 t of how humans perceive and valuate the environment to optimally guide be
 havior” (Polanía et al.\, 2019).\n\nReference: Polania\, R.\, Woodford\
 , M.\, & Ruff\, C. C. (2019). Efficient coding of subjective value. Nature
  Neuroscience\, 22(1)\, 134-142. https://doi.org/10.5167/uzh-160002
LOCATION:https://cam-ac-uk.zoom.us/j/92612577704?pwd=MUtqMjVQdXNmUTVIYjRkM
 G1NUW9GZz09
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