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SUMMARY:Computational Neuroscience Journal Club - Mate Lengyel and Jasmine
  Stone
DTSTART:20210601T140000Z
DTEND:20210601T153000Z
UID:TALK160858@talks.cam.ac.uk
CONTACT:Jake Stroud
DESCRIPTION:Please join us for our fortnightly journal club online via zoo
 m where two presenters will jointly present a topic together. The next top
 ic is ‘Inference noise in reward-guided learning’ presented by Mate Le
 ngyel and Jasmine Stone.\n\nZoom information: https://us02web.zoom.us/j/84
 958321096?pwd=dFpsYnpJYWVNeHlJbEFKbW1OTzFiQT09\nMeeting ID: 841 9788 6178\
 nPasscode: 659046\n\nMaking decisions in uncertain and volatile environmen
 ts is something humans and animals must do as they interact with the world
 . These decisions are variable and often suboptimal. Computational noise h
 as been proposed as a source of this variability. However\, there may be s
 ome benefits to computational noise in decision making as well — in part
 icular\, humans and animals are much more adaptable than current AI system
 s with exact (noise-free) computations\, and computation noise may have mo
 re of an effect in higher volatility environment where this adaptability i
 s more important.\n\nWe present a set of four studies\; two show computati
 onal noise as a bug corrupting optimal decisions\, while two show computat
 ional noise as a feature\, enabling adaptation in volatile environments.\n
 \nList of references:\n\nBUG:\n\nDrugowitsch\, J.\, Wyart\, V.\, Devauchel
 le\, A.-D.\, & Koechlin\, E. (2016). Computational Precision of Mental Inf
 erence as Critical Source of Human Choice Suboptimality. Neuron\, 92(6)\, 
 1398–1411. https://doi.org/10.1016/j.neuron.2016.11.005\n\nFindling\, C.
 \, Skvortsova\, V.\, Dromnelle\, R.\, Palminteri\, S.\, & Wyart\, V. (2019
 ). Computational noise in reward-guided learning drives behavioral variabi
 lity in volatile environments. Nature Neuroscience\, 22(12)\, 2066–2077.
  https://doi.org/10.1038/s41593-019-0518-9\n\nFEATURE:\n\nFindling\, C.\, 
 Chopin\, N. & Koechlin\, E. Imprecise neural computations as a source of a
 daptive behaviour in volatile environments. Nat Hum Behav 5\, 99–112 (20
 21). https://doi.org/10.1038/s41562-020-00971-z\n\nFindling\, C.\, & Wyart
 \, V. (2020). Computation noise promotes cognitive resilience to adverse c
 onditions during decision-making [Preprint]. Neuroscience. https://doi.org
 /10.1101/2020.06.10.145300\n\n\n\nOPTIONAL FURTHER READING/REVIEW\n\nBUG:\
 n\nBeck\, J. M.\, Ma\, W. J.\, Pitkow\, X.\, Latham\, P. E.\, & Pouget\, A
 . (2012). Not Noisy\, Just Wrong: The Role of Suboptimal Inference in Beha
 vioral Variability. Neuron\, 74(1)\, 30–39. https://doi.org/10.1016/j.ne
 uron.2012.03.016\n\nWyart\, V.\, & Koechlin\, E. (2016). Choice variabilit
 y and suboptimality in uncertain environments. Current Opinion in Behavior
 al Sciences\, 11\, 109–115. https://doi.org/10.1016/j.cobeha.2016.07.003
 \n\nFEATURE: \n\nFindling\, C.\, & Wyart\, V. (2021). Computation noise in
  human learning and decision-making: Origin\, impact\, function. Current O
 pinion in Behavioral Sciences\, 38\, 124–132. https://doi.org/10.1016/j.
 cobeha.2021.02.018
LOCATION:Online on Zoom
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