Reinforcement biases subsequent perceptual decisions when confidence is low: A widespread behavioral phenomenon
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Reinforcement biases subsequent perceptual decisions when confidence is low: A widespread behavioral phenomenon. / Lak, Armin; Hueske, Emily; Hirokawa, Junya; Masset, Paul; Ott, Torben; Urai, Anne E.; Donner, Tobias H.; Carandini, Matteo; Tonegawa, Susumu; Uchida, Naoshige; Kepecs, Adam.
in: ELIFE, Jahrgang 9, e49834, 15.04.2020.Publikationen: SCORING: Beitrag in Fachzeitschrift/Zeitung › SCORING: Zeitschriftenaufsatz › Forschung › Begutachtung
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TY - JOUR
T1 - Reinforcement biases subsequent perceptual decisions when confidence is low: A widespread behavioral phenomenon
AU - Lak, Armin
AU - Hueske, Emily
AU - Hirokawa, Junya
AU - Masset, Paul
AU - Ott, Torben
AU - Urai, Anne E.
AU - Donner, Tobias H.
AU - Carandini, Matteo
AU - Tonegawa, Susumu
AU - Uchida, Naoshige
AU - Kepecs, Adam
N1 - © 2020, Lak et al.
PY - 2020/4/15
Y1 - 2020/4/15
N2 - Learning from successes and failures often improves the quality of subsequent decisions. Past outcomes, however, should not influence purely perceptual decisions after task acquisition is complete since these are designed so that only sensory evidence determines the correct choice. Yet, numerous studies report that outcomes can bias perceptual decisions, causing spurious changes in choice behavior without improving accuracy. Here we show that the effects of reward on perceptual decisions are principled: past rewards bias future choices specifically when previous choice was difficult and hence decision confidence was low. We identified this phenomenon in six datasets from four laboratories, across mice, rats, and humans, and sensory modalities from olfaction and audition to vision. We show that this choice-updating strategy can be explained by reinforcement learning models incorporating statistical decision confidence into their teaching signals. Thus, reinforcement learning mechanisms are continually engaged to produce systematic adjustments of choices even in well-learned perceptual decisions in order to optimize behavior in an uncertain world.
AB - Learning from successes and failures often improves the quality of subsequent decisions. Past outcomes, however, should not influence purely perceptual decisions after task acquisition is complete since these are designed so that only sensory evidence determines the correct choice. Yet, numerous studies report that outcomes can bias perceptual decisions, causing spurious changes in choice behavior without improving accuracy. Here we show that the effects of reward on perceptual decisions are principled: past rewards bias future choices specifically when previous choice was difficult and hence decision confidence was low. We identified this phenomenon in six datasets from four laboratories, across mice, rats, and humans, and sensory modalities from olfaction and audition to vision. We show that this choice-updating strategy can be explained by reinforcement learning models incorporating statistical decision confidence into their teaching signals. Thus, reinforcement learning mechanisms are continually engaged to produce systematic adjustments of choices even in well-learned perceptual decisions in order to optimize behavior in an uncertain world.
UR - http://www.scopus.com/inward/record.url?scp=85084338705&partnerID=8YFLogxK
U2 - 10.7554/eLife.49834
DO - 10.7554/eLife.49834
M3 - SCORING: Journal article
C2 - 32286227
AN - SCOPUS:85084338705
VL - 9
JO - ELIFE
JF - ELIFE
SN - 2050-084X
M1 - e49834
ER -
