Confidence-guided updating of choice bias during perceptual decisions is a widespread behavioral phenomenon
- University College London, United Kingdom
- MIT, United States
- Doshisha University, Japan
- Cold Spring Harbor Laboratory, United States
- University Medical Center Hamburg-Eppendorf, Germany
- The Picower Institute for Learning and Memory, RIKEN-MIT Center for Neural Circuit Genetics, Massachusetts Institute of Technology, United States
- Harvard University, United States
Abstract
Learning from past successes and failures improves decisions to produce appropriate actions in each perceived situation. However, reinforcement learning is not thought to be engaged during well-trained perceptual decision tasks, —after task acquisition is complete and performance is stable—, since choice accuracy is limited by perception. We report a novel form of reinforcement learning during perceptual decisions: past rewards bias future perceptual choices specifically when the previous stimulus was difficult to judge, and the confidence in obtaining the reward 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 reinforcement learning models incorporating decision confidence into their teaching signal explain this choice updating. 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.
Data availability
The data used in this study is available at http://dx.doi.org/10.6084/m9.figshare.4300043
Article and author information
Author details
Funding
Wellcome (106101)
- Armin Lak
Wellcome (213465)
- Armin Lak
National Institutes of Health (R01 MH110404)
- Naoshige Uchida
National Institutes of Health (R01MH097061 and R01DA038209)
- Naoshige Uchida
Wellcome (205093)
- Matteo Carandini
Deutsche Forschungsgemeinschaft (DO 1240/2-1 and DO 1240/3-1)
- Tobias H Donner
RIKEN-CBS
- Emily Hueske
- Susumu Tonegawa
JPB Foundation
- Emily Hueske
- Susumu Tonegawa
Howard Hughes Medical Institute
- Emily Hueske
- Susumu Tonegawa
German Academic Exchange Service
- Anne E Urai
The funders had no role in study design, data collection and interpretation, or the decision to submit the work for publication.
Ethics
Animal experimentation: The experimental procedures were approved by Institutional committees at Cold Spring Harbor Laboratory (for experiments on rats), MIT and Harvard University (for mice auditory experiments) and were in accordance with National Institute of Health standards (project ID: 18-14-11-08-1). Experiments on mice visual decisions were approved by the home Office of the United Kingdom (license 70/8021). Experiments in humans were approved by the ethics committee at the University of Amsterdam (project ID: 2014-BC-3376).
Human subjects: The ethics committee at the University of Amsterdam approved the study, and all observers gave their informed consent.project ID: 2014-BC-3376
Copyright
© 2020, Lak et al.
This article is distributed under the terms of the Creative Commons Attribution License permitting unrestricted use and redistribution provided that the original author and source are credited.
Metrics
-
- 7,789
- views
-
- 1,172
- downloads
-
- 91
- citations
Views, downloads and citations are aggregated across all versions of this paper published by eLife.
Download links
A two-part list of links to download the article, or parts of the article, in various formats.
Downloads (link to download the article as PDF)
Open citations (links to open the citations from this article in various online reference manager services)
Cite this article (links to download the citations from this article in formats compatible with various reference manager tools)
Confidence-guided updating of choice bias during perceptual decisions is a widespread behavioral phenomenon
eLife 9:e49834.
https://doi.org/10.7554/eLife.49834
Further reading
-
- Neuroscience
Sequenced reactivations of hippocampal neurons called replays, concomitant with sharp-wave ripples in the local field potential, are critical for the consolidation of episodic memory, but whether replays depend on the brain’s reward or novelty signals is unknown. Here, we combined chemogenetic silencing of dopamine neurons in ventral tegmental area (VTA) and simultaneous electrophysiological recordings in dorsal hippocampal CA1, in freely behaving male rats experiencing changes to reward magnitude and environmental novelty. Surprisingly, VTA silencing did not prevent ripple increases where reward was increased, but caused dramatic, aberrant ripple increases where reward was unchanged. These increases were associated with increased reverse-ordered replays. On familiar tracks this effect disappeared, and ripples tracked reward prediction error (RPE), indicating that non-VTA reward signals were sufficient to direct replay. Our results reveal a novel dependence of hippocampal replay on dopamine, and a role for a VTA-independent RPE signal that is reliable only in familiar environments.
-
- Neuroscience
Active inference integrates perception, decision-making, and learning into a united theoretical framework, providing an efficient way to trade off exploration and exploitation by minimizing (expected) free energy. In this study, we asked how the brain represents values and uncertainties (novelty and variability), and resolves these uncertainties under the active inference framework in the exploration-exploitation trade-off. Twenty-five participants performed a contextual two-armed bandit task, with electroencephalogram (EEG) recordings. By comparing the model evidence for active inference and reinforcement learning models of choice behavior, we show that active inference better explains human decision-making under novelty and variability, which entails exploration or information seeking. The EEG sensor-level results show that the activity in the frontal, central, and parietal regions is associated with novelty, while the activity in the frontal and central brain regions is associated with variability. The EEG source-level results indicate that the expected free energy is encoded in the frontal pole and middle frontal gyrus and uncertainties are encoded in different brain regions but with overlap. Our study dissociates the expected free energy and uncertainties in active inference theory and their neural correlates, speaking to the construct validity of active inference in characterizing cognitive processes of human decisions. It provides behavioral and neural evidence of active inference in decision processes and insights into the neural mechanism of human decisions under uncertainties.
