Can our decisions be guided by unconscious or implicit influences? According to the somatic marker hypothesis, emotion-based signals can guide our decisions in uncertain environments outside awareness. Postdecision wagering, in which participants make wagers on the outcomes of their decisions, has been recently proposed as an objective and sensitive measure of conscious content. In 5 experiments we employed variations of a classic decision-making assessment, the Iowa Gambling Task, in combination with wagering in order to investigate the role played by unconscious influences. We examined the validity of postdecision wagering by comparing it with alternative measures of conscious knowledge, specifically confidence ratings and quantitative questions. Consistent with a putative role for unconscious influences, in Experiments 2 and 3 we observed a lag between choice accuracy and the onset of advantageous wagering. However, the lag was eliminated by a change in the wagering payoff matrix (Experiment 2) and by a switch from a binary wager response to either a binary or a 4-point confidence response (Experiment 3), and wagering underestimated awareness compared to explicit quantitative questions (Experiments 1 and 4). Our results demonstrate the insensitivity of postdecision wagering as a direct measure of conscious knowledge and challenge the claim that implicit processes influence decision making under uncertainty.
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Biol Lett
June 2024
School of Psychology and Neuroscience, University of St Andrews, St Andrews KY16 9AJ, UK.
When chimpanzees search for hidden food, do they realize that their guesses may not be correct? We applied a post-decision wagering paradigm to a simple two-cup search task, varying whether we gave participants visual access to the baiting and then asking after they had chosen one of the cups whether they would prefer a smaller but certain reward instead of their original choice (experiment 1). Results showed that chimpanzees were more likely to accept the smaller reward in occluded than visible conditions. Experiment 2 found the same effect when we blocked visual access but manipulated the number of hiding locations for the food piece, showing that the effect is not owing to representation type.
View Article and Find Full Text PDFSci Rep
January 2024
Laboratory for Neural Computation and Adaptation, RIKEN Center for Brain Science, Wako, Japan.
There are many modeling works that aim to explain people's behaviors that violate classical economic theories. However, these models often do not take into full account the multi-stage nature of real-life problems and people's tendency in solving complicated problems sequentially. In this work, we propose a descriptive decision-making model for multi-stage problems with perceived post-decision information.
View Article and Find Full Text PDFJ Exp Psychol Learn Mem Cogn
June 2024
Graduate School of Human and Environmental Studies, Kyoto University.
It has been reported that visual statistical learning (VSL) is facilitated in skewed distributions. However, it remains unclear whether enhancement of VSL in Zipfian distributions is due to consciousness of the regularities presented at high frequency. This study addressed this issue.
View Article and Find Full Text PDFCell Rep
March 2022
Department of Physiology, The University of Tokyo School of Medicine, Bunkyo-ku, Tokyo 113-0033, Japan; Juntendo University, Graduate School of Medicine, Bunkyo-ku, Tokyo 113-8421, Japan; Laboratory for Cognition Circuit Dynamics, RIKEN Center for Brain Science, Wako-shi, Saitama 351-0198, Japan.
Introspection based on the integration of uncertain evidence is critical for acting upon abstract thinking and imagining future scenarios. However, it is unknown how confidence read-outs from multiple sources of different concepts are integrated, especially considering the relationships among the concepts. In this study, monkeys performed wagering based on an estimation of their performance in a preceding mnemonic decision.
View Article and Find Full Text PDFNat Commun
September 2021
Paul G. Allen School of Computer Science and Engineering, University of Washington, Seattle, WA, USA.
In perceptual decisions, subjects infer hidden states of the environment based on noisy sensory information. Here we show that both choice and its associated confidence are explained by a Bayesian framework based on partially observable Markov decision processes (POMDPs). We test our model on monkeys performing a direction-discrimination task with post-decision wagering, demonstrating that the model explains objective accuracy and predicts subjective confidence.
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