Explicit representation of confidence informs future value-based decisions

Folke, Tomas; Jacobsen, Catrine; Fleming, Stephen M.; Martino, Benedetto De

doi:10.1038/s41562-016-0002

Cited by 132 publications

(209 citation statements)

References 60 publications

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“…confidence in decisions. According to Folke et al (2016) Folke et al (2017, the difference in action values is a confidence correlate. We showed that the model-free system had exaggerated confidence correlate in decisions while having no difference in performance with the model-based method; i.e.…”

Section: Discussionmentioning

confidence: 99%

“…Confidence correlate of model-based and model-free strategies According to Folke et al (2016)Folke et al (2017, confidence can be strongly predicted by the difference of action values; the same is reported in perceptual decisionmaking where the difference in evidence is correlated with confidence Aitchison et al (2015). We exploited the same concept and checked if model-based and model-free methods differ in estimating the difference of Q-values for first-step choices.…”

Section: Figurementioning

confidence: 93%

“…The second criterion was if their behavior was best described by a random agent (an agent that make a decision with an equal probability between the available choices, regardless of anything) rather than a reinforcement learning agent. One subject only chose a single rate for her confidence more than 95% of trials in the memory task, so she was excluded Folke et al (2017). Thus thirty-seven subjects remained for analysis.…”

Section: Methodsmentioning

confidence: 99%

“…confidence in decisions. If one of the methods results in a higher difference among decision values, it would induce higher confidence in decisionsAitchison et al (2015); Folke et al (2017).…”

Section: Introductionmentioning

confidence: 99%

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Higher Meta-cognitive Ability Predicts Less Reliance on Over Confident Habitual Learning System

Ershadmanesh

Miandari

Vahabie

et al. 2019

Preprint

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Many studies on human and animals have provided evidence for the contribution of goal-directed and habitual valuation systems in learning and decision-making. These two systems can be modeled using model-based (MB) and model-free (MF) algorithms in Reinforcement Learning (RL) framework.Here, we study the link between the contribution of these two learning systems to behavior and meta-cognitive capabilities. Using computational modeling we showed that in a highly variable environment, where both learning strategies have chance level performances, model-free learning predicts higher confidence in decisions compared to model-based strategy. Our experimental results showed that the subjects' meta-cognitive ability is negatively correlated with the contribution of model-free system to their behavior while having no correlation with the contribution of model-based system. Over-confidence of the model-free system justifies this counter-intuitive result. This is a new explanation for individual difference in learning style. * Corresponding author (saraershad@ipm.ir) † These two authors contributed equally

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Section: Discussionmentioning

confidence: 99%

Section: Figurementioning

confidence: 93%

Section: Methodsmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

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Higher Meta-cognitive Ability Predicts Less Reliance on Over Confident Habitual Learning System

Ershadmanesh

Miandari

Vahabie

et al. 2019

Preprint

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“…For instance, a person should be more likely to pursue the intention of having sushi, the stronger that intention is (Ajzen, 1991;Sheeran, Webb, & Gollwitzer, 2005;Fleming et al, 2009). Intentional strength in turn might depend on confidence regarding an internal decision (Folke, Jacobsen, Fleming, & De Martino, 2016) or choice values (Rushworth, 2008), e.g., a strong preference for sushi over pizza. Yet, few goals are worth pursuing at any cost.…”

Section: Introductionmentioning

confidence: 99%

Two Ways to Change Your Mind: Effects of Intentional Strength and Motor Costs on Changes of Intention

Löffler

Sylaidi²,

Fountas

et al. 2019

Preprint

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Changes of Mind are a striking example of the human ability to flexibly reverse decisions after commitment to an initial choice, and to change actions according to circumstances. Previous studies of Changes of Mind largely focused on perceptual choices. Here we investigate reversals of voluntary, endogenous action decisions. In a novel version of the random-dot motion task, participants moved to a target that matched both the perceived dot-motion direction and an internally-generated intention (which colour target to move to). Movement trajectories revealed whether and when participants 1) perceived a change in dot-motion direction, or additionally 2) changed the colour that they chose to move to ('Change of Intention'). Changes of Intention were less frequent in participants with strong colour intentions, as indicated by high performance costs in trials where perceptual information conflicted with the endogenous intention (Exp. 1). Additionally, Changes of Intention were more frequent when motor costs of intention pursuit were high (Exp. 2). These findings were simulated using an attractor network model that continuously integrates voluntary intentions, sensory evidence, and motor costs. This argues in favour of a unifying framework for dynamic decision-making processes, in which voluntary actions emerge from a dynamic combination of internal action tendencies and external environmental factors.

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To covet what we see: Autistic traits modulate the relationship between looking and choosing

Hedger

Chakrabarti

2020

Autism Research

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Behavioral studies indicate that autistic traits predict reduced gaze toward social stimuli. Moreover, experiments that require participants to make an explicit choice between stimuli indicate reduced preferences for social stimuli in individuals with high autistic traits. These observations, in combination, fit with the idea that gaze is actively involved in the formation of choices—gaze toward a stimulus increases the likelihood of its subsequent selection. Although these aspects of gaze and choice behavior have been well characterized separately, it remains unclear how autistic traits affect the relationship between gaze and socially relevant choices. In a choice‐based eye‐tracking paradigm, we observed that autistic traits predict less frequent and delayed selection of social stimuli. Critically, eye tracking revealed novel phenomena underlying these choice behaviors: first, the relationship between gaze and choice behavior was weaker in individuals with high autistic traits—an increase in gaze to a stimulus was associated with a smaller increase in choice probability. Second, time‐series analyses revealed that gaze became predictive of choice behaviors at longer latencies in observers with high autistic traits. This dissociation between gaze and choice in individuals with high autistic traits may reflect wider atypicalities in value coding. Such atypicalities may predict the development of atypical social behaviors associated with the autism phenotype. Lay Summary When presented with multiple stimuli to choose from, we tend to look more toward the stimuli we later choose. Here, we found that this relationship between looking and choosing was reduced in individuals with high autistic traits. These data indicate that autistic traits may be associated with atypical processing of value, which may contribute to the reduced preferences for social stimuli exhibited by individuals with autism.

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Explicit representation of confidence informs future value-based decisions

Cited by 132 publications

References 60 publications

Higher Meta-cognitive Ability Predicts Less Reliance on Over Confident Habitual Learning System

Higher Meta-cognitive Ability Predicts Less Reliance on Over Confident Habitual Learning System

Two Ways to Change Your Mind: Effects of Intentional Strength and Motor Costs on Changes of Intention

To covet what we see: Autistic traits modulate the relationship between looking and choosing

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