Retrospective confidence judgments by rhesus monkeys

Shields, Wendy E.; Smith, J. David; Washburn, David A.

doi:10.1037/e537102012-721

Cited by 44 publications

(66 citation statements)

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“…Hampton, Zivin, & Murray, 2004) or to make confidence judgements (e.g. Shields, Smith, Guttmanova, & Washburn, 2005;Son & Kornell, 2005;Kornell, Son, & Terrace, 2007). We have not yet applied BEM to those tasks and it is very possible that it might fail.…”

Section: Resultsmentioning

confidence: 99%

Metacognition in animals: how do we know that they know?

Jozefowiez¹,

Staddon²,

Cerutti³

2009

CCBR

136

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Research on animal metacognition has typically used choice discriminations whose difficulty can be varied. Animals are given some opportunity to escape the discrimination task by emitting a so-called uncertain response. The usual claim is that an animal possesses metacognition if (a) the probability of picking the uncertain response increases with task difficulty, and (b) animals are more accurate on "free-choice" trials -i.e., trials where the uncertain response was available but was not chosen-than on "forced-choice" trials, where the uncertain response is unavailable. We describe a simple behavioral economic model (BEM), based on familiar learning principles, and thus lacking any metacognition construct, which is able to meet both criteria in most of these tasks. We conclude that rather than designing ever more complex experiments to identify "metacognition," a necessarily ill-defined concept, knowledge might better be advanced not by further refining behavioral criteria for the concept, but by the development and testing of theoretical models for the clever behavior that many animals show in these experiments.

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Section: Resultsmentioning

confidence: 99%

Metacognition in animals: how do we know that they know?

Jozefowiez¹,

Staddon²,

Cerutti³

2009

CCBR

136

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“…In order to test animals in this task, the different options were linked with different reward contingencies: correct choices were rewarded with one unit of food reward, uncertain responses were rewarded with a smaller amount of food while incorrect choices lead to omission of reward and a time-out punishment. Smith and colleagues studied monkeys, dolphins and rats and compared their performance with humans [27][28][29][30][31]. Under these conditions, monkeys and dolphins showed a qualitative similarity in response strategies as well as a quantitative agreement in the response distributions of animals and humans.…”

Section: Behavioural Reports Of Confidence In Humans and Other Animalsmentioning

confidence: 99%

A computational framework for the study of confidence in humans and animals

Kepecs

Mainen

2012

Phil. Trans. R. Soc. B

268

289

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Confidence judgements, self-assessments about the quality of a subject's knowledge, are considered a central example of metacognition. Prima facie, introspection and self-report appear the only way to access the subjective sense of confidence or uncertainty. Contrary to this notion, overt behavioural measures can be used to study confidence judgements by animals trained in decision-making tasks with perceptual or mnemonic uncertainty. Here, we suggest that a computational approach can clarify the issues involved in interpreting these tasks and provide a much needed springboard for advancing the scientific understanding of confidence. We first review relevant theories of probabilistic inference and decision-making. We then critically discuss behavioural tasks employed to measure confidence in animals and show how quantitative models can help to constrain the computational strategies underlying confidence-reporting behaviours. In our view, post-decision wagering tasks with continuous measures of confidence appear to offer the best available metrics of confidence. Since behavioural reports alone provide a limited window into mechanism, we argue that progress calls for measuring the neural representations and identifying the computations underlying confidence reports. We present a case study using such a computational approach to study the neural correlates of decision confidence in rats. This work shows that confidence assessments may be considered higher order, but can be generated using elementary neural computations that are available to a wide range of species. Finally, we discuss the relationship of confidence judgements to the wider behavioural uses of confidence and uncertainty.

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“…Son and Kornell (2005) and Shields, Smith, Guttmannova, and Washburn (2005) did this by designing a betting paradigm. High-confidence bets resulted in larger rewards and larger penalties for correct and incorrect responses, respectively.…”

Section: Discussionmentioning

confidence: 99%

Humans and Monkeys Exert Metacognitive Control Based on Learning Difficulty in a Perceptual Categorization Task

Redford

2010

Psychol Rec

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Recently, Redford (2010) Metacognition-defined as thinking about thinking-involves a monitoring and control component (Nelson & Narens, 1990). The monitoring component is responsible for assessing the mind's basic mental processes (Dunlosky & Nelson, 1992;Koriat & Bjork, 2005;Koriat & Ma'ayan, 2005;Serra & Dunlosky, 2005;Thiede, Anderson, & Therriault, 2003). Metacognitive monitoring provides information related to how difficult information will be to learn and how well information has been learned. Metacognitive control uses this information to control study. For example, students who quit studying because they decide that the information is already well learned are exerting metacognitive control. In this case, metacognitive monitoring provided information regarding the state of learning (i.e., the information was well learned), and metacognitive control enacted the appropriate action (i.e., to terminate study). Effective metacognitive monitoring and control have been shown to be critical for learning (Thiede, 1999).

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Retrospective confidence judgments by rhesus monkeys

Cited by 44 publications

References 0 publications

Metacognition in animals: how do we know that they know?

Metacognition in animals: how do we know that they know?

A computational framework for the study of confidence in humans and animals

Humans and Monkeys Exert Metacognitive Control Based on Learning Difficulty in a Perceptual Categorization Task

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