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Metacognition in dogs: Do dogs know they could be wrong?

ABSTRACT: In the current study, we investigated the question of whether dogs were sensitive to the information that they themselves had or had not acquired. For this purpose, we conducted three consecutive experiments in which dogs had to find a reward that was hidden behind one of two V-shaped fences with a gap at the point of the V. This setup allowed us to distinguish between selecting one of the fences by walking around it and seeking additional information by checking through the gap in the fence. We varied whether dogs had visual access to the baiting procedure or not. In addition, we manipulated the type and quality of reward as well as the time delay between baiting and choosing to analyze if the dogs' searching behavior was affected. Our results were partly consistent with the findings of Call (Animal Cognition, 13 (5), 689-700, 2010) with great apes, on whose findings we based our experiments. We found that dogs checked more often through the corner of the V-shaped fence when they had not seen where the reward was hidden. Interestingly, dogs rewarded with toys selected the correct fence more often than dogs rewarded with food. Even though dogs' performance was not affected by the food quality condition, dogs were significantly faster in fetching a high-quality food reward as opposed to a low-quality food reward. When testing whether forgetting and checking would increase as a function of delay, we found that although dogs slightly decreased in their success in finding the food when time delays were longer, they were not more likely to check before choosing. We show that - similar to apes - dogs seek additional information in uncertain situations, but their behavior in uncertain situations is less flexible compared to great apes.

SUBMITTER: Belger J

PROVIDER: S-EPMC6276073 | biostudies-literature | 2018 Dec

REPOSITORIES: biostudies-literature

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Metacognition in dogs: Do dogs know they could be wrong?

Belger Julia J Bräuer Juliane J

Learning & behavior 20181201 4

In the current study, we investigated the question of whether dogs were sensitive to the information that they themselves had or had not acquired. For this purpose, we conducted three consecutive experiments in which dogs had to find a reward that was hidden behind one of two V-shaped fences with a gap at the point of the V. This setup allowed us to distinguish between selecting one of the fences by walking around it and seeking additional information by checking through the gap in the fence. We ...[more]

PMID: 30421122

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Project description:IntroductionPrevious studies on metacognitive ability were explored using self-report questionnaires that are difficult to adequately measure and evaluate when the capacity for self-reference is undeveloped. This study aimed to validate the Congruency-based Metacognition Scale (CMS) to measure metacognition and the feeling of confidence abilities and to investigate the development of metacognition during adolescence.MethodsThe CMS was administered to 633 child-parent pairs in Japan (child, mean age = 16.0 years, 46.0% female; parent, mean age = 48.3 years, 94.9% mother). The CMS metacognition score was assessed based on congruency scores between the self-report of the child from a third-person perspective (3PP) and the parent's report from the first-person perspective (1PP). The CMS self-judgment accuracy score was assessed by the congruency scores between the children's self-report from the 1PP and 3PP. For both measures, the more distant the 3PP on the self-report was from the 1PP on the parent's report and child self-report means low ability. An exploratory factor analysis (EFA) was conducted to examine construct validity and then a confirmatory factor analysis (CFA) was used. Criterion validity was examined by calculating Pearson's correlation coefficients with scores on the Beck Cognitive Insight Scale (BCIS) and Autism Quotient (AQ). We used intraclass correlation and Cronbach's alpha to examine the test-retest and internal consistency reliability.ResultsBased on the results of the EFA and CFA, we adopted one factor structure with five items. The CMS metacognition and CMS self-judgment accuracy showed evidence criterion validity, exhibiting significant correlations with the BCIS self-reflectiveness (r = 0.16) and self-certainty scores (r = 0.17), respectively. Regarding to the AQ, only the CMS metacognition score had significant correlations with the social skills (r = 0.22) and total scale score (r = 0.20). The test-retest reliability showed adequate (intraclass correlation coefficient 0.70-0.81 and the Cronbach's alpha coefficient 0.63-0.59). Adolescents were found to have significantly lower metacognitive ability compared to young adults.ConclusionCMS could be a valid and reliable measure to examine metacognitive abilities for adolescents.

Project description:The human ability to introspect on thoughts, perceptions or actions − metacognitive ability − has become a focal topic of both cognitive basic and clinical research. At the same time it has become increasingly clear that currently available quantitative tools are limited in their ability to make unconfounded inferences about metacognition. As a step forward, the present work introduces a comprehensive modeling framework of metacognition that allows for inferences about metacognitive noise and metacognitive biases during the readout of decision values or at the confidence reporting stage. The model assumes that confidence results from a continuous but noisy and potentially biased transformation of decision values, described by a confidence link function. A canonical set of metacognitive noise distributions is introduced which differ, amongst others, in their predictions about metacognitive sign flips of decision values. Successful recovery of model parameters is demonstrated, and the model is validated on an empirical data set. In particular, it is shown that metacognitive noise and bias parameters correlate with conventional behavioral measures. Crucially, in contrast to these conventional measures, metacognitive noise parameters inferred from the model are shown to be independent of performance. This work is accompanied by a toolbox (ReMeta) that allows researchers to estimate key parameters of metacognition in confidence datasets. eLife digest Metacognition is a person’s ability to think about their own thoughts. For example, imagine you are walking in a dark forest when you see an elongated object. You think it is a stick rather than a snake, but how sure are you? Reflecting on one’s certainty about own thoughts or perceptions – confidence – is a prime example of metacognition. While our ability to think about our own thoughts in this way provides many, perhaps uniquely human, advantages, confidence judgements are prone to biases. Often, humans tend to be overconfident: we think we are right more often than we actually are. Internal noise of neural processes can also affect confidence. Understanding these imperfections in metacognition could shed light on how humans think, but studying this phenomenon is challenging. Current methods are lacking either mechanistic insight about the sources of metacognitive biases and noise or rely on unrealistic assumptions. A better model for how metacognition works could provide a clearer picture. Guggenmos developed a mathematical model and a computer toolbox to help researchers investigate how humans or animals estimate confidence in their own thoughts and resulting decisions . The model splits metacognition apart, allowing scientists to explore biases and sources of noise at different phases in the process. It takes two kinds of data: the decisions study participants make, and how sure they are about their decision being correct. It then recreates metacognition in three phases: the primary decision, the metacognitive readout of the evidence, and the confidence report. This allows investigators to see where and when noise and bias come into play. Guggenmos tested the model using independent data from a visual discrimination task and found that it was able to predict how confident participants reported to be in their decisions. Metacognitive ability can change in people with mental illness. People with schizophrenia have often been found to be overconfident in their decisions, while people with depression can be underconfident. Using this model to separate the various facets of metacognition could help to explain why. It could also shed light on human thinking in general.

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Metacognition in dogs: Do dogs know they could be wrong?

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Metacognition in dogs: Do dogs know they could be wrong?

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