Identifying the Computational Parameters Gone Awry in Psychosis

Pfuhl, Gerit; Sandvik, Kristin; Biegler, Robert; Tjelmeland, Håkon

doi:10.1007/978-3-319-23344-4_3

Cited by 3 publications

(4 citation statements)

References 20 publications

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“…The larger unsystematic deviation found here is in agreement with the results from Moutoussis, Bentall, El-Deredy, and Dayan (2011) who modelled the Draws to Decision version of the beads task. The more stochastic responding may reflect a propensity to see a change in jar, particularly in those cases where the number of beads considered is large (Pfuhl, Sandvik, Biegler, & Tjelmeland, 2015). The model by Adams et al (2018) and other paradigms support the notion that patients perceive the world as more volatile, i.e.…”

Section: Discussionsupporting

confidence: 55%

Probabilistic reasoning in schizophrenia is volatile but not biased

Pfuhl¹,

Tjelmeland²

2019

Preprint

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We update our beliefs based on evidence. Aberrant belief updating has been linked to schizophrenia and autism. It is not clear whether the faulty updating is due to reducedgeneral cognitive abilities, overweighting of recent information, or lower thresholds for switching from one belief to another. A common task to assess belief updating isthe beads task. Patients with schizophrenia show hasty decision-making.We here present a model describing the deviations from an ideal Bayesian observer and apply the model to three independent datasets, totalling n=176 healthy controlsand n=128 patients with schizophrenia. The parameters describe a) the number of beads considered (memory), b) systematic deviation and c) unsystematic deviations (volatility) from probability estimates.We find that, on average, patients use fewer beads and or more volatile responding. However, patients have, on average, probability estimates that are closer to the true probabilities. Closer investigations yielded relevant differences among the datasets and sequences used. Morechallenging sequences improve the performance of patients.Our model captures well the cognitive mechanisms proposed to contribute to the performance differences in the beads task.

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Section: Discussionsupporting

confidence: 55%

Probabilistic reasoning in schizophrenia is volatile but not biased

Pfuhl¹,

Tjelmeland²

2019

Preprint

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“…Behavioral measures are also increasingly used. Examples include computer-based tasks that involve attention-shifting (e.g., Callinan, Johnson, & Wells, 2015), cognitive reflection task (e.g., Mækelæ, Moritz, & Pfuhl, 2018), or measuring implicit metacognition (e.g., Kreis et al, 2019; Pfuhl, Sandvik, Biegler, & Tjelmeland, 2015).…”

Section: Metacognition As It Is Used In Different Fieldsmentioning

confidence: 99%

Metacognition in Psychology

Norman

Pfuhl

Sæle

et al. 2019

Review of General Psychology

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How has the concept of metacognition been used within basic and applied psychological research? We begin our answer by presenting a broad definition of metacognition, an historical overview of its development and its presence in research databases. To assess which function and facets are most frequently addressed within each of the sub-disciplines, we present results from separate literature searches. We then review how metacognition has been defined and empirically explored within selected sub-disciplines in terms of typical research questions, conceptual definitions, how the concept has been measured, and examples of interesting findings and implications. We identify similarities, inconsistencies, and disagreements across fields and point out areas for future research. Our overall conclusion is that it is useful to consider metacognition as a broad umbrella concept across different domains and across basic and applied research. Nonetheless, we recommend that researchers be more specific and explicit about their approach and assumptions whenever using metacognition in their research.

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“…Therefore, the precision could not directly be measured. To improve on this situation, Pfuhl et al (2015) developed a task that measured the precision of a subjects' memory representations and their confidence about this precision. Subjects saw a squiggly shape and after a brief delay had to indicate which shape they saw.…”

Section: Assessing Reliability and Precision Of Prior Beliefsmentioning

confidence: 99%

“…Langdon, Ward and Coltheart (2010) did change the jar and measured the probability but did not ask when the subject was sure that a change in jar occurred nor did they inform subjects about this possibility. Pfuhl et al (2015) did inform their subjects that a change can occur and measured the probabilities but did not ask for when a change occurs. In effect, they measured the response to a change but not whether a subject was aware of a change.…”

Section: Evidence Integration Taskmentioning

confidence: 99%