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Paper: PS-1A.33
Session: Poster Session 1A
Location: H Lichthof
Session Time: Saturday, September 14, 16:30 - 19:30
Presentation Time:Saturday, September 14, 16:30 - 19:30
Presentation: Poster
Publication: 2019 Conference on Cognitive Computational Neuroscience, 13-16 September 2019, Berlin, Germany
Paper Title: Probabilistic reasoning in schizophrenia is volatile but not biased
Manuscript:  Click here to view manuscript
License: Creative Commons License
This work is licensed under a Creative Commons Attribution 3.0 Unported License.
Authors: Gerit Pfuhl, UiT The Arctic University of Norway, Norway; HÃ¥kon Tjelmeland, NTNU, Norway
Abstract: 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 reduced general cognitive abilities, overweighting of recent information, or lower thresholds for switching from one belief to another. A common task to assess belief updating is the 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 controls and 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. More challenging sequences improve the performance of patients. Our model captures well the cognitive mechanisms proposed to contribute to the performance differences in the beads task.