A central challenge in cognitive science is to distinguish between multiple processes that can result in similar behaviors. In reinforcement learning, one prominent example concerns two potential drivers of choice repetition: a learning asymmetry, in which agents learn differently from outcomes depending on their valence and/or whether they confirm choice, and choice perseveration, an outcome-independent tendency to repeat past choices. Evidence for asymmetric learning has typically relied on computational models that control for perseveration, or specific behavioral markers.
Here, we show both these approaches have critical flaws and can spuriously detect learning asymmetries even in perseverative, symmetric-learning agents. To address this, we introduce a statistical test that distinguishes genuine learning asymmetries from spurious effects. Applying this test to a large dataset spanning ten published experiments across four studies, we find that some previously reported confirmation biases are fragile, albeit others remain robust even at an across-study level.
Finally, we propose a task design that can yield a more valid qualitative signature of confirmation bias. Our approach provides a reliable framework for disentangling processes underlying choice repetition, while providing tools for the wider research community that can minimize potential spurious effects arising from process mimicry and biased parameter estimation. J.V.P. is a pre-doctoral fellow of the International Max Planck Research School on Computational Methods in Psychiatry and Ageing Research (IMPRS COMP2PSYCH).
J.V.P. discloses support for the research of this work from the Max Planck research school (grant code: IMPRS COMP2PSYCH). R.J.D. discloses support for the research of this work from the Max Planck Society. R.M. declares no relevant funding.
Max Planck Centre for Computational Psychiatry and Ageing, University College London, Russell Square House, London, England Juan Vidal-Perez, Raymond J. Dolan & Rani Moran Wellcome Centre for Human Neuroimaging, University College London, London, England Department of Psychology, School of Biological and Behavioural Sciences, Queen Mary University of London, London, United Kingdom Correspondence to Juan Vidal-Perez or Rani Moran. The authors declare no competing interests.
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