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Evidence integration and decision confidence are modulated by stimulus consistency

Nature Human Behaviour volume 6, pages 988–999 (2022)Cite this article

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Abstract

Evidence integration is a normative algorithm for choosing between alternatives with noisy evidence, which has been successful in accounting for vast amounts of behavioural and neural data. However, this mechanism has been challenged by non-integration heuristics, and tracking decision boundaries has proven elusive. Here we first show that the decision boundaries can be extracted using a model-free behavioural method termed decision classification boundary, which optimizes choice classification based on the accumulated evidence. Using this method, we provide direct support for evidence integration over non-integration heuristics, show that the decision boundaries collapse across time and identify an integration bias whereby incoming evidence is modulated based on its consistency with preceding information. This consistency bias, which is a form of pre-decision confirmation bias, was supported in four cross-domain experiments, showing that choice accuracy and decision confidence are modulated by stimulus consistency. Strikingly, despite its seeming sub-optimality, the consistency bias fosters performance by enhancing robustness to integration noise.

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Fig. 1: Experimental paradigms and behavioural signature of integration to boundary.
Fig. 2: Model-free extraction of the decision boundaries.
Fig. 3: Results of experiments 1 and 2.
Fig. 4: Experimental paradigms in experiments 3 and 4.
Fig. 5: Results of experiments 3 and 4.
Fig. 6: Stimulus consistency and normativity.

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Data availability

The data that support the findings of this paper are available at https://osf.io/vywbx/.

Code availability

The codes used for all studies are available at https://osf.io/vywbx/.

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Acknowledgements

This research was supported by a grant to Marius Usher from the Israel Science Foundation (grant no. 1413/17). R.M. is a member of the Max Planck Centre for Computational Psychiatry and Ageing research at UCL, which is funded by the Max Planck Society, Munich, Germany (https://www.mpg.de/en, grant no. 647070403019). The funders had no role in study design, data collection and analysis, decision to publish or preparation of the manuscript. We thank T. Sharot, B. Blain, I. Cogliati Dezza, L. Globig, C. Kelly, V. Vellani, S. Zheng, D. Lee and N. Nachman for critical reading of the manuscript and helpful comments.

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Author notes

  1. These authors jointly supervised this work: Rani Moran, Marius Usher.

Authors and Affiliations

  1. Department of Experimental Psychology, University College London, London, UK

    Moshe Glickman

  2. Max Planck UCL Centre for Computational Psychiatry and Ageing Research, University College London, London, UK

    Moshe Glickman & Rani Moran

  3. Wellcome Centre for Human Neuroimaging, University College London, London, UK

    Rani Moran

  4. School of Psychology, University of Tel Aviv, Tel Aviv, Israel

    Marius Usher

  5. Sagol School of Neuroscience, University of Tel Aviv, Tel Aviv, Israel

    Marius Usher

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  1. Moshe Glickman
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  2. Rani Moran
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  3. Marius Usher
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Contributions

M.G. and M.U. developed the study concept. M.G., R.M. and M.U. designed the experiments. M.G. and R.M. performed the experiments. M.G. analysed the data and carried out the computational modelling. M.G., R.M. and M.U. wrote the paper and contributed to data discussion and interpretation at all stages.

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Correspondence to Moshe Glickman or Marius Usher.

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Nature Human Behaviour thanks Birte Forstmann, Redmond O’Connell and the other, anonymous, reviewer(s) for their contribution to the peer review of this work. Peer reviewer reports are available.

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Glickman, M., Moran, R. & Usher, M. Evidence integration and decision confidence are modulated by stimulus consistency. Nat Hum Behav 6, 988–999 (2022). https://doi.org/10.1038/s41562-022-01318-6

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