Idiosyncratic tendency to choose one alternative over others in the absence of an identified reason is a common observation in two-alternative forced-choice experiments. Here we quantify idiosyncratic choice biases in a perceptual discrimination task and a motor task. We report substantial and significant biases in both cases that cannot be accounted for by the experimental context. Then, we present theoretical evidence that even in an idealized experiment, in which the settings are symmetric, idiosyncratic choice bias is expected to emerge from the dynamics of competing neuronal networks. We thus argue that idiosyncratic choice bias reflects the microscopic dynamics of choice and therefore is virtually inevitable in any comparison or decision task.
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The datasets generated and analyzed during the current study are available from the corresponding author and in the ICB repository, https://github.com/Lior-Lebovich/ICB.
The custom codes used for simulations and analyses are in the ICB repository, https://github.com/Lior-Lebovich/ICB.
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We thank T. Boraud, G. Mongillo, H. Sompolinsky and T. Tron for discussions and L. Kaplan for assistance with the online experiments. This work was conducted within the scope of the France-Israel Laboratory of Neuroscience. D. H. thanks the Department of Neurobiology at the Hebrew University for its warm hospitality. This work was supported by the Israel Science Foundation (Y. LO., Grant No. 757/16), the DFG (CRC 1080 to Y. LO.), the Gatsby Charitable Foundation (Y. LO.), ANR-09-SYSC-002-01 (D. H.) and the France-Israel High Council for Science and Technology (D. H. and Y. LO.). The funders had no role in study design, data collection and analysis, decision to publish or preparation of the manuscript.
The authors declare no competing interests.
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Lebovich, L., Darshan, R., Lavi, Y. et al. Idiosyncratic choice bias naturally emerges from intrinsic stochasticity in neuronal dynamics. Nat Hum Behav 3, 1190–1202 (2019). https://doi.org/10.1038/s41562-019-0682-7
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