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Regulation of evidence accumulation by pupil-linked arousal processes

Abstract

Effective decision-making requires integrating evidence over time. For simple perceptual decisions, previous work suggests that humans and animals can integrate evidence over time, but not optimally. This suboptimality could arise from sources including neuronal noise, weighting evidence unequally over time (that is, the ‘integration kernel’), previous trial effects and an overall bias. Here, using an auditory evidence accumulation task in humans, we report that people exhibit all four suboptimalities, some of which covary across the population. Pupillometry shows that only noise and the integration kernel are related to the change in pupil response. Moreover, these two different suboptimalities were related to different aspects of the pupil signal, with the individual differences in pupil response associated with individual differences in the integration kernel, while trial-by-trial fluctuations in pupil response were associated with trial-by-trial fluctuations in noise. These results suggest that different suboptimalities relate to distinct pupil-linked processes, possibly related to tonic and phasic norepinephrine activity.

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Fig. 1: Basic behaviour of 108 participants.
Fig. 2: Regression model.
Fig. 3: Interaction between suboptimalities across participants.
Fig. 4: Interaction between pupil change and integration behaviour across participants.
Fig. 5: Trial-by-trial interaction between pupil change and integration behaviour.
Fig. 6: Bounded DDM fits and pupil change.

Code availability

Experiment code was created with Psychtoolbox-3 and custom MATLAB code. All behavioural and pupil analyses were created with custom MATLAB and R code. All code can be found at https://github.com/janekeung129/clicks-pupil. Code for fitting the DDM with sticky bound1,41 is provided at http://github.com/misun6312/PBupsModel.jl.

Data availability

The datasets generated and analysed during the current study are available from the corresponding author upon reasonable request.

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Acknowledgements

The authors received no specific funding for this work. We thank M. Alberhasky, C. Andrade, D. Carrera, K. Chung, M. de Leon, Z. Dzhalilova, A. Esprit, A. Foley, E. Giron, B. Gonzalez, A. Haddad, L. Hall, M. Higgs, M. Jacobs, M.-H. Kang, K. Kellohen, N. Kwatra, H. Kyllo, A. Lawwill, S. Low, C. Lynch, A. Ornelas, G. Patterson, F. Santos, S. Savita, C. Sikora, V. Thornton, G. Vargas, C. West and C. Wong for help with running the experiments. The funders had no role in study design, data collection and analysis, decision to publish or preparation of the manuscript.

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W.K. analysed the data. T.H. collected and preprocessed the data. T.A.H. and R.C.W. designed the experiment. W.K. and R.C.W. wrote the manuscript. All three authors contributed to interpretation of the results and critical discussion.

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Correspondence to Waitsang Keung.

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Supplementary Notes 1–5, Supplementary Figures 1–15, and Supplementary References.

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Supplementary Software

Description: Custom code that implements the major analyses described in the paper

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Keung, W., Hagen, T.A. & Wilson, R.C. Regulation of evidence accumulation by pupil-linked arousal processes. Nat Hum Behav 3, 636–645 (2019). https://doi.org/10.1038/s41562-019-0551-4

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