Optimal policy for attention-modulated decisions explains human fixation behavior

  1. Anthony Injoon Jang
  2. Ravi Sharma
  3. Jan Drugowitsch  Is a corresponding author
  1. Harvard Medical School, United States
  2. UC San Diego School of Medicine, United States

Abstract

Traditional accumulation-to-bound decision-making models assume that all choice options are processed with equal attention. In real life decisions, however, humans alternate their visual fixation between individual items to efficiently gather relevant information (Yang et al., 2016). These fixations also causally affect one's choices, biasing them toward the longer-fixated item (Krajbich et al., 2010). We derive a normative decision-making model in which attention enhances the reliability of information, consistent with neurophysiological findings (Cohen and Maunsell, 2009). Furthermore, our model actively controls fixation changes to optimize information gathering. We show that the optimal model reproduces fixation-related choice biases seen in humans and provides a Bayesian computational rationale for this phenomenon. This insight led to additional predictions that we could confirm in human data. Finally, by varying the relative cognitive advantage conferred by attention, we show that decision performance is benefited by a balanced spread of resources between the attended and unattended items.

Data availability

The human behavioral data and code are available through an open source license at https://github.com/DrugowitschLab/Optimal-policy-attention-modulated-decisions

Article and author information

Author details

  1. Anthony Injoon Jang

    Department of Neurobiology, Harvard Medical School, Boston, United States
    Competing interests
    The authors declare that no competing interests exist.
  2. Ravi Sharma

    Department of Family Medicine and Public Health, UC San Diego School of Medicine, San Diego, United States
    Competing interests
    The authors declare that no competing interests exist.
  3. Jan Drugowitsch

    Department of Neurobiology, Harvard Medical School, Boston, United States
    For correspondence
    jan_drugowitsch@hms.harvard.edu
    Competing interests
    The authors declare that no competing interests exist.
    ORCID icon "This ORCID iD identifies the author of this article:" 0000-0002-7846-0408

Funding

National Institute of Mental Health (R01MH115554)

  • Jan Drugowitsch

James S. McDonnell Foundation (220020462)

  • Jan Drugowitsch

The funders had no role in study design, data collection and interpretation, or the decision to submit the work for publication.

Ethics

Human subjects: Human behavioral data were obtained from previously published work from the California Institute of Technology (Krajbich et al., 2010). Caltech's Human Subjects Internal Review Board approved the experiment. Written informed consent was obtained from all participants.

Reviewing Editor

  1. Konstantinos Tsetsos, University Medical Center Hamburg-Eppendorf, Germany

Publication history

  1. Received: September 24, 2020
  2. Accepted: March 17, 2021
  3. Accepted Manuscript published: March 26, 2021 (version 1)
  4. Version of Record published: April 23, 2021 (version 2)

Copyright

© 2021, Jang et al.

This article is distributed under the terms of the Creative Commons Attribution License permitting unrestricted use and redistribution provided that the original author and source are credited.

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  1. Anthony Injoon Jang
  2. Ravi Sharma
  3. Jan Drugowitsch
(2021)
Optimal policy for attention-modulated decisions explains human fixation behavior
eLife 10:e63436.
https://doi.org/10.7554/eLife.63436
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