Eye movements reveal spatiotemporal dynamics of visually-informed planning in navigation
Abstract
Goal-oriented navigation is widely understood to depend upon internal maps. Although this may be the case in many settings, humans tend to rely on vision in complex, unfamiliar environments. To study the nature of gaze during visually-guided navigation, we tasked humans to navigate to transiently visible goals in virtual mazes of varying levels of difficulty, observing that they took near-optimal trajectories in all arenas. By analyzing participants’ eye movements, we gained insights into how they performed visually-informed planning. The spatial distribution of gaze revealed that environmental complexity mediated a striking tradeoff in the extent to which attention was directed towards two complimentary aspects of the world model: the reward location and task-relevant transitions. The temporal evolution of gaze revealed rapid, sequential prospection of the future path, evocative of neural replay. These findings suggest that the spatiotemporal characteristics of gaze during navigation are significantly shaped by the unique cognitive computations underlying real-world, sequential decision making.
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Links to data and code are included in the manuscript.
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Author details
Funding
National Institutes of Health (U19-NS118246)
- Seren Zhu
- Nastaran Arfaei
- Dora E Angelaki
National Institutes of Health (R01-EY022538)
- Seren Zhu
- Nastaran Arfaei
- Dora E Angelaki
National Science Foundation (DBI-1707398)
- Kaushik Janakiraman Lakshminarasimhan
Gatsby Charitable Foundation
- Kaushik Janakiraman Lakshminarasimhan
The funders had no role in study design, data collection and interpretation, nor the decision to submit the work for publication.
Ethics
Human subjects: All experimental procedures were approved by the Institutional Review Board at New York University and all participants signed an informed consent form (IRB-FY2019-2599).
Copyright
© 2022, Zhu 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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