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Distinct detection and discrimination sensitivities in visual processing of real versus unreal optic flow

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Abstract

We examined the intricate mechanisms underlying visual processing of complex motion stimuli by measuring the detection sensitivity to contraction and expansion patterns and the discrimination sensitivity to the location of the center of motion (CoM) in various real and unreal optic flow stimuli. We conducted two experiments (N = 20 each) and compared responses to both "real" optic flow stimuli containing information about self-movement in a three-dimensional scene and "unreal" optic flow stimuli lacking such information. We found that detection sensitivity to contraction surpassed that to expansion patterns for unreal optic flow stimuli, whereas this trend was reversed for real optic flow stimuli. Furthermore, while discrimination sensitivity to the CoM location was not affected by stimulus duration for unreal optic flow stimuli, it showed a significant improvement when stimulus duration increased from 100 to 400 ms for real optic flow stimuli. These findings provide compelling evidence that the visual system employs distinct processing approaches for real versus unreal optic flow even when they are perfectly matched for two-dimensional global features and local motion signals. These differences reveal influences of self-movement in natural environments, enabling the visual system to uniquely process stimuli with significant survival implications.

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Data transparency and code availability

The original study materials, anonymized primary and processed research data, and original analysis scripts of this study are available via the Open Science Framework at: https://osf.io/jcnh2/?view_only=ee71af5d05dc4357abcc35265b1a3169

Notes

  1. Also known as focus of expansion (FoE) for forward translational self-movement.

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Acknowledgements

We thank Zhoukuidong Shan for his assistance with programming and Lee Stone for his helpful comments on a previous draft of the paper. We also thank two anonymous reviewers for their helpful comments, which have significantly improved the quality and clarity of our paper.

Funding

This study was supported by research grants from the National Natural Science Foundation of China (32161133009, 32071041), Shanghai Science and Technology Committee (20ZR1439500, 19JC1410101), China Ministry of Education (ECNU 111 Project, Base B1601), and NYU Shanghai (the major grant seed fund and the boost fund).

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Authors and Affiliations

  1. Shanghai Frontiers Science Center of Artificial Intelligence and Deep Learning, Division of Arts and Sciences, NYU, New York University Shanghai, Shanghai, China

    Li Li

  2. NYU-ECNU Institute of Brain and Cognitive Science, New York University Shanghai, Shanghai, China

    Li Li, Xuechun Shen & Shuguang Kuai

  3. Shanghai Key Laboratory of Brain Functional Genomics, School of Psychology and Cognitive Science, East China Normal University, Shanghai, China

    Li Li, Xuechun Shen & Shuguang Kuai

  4. ECNU-NYU Joint Research Center of Brain Imaging, East China Normal University, Shanghai, China

    Li Li, Xuechun Shen & Shuguang Kuai

  5. Faculty of Arts and Science, New York University Shanghai, Shanghai, China

    Li Li

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  1. Li Li
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  2. Xuechun Shen
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  3. Shuguang Kuai
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Contributions

LL and SK conceptualized the experiments. LL designed the experiments. XS ran the experiments. XS and LL analyzed the data. LL and XS wrote the first draft and revised the paper. We declare no competing financial interests.

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Correspondence to Li Li.

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This research complies with the Declaration of Helsinki (2023), aside from the requirement to preregister human subjects research, and received approval from the Institutional Review Board at New York University Shanghai (ID: 0062016).

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We obtained written informed consent from all participants before the commencement of each experiment in this study. The consent form was approved by the Institutional Review Board at New York University Shanghai.

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Li, L., Shen, X. & Kuai, S. Distinct detection and discrimination sensitivities in visual processing of real versus unreal optic flow. Psychon Bull Rev 32, 1540–1550 (2025). https://doi.org/10.3758/s13423-024-02616-y

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