Abstract
Saccadic eye movements shift the fovea between objects of interest to build a visual percept. In humans, saccades are predominantly executed along the cardinal axes, particularly in the horizontal direction. It is unknown how this horizontal saccade bias could arise mechanistically, though previous work suggests contributions from neural, image-based, and ocular motor factors. Here we used two publicly available eye movement datasets to first investigate which image features–spatial frequency, saliency, and structural content–relate to the horizontal saccade bias. Among the three image features, we found that orientation anisotropies in saliency content best predicted the strength of the horizontal saccade bias. Based on this result, we next implemented a saccade target selection model combining allocentric biases aligned with image orientation and egocentric biases aligned with eye or head orientation, independent of image content. As in prior work, this combination successfully replicated human saccade distributions during free viewing of upright images. When applied to tilted images, the model produced effects of image tilt and saccade size that were correlated with prior empirical findings, though with reduced amplitude, suggesting that current saliency models do not fully capture image effects. Taken together, these results suggest that saccade generation reflects both the allocentric biases present in the structure of natural scenes and the egocentric biases present in the saccade generation system itself. An open question is why the egocentric saccade bias exists, but our results suggest that it is adaptive in response to regularities in the world and our typical upright orientation.
Similar content being viewed by others
References
Tatler, B. W. & Vincent, B. T. The prominence of behavioural biases in eye guidance. Vis. Cogn. 17, 1029–1054 (2009).
Foulsham, T., Kingstone, A. & Underwood, G. Turning the world around: patterns in saccade direction vary with picture orientation. Vis. Res. 48, 1777–1790 (2008).
Otero-Millan, J., Macknik, S. L., Langston, R. E. & Martinez-Conde S. An oculomotor continuum from exploration to fixation. Proc. Natl. Acad. Sci. 110, 6175–6180 (2013).
Bischof, W. F., Anderson, N. C., Doswell, M. T. & Kingstone, A. Visual exploration of omnidirectional panoramic scenes. J. Vis. 20, 23 (2020).
Anderson, N. C., Bischof, W. F., Foulsham, T. & Kingstone, A. Turning the (virtual) world around: patterns in saccade direction vary with picture orientation and shape in virtual reality. J. Vis. 20, 21 (2020).
Lee, S. P. & Badler, J. B. & Badler, N. I. Eyes alive. in ACM Transactions on Graphics (TOG) vol. 21 637–644 (ACM, (2002).
Bays, P. M. & Husain, M. Active Inhibition and memory promote exploration and search of natural scenes. J. Vis. 12, 8–8 (2012).
Gilchrist, I. D. & Harvey, M. Evidence for a systematic component within scan paths in visual search. Vis. Cogn. 14, 704–715 (2006).
Najemnik, J. & Geisler, W. S. Optimal eye movement strategies in visual search. Nature 434, 387–391 (2005).
Burlingham, C. S., Sendhilnathan, N., Komogortsev, O., Murdison, T. S. & Proulx, M. J. Motor laziness constrains fixation selection in real-world tasks. Proc. Natl. Acad. Sci. 121, e2302239121 (2024).
Reeves, S. M. & Otero-Millan, J. The influence of scene Tilt on saccade directions is amplitude dependent. J. Neurol. Sci. 448, 120635 (2023).
Liang, J. R. et al. Scaling of horizontal and vertical fixational eye movements. Phys Rev. E 71, 85 (2005).
Bowers, N. R., Gautier, J., Lin, S. & Roorda, A. Fixational eye movements in passive versus active sustained fixation tasks. J. Vis. 21, 16 (2021).
Lee, Y. T. et al. Disrupted microsaccade responses in late-life depression. Sci. Rep. 15, 2827 (2025).
Van Renswoude, D. R., Johnson, S. P., Raijmakers, M. E. J. & Visser, I. Do infants have the horizontal bias? Infant Behav. Dev. 44, 38–48 (2016).
Abed, F. Cultural influences on visual scanning patterns. J. Cross-Cult Psychol. 22, 525–534 (1991).
Koevoet, D. et al. Effort Drives Saccade Selection eLife 13, 50 (2025).
Coppola, D. M., Purves, H. R., McCoy, A. N. & Purves, D. The distribution of oriented contours in the real world. Proc. Natl. Acad. Sci. 95, 4002–4006 (1998).
Switkes, E., Mayer, M. J. & Sloan, J. A. Spatial frequency analysis of the visual environment: anisotropy and the carpentered environment hypothesis. Vis. Res. 18, 1393–1399 (1978).
van der Schaaf, A. & van Hateren, J. H. Modelling the power spectra of natural images: statistics and information. Vis. Res. 36, 2759–2770 (1996).
Girshick, A. R., Landy, M. S. & Simoncelli, E. P. Cardinal rules: visual orientation perception reflects knowledge of environmental statistics. Nat. Neurosci. 14, 926–932 (2011).
Howard, I. P. Human Visual Orientation (J. Wiley, 1982).
Bonds, A. B. An oblique effect in the visual evoked potential of the Cat. Exp. Brain Res. 46, 151–154 (1982).
Raman, R. & Sarkar, S. Significance of natural scene statistics in Understanding the anisotropies of perceptual Filling-in at the blind spot. Sci. Rep. 7, 3586 (2017).
Araragi, Y. & Nakamizo, S. Anisotropy of tolerance of perceptual completion at the blind spot. Vis. Res. 48, 618–625 (2008).
Mitchell, D. E., Freeman, R. D. & Westheimer, G. Effect of orientation on the modulation sensitivity for interference fringes on the Retina*. J. Opt. Soc. Am. 57, 246 (1967).
Harrison, W. J., Bays, P. M. & Rideaux, R. Neural tuning instantiates prior expectations in the human visual system. Nat. Commun. 14, 5320 (2023).
Keil, M. S. & Cristóbal, G. Separating the chaff from the wheat: possible origins of the oblique effect. J. Opt. Soc. Am. A. 17, 697 (2000).
Li, B., Peterson, M. R. & Freeman, R. D. Oblique effect: A neural basis in the visual cortex. J. Neurophysiol. 90, 204–217 (2003).
Dragoi, V., Turcu, C. M. & Sur, M. Stability of cortical responses and the statistics of natural scenes. Neuron 32, 1181–1192 (2001).
Barbot, A., Xue, S. & Carrasco, M. Asymmetries in visual acuity around the visual field. J. Vis. 21, 2 (2021).
Himmelberg, M. M., Winawer, J. & Carrasco, M. Polar angle asymmetries in visual perception and neural architecture. Trends Neurosci. 46, 445–458 (2023).
Simoncelli, E. P. & Olshausen, B. A. Natural image statistics and neural representation. Annu. Rev. Neurosci. 24, 1193–1216 (2001).
Field, D. J. Relations between the statistics of natural images and the response properties of cortical cells. J. Opt. Soc. Am. A. 4, 2379 (1987).
Reeves, S. M., Cooper, E. A., Rodriguez, R. & Otero-Millan, J. Head Orientation Influences Saccade Directions during Free Viewing. eneuro 9, ENEURO.0273-22.2022 (2022).
Bovik, A., Cormack, L., Van Der Linde, I. & Rajashekar, U. DOVES: a database of visual eye movements. Spat. Vis. 22, 161–177 (2009).
Sadeghi, R., Ressmeyer, R., Yates, J. & Otero-Millan, J. Open Iris - An Open Source Framework for Video-Based Eye-Tracking Research and Development. in Proceedings of the 2024 Symposium on Eye Tracking Research and Applications 1–7ACM, Glasgow United Kingdom, (2024). https://doi.org/10.1145/3649902.3653348
Engbert, R. & Kliegl, R. Microsaccades uncover the orientation of Covert attention. Vis. Res. 43, 1035–1045 (2003).
Linardos, A., Kümmerer, M., Press, O., Bethge, M. & DeepGaze, I. I. E. Calibrated prediction in and out-of-domain for state-of-the-art saliency modeling. Preprint at (2021). http://arxiv.org/abs/2105.12441
Le Meur, O. & Liu, Z. Saccadic model of eye movements for free-viewing condition. Vis. Res. 116, 152–164 (2015).
Kümmerer, M., Bethge, M., Wallis, T. S. A. & DeepGaze, I. I. I. Modeling free-viewing human scanpaths with deep learning. J. Vis. 22, 7 (2022).
Sun, W., Chen, Z. & Wu, F. Visual scanpath prediction using IOR-ROI recurrent mixture density network. IEEE Trans. Pattern Anal. Mach. Intell. 43, 2101–2118 (2021).
Saez, D. Correcting Image Orientation Using Convolutional Neural Networks. (2017). https://d4nst.github.io/2017/01/12/image-orientation/
Chong, I. G. & Jun, C. H. Performance of some variable selection methods when multicollinearity is present. Chemom Intell. Lab. Syst. 78, 103–112 (2005).
Alberts, B. B. G. T., de Brouwer, A. J., Selen, L. P. J. & Medendorp, W. P. A Bayesian Account of Visuo-Vestibular Interactions in the Rod-and-Frame Task. eneuro ENEURO.0093-16.2016 (2016). https://doi.org/10.1523/ENEURO.0093-16.2016
Pansell, T., Sverkersten, U. & Ygge, J. Visual Spatial clues enhance ocular torsion response during visual Tilt. Exp. Brain Res. 175, 567–574 (2006).
Linka, M., Karimpur, H. & de Haas, B. Protracted development of gaze behaviour. Nat. Hum. Behav. 1–11. https://doi.org/10.1038/s41562-025-02191-9 (2025).
Costela, F. M. et al. Characteristics of spontaneous Square-Wave jerks in the healthy macaque monkey during visual fixation. PLoS ONE. 10, e0126485 (2015).
Snodderly, D. M. Effects of light and dark environments on macaque and human fixational eye movements. Vis. Res. 27, 401–415 (1987).
Willett, S. M. & Mayo, J. P. Microsaccades are directed toward the midpoint between targets in a variably cued attention task. Proc. Natl. Acad. Sci. 120, e2220552120 (2023).
Kobayashi, H. & Kohshima, S. Unique morphology of the human eye and its adaptive meaning: comparative studies on external morphology of the primate eye. J. Hum. Evol. 40, 419–435 (2001).
Robinson, D. A. Eye movements evoked by collicular stimulation in the alert monkey. Vis. Res. 12, 1795–1808 (1972).
Wang, L., Liu, M., Segraves, M. A. & Cang, J. Visual experience is required for the development of eye movement maps in the mouse superior colliculus. J. Neurosci. 35, 12281–12286 (2015).
Lowe, K. A., Zinke, W., Cosman, J. D. & Schall, J. D. Frontal eye fields in macaque monkeys: prefrontal and premotor contributions to visually guided saccades. Cereb. Cortex. 32, 5083–5107 (2022).
Poletti, M., Intoy, J. & Rucci, M. Accuracy and precision of small saccades. Sci. Rep. 10, 16097 (2020).
Pitzalis, S. & Di Russo, F. Spatial anisotropy of saccadic latency in normal subjects and Brain-Damaged patients. Cortex 37, 475–492 (2001).
Jensen, K., Beylergil, S. B. & Shaikh, A. G. Slow saccades in cerebellar disease. Cerebellum Ataxias. 6, 1 (2019).
Ohl, S., Kroell, L. M. & Rolfs, M. Saccadic selection in visual working memory is robust across the visual field and linked to saccade metrics: evidence from nine experiments and more than 100,000 trials. J. Exp. Psychol. Gen. 153, 544–563 (2024).
Acknowledgements
Funding for this work was provided by the National Eye Institute Award R00EY027846, the National Institutes of Health Training Grant 5T32EY007043-43, and the UC Berkeley Center for the Innovation in Vision and Optics (CIVO). The authors would like to thank Emily A Cooper for her comments.
Funding
for this work was provided by the National Eye Institute Award R00EY027846, the National Institutes of Health Training Grant 5T32EY007043-43, and the UC Berkeley Center for the Innovation in Vision and Optics (CIVO). The authors would like to thank Emily A Cooper for her comments.
Author information
Authors and Affiliations
Contributions
SMR and JOM designed the research, SMR conducted the data analysis, SMR and JOM directed and reviewed analysis, SMR and JOM wrote and reviewed the manuscript.
Corresponding author
Ethics declarations
Competing interests
The authors declare no competing interests.
Additional information
Publisher’s note
Springer Nature remains neutral with regard to jurisdictional claims in published maps and institutional affiliations.
Supplementary Information
Below is the link to the electronic supplementary material.
Rights and permissions
Open Access This article is licensed under a Creative Commons Attribution 4.0 International License, which permits use, sharing, adaptation, distribution and reproduction in any medium or format, as long as you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons licence, and indicate if changes were made. The images or other third party material in this article are included in the article’s Creative Commons licence, unless indicated otherwise in a credit line to the material. If material is not included in the article’s Creative Commons licence and your intended use is not permitted by statutory regulation or exceeds the permitted use, you will need to obtain permission directly from the copyright holder. To view a copy of this licence, visit http://creativecommons.org/licenses/by/4.0/.
About this article
Cite this article
Reeves, S.M., Otero-Millan, J. Horizontal saccade bias results from combination of saliency anisotropies and egocentric biases. Sci Rep (2026). https://doi.org/10.1038/s41598-026-35572-9
Received:
Accepted:
Published:
DOI: https://doi.org/10.1038/s41598-026-35572-9
