City Research Online

Gain control of saccadic eye movements is probabilistic

Lisi, M., Solomon, J. A. ORCID: 0000-0001-9976-4788 & Morgan, M. J. (2019). Gain control of saccadic eye movements is probabilistic. Proceedings of the National Academy of Sciences, 116(32), pp. 16137-16142. doi: 10.1073/pnas.1901963116


Saccades are rapid eye movements that orient the visual axis toward objects of interest to allow their processing by the central, highacuity retina. Our ability to collect visual information efficiently relies on saccadic accuracy, which is limited by a combination of uncertainty in the location of the target and motor noise. It has been observed that saccades have a systematic tendency to fall short of their intended targets, and it has been suggested that this bias originates from a cost function that overly penalizes hypermetric errors. Here we tested this hypothesis by systematically manipulating the positional uncertainty of saccadic targets. We found that increasing uncertainty produced not only a larger spread of the saccadic endpoints but also more hypometric errors and a systematic bias toward the average of target locations in a given block, revealing that prior knowledge was integrated into saccadic planning. Moreover, by examining how variability and bias co-varied across conditions, we estimated the asymmetry of the cost function and found that it was related to individual differences in the additional time needed to program secondary saccades for correcting hypermetric errors, relative to hypometric ones. Taken together, these findings reveal that the saccadic system uses a probabilistic-Bayesian control strategy to compensate for uncertainty in a statistically principled way and to minimize the expected cost of saccadic errors.

Publication Type: Article
Publisher Keywords: Motor control, cost function, eye moevements, saccades
Subjects: R Medicine > RE Ophthalmology
Departments: School of Health & Psychological Sciences > Optometry & Visual Sciences
SWORD Depositor:
[thumbnail of LisiEtAlPNASms.pdf]
Text - Published Version
Available under License Creative Commons Attribution Non-commercial No Derivatives.

Download (3MB) | Preview


Add to AnyAdd to TwitterAdd to FacebookAdd to LinkedinAdd to PinterestAdd to Email


Downloads per month over past year

View more statistics

Actions (login required)

Admin Login Admin Login