King's College London

Research portal

Evidence of inverted gravity-driven variation in predictive sensorimotor function

Research output: Contribution to journalArticle

Andrew Isaac Meso, Robert L. De Vai, Ashakee Mahabeer, Peter J. Hills

Original languageEnglish
JournalEuropean Journal of Neuroscience
DOIs
Published13 Aug 2020

King's Authors

Abstract

We move our eyes to place the fovea into the part of a viewed scene currently of interest. Recent evidence suggests that each human has signature patterns of eye movements like handwriting which depend on their sensitivity, allocation of attention and experience. Use of implicit knowledge of how earth's gravity influences object motion has been shown to aid dynamic perception. We used a projected ball-tracking task with a plain background offering no context cues to probe the effect of acquired experience about physical laws of gravitation on performance differences of 44 participants under a simulated gravity and an atypical (upward) antigravity condition. Performance measured by the unsigned difference between instantaneous eye and stimulus positions (RMSE) was consistently worse in the antigravity condition. In the vertical RMSE, participants took about 200 ms longer to improve to the best performance for antigravity compared to gravity trials. The antigravity condition produced a divergence of individual performance which was correlated with levels of questionnaire-based quantified traits of schizotypy but not control traits. Grouping participants by high or low traits revealed a negative relationship between schizotypy trait level and both initiation and maintenance of tracking, a result consistent with trait-related impoverished sensory prediction. The findings confirm for the first time that where cues enabling exact estimation of acceleration are unavailable, knowledge of gravity contributes to dynamic prediction improving motion processing. With acceleration expectations violated, we demonstrate that antigravity tracking could act as a multivariate diagnostic window into predictive brain function.

View graph of relations

© 2018 King's College London | Strand | London WC2R 2LS | England | United Kingdom | Tel +44 (0)20 7836 5454