Abstract

Prediction is a core function of the human visual system. Contemporary research suggests the brain builds predictive internal models of the world to facilitate interactions with our dynamic environment. Here, we wanted to examine the behavioural and neurological consequences of disrupting a core property of peoples’ internal models, using naturalistic stimuli. We had people view videos of basketball and asked them to track the moving ball and predict jump shot outcomes, all while we recorded eye movements and brain activity. To disrupt people’s predictive internal models, we inverted footage on half the trials, so dynamics were inconsistent with how movements should be shaped by gravity. When viewing upright videos people were better at predicting shot outcomes, at tracking the ball position, and they had enhanced alpha-band oscillatory activity in occipital brain regions. The advantage for predicting upright shot outcomes scaled with improvements in ball tracking and occipital alpha-band activity. Occipital alpha-band activity has been linked to selective attention and spatially-mapped inhibitions of visual brain activity. We propose that when people have a more accurate predictive model of the environment, they can more easily parse what is relevant, allowing them to better target irrelevant positions for suppression—resulting in both better predictive performance and in neural markers of inhibited information processing.

Details

Title
Visual predictions, neural oscillations and naïve physics
Author
Saurels, Blake W 1 ; Hohaia Wiremu 1 ; Yarrow Kielan 2 ; Johnston, Alan 3 ; Arnold, Derek H 1 

 The University of Queensland, School of Psychology, Brisbane, Australia (GRID:grid.1003.2) (ISNI:0000 0000 9320 7537) 
 City, University of London, Department of Psychology, London, UK (GRID:grid.28577.3f) (ISNI:0000 0004 1936 8497) 
 University of Nottingham, School of Psychology, Nottingham, UK (GRID:grid.4563.4) (ISNI:0000 0004 1936 8868) 
Publication year
2021
Publication date
2021
Publisher
Nature Publishing Group
e-ISSN
20452322
Source type
Scholarly Journal
Language of publication
English
ProQuest document ID
2559540244
Copyright
© The Author(s) 2021. This work is published under http://creativecommons.org/licenses/by/4.0/ (the “License”). Notwithstanding the ProQuest Terms and Conditions, you may use this content in accordance with the terms of the License.