4.7 Article

Visual predictions, neural oscillations and naive physics

Journal

SCIENTIFIC REPORTS
Volume 11, Issue 1, Pages -

Publisher

NATURE PORTFOLIO
DOI: 10.1038/s41598-021-95295-x

Keywords

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Funding

  1. Australian Research Council [GA68476]

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The human visual system possesses predictive capabilities, with the brain building predictive internal models to adapt to dynamic environments. In a study disrupting people's internal models, it was found that individuals were better at predicting shot outcomes and tracking the ball's position while watching upright videos, with enhanced brain activity in occipital regions. This suggests that accurate predictive models enable individuals to better focus on relevant information and suppress irrelevant stimuli, leading to improved predictive performance and inhibited information processing.
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.

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