A mechanistic account of visual discomfort

Olivier Penacchio; Xavier Otazu; Arnold J Wilkins; Sarah M Haigh

doi:10.3389/fnins.2023.1200661

A mechanistic account of visual discomfort

Front Neurosci. 2023 Jul 20:17:1200661. doi: 10.3389/fnins.2023.1200661. eCollection 2023.

Authors

Olivier Penacchio^{1

2

3}, Xavier Otazu^{1

2}, Arnold J Wilkins⁴, Sarah M Haigh^{5

6}

Affiliations

¹ Department of Computer Science, Universitat Autònoma de Barcelona, Bellaterra, Spain.
² Computer Vision Center, Universitat Autònoma de Barcelona, Bellaterra, Spain.
³ School of Psychology and Neuroscience, University of St Andrews, St Andrews, United Kingdom.
⁴ Department of Psychology, University of Essex, Colchester, United Kingdom.
⁵ Department of Psychology, University of Nevada Reno, Reno, NV, United States.
⁶ Institute for Neuroscience, University of Nevada Reno, Reno, NV, United States.

Abstract

Much of the neural machinery of the early visual cortex, from the extraction of local orientations to contextual modulations through lateral interactions, is thought to have developed to provide a sparse encoding of contour in natural scenes, allowing the brain to process efficiently most of the visual scenes we are exposed to. Certain visual stimuli, however, cause visual stress, a set of adverse effects ranging from simple discomfort to migraine attacks, and epileptic seizures in the extreme, all phenomena linked with an excessive metabolic demand. The theory of efficient coding suggests a link between excessive metabolic demand and images that deviate from natural statistics. Yet, the mechanisms linking energy demand and image spatial content in discomfort remain elusive. Here, we used theories of visual coding that link image spatial structure and brain activation to characterize the response to images observers reported as uncomfortable in a biologically based neurodynamic model of the early visual cortex that included excitatory and inhibitory layers to implement contextual influences. We found three clear markers of aversive images: a larger overall activation in the model, a less sparse response, and a more unbalanced distribution of activity across spatial orientations. When the ratio of excitation over inhibition was increased in the model, a phenomenon hypothesised to underlie interindividual differences in susceptibility to visual discomfort, the three markers of discomfort progressively shifted toward values typical of the response to uncomfortable stimuli. Overall, these findings propose a unifying mechanistic explanation for why there are differences between images and between observers, suggesting how visual input and idiosyncratic hyperexcitability give rise to abnormal brain responses that result in visual stress.

Keywords: computational modelling; efficient coding; hypermetabolism; interindividual differences; natural scenes; urban scenes; visual discomfort; visual stress.