Steady-state visual evoked potential responses predict visual discomfort judgements

Eur J Neurosci. 2021 Nov;54(10):7575-7598. doi: 10.1111/ejn.15492. Epub 2021 Nov 9.

Abstract

It has been suggested that aesthetically pleasing stimuli are processed efficiently by the visual system, whereas uncomfortable stimuli are processed inefficiently. This study consists of a series of three experiments investigating this idea using a range of images of abstract artworks, photographs of natural scenes, and computer-generated stimuli previously shown to be uncomfortable. Subjective judgements and neural correlates were measured using electroencephalogram (EEG) (steady-state visual evoked potentials, SSVEPs). In addition, global image statistics (contrast, Fourier amplitude spectral slope and fractal dimension) were taken into account. When effects of physical image contrast were controlled, fractal dimension predicted discomfort judgements, suggesting the SSVEP response is more likely to be influenced by distribution of edges than the spectral slope. Importantly, when effects of physical contrast and fractal dimension were accounted for using linear mixed effects modelling, SSVEP responses predicted subjective judgements of images. Specifically, when stimuli were not matched for perceived contrast, there was a positive relationship between SSVEP responses and how pleasing a stimulus was judged to be, and conversely a negative relationship between discomfort and SSVEP response. This is significant as it shows that the neural responses in early visual areas contribute to the subjective (un)pleasantness of images, although the results of this study do not provide clear support for the theory of efficient coding as the cause of perceived pleasantness or discomfort of images, and so other explanations need to be considered.

Keywords: EEG; artworks; fractal dimension; natural images; spectral slope.

MeSH terms

  • Electroencephalography*
  • Evoked Potentials, Visual*
  • Neurologic Examination
  • Photic Stimulation

Associated data

  • figshare/10.6084/m9.figshare.9285065