Temporal dynamics of neural activity in an integration of visual and contextual information in an esthetic preference task

While viewing works of art in galleries, we evaluate them by integrating at least two types of information: their visual properties (e.g., colors, symmetry, and proportion) and contextual information accompanying them (e.g., titles and names of artists). How rapidly the brain integrates visual and contextual information of artworks remains to be investigated. Using electroencephalography (EEG), we investigated neural activity when subjects with no professional experience in art viewed images of sculptures (masterpieces from the Classical and Renaissance periods, characterized by a canonical proportion of the golden ratio) and performed a five-scale rating of how appealing they were. At the beginning of each trial, we manipulated the expectations of the subjects for an upcoming sculpture by presenting information about its authenticity (either “genuine” or “fake”), although all images were actually taken from genuine artworks. The image of the sculpture was then presented, either in its original proportion or after being deformed by a photo-editing software. This 2 × 2 factorial design enabled us to identify whether each component of the EEG response was sensitive to contextual information (genuine or fake), visual information (original or deformed), or both. Results revealed that amplitudes of a positive EEG component emerging at 200–300 ms after the presentation of the artworks (mainly distributed over the parietal cortex) were significantly modulated by both visual and contextual factors, indicating a rapid integration of these two types of information in the brain.

► We evaluate an artwork based on its shape, color, or proportion etc. (bottom-up cue).
► Another cue is contextual information accompanying that work (e.g. name of artist).
► When the brain integrates those bottom-up and contextual cues remains unknown.
► Our EEG results showed a rapid integration of those cues in an initial 300 ms.