Binocularly suppressed stimuli induce brain activities related to aesthetic emotions

Abstract

Introduction: Aesthetic emotions are a class of emotions aroused by evaluating aesthetically appealing objects or events. While evolutionary aesthetics suggests the adaptive roles of these emotions, empirical assessments are lacking. Previous neuroscientific studies have demonstrated that visual stimuli carrying evolutionarily important information induce neural responses even when presented non-consciously. To examine the evolutionary importance of aesthetic emotions, we conducted a neuroscientific study using magnetoencephalography (MEG) to measure induced neural responses to non-consciously presented portrait paintings categorised as biological and non-biological and examined associations between the induced responses and aesthetic ratings.

Methods: MEG and pre-rating data were collected from 23 participants. The pre-rating included visual analogue scales for object saliency, facial saliency, liking, and beauty scores, in addition to 'biologi-ness,' which was used for subcategorising stimuli into biological and non-biological. The stimuli were presented non-consciously using a continuous flash suppression paradigm or consciously using binocular presentation without flashing masks, while dichotomic behavioural responses were obtained (beauty or non-beauty). Time-frequency decomposed MEG data were used for correlation analysis with pre-rating scores for each category.

Results: Behavioural data revealed that saliency scores of non-consciously presented stimuli influenced dichotomic responses (beauty or non-beauty). MEG data showed that non-consciously presented portrait paintings induced spatiotemporally distributed low-frequency brain activities associated with aesthetic ratings, which were distinct between the biological and non-biological categories and conscious and non-conscious conditions.

Conclusion: Aesthetic emotion holds evolutionary significance for humans. Neural pathways are sensitive to visual images that arouse aesthetic emotion in distinct ways for biological and non-biological categories, which are further influenced by consciousness. These differences likely reflect the diversity in mechanisms of aesthetic processing, such as processing fluency, active elaboration, and predictive processing. The aesthetic processing of non-conscious stimuli appears to be characterised by fluency-driven affective processing, while top-down regulatory processes are suppressed. This study provides the first empirical evidence supporting the evolutionary significance of aesthetic processing.

Keywords: aesthetic emotion; continuous flash suppression; magnetoencephalography; neuroaesthetics; vision.

FIGURE 1

(A) Examples of facial stimuli after editing; (left top) the stimulus that scored the highest average ‘biologi-ness’ score (ID#19), (right top) the stimulus that scored the highest average beauty score (ID#06), (left bottom) the stimulus that scored the lowest average ‘biologi-ness’, object and facial saliency, and beauty scores (ID#48), and (right bottom) the stimulus that scored the lowest average liking score (ID#35). (B) A non-magnetic stereoscope, placed on the MEG dewer before starting the MEG experiment. (C) Setup for the MEG experiment showing one of our researchers laying down on the bed (instead of the participant) for the purposes of photographing. (D) Schematic illustration of the CFS task. Participants were presented different stimuli to the dominant and non-dominant eyes through the stereoscope. All trials started from the presentation of the fixations, then diverted according to the condition (FF, MF, and MB). FF, face-face condition; MF, Mondrian-face condition; MB, Mondrian-background condition; VA, visual angle.

FIGURE 2

Results of behavioural data analysis for the biological (left panels) and non-biological (right panels) categories. (A) A violin plot visualising the distribution of each pre-rating score, with the mean value represented by a red line. (B) A spider plot contrasting the mean of each pre-rating score in the FF conditions, in which participants responded as ‘yes’ (red: ‘beauty’) and ‘no’ (blue: ‘non-beauty’) to the Q2 (‘beauty?’ question), respectively. (C) A spider plot contrasting the mean of each pre-rating score in the MF conditions, in which participants responded as ‘yes’ (red: ‘beauty’) and ‘no’ (blue: ‘non-beauty’) to the Q2 (‘beauty?’ question), respectively. An asterisk (*) indicates a significant difference in pre-ratings scores between ‘yes’ (‘beauty’ response) and ‘no’ (‘non-beauty’ response) trials. FF, face-face condition; MF, Mondrian-face condition; BIOL, ‘biologi-ness’ rating; OBJ, object saliency rating; FACE, facial saliency rating; LIKE; liking rating; BEAU, beauty rating.

FIGURE 3

ROI time-series averaged within trials of the (A) FF-biological, (B) MF-biological, (C) FF-non-biological, (D) MF-non-biological, and (E) MB conditions. The top plot in each panel visualises the butterfly plot, where each line represents each of the 68 ROIs. The bottom plot in each panel visualises the root-mean-square (RMS) waveform, where the signals were averaged across all (black line) or occipital (red line) ROIs. All waveforms were corrected for baseline (–100 to 0 ms). FF, face-face condition; MF, Mondrian-face condition; MB, Mondrian-background condition.

FIGURE 4

Results of the cluster-based permutation tests between the FF vs. MF conditions for the (A) biological and (B) non-biological categories. All TF images are scaled equally, with significant clusters emphasised using black bold lines. The regions (ROIs) in the template brain images were coloured red when any positive clusters were found in the ROI or blue when any negative clusters were found in the ROI. The results for hγ band are not displayed, because no significant clusters were found in the band. FF, face-face condition; MF, Mondrian-face condition; LH, left hemisphere; RH, right hemisphere; lγ, low-gamma; hγ, high-gamma.

FIGURE 5

Results of the cluster-based permutation tests for evaluating correlations between regional TF data and pre-rating scores [(A,E) object saliency, (B,F) facial saliency, (C,G) liking, and (D,H) beauty] in each condition [(A–D) FF-biological and (E–H) MF-biological] in the biological category. All TF images are scaled equally, with significant clusters emphasised using black bold lines. The regions (ROIs) in the template brain images were coloured red when any positive clusters were found in the ROI or blue when any negative clusters were found in the ROI. The results for hγ band are not displayed, because no significant clusters were found in the band. FF, face-face condition; MF, Mondrian-face condition; LH, left hemisphere; RH, right hemisphere; lγ, low-gamma; hγ, high-gamma.

FIGURE 6

Results of the cluster-based permutation tests for evaluating correlations between regional TF data and pre-rating scores [(A,E) object saliency, (B,F) facial saliency, (C,G) liking, and (D,H) beauty] in each condition [(A–D) FF-non-biological and (E–H) MF-non-biological] in the non-biological category. All TF images are scaled equally, with significant clusters emphasised using black bold lines. The regions (ROIs) in the template brain images were coloured red when any positive clusters were found in the ROI or blue when any negative clusters were found in the ROI. The results for hγ band are not displayed, because no significant clusters were found in the band. FF, face-face condition; MF, Mondrian-face condition; LH, left hemisphere; RH, right hemisphere; lγ, low-gamma; hγ, high-gamma.