Distorted facial perception of the partner
Description
The present research studies the emotional and electrophysiological response of a person to seeing a distorted image of his or her partner's face in order to measure the impact of physical appearance on interpersonal relationships. Studying the effect of physical appearance on interpersonal relationships is of great relevance to identify projection biases that may act as a mechanism of attraction to a partner and how attraction may be diminished by physical changes (aging, body changes, etc.) [5]. Although it is often argued that there are other more important aspects such as personality, values and affinity to maintain a relationship, some previous evidence reveals that there must be a minimum of physical attraction [12]. Assessing the effect of distorted facial perception of the partner can help to analyze how projection biases affect the emotional response and physical attraction that people feel with their partners. For this work, 15 participants with partners between the ages of 20 and 30 were recruited. They were asked for 10 facial photos of their partners. The images were edited in terms of age distortions, facial enlargement, deformity (ugly), low quality with motion effect and sadness effect. Once the facial distortions were applied, each participant was randomly shown a total of 30 photos (one undistorted by two distorted faces) for 3 seconds each photo. After each photo, an emotional test was applied to assess the level of liking based on the 4-point hedonistic scale (dislike, indifference, liking and enjoyment). The database contains the raw and preprocessed recorded data, volunteer information such as age and gender, subjective evaluation, information on the channels used. The results show that there is an increase in the amplitude of the P300 wave which shows that people present a different emotional reaction between normal and distorted photos due to the projection and facial adaptation biases they have towards their partner.
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The data was collected using a Unicorn Hybrid Black Brain Interface with 8 DC-coupled analog input channels of 24 Bit resolution. The electrode placement montage was following the 10-20 International System. The EEG signals have been acquired from Fz, C3, Cz, C4, Pz, PO7, Oz and PO8 electrodes as shown in the electrode_configuration image, respectively. The brain interface has two reference electrodes that were fitted on the right and left mastoid bones of the subject. The frequency sampling rate was 250 Hz per channel and the bandwidth acquired was from 0 to 125 Hz. The environment conditions for the signal acquisition was an indoor closed room with lights off and low ambient noise level. The visual stimuli was presented on a computer monitor. The subjects were advised to not blink their eyes before and during the visual stimulus to prevent noise. The resultant raw files recorded after each participant were GDF, EDF and CSV file for each. These files were then imported into Matlab to be processed using the eeglab toolbox. A band pass filter from 1 to 30Hz was applied to the signals to remove noise. Independent Component Analysis was executed to remove any unwanted components from the signal; any components that showed brain activity under 70% were removed after they were labeled with IClabel. The data was segmented to extract epochs from -500 ms to 2000 ms, and baseline correction was made between -500 ms and stimuli onset. Finally, the ERPs were calculated by appending the datasets for neutral, negative, and positive stimuli and running an ERP study on eeglab with the new datasets.