Abstract
Liking is one of the most important psychological processes associated with the reward system, being involved in affective processing and pleasure/displeasure encoding. Currently, there is no consensus regarding the combination of physiological indicators which best predict liking, especially when applied to dynamic stimuli such as videos. There is a lack of a standard methodology to assess likeability over time and therefore in assessing narrative and semantic aspects of the stimulus. We developed a time-dependent method to evaluate the physiological correlates of likeability for three different thematic categories, namely: adventure (AV), comedy (CM), and nature landscape (LS). Twenty-eight healthy adults with ages ranging from 18 to 35 years (average: 23.85 years) were enrolled in the study. The participants were asked to provide likeability ratings for videos as they watched them, using a response box. Three 60-s videos were presented, one for each category, in randomized order while the participant’s physiological data [electroencephalogram (EEG), electrocardiogram (ECG) and eye tracking (ET)] was recorded. The comedy video (CM) presented the smallest minimum accumulated normalized rating (ANR; p = 0.013) and the LS video presented the highest maximum ANR (p = 0.039). The LS video presented the longest time for first response (p < 0.001) and the AV video presented the shortest time for maximum response (p = 0.016). The LS video had the highest mean likeability rating with 1.43 ± 2.31 points; and the CM video had the lowest with 0.57 ± 1.77. Multiple linear regression models were created to predict the likeability of each video using the following physiological indicators; AV: power in beta band at C4 and P4 (p = 0.004, adj. R2 = 0.301); CM: alpha power in Fp2 (p = 0.001, adj. R2 = 0.326) and LS: alpha power in P4, F8, and Fp2; beta power in C4 and P4 and pupil size, (p = 0.002, adj. R2 = 0.489). Despite its limitations (e.g., using one 1-min video per category) our findings suggest that there is a considerable difference in the psychophysiological correlates of stimuli with different contextual properties and that the use of time-dependent methods to assess videos should be considered as best practices.
Highlights
The brain reward system is composed of three subsystems involving learning, emotional and motivational processing, according to Berridge and collaborators
Accumulated Normalized Ratings Significant differences were observed in minimum (p = 0.013) and maximum ratings (p = 0.049)
Post hoc tests showed that CM video minimum rating is significantly lower than AV video minimum rating (p = 0.04) while no significant differences were found in the pairwise comparison of maximum rating
Summary
The brain reward system is composed of three subsystems involving learning, emotional and motivational processing, according to Berridge and collaborators. These components are responsible for reward learning, liking and wanting (Berridge, 2004; Berridge et al, 2009; Berridge and Kringelbach, 2013, 2015). Liking is recognized as one of the most important psychological processes associated with the reward system It is associated with affective processing and pleasure/displeasure encoding, which provides feedback that guides the interaction with every stimulus which one encounters (Steiner et al, 2001; Berridge et al, 2009; Kringelbach and Berridge, 2010; Smith et al, 2011; Berridge and Kringelbach, 2013, 2015). The declarative component of liking can be measured through the explicit response of the subject; the non-declarative component requires a more specific approach, such as the psychophysiological evaluation of affective reactions or behavioral analysis
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