Unraveling the neural representations of preference with a naturalistic neuroimaging approach

Poster Session D - Monday, April 15, 2024, 8:00 – 10:00 am EDT, Sheraton Hall ABC

Feng-Chun Ben Chou¹ (f11227106@ntu.edu.tw), Tung-An Phoenix Chiu¹, Po-Yuan Alan Hsiao¹, Chih-Yuan Edward Chang¹, Pin-Hao Andy Chen¹; ¹National Taiwan University

Our brains innately compare and contrast diverse stimuli in daily life, even when making preferences among similar stimuli presented concurrently. In contrast, when each stimulus is evaluated independently, the difficulty level of making preferences escalates. Therefore, this study aims to investigate the neural mechanism of preference and how preferences are represented in the brain. We examined 70 participants using functional magnetic resonance imaging (fMRI) as they viewed 18 varied videos. Without receiving prior notice, participants were then asked to rank their preferences for each video pair, totaling 153 pairs, and also to rate their liking for each video individually outside of the scanner. Using representational similarity analysis (RSA) across 100 brain regions of interest (ROIs), we examined the correlations between preferences and neural representations of those videos. Even after adjusting for the effect of subjective liking, our RSA results still revealed a number of significant associations between preferences and various brain regions, including regions involved in selective attention (e.g., dlPFC), memory formation (e.g., hippocampus), evaluation processing (e.g., NAcc), and regions engaged in the computation of psychological distances across dimensions, such as the inferior frontal gyrus (IFG), superior temporal sulcus (STS) and supplementary motor area (SMA). Our results indicate that preference formation in the brain is a natural and complex process, involving memory, evaluation, selective attention as well as the calculation of psychological distances between stimuli. In conclusion, our study adds to a deeper understanding of preference mechanisms, emphasizing the complexity of human evaluative processes.

Topic Area: THINKING: Decision making