Dataset of natural conversations about appearance using fNIRS.

Self-objectification, marked by an overemphasis on how one's appearance is viewed by others, promotes increased body surveillance and dissatisfaction. Natural conversations centered around appearance, such as "fat talk"-where individuals, often women, engage in negative or self-deprecating remarks about their bodies or weight-are commonly used to induce a state of self-objectification. However, there is a notable lack of public datasets on brain signals during fat talk. In this dataset, we collected brain data from 31 female participants (aged 19.55 ± 0.89 years) using a 40-channel portable near-infrared device during fat talk and non-fat talk (topics such as travel and home decoration), primarily covering the frontal and parietal areas. Data analyses of subjective reports and fNIRS data revealed an increase in body surveillance and dissatisfaction, suggesting a significant activation of the self-objectification state. This dataset can be utilized to explore fNIRS data processing during natural interpersonal conversations and to gain insights into emotional and cognitive responses under conditions of self-dysregulation.