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.

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Publication Details

Journal
Scientific Data
Published
2025-08-26
DOI
https://doi.org/10.1038/s41597-025-05574-9
Primary Topic
Face recognition and analysis
Type
article
Field-Weighted Citation Impact
0.00

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article

Dataset of natural conversations about appearance using fNIRS

Yafeng Pan, Yinying Hu, Xiangping Gao, Yuqi Liu et al.
Scientific Data
Face recognition and analysis
article

Dataset of natural conversations about appearance using fNIRS

Yafeng Pan, Yinying Hu, Xiangping Gao, Yuqi Liu, Yifeng Hou
article en

Abstract

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.

Scientific DataVol. 12(1)
Shanghai Normal University (CN), Zhejiang Lab (CN), First Affiliated Hospital Zhejiang University (CN), Zhejiang University (CN)
National Natural Science Foundation of China, Natural Science Foundation of Zhejiang Province
Openalex Percentile: Top 79%
Face recognition and analysis
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Dataset of natural conversations about appearance using fNIRS — Yafeng Pan, Yinying Hu, et al. · Scientific Data (2025) | TGRS Research Map | TGRS