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| Autores principales: | , , , , |
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| Formato: | Preprint |
| Publicado: |
2025
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| Materias: | |
| Acceso en línea: | https://arxiv.org/abs/2507.00320 |
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| _version_ | 1866913920003866624 |
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| author | Westlin, Christiana Singh, Ashutosh Erdogmus, Deniz Stratis, Georgios Barrett, Lisa Feldman |
| author_facet | Westlin, Christiana Singh, Ashutosh Erdogmus, Deniz Stratis, Georgios Barrett, Lisa Feldman |
| contents | In the science of emotion, it is widely assumed that folk emotion categories form a biological and psychological typology, and studies are routinely designed and analyzed to identify emotion-specific patterns. This approach shapes the observations that studies report, ultimately reinforcing the assumption that guided the investigation. Here, we reanalyzed data from one such typologically-guided study that reported mappings between individual brain patterns and group-averaged ratings of 34 emotion categories. Our reanalysis was guided by an alternative view of emotion categories as populations of variable, situated instances, and which predicts a priori that there will be significant variation in brain patterns within a category across instances. Correspondingly, our analysis made minimal assumptions about the structure of the variance present in the data. As predicted, we did not observe the original mappings and instead observed significant variation across individuals. These findings demonstrate how starting assumptions can ultimately impact scientific conclusions and suggest that a hypothesis must be supported using multiple analytic methods before it is taken seriously. |
| format | Preprint |
| id |
arxiv_https___arxiv_org_abs_2507_00320 |
| institution | arXiv |
| publishDate | 2025 |
| record_format | arxiv |
| spellingShingle | Exploring Theory-Laden Observations in the Brain Basis of Emotional Experience Westlin, Christiana Singh, Ashutosh Erdogmus, Deniz Stratis, Georgios Barrett, Lisa Feldman Machine Learning Computer Vision and Pattern Recognition Neurons and Cognition In the science of emotion, it is widely assumed that folk emotion categories form a biological and psychological typology, and studies are routinely designed and analyzed to identify emotion-specific patterns. This approach shapes the observations that studies report, ultimately reinforcing the assumption that guided the investigation. Here, we reanalyzed data from one such typologically-guided study that reported mappings between individual brain patterns and group-averaged ratings of 34 emotion categories. Our reanalysis was guided by an alternative view of emotion categories as populations of variable, situated instances, and which predicts a priori that there will be significant variation in brain patterns within a category across instances. Correspondingly, our analysis made minimal assumptions about the structure of the variance present in the data. As predicted, we did not observe the original mappings and instead observed significant variation across individuals. These findings demonstrate how starting assumptions can ultimately impact scientific conclusions and suggest that a hypothesis must be supported using multiple analytic methods before it is taken seriously. |
| title | Exploring Theory-Laden Observations in the Brain Basis of Emotional Experience |
| topic | Machine Learning Computer Vision and Pattern Recognition Neurons and Cognition |
| url | https://arxiv.org/abs/2507.00320 |