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Decoding neural emotion patterns through large language model embeddings
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DOI：10.1016/j.neucom.2025.132513.png)
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Abstract
En 中文
• This study introduces a computational framework for mapping language emotion to brain regions without requiring neuroimaging. • The integration of embeddings and neuro-anatomical mapping differentiates through distinct activation patterns. • The framework demonstrates high spatial specificity by mapping discrete emotions to neuro-anatomically plausible regions. • Predicted regional assignment are derived from established neuroimaging coordinates requiring further independent validation. • In favor of reproducible research and to advance the field, all code used in this study is made publicly available.
Keywords:
68T01
92–08
0705Mh
8719La
Artificial intelligence
Mental health
Depression
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