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Fernandino-2016-Heteromodal Areas Encode Sensory-Motor features-JNeuro by lfernandino is a document available to read on EtoBox.
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The study investigates how heteromodal cortical areas encode sensory-motor features of word meaning using predictive machine learning on fMRI data. It finds that these areas can successfully decode individual concrete concepts based on sensory-motor attributes, indicating that the brain represents concepts as multimodal combinations of sensory and motor information. The results suggest that the general semantic network plays a crucial role in concept retrieval by integrating sensory-motor information.
- Author
- lfernandino
- Language
- EN