1. Behavioral correlates of cortical semantic representations modeled by word vectors.
- Author
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Nishida S, Blanc A, Maeda N, Kado M, and Nishimoto S
- Subjects
- Adult, Auditory Perception physiology, Behavior physiology, Brain diagnostic imaging, Brain Mapping statistics & numerical data, Computational Biology, Female, Functional Neuroimaging statistics & numerical data, Humans, Language, Magnetic Resonance Imaging statistics & numerical data, Male, Middle Aged, Models, Neurological, Models, Psychological, Motion Pictures, Visual Perception physiology, Young Adult, Brain physiology, Natural Language Processing, Semantics
- Abstract
The quantitative modeling of semantic representations in the brain plays a key role in understanding the neural basis of semantic processing. Previous studies have demonstrated that word vectors, which were originally developed for use in the field of natural language processing, provide a powerful tool for such quantitative modeling. However, whether semantic representations in the brain revealed by the word vector-based models actually capture our perception of semantic information remains unclear, as there has been no study explicitly examining the behavioral correlates of the modeled brain semantic representations. To address this issue, we compared the semantic structure of nouns and adjectives in the brain estimated from word vector-based brain models with that evaluated from human behavior. The brain models were constructed using voxelwise modeling to predict the functional magnetic resonance imaging (fMRI) response to natural movies from semantic contents in each movie scene through a word vector space. The semantic dissimilarity of brain word representations was then evaluated using the brain models. Meanwhile, data on human behavior reflecting the perception of semantic dissimilarity between words were collected in psychological experiments. We found a significant correlation between brain model- and behavior-derived semantic dissimilarities of words. This finding suggests that semantic representations in the brain modeled via word vectors appropriately capture our perception of word meanings., Competing Interests: I have read the journal’s policy and the authors of this manuscript have the following competing interests: This study was funded by NTT Data Corp. NM and MK are employees of NTT Data Corp. more...
- Published
- 2021
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