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Tracking the neural codes for words and phrases during semantic composition, working-memory storage, and retrieval
Théo Desbordes1, Jean-Rémi King2, Stanislas Dehaene3
1Meta AI, Paris, France; Cognitive Neuroimaging Unit, NeuroSpin Center, 91191 Gif-sur-Yvette, France.
Cell Reports
|February 27, 2024
Summary
The brain processes phrases by first encoding individual words, then compressing them in working memory. Retrieval speed depends on semantic complexity, with simpler properties accessed faster.
Area of Science:
- Cognitive Neuroscience
- Neuroimaging
- Computational Linguistics
Background:
- Understanding semantic composition is key to human cognition.
- Neural mechanisms underlying phrase comprehension are not fully understood.
- Previous research lacks detailed temporal analysis of semantic processing.
Purpose of the Study:
- To investigate the cortical mechanisms of semantic composition.
- To identify distinct processing stages during phrase comprehension.
- To examine the role of working memory in semantic complexity.
Main Methods:
- Magnetoencephalography (MEG) was used to record brain activity.
- Participants read noun phrases of varying lengths (one, two, and five words).
- MEG signals were decoded to identify neural representations over time.
Main Results:
- Three distinct processing stages were identified during phrase comprehension.
- Individual word representations were context-dependent and sustained.
- Working memory activation increased with semantic complexity.
- Retrieval speed and accuracy varied with semantic complexity, favoring surface properties.
Conclusions:
- The brain initially uses factorized representations for successive words.
- Phrases are later compressed in working memory for efficient storage.
- A decompression period is necessary for accessing complex semantic information.
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