"When two people interact, their brain activity becomes synchronized, but it was unclear until now to what extent this "brain-to-brain coupling" is due to linguistic information or other factors, such as body language or tone of voice.
Researchers report August 2 in the journal Neuron that brain-to-brain coupling during conversation can be modeled by considering the words used during that conversation, and the context in which they are used.
"We can see
"We can see
---linguistic content emerge word-by-word in the speaker's brain before they actually articulate what they're trying to say,
---and the same linguistic content rapidly reemerges in the listener's brain after they hear it," says first author and neuroscientist Zaid Zada.....the researchers were able to observe brain activity associated with the context-specific meaning of words in the brains of both speaker and listener.
They showed that word-specific brain activity peaked in the speaker's brain around 250 ms before they spoke each word, and corresponding spikes in brain activity associated with the same words appeared in the listener's brain approximately 250 ms after they heard them. "This shows just how important context is, because it best explains the brain data," says Zada. "Large language models take all these different elements of linguistics like syntax and semantics and represent them in a single high-dimensional vector. We show that this type of unified model is able to outperform other hand-engineered models from linguistics."
They showed that word-specific brain activity peaked in the speaker's brain around 250 ms before they spoke each word, and corresponding spikes in brain activity associated with the same words appeared in the listener's brain approximately 250 ms after they heard them. "This shows just how important context is, because it best explains the brain data," says Zada. "Large language models take all these different elements of linguistics like syntax and semantics and represent them in a single high-dimensional vector. We show that this type of unified model is able to outperform other hand-engineered models from linguistics."
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