Driving and suppressing the human language network using large language models
Transformer models such as GPT generate human-like language and are highly predictive of human brain responses to language. Here, using fMRI-measured brain responses to 1,000 diverse sentences, we first show that a GPT-based encoding model can predict the magnitude of brain response associated with...
| Main Authors: | , , , , , , , |
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| Other Authors: | |
| Format: | Article |
| Language: | en_US |
| Published: |
Springer Nature
2024
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| Online Access: | https://hdl.handle.net/1721.1/153265 |