Generative causal testing to bridge data-driven models and scientific theories in language neurosciencetranslating…

arXiv:2410.00812v3 Announce Type: replace-cross Abstract: Representations from large language models are highly effective at predicting BOLD fMRI responses to language stimuli. However, these representations are largely opaque: it is unclear what features of the language stimulus drive the response in each brain area. We present generative causal testing (GCT), a framework for generating concise explanations of language selectivity in the brain from predictive models and then testing those expl