Fine-tuning language encoding models on fMRI responses improves prediction performance for ECoG brain signals in frequency bands beyond fMRI resolution.
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Proposes functional whole-brain models defined by four criteria that integrate empirical connectomes, dynamical realism, and task-performing competence across cognitive domains.
RSA on 7T fMRI during natural scene viewing identifies ventromedial and lateral occipitotemporal representational routes for scene context versus animate content, with differential alignment to vision and language models.
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Fine-tuning language encoding models on slow fMRI improves prediction for fast ECoG
Fine-tuning language encoding models on fMRI responses improves prediction performance for ECoG brain signals in frequency bands beyond fMRI resolution.
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Functional Whole-Brain Models: A New Framework for Unifying Brain Structure and Cognitive Function
Proposes functional whole-brain models defined by four criteria that integrate empirical connectomes, dynamical realism, and task-performing competence across cognitive domains.
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Shared representations in brains and models reveal a two-route cortical organization during scene perception
RSA on 7T fMRI during natural scene viewing identifies ventromedial and lateral occipitotemporal representational routes for scene context versus animate content, with differential alignment to vision and language models.