"We present a computational model that predicts the functional magnetic resonance imaging (fMRI) neural activation associated with words for which fMRI data are not yet available. This model is trained with a combination of data from a trillion-word text corpus and observed fMRI data associated with viewing several dozen concrete nouns. Once trained, the model predicts fMRI activation for thousands of other concrete nouns in the text corpus,with highly significant accuracies over the 60 nouns for which we currently have fMRI data."
https://www.cs.cmu.edu/~tom/pubs/science2008.pdf -- "Predicting Human Brain Activity Associated with the Meanings of Nouns"
"We present a computational model that predicts the functional magnetic resonance imaging (fMRI) neural activation associated with words for which fMRI data are not yet available. This model is trained with a combination of data from a trillion-word text corpus and observed fMRI data associated with viewing several dozen concrete nouns. Once trained, the model predicts fMRI activation for thousands of other concrete nouns in the text corpus,with highly significant accuracies over the 60 nouns for which we currently have fMRI data."
This is a frequently cited paper - I stumbled across it recently as a drive-by mention in this blog post about word embeddings: http://www.offconvex.org/2015/12/12/word-embeddings-1/
Anyway - totally tangential to the topic of the OP. But maybe some interesting food for thought.