Predicting Human Brain Activity Associated with the Meanings of Nouns Export

@article{citeulike:2845964, abstract = {The question of how the human brain represents conceptual knowledge has been debated in many scientific fields. Brain imaging studies have shown that different spatial patterns of neural activation are associated with thinking about different semantic categories of pictures and words (for example, tools, buildings, and animals). 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. 10.1126/science.1152876}, author = {Mitchell, Tom M. and Shinkareva, Svetlana V. and Carlson, Andrew and Chang, Kai-Min and Malave, Vicente L. and Mason, Robert A. and Just, Marcel A.}, citeulike-article-id = {2845964}, citeulike-linkout-0 = {http://dx.doi.org/10.1126/science.1152876}, citeulike-linkout-1 = {http://www.sciencemag.org/cgi/content/abstract/320/5880/1191}, citeulike-linkout-2 = {http://view.ncbi.nlm.nih.gov/pubmed/18511683}, citeulike-linkout-3 = {http://www.hubmed.org/display.cgi?uids=18511683}, day = {30}, doi = {10.1126/science.1152876}, journal = {Science}, keywords = {brain, computational-modeling, fmri, noun, science}, month = {May}, number = {5880}, pages = {1191--1195}, posted-at = {2008-05-30 17:05:57}, priority = {2}, title = {Predicting Human Brain Activity Associated with the Meanings of Nouns}, url = {http://dx.doi.org/10.1126/science.1152876}, volume = {320}, year = {2008} }

TY - JOUR ID - citeulike:2845964 L3 - citeulike-article-id:2845964 N2 - The question of how the human brain represents conceptual knowledge has been debated in many scientific fields. Brain imaging studies have shown that different spatial patterns of neural activation are associated with thinking about different semantic categories of pictures and words (for example, tools, buildings, and animals). 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. 10.1126/science.1152876 IS - 5880 JF - Science EP - 1195 TI - Predicting Human Brain Activity Associated with the Meanings of Nouns VL - 320 SP - 1191 KW - brain KW - computational-modeling KW - fmri KW - noun KW - science AU - Mitchell, Tom AU - Shinkareva, Svetlana AU - Carlson, Andrew AU - Chang, Kai-Min AU - Malave, Vicente AU - Mason, Robert AU - Just, Marcel PY - 2008/05/30/ UR - http://dx.doi.org/10.1126/science.1152876 ER -