This fascinating video depicts work reported in the following paper: Huth, A., de Heer, W., Griffiths, T. et al. Natural speech reveals the semantic maps that tile human cerebral cortex. Nature 532, 453–458 (2016). https://doi.org/10.1038/nature17637
Abstract: The meaning of language is represented in regions of the cerebral cortex collectively known as the ‘semantic system’. However, little of the semantic system has been mapped comprehensively, and the semantic selectivity of most regions is unknown. Here we systematically map semantic selectivity across the cortex using voxel-wise modelling of functional MRI (fMRI) data collected while subjects listened to hours of narrative stories. We show that the semantic system is organized into intricate patterns that seem to be consistent across individuals. We then use a novel generative model to create a detailed semantic atlas. Our results suggest that most areas within the semantic system represent information about specific semantic domains, or groups of related concepts, and our atlas shows which domains are represented in each area. This study demonstrates that data-driven methods—commonplace in studies of human neuroanatomy and functional connectivity—provide a powerful and efficient means for mapping functional representations in the brain.
Here's a summary Nature appended to the article:
It is thought that the meanings of words and language are represented in a semantic system distributed across much of the cerebral cortex. However, little is known about the detailed functional and anatomical organization of this network. Alex Huth, Jack Gallant and colleagues set out to map the functional representations of semantic meaning in the human brain using voxel-based modelling of functional magnetic resonance imaging (fMRI) recordings made while subjects listened to natural narrative speech. They find that each semantic concept is represented in multiple semantic areas, and each semantic area represents multiple semantic concepts. The recovered semantic maps are largely consistent across subjects, however, providing the basis for a semantic atlas that can be used for future studies of language processing. An interactive version of the atlas can be explored at http://gallantlab.org/huth2016.