How does the human brain process and represent the meaning of language? We investigate this question by building computational models of language processing and then using those models to predict functional magnetic resonance imaging (fMRI) responses to natural language stimuli. The technique we use, voxel-wise encoding models, provides a sensitive method for probing richly detailed cortical representations. This method also allows us to take advantage of natural stimuli, which elicit stronger, more reliable, and more varied brain responses than tightly controlled experimental stimuli. In this talk I will discuss how we have used these methods to study how the human brain represents the meaning of language, and how those representations are linked to visual representations. The results suggest that the language and visual systems in the human brain might form a single, contiguous map over which meaning is represented.