EEG responds to conceptual stimuli and corpus semantics

Mitchell et al. (2008) demonstrated that corpus-extracted models of semantic knowledge can predict neural activation patterns recorded using fMRI. This could be a very powerful technique for evaluating conceptual models extracted from corpora; however, fMRI is expensive and imposes strong constraints on data collection. Following on experiments that demonstrated that EEG activation patterns encode enough information to discriminate broad conceptual categories, we show that corpus-based semantic representations can predict EEG activation patterns with significant accuracy, and we evaluate the relative performance of different corpus-models on this task.