The Alice Datasets combine observations from magnetic resonance imaging as well as electrophysiology while human participants listened to the same literary narrative in English. Along with these neural signals and the text of the story, we also provide a variety of word-by-word predictors motivated by research in computational linguistics and cognitive science. These predictors range from prosody to morphology to syntax. These annotated, naturalistic datasets can be used to replicate prior work and test new hypotheses about natural language comprehension in the brain.