Cephalonauts One: A deep fMRI dataset for decoding naturalistic speech in the human brain

Cephalonauts One is a whole-brain 3 Tesla (3T) functional magnetic resonance imaging (fMRI) dataset recorded while subjects listened to audio podcasts. Three healthy subjects underwent multiple scanning sessions, each consisting of five 15-minute runs, while listening to podcasts in their native language. The current release contains 14, 20, and 17 hours of fMRI data per subject, respectively, making it one of the deepest per-subject fMRI datasets with naturalistic speech stimuli available. The dataset pairs brain activity with the corresponding podcast audio, transcript annotations, and derived stimulus embeddings. Furthermore, we introduce a brain decoding benchmark formulated as audio segment retrieval: given fMRI activity from a held-out session, the decoder must identify the corresponding time-aligned podcast audio segment among candidate segments. We provide standardized splits, evaluation metrics, and baseline decoders for this task. Finally, a scaling analysis shows that decoding performance improves continuously with the amount of training data per subject. Data & code: https://huggingface.co/datasets/karavela/cephalonauts_one