The "Podcast" ECoG dataset

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Authors: Zaid Zada, Samuel A. Nastase, Bobbi Aubrey, Itamar Jalon, Ariel Goldstein, Sebastian Michelmann, Haocheng Wang, Liat Hasenfratz, Werner Doyle, Daniel Friedman, Patricia C. Dugan, Lucía Melloni
+4 more Sasha Devore, Orrin Devinsky, Adeen Flinker, Uri Hasson
Cited by: 0

Abstract

Naturalistic electrocorticography (ECoG) data are a rare but essential resource for studying the brain's linguistic capabilities. This dataset shares recordings from nine participants (1,330 electrodes) listening to a 30-minute audio podcast (This American Life, "So a Monkey and a Horse Walk Into a Bar: Act One, Monkey in the Middle"). It includes raw and high-gamma band preprocessed ECoG data, auditory stimuli (audio files and aligned word-level transcript), and extracted linguistic features ranging from spectrotemporal properties to phonetic, syntactic, non-contextual and contextual word embeddings. Detailed tutorials are provided for preprocessing, feature extraction, and encoding analyses. The dataset follows BIDS-iEEG standards and is available under CC0 license on OpenNeuro (doi:10.18112/openneuro.ds005574.v1.0.2).

Fields of Study & Subjects

Neurobiology of Language and Bilingualism Neuroscience and Music Perception Neural dynamics and brain function

Publication details

Journal / source
Zenodo (CERN European Organization for Nuclear Research)
Publication date
9 February 2026
Language
EN
Document type
Dataset