{"success":true,"database":"eegdash","data":{"_id":"6953f4249276ef1ee07a3404","dataset_id":"ds005574","associated_paper_doi":"10.1038/s41597-025-05462-2","authors":["Zaid Zada","Samuel A. Nastase","Bobbi Aubrey","Itamar Jalon","Ariel Goldstein","Sebastian Michelmann","Haocheng Wang","Liat Hasenfratz","Werner Doyle","Daniel Friedman","Patricia Dugan","Lucia Melloni","Sasha Devore","Orrin Devinsky","Adeen Flinker","Uri Hasson"],"bids_version":"1.10.0","contact_info":null,"contributing_labs":null,"data_processed":true,"dataset_doi":"doi:10.18112/openneuro.ds005574.v1.0.2","datatypes":["ieeg"],"demographics":{"subjects_count":9,"ages":[],"age_min":null,"age_max":null,"age_mean":null,"species":null,"sex_distribution":null,"handedness_distribution":null},"experimental_modalities":null,"external_links":{"paper_url":"https://www.nature.com/articles/s41597-025-05462-2.pdf"},"funding":["National Institutes of Health grant DP1HD091948","National Institutes of Health grant R01NS109367"],"ingestion_fingerprint":"c795fba73adb54921af76f40ac09f4db729ba3a316427aeaf65743898dd94c0b","license":"CC0","n_contributing_labs":null,"name":"The \"Podcast\" ECoG dataset","readme":"The \"Podcast\" ECoG dataset for modeling neural activity during natural story listening.\nWe introduce the “Podcast” electrocorticography (ECoG) dataset for modeling neural activity supporting natural narrative comprehension. This dataset combines the exceptional spatiotemporal resolution of human intracranial electrophysiology with a naturalistic experimental paradigm for language comprehension. In addition to the raw data, we provide a minimally preprocessed version in the high-gamma spectral band to showcase a simple pipeline and to make it easier to use. Furthermore, we include the auditory stimuli, an aligned word-level transcript, and linguistic features ranging from low-level acoustic properties to large language model (LLM) embeddings. We also include tutorials replicating previous findings and serve as a pedagogical resource and a springboard for new research. The dataset comprises 9 participants with 1,330 electrodes, including grid, depth, and strip electrodes. The participants listened to a 30-minute story with over 5,000 words. By using a natural story with high-fidelity, invasive neural recordings, this dataset offers a unique opportunity to investigate language comprehension.","recording_modality":["ieeg"],"senior_author":null,"sessions":[],"size_bytes":15507585180,"source":"openneuro","study_design":null,"study_domain":null,"tasks":["podcast"],"timestamps":{"digested_at":"2026-05-31T16:21:16.407624+00:00","dataset_created_at":null,"dataset_modified_at":null},"total_files":9,"storage":{"backend":"s3","base":"s3://openneuro.org/ds005574","raw_key":"dataset_description.json","dep_keys":["CHANGES","README","participants.json","participants.tsv"]},"tagger_meta":{"model":"openai/gpt-4o","tagged_at":"2026-06-10T08:19:41Z","source":"eegdash-llm-tagger"},"tags":{"pathology":["Healthy"],"modality":["Auditory"],"type":["Perception"],"confidence":{"pathology":0.9,"modality":0.9,"type":0.8},"reasoning":{"few_shot_analysis":"The key few-shot example here is the 'Subcortical responses to music and speech' dataset which involves healthy participants listening to auditory stimuli, indicating a 'Healthy' pathology, 'Auditory' modality, and 'Perception' type. The task involves listening to stimuli, similar to the podcast ECoG dataset where participants were engaged in narrative listening.","metadata_analysis":"The dataset's metadata specifies that it is used for 'natural narrative comprehension' with auditory stimuli in the form of podcasts. Notably, 'participants listened to a 30-minute story', which is auditory by nature. The primary focus seems to be on 'language comprehension', indicating a research focus on understanding language, which is aligned with 'Perception'. There is no mention of any clinical condition in the participants' overview, which suggests a 'Healthy' population.","paper_abstract_analysis":"No specific abstract is provided, but the dataset is described in the readme as focusing on neural activity during natural story listening using ECoG. This reinforces the focus on auditory processing and comprehension.","evidence_alignment_check":"1. Pathology: Metadata states no clinical condition ('description mentions comprehension during natural story listening' and participants overview lacks clinical mention), few-shot suggests 'Healthy' based on similar examples. These align to 'Healthy'. 2. Modality: Direct quote 'auditory stimuli' defines modality, aligning with the example suggesting 'Auditory'. 3. Type: Both meta and example suggest 'Perception' since the dataset is focused on story comprehension, a task typical of auditory discrimination and processing studies.","decision_summary":"1. Pathology likely 'Healthy' as few-shot examples and dataset description both lack clinical focus. 2. Modality clearly 'Auditory' from explicit metadata of story listening. 3. Type judged as 'Perception', focusing on auditory understanding and story comprehension. Each choice is strongly aligned with both few-shot patterns and direct metadata statements."}},"computed_title":"The \"Podcast\" ECoG dataset","nchans_counts":[{"val":138,"count":1},{"val":91,"count":1},{"val":167,"count":1},{"val":114,"count":1},{"val":205,"count":1},{"val":124,"count":1},{"val":178,"count":1},{"val":174,"count":1},{"val":264,"count":1}],"sfreq_counts":[{"val":512.0,"count":8},{"val":2048.0,"count":1}],"stats_computed_at":"2026-05-31T19:34:32.601586+00:00","total_duration_s":16199.98388671875,"canonical_name":null,"name_confidence":0.55,"name_meta":{"suggested_at":"2026-04-14T10:18:35.343Z","model":"openai/gpt-5.2 + openai/gpt-5.4-mini + deterministic_fallback"},"name_source":"canonical","author_year":"Zada2024","bad_channels_info":null,"references_and_links":["https://hassonlab.github.io/podcast-ecog-tutorials","https://github.com/hassonlab/podcast-ecog-paper"],"associated_paper_meta":{"channel":"search","confidence":"high","author_overlap":16,"is_oa":true,"oa_status":"gold","source":"paper_resolver"}}}