{"dataset":{"id":"61242","dataset_id":"on007591","name":"Delineating neural contributions to EEG-based speech decoding","description":"This dataset comprises 128-channel EEG recordings collected during a speech production paradigm designed to investigate neural correlates of overt, minimally overt, and covert speech. Participants produced one of five color words under each speech condition, with additional peripheral recordings including EOG, EMG, microphone, and display markers to support speech decoding analyses. The dataset includes both calibration sessions for decoder training and online sessions for real-time decoding evaluation.","owner_user_id":15,"status":"active","github_repo":"nemarDatasets/on007591","concept_doi":"10.82901/nemar.on007591","latest_version_doi":"10.82901/nemar.on007591.v1.0.0","created_at":"2026-06-30 13:31:33","updated_at":"2026-08-18 23:43:58","zenodo_concept_id":null,"is_sandbox":0,"visibility":"public","ezid_status":"public","enrichment_json":"{\n  \"version\": \"2.0\",\n  \"pipeline_stage\": \"validated\",\n  \"title\": \"Delineating neural contributions to EEG-based speech decoding\",\n  \"description\": \"This dataset comprises 128-channel EEG recordings collected during a speech production paradigm designed to investigate neural correlates of overt, minimally overt, and covert speech. Participants produced one of five color words under each speech condition, with additional peripheral recordings including EOG, EMG, microphone, and display markers to support speech decoding analyses. The dataset includes both calibration sessions for decoder training and online sessions for real-time decoding evaluation.\",\n  \"methods_description\": \"128-channel EEG was recorded alongside bipolar EOG, EMG (upper and lower orbicularis oris), microphone, and display channels, plus a trigger channel marking trial onsets. Each trial consisted of 5 repetitions of a spoken color word (1.25 sec per repetition) under overt, minimally overt, or covert speech conditions. EEG channels were recorded with a 10x preamp gain, and raw values were converted to Volts (×1e-6).\",\n  \"license\": \"CC0\",\n  \"dataset_type\": \"raw\",\n  \"authors\": {\n    \"Motoshige Sato\": {\n      \"orcid\": \"0000-0002-8630-5619\"\n    },\n    \"Yasuo Kabe\": {},\n    \"Sensho Nobe\": {},\n    \"Akito Yoshida\": {\n      \"orcid\": \"0000-0002-6180-1296\"\n    },\n    \"Masakazu Inoue\": {},\n    \"Mayumi Shimizu\": {},\n    \"Kenichi Tomeoka\": {\n      \"orcid\": \"0009-0005-9176-7155\"\n    },\n    \"Shuntaro Sasai\": {\n      \"orcid\": \"0000-0002-9941-6510\"\n    }\n  },\n  \"keywords\": [\n    {\n      \"term\": \"EEG\"\n    },\n    {\n      \"term\": \"speech decoding\"\n    },\n    {\n      \"term\": \"covert speech\"\n    },\n    {\n      \"term\": \"Speech Production Measurement\",\n      \"subject_scheme\": \"MeSH\",\n      \"scheme_uri\": \"https://id.nlm.nih.gov/mesh/\",\n      \"value_uri\": \"http://id.nlm.nih.gov/mesh/D013068\"\n    },\n    {\n      \"term\": \"Electromyography\",\n      \"subject_scheme\": \"MeSH\",\n      \"value_uri\": \"http://id.nlm.nih.gov/mesh/D004576\"\n    },\n    {\n      \"term\": \"brain-computer interface\"\n    }\n  ],\n  \"related_identifiers\": [\n    {\n      \"identifier\": \"10.1101/2024.05.09.591996\",\n      \"identifier_type\": \"DOI\",\n      \"relation_type\": \"IsDescribedBy\"\n    },\n    {\n      \"identifier\": \"https://github.com/nemarDatasets/on007591\",\n      \"identifier_type\": \"URL\",\n      \"relation_type\": \"IsDescribedBy\"\n    },\n    {\n      \"identifier\": \"https://nemar.org/dataset/on007591\",\n      \"identifier_type\": \"URL\",\n      \"relation_type\": \"IsDescribedBy\"\n    },\n    {\n      \"identifier\": \"10.18112/openneuro.ds007591.v1.0.1\",\n      \"identifier_type\": \"DOI\",\n      \"relation_type\": \"IsDerivedFrom\"\n    }\n  ],\n  \"funding_references\": [\n    {\n      \"funder_name\": \"JST\",\n      \"award_number\": \"JPMJMS2012\",\n      \"award_title\": \"Moonshot R&D\"\n    }\n  ],\n  \"resource_type_general\": \"Dataset\",\n  \"resource_type_specific\": \"EEG Dataset\",\n  \"modalities\": [\n    \"eeg\"\n  ],\n  \"sizes\": [\n    \"1.7 GB (22 files)\"\n  ],\n  \"formats\": [\n    \".edf\",\n    \".json\",\n    \".md\",\n    \".tsv\",\n    \".yml\"\n  ],\n  \"source_hash\": \"312b5c80db1777a1d13cd30a6fa9ac759df93c9fce44b4ea2a426f68ecf68eb9\"\n}","last_activity_at":"2026-06-30 13:31:33","source":"openneuro","source_id":"ds007591","subject_count":3,"modalities":"eeg","age_min":null,"age_max":null,"file_size":1737860459,"total_files":127,"tasks":"covert,minimallyovert,overt","metadata_columns_error":null,"staleness_warn_stage":null,"staleness_admin_notified_at":null,"authors":"Motoshige Sato, Yasuo Kabe, Sensho Nobe, Akito Yoshida, Masakazu Inoue, Mayumi Shimizu, Kenichi Tomeoka, Shuntaro Sasai","license":"CC0","readme":"[![DOI](https://img.shields.io/badge/DOI-10.82901%2Fnemar.on007591-blue)](https://doi.org/10.82901/nemar.on007591)\n\n# Delineating neural contributions to EEG-based speech decoding\n\n## Overview\n128-channel EEG recordings during speech production tasks.\nParticipants produced one of 5 color words (green, magenta, orange, violet, yellow)\nunder three speech conditions: overt, minimally overt, and covert.\n\nEach trial consists of 5 repetitions of the same word (1.25 sec per repetition).\n\n## Channel layout (139 channels total)\n- Channels 1-128: EEG\n- Channels 129-130: DISPLAY (bipolar pair, misc)\n- Channels 131-132: MIC (bipolar pair, misc)\n- Channels 133-134: EOG (bipolar pair)\n- Channels 135-136: EMG upper orbicularis oris (bipolar pair)\n- Channels 137-138: EMG lower orbicularis oris (bipolar pair)\n- Channel 139: TRIGGER (marks trial onsets)\n\n## Session types\n- calibration: Offline data collection for decoder training\n- online: Real-time decoding with trained decoder\n\n## Preprocessing note\nThe EEG channels were recorded with a 10x preamp gain.\nRaw values have been converted to Volts (×1e-6).\n\n## Code\nCode for data loading, preprocessing, and decoding models is available at:\nhttps://github.com/arayabrain/uhd-gmail-public\n","bids_version":"1.9.0","sessions_count":6,"publish_date":null,"embedding_dirty":0,"license_tier":"public","zarr_status":"ready","zarr_converted_at":"2026-08-23 03:49:37","zarr_store_count":21,"zarr_index_etag":"27e6fb0afd2579e1c80a9e3107314789","zarr_source_commit":"e77a6f3d6c509d91519aa21acfecfdf0961064fb","archive_status":"ready","archive_size":1206172323,"archive_retry_count":0,"records_status":"ready","archive_skip_reason":null,"zarr_errors":0,"zarr_failure_count":0,"zarr_deterministic":0,"zarr_failed_at":null,"num_dataset_citations":0,"num_datapaper_citations":1,"n_channels":128,"electrode_system":"other","has_hed":0,"hed_version":null,"is_exemplar":0,"bytes_present":1737664894,"data_complete":1,"withdrawn_at":null,"withdrawn_reason":null,"archive_complete":null,"archive_absent_files":null,"archive_declared_files":null,"zarr_pool_breaks":null,"total_recording_duration":24393,"recording_duration_min":563,"recording_duration_max":2119,"recording_count":21,"recordings_unavailable":0,"recordings_measured":21,"channel_count_min":139,"channel_count_max":139,"sampling_frequency":256,"power_line_frequency":50,"eeg_reference":"n/a (raw, pre-reference)","placement_scheme":null,"sweep_stamps":"{\"enrichment_updated_at\":\"2026-08-18 23:43:45\",\"metadata_updated_at\":\"2026-08-18 23:43:54\",\"archive_checked_at\":\"2026-06-30 13:43:50\",\"zarr_checked_at\":null,\"records_checked_at\":\"2026-06-30 13:41:03\",\"citations_updated_at\":\"2026-09-08 03:00:53\",\"channel_montage_checked_at\":null,\"hed_checked_at\":null,\"data_checked_at\":\"2026-09-03 03:01:46\",\"availability_report_at\":\"2026-07-23 01:33:03\",\"recording_stats_at\":\"2026-09-02 11:34:03\",\"signal_defaults_at\":\"2026-09-02 12:56:12\"}","participants":3,"num_citations":1,"latest_version":"v1.0.0","zarr_verify_status":null,"zarr_verified_at":null,"owner_username":"nemarAdmin","owner_github":"nemarAdmin","file_size_formatted":"1.62 GB","zarr_data_failures":null,"zarr_index_url":"https://zarr.nemar.org/on007591/zarr/index.json","attestation_deposit_type":null,"attestation_key_status":null,"attestation_deidentified":null,"attestation_no_duplicate":null,"attestation_upstream_source":null,"attestation_accepted_at":null}}