{"dataset":{"id":"61212","dataset_id":"on007058","name":"Silent Visual Reading EEG","description":"This dataset contains raw and processed EEG recordings from participants performing silent visual reading of naturalistic narrative stories, investigating auditory representations of words during silent reading. Data include BrainVision-format EEG recordings organized according to BIDS, along with derivative processed EEG signals, metadata linking sessions to stories and runs, and word-level feature embeddings.","owner_user_id":15,"status":"active","github_repo":"nemarDatasets/on007058","concept_doi":"10.82901/nemar.on007058","latest_version_doi":"10.82901/nemar.on007058.v1.0.0","created_at":"2026-06-29 22:01:33","updated_at":"2026-08-19 00:07:35","zenodo_concept_id":null,"is_sandbox":0,"visibility":"public","ezid_status":"public","enrichment_json":"{\n  \"version\": \"2.0\",\n  \"pipeline_stage\": \"validated\",\n  \"title\": \"Silent Visual Reading EEG\",\n  \"description\": \"This dataset contains raw and processed EEG recordings from participants performing silent visual reading of naturalistic narrative stories, investigating auditory representations of words during silent reading. Data include BrainVision-format EEG recordings organized according to BIDS, along with derivative processed EEG signals, metadata linking sessions to stories and runs, and word-level feature embeddings.\",\n  \"methods_description\": \"EEG data were recorded in BrainVision format (.eeg, .vhdr, .vmrk) while participants viewed word stimuli forming naturalistic narratives on a grey background with a central fixation cross. Event annotations mark word onsets in unique and repeated stories, as well as run onset and offset triggers. Processed derivatives include epoch-level EEG data organized by channel, metadata tables matching sessions to stories and runs, and story/expectation indices for each epoch.\",\n  \"license\": \"CC0\",\n  \"dataset_type\": \"raw\",\n  \"authors\": {\n    \"Jiawei Li\": {},\n    \"Adrien Doerig\": {},\n    \"Radoslaw Martin Cichy\": {}\n  },\n  \"keywords\": [\n    {\n      \"term\": \"EEG\"\n    },\n    {\n      \"term\": \"silent reading\"\n    },\n    {\n      \"term\": \"language comprehension\"\n    },\n    {\n      \"term\": \"word processing\"\n    },\n    {\n      \"term\": \"auditory representation\"\n    },\n    {\n      \"term\": \"BIDS\"\n    }\n  ],\n  \"related_identifiers\": [\n    {\n      \"identifier\": \"https://github.com/nemarDatasets/on007058\",\n      \"identifier_type\": \"URL\",\n      \"relation_type\": \"IsDescribedBy\"\n    },\n    {\n      \"identifier\": \"https://nemar.org/dataset/on007058\",\n      \"identifier_type\": \"URL\",\n      \"relation_type\": \"IsDescribedBy\"\n    },\n    {\n      \"identifier\": \"10.21105/joss.01896\",\n      \"identifier_type\": \"DOI\",\n      \"relation_type\": \"References\"\n    },\n    {\n      \"identifier\": \"10.1038/s41597-019-0104-8\",\n      \"identifier_type\": \"DOI\",\n      \"relation_type\": \"References\"\n    },\n    {\n      \"identifier\": \"10.18112/openneuro.ds007058.v1.1.0\",\n      \"identifier_type\": \"DOI\",\n      \"relation_type\": \"IsDerivedFrom\"\n    }\n  ],\n  \"resource_type_general\": \"Dataset\",\n  \"resource_type_specific\": \"EEG Dataset\",\n  \"modalities\": [\n    \"eeg\"\n  ],\n  \"sizes\": [\n    \"37.9 GB (2007 files)\"\n  ],\n  \"formats\": [\n    \".DS_Store\",\n    \".csv\",\n    \".eeg\",\n    \".json\",\n    \".md\",\n    \".npy\",\n    \".npz\",\n    \".tsv\",\n    \".vhdr\",\n    \".vmrk\",\n    \".yml\"\n  ],\n  \"source_hash\": \"046c602e94a702755b7e0dc82fed09b8c0176e719483c6abbbab8b6a4f4a9916\"\n}","last_activity_at":"2026-06-29 22:01:33","source":"openneuro","source_id":"ds007058","subject_count":10,"modalities":"eeg","age_min":20,"age_max":31,"file_size":37909957888,"total_files":3772,"tasks":"read","metadata_columns_error":null,"staleness_warn_stage":null,"staleness_admin_notified_at":null,"authors":"Jiawei Li, Adrien Doerig, Radoslaw Martin Cichy","license":"CC0","readme":"[![DOI](https://img.shields.io/badge/DOI-10.82901%2Fnemar.on007058-blue)](https://doi.org/10.82901/nemar.on007058)\n\n# EEG Dataset for \"Auditory representations of words during silent visual reading\"\n\nThis dataset contains the raw and processed EEG data accompanying the paper.\nIf you use these data in your research, please cite the above paper.\n\n---\n\n## Dataset Description\n\nThe dataset includes raw EEG recordings in **BrainVision format**:\n\n* `.eeg`\n* `.vhdr`\n* `.vmrk`\n\nAll participants’ data follow the **BIDS (Brain Imaging Data Structure)** specification.\n\n### Event Annotations\n\nEach run includes an **events file** with onsets, durations, trial types, and event values for all trials.\n\n### Stimulus Presentation\n\nParticipants viewed word stimuli forming naturalistic narratives, presented on a grey background with a central fixation cross.\n\nTrigger | Type |\n| :--- | :--- \n `S111` | Onset of a word in a unique story\n `S71` | Onset of a word in a repeated story\n\n### Additional Triggers\n\n* **Run onset:** `S71`\n* **Run end:** `S78`\n\n---\n\n## Derivatives\n\nProcessed data files are stored in the `./derivatives` folder.  \nThis folder contains the processed EEG, as well as the accompanying meta-data and feature embeddings.\n\n### MetaData\n\nThe following files are found in the `./derivatives/MetaData/` sub-folder:\n\n#### Story–Run–Session Match Table\n**Path:** `./derivatives/MetaData/session_story_run`  \n**Description:**  \nA table matching each recording session to the specific story and run it contains.\n\n#### Story Indexes for Each Epoch\n**Path:** `./derivatives/MetaData/story_epoch_match`  \n**Description:**  \nProvides the specific story index corresponding to each epoch in the processed EEG data.\n\n#### Expected Index for Each Epoch\n**Path:** `./derivatives/MetaData/expect_or_not`  \n**Description:**  \nIndicates whether the epoch was expected or unexpected.  \n**Values:**  \n- `1` = expected  \n- `0` = unexpected\n\n### Processed EEG Data\n\nThe preprocessed EEG signals are located in: `./derivatives/eeg_processed/`\n\n\nData are organized by channel, where each channel file has the following specifications:\n\n- **Shape:** `(nWords, nTimepoints)`  \n- **nWords:** number of words (epochs)  \n- **nTimepoints:** number of time points per epoch\n\n### Corresponding Feature Embeddings\n\nFeature (embeddings) are stored in: `./derivatives/Features/`\n\nThese feature files follow the same word-level indexing (`nWords`) as the EEG data:\n\n- **Shape:** `(nWords,)`  \n- **nWords:** number of words (epochs) in the EEG data\n\n---\n\n## References\n\n* Appelhoff, S., Sanderson, M., Brooks, T., Vliet, M., Quentin, R., Holdgraf, C., Chaumon, M., Mikulan, E., Tavabi, K., Höchenberger, R., Welke, D., Brunner, C., Rockhill, A., Larson, E., Gramfort, A., & Jas, M. (2019). **MNE-BIDS: Organizing electrophysiological data into the BIDS format and facilitating their analysis.** *Journal of Open Source Software, 4*(1896). [https://doi.org/10.21105/joss.01896](https://doi.org/10.21105/joss.01896)\n* Pernet, C. R., Appelhoff, S., Gorgolewski, K. J., Flandin, G., Phillips, C., Delorme, A., & Oostenveld, R. (2019). **EEG-BIDS, an extension to the brain imaging data structure for electroencephalography.** *Scientific Data, 6*, 103. [https://doi.org/10.1038/s41597-019-0104-8](https://doi.org/10.1038/s41597-019-0104-8)","bids_version":"1.7.0","sessions_count":7,"publish_date":null,"embedding_dirty":0,"license_tier":"public","zarr_status":"ready","zarr_converted_at":"2026-08-23 14:53:58","zarr_store_count":395,"zarr_index_etag":"f797a0f494a36cef9202dbb98b1cdcbd","zarr_source_commit":"7cb176cebd6ea73da15187bcab6477cf03b560bf","archive_status":"ready","archive_size":34155129719,"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":0,"n_channels":63,"electrode_system":"10-10","has_hed":0,"hed_version":null,"is_exemplar":0,"bytes_present":37895748751,"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":133299.77499999988,"recording_duration_min":212.85,"recording_duration_max":460.655,"recording_count":395,"recordings_unavailable":0,"recordings_measured":395,"channel_count_min":63,"channel_count_max":63,"sampling_frequency":200,"power_line_frequency":50,"eeg_reference":null,"placement_scheme":"based on the extended 10/20 system","sweep_stamps":"{\"enrichment_updated_at\":\"2026-08-19 00:07:15\",\"metadata_updated_at\":\"2026-08-19 00:07:30\",\"archive_checked_at\":\"2026-06-29 22:42:24\",\"zarr_checked_at\":null,\"records_checked_at\":\"2026-06-29 22:13:18\",\"citations_updated_at\":null,\"channel_montage_checked_at\":null,\"hed_checked_at\":\"2026-06-30 05:41:02\",\"data_checked_at\":\"2026-09-01 03:00:33\",\"availability_report_at\":\"2026-07-23 01:31:11\",\"recording_stats_at\":\"2026-09-02 11:33:51\",\"signal_defaults_at\":\"2026-09-02 12:51:22\"}","participants":10,"num_citations":0,"latest_version":"v1.0.0","zarr_verify_status":null,"zarr_verified_at":null,"owner_username":"nemarAdmin","owner_github":"nemarAdmin","file_size_formatted":"35.31 GB","zarr_data_failures":null,"zarr_index_url":"https://zarr.nemar.org/on007058/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}}