{"dataset":{"id":"54122","dataset_id":"on003703","name":"Frequency Tagging of Syntactic Structure or Lexical Properties","description":"This dataset comprises electroencephalography (EEG) recordings investigating the neural correlates of syntactic structure and lexical properties using frequency tagging methodology. Participants were presented with linguistic stimuli while EEG activity was recorded to identify frequency-specific neural responses associated with different linguistic features. The dataset provides raw neurophysiological data suitable for studying the temporal dynamics of language processing at the neural level.","owner_user_id":15,"status":"active","github_repo":"nemarDatasets/on003703","concept_doi":"10.82901/nemar.on003703","latest_version_doi":"10.82901/nemar.on003703.v1.0.0","created_at":"2026-06-22 12:31:17","updated_at":"2026-07-10 22:19:22","zenodo_concept_id":null,"is_sandbox":0,"visibility":"public","ezid_status":"public","enrichment_json":"{\n  \"version\": \"2.0\",\n  \"pipeline_stage\": \"enriched\",\n  \"title\": \"Frequency Tagging of Syntactic Structure or Lexical Properties\",\n  \"description\": \"This dataset comprises electroencephalography (EEG) recordings investigating the neural correlates of syntactic structure and lexical properties using frequency tagging methodology. Participants were presented with linguistic stimuli while EEG activity was recorded to identify frequency-specific neural responses associated with different linguistic features. The dataset provides raw neurophysiological data suitable for studying the temporal dynamics of language processing at the neural level.\",\n  \"methods_description\": \"EEG data were collected during a frequency tagging paradigm designed to isolate neural responses to syntactic structure or lexical properties. Participants were presented with linguistic stimuli while continuous EEG activity was recorded. The frequency tagging methodology allows for the identification of frequency-specific neural responses associated with different linguistic features. The dataset is organized according to the Brain Imaging Data Structure (BIDS) standard for electrophysiological data.\",\n  \"license\": \"CC0\",\n  \"dataset_type\": \"raw\",\n  \"authors\": {\n    \"Evgenii Kalenkovich\": {},\n    \"Anna Shestakova\": {},\n    \"Nina Kazanina\": {}\n  },\n  \"keywords\": [\n    {\n      \"term\": \"EEG\"\n    },\n    {\n      \"term\": \"frequency tagging\"\n    },\n    {\n      \"term\": \"syntax\"\n    },\n    {\n      \"term\": \"semantics\"\n    },\n    {\n      \"term\": \"language processing\"\n    },\n    {\n      \"term\": \"lexical semantics\"\n    },\n    {\n      \"term\": \"neural oscillations\"\n    },\n    {\n      \"term\": \"EEG frequency analysis\"\n    },\n    {\n      \"term\": \"neural responses\"\n    }\n  ],\n  \"related_identifiers\": [\n    {\n      \"identifier\": \"https://github.com/nemarDatasets/on003703\",\n      \"identifier_type\": \"URL\",\n      \"relation_type\": \"IsDescribedBy\"\n    },\n    {\n      \"identifier\": \"https://nemar.org/dataexplorer/detail?dataset_id=on003703\",\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/sdata.2018.110\",\n      \"identifier_type\": \"DOI\",\n      \"relation_type\": \"References\"\n    },\n    {\n      \"identifier\": \"10.18112/openneuro.ds003703.v1.0.0\",\n      \"identifier_type\": \"DOI\",\n      \"relation_type\": \"IsDerivedFrom\"\n    }\n  ],\n  \"funding_references\": [\n    {\n      \"funder_name\": \"RF Government\",\n      \"award_number\": \"075-15-2019-1930\",\n      \"award_title\": \"International Laboratory for Social Neuroscience of the Institute for Cognitive Neuroscience HSE\"\n    }\n  ],\n  \"resource_type_general\": \"Dataset\",\n  \"resource_type_specific\": \"MEG Dataset\",\n  \"modalities\": [\n    \"meg\"\n  ],\n  \"sizes\": [\n    \"208.8 GB (404 files)\"\n  ],\n  \"formats\": [\n    \".csv\",\n    \".fif\",\n    \".gitattributes\",\n    \".json\",\n    \".md\",\n    \".npy\",\n    \".npz\",\n    \".py\",\n    \".rds\",\n    \".tsv\",\n    \".yml\"\n  ],\n  \"source_hash\": \"28d79ff1f4084a3a4acbf5bf966e7408b72b7d2bc3d6fec7a67d4164d1e2b223\"\n}","last_activity_at":"2026-06-22 12:31:17","source":"openneuro","source_id":"ds003703","subject_count":34,"modalities":"meg","age_min":18,"age_max":38,"file_size":208852131488,"total_files":900,"tasks":"listeningToSpeech,rest","metadata_columns_error":null,"staleness_warn_stage":null,"staleness_admin_notified_at":null,"authors":"Evgenii Kalenkovich, Anna Shestakova, Nina Kazanina","license":"CC0","readme":"[![DOI](https://img.shields.io/badge/DOI-10.82901%2Fnemar.on003703-blue)](https://doi.org/10.82901/nemar.on003703)\n\nReferences\r\n----------\r\nAppelhoff, 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. and 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\r\n\r\nNiso, G., Gorgolewski, K. J., Bock, E., Brooks, T. L., Flandin, G., Gramfort, A., Henson, R. N., Jas, M., Litvak, V., Moreau, J., Oostenveld, R., Schoffelen, J., Tadel, F., Wexler, J., Baillet, S. (2018). MEG-BIDS, the brain imaging data structure extended to magnetoencephalography. Scientific Data, 5, 180110. http://doi.org/10.1038/sdata.2018.110\r\n\r\n","bids_version":"1.4.0","sessions_count":null,"publish_date":null,"embedding_dirty":0,"license_tier":"public","zarr_status":"ready","zarr_converted_at":"2026-08-04 19:04:29","zarr_store_count":102,"zarr_index_etag":"53fb47f19491e08735453296297faae6","zarr_source_commit":"f8bc1aebc9392e655c7f230732340c09207977da","archive_status":null,"archive_size":null,"archive_retry_count":0,"records_status":"ready","archive_skip_reason":"dataset 194.5 GB exceeds 100.0 GB archive limit; use direct download","zarr_errors":102,"zarr_failure_count":102,"zarr_deterministic":1,"zarr_failed_at":"2026-08-04 19:04:29","num_dataset_citations":1,"num_datapaper_citations":0,"n_channels":null,"electrode_system":null,"has_hed":0,"hed_version":null,"is_exemplar":0,"bytes_present":208849060547,"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":78538,"recording_duration_min":294,"recording_duration_max":1226,"recording_count":204,"recordings_unavailable":102,"recordings_measured":102,"channel_count_min":314,"channel_count_max":314,"sampling_frequency":null,"power_line_frequency":null,"eeg_reference":null,"placement_scheme":null,"sweep_stamps":"{\"enrichment_updated_at\":\"2026-06-22 12:56:13\",\"metadata_updated_at\":\"2026-06-22 12:56:13\",\"archive_checked_at\":\"2026-06-22 12:57:07\",\"zarr_checked_at\":null,\"records_checked_at\":\"2026-06-22 12:57:45\",\"citations_updated_at\":\"2026-09-08 03:00:52\",\"channel_montage_checked_at\":null,\"hed_checked_at\":\"2026-06-30 04:46:40\",\"data_checked_at\":\"2026-08-02 03:01:14\",\"availability_report_at\":\"2026-07-23 01:14:58\",\"recording_stats_at\":\"2026-09-02 11:32:31\",\"signal_defaults_at\":\"2026-09-02 12:02:39\"}","participants":34,"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":"195 GB","zarr_data_failures":{"count":102,"detail_ref":"zarr/index.json","compacted_by":"migration_0074"},"zarr_index_url":"https://zarr.nemar.org/on003703/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}}