{"dataset":{"id":"56830","dataset_id":"on004381","name":"Intraoperative EEG dataset during medianus-tibialis stimulation with 8 different rates","description":"This intraoperative EEG dataset comprises somatosensory evoked potentials (SEP) recorded from 14 adult and 4 pediatric subjects during median and tibial nerve stimulation at 8 different stimulation rates. The dataset was collected to optimize signal-to-noise ratio in short-duration SEP recordings through systematic variation of stimulus repetition rates, with both raw continuous EEG data and processed derivatives provided for 34 median SEP and 32 tibial SEP sessions.","owner_user_id":15,"status":"active","github_repo":"nemarDatasets/on004381","concept_doi":"10.82901/nemar.on004381","latest_version_doi":"10.82901/nemar.on004381.v1.0.0","created_at":"2026-06-24 05:31:49","updated_at":"2026-07-10 22:30:21","zenodo_concept_id":null,"is_sandbox":0,"visibility":"public","ezid_status":"public","enrichment_json":"{\n  \"version\": \"2.0\",\n  \"pipeline_stage\": \"validated\",\n  \"title\": \"Intraoperative EEG dataset during medianus-tibialis stimulation with 8 different rates\",\n  \"description\": \"This intraoperative EEG dataset comprises somatosensory evoked potentials (SEP) recorded from 14 adult and 4 pediatric subjects during median and tibial nerve stimulation at 8 different stimulation rates. The dataset was collected to optimize signal-to-noise ratio in short-duration SEP recordings through systematic variation of stimulus repetition rates, with both raw continuous EEG data and processed derivatives provided for 34 median SEP and 32 tibial SEP sessions.\",\n  \"methods_description\": \"EEG data were recorded continuously during median and tibial nerve stimulation at varying rates. Offline processing included high-pass filtering at 200 Hz, stimulus artifact detection via local peak detection, and sweep definition with post-stimulus recording lengths of 50 ms for median SEP and 100 ms for tibial SEP. Data were resampled to 1200 Hz, and sweeps with amplitude exceeding 10 µV were classified as artifact-ridden and excluded.\",\n  \"license\": \"CC0\",\n  \"dataset_type\": \"raw\",\n  \"authors\": {\n    \"Giorgio Selmin\": {\n      \"orcid\": \"0000-0002-4252-6495\"\n    },\n    \"Vasileios Dimakopoulos\": {\n      \"orcid\": \"0000-0001-9490-565X\"\n    },\n    \"Niklaus Krayenbühl\": {},\n    \"Luca Regli\": {},\n    \"Johannes Sarnthein\": {\n      \"orcid\": \"0000-0001-9141-381X\"\n    }\n  },\n  \"keywords\": [\n    {\n      \"term\": \"EEG\"\n    },\n    {\n      \"term\": \"somatosensory evoked potentials\"\n    },\n    {\n      \"term\": \"intraoperative monitoring\"\n    },\n    {\n      \"term\": \"median nerve stimulation\"\n    },\n    {\n      \"term\": \"tibial nerve stimulation\"\n    },\n    {\n      \"term\": \"signal-to-noise ratio\"\n    }\n  ],\n  \"related_identifiers\": [\n    {\n      \"identifier\": \"https://github.com/nemarDatasets/on004381\",\n      \"identifier_type\": \"URL\",\n      \"relation_type\": \"IsDescribedBy\"\n    },\n    {\n      \"identifier\": \"https://nemar.org/dataexplorer/detail?dataset_id=on004381\",\n      \"identifier_type\": \"URL\",\n      \"relation_type\": \"IsDescribedBy\"\n    },\n    {\n      \"identifier\": \"10.1016/j.clinph.2023.03.008\",\n      \"identifier_type\": \"DOI\",\n      \"relation_type\": \"IsDescribedBy\"\n    },\n    {\n      \"identifier\": \"10.18112/openneuro.ds004381.v1.0.2\",\n      \"identifier_type\": \"DOI\",\n      \"relation_type\": \"IsDerivedFrom\"\n    }\n  ],\n  \"funding_references\": [\n    {\n      \"funder_name\": \"Alexander S. Onassis Public Benefit Foundation Scholarship\"\n    },\n    {\n      \"funder_name\": \"Swiss National Science Foundation\",\n      \"award_number\": \"204651\"\n    },\n    {\n      \"funder_name\": \"Alexander S. Onassis Public Benefit Foundation\"\n    }\n  ],\n  \"resource_type_general\": \"Dataset\",\n  \"resource_type_specific\": \"EEG Dataset\",\n  \"modalities\": [\n    \"eeg\"\n  ],\n  \"sizes\": [\n    \"8.3 GB (446 files)\"\n  ],\n  \"formats\": [\n    \".edf\",\n    \".json\",\n    \".m\",\n    \".md\",\n    \".tsv\",\n    \".yml\"\n  ],\n  \"source_hash\": \"9c3f955a8c9c099c495496e7c6f65d3bd642fd4ea2121b75fbcd7a50b53bd8b2\"\n}","last_activity_at":"2026-06-24 05:31:49","source":"openneuro","source_id":"ds004381","subject_count":18,"modalities":"eeg","age_min":4,"age_max":87,"file_size":13275544004,"total_files":2478,"tasks":"sepRate","metadata_columns_error":null,"staleness_warn_stage":null,"staleness_admin_notified_at":null,"authors":"Giorgio Selmin, Vasileios Dimakopoulos, Niklaus Krayenbühl, Luca Regli, Johannes Sarnthein","license":"CC0","readme":"[![DOI](https://img.shields.io/badge/DOI-10.82901%2Fnemar.on004381-blue)](https://doi.org/10.82901/nemar.on004381)\n\n# Intraoperative EEG dataset during medianus-tibialis stimulation with 8 different rates\nThis dataset was obtained from the publication [1] wherein we varyied the stimulus repetition rate and recorded medianus and tibial nerve SEP. \nWe randomly sampled a number of sweeps corresponding to recording durations up to 20 s and calculated the signal-to-noise ratio (SNR).\n\nThere are 14 adults subjects and 4 children subjects with continuous EEG data split in sessions (tibial left/right, medianus left/right) and runs (1 run for each stimulation rate).\nWe also provide processed data (derivatives) for all the sessions. \nIn total there are 34 medianus SEP and 32 tibial SEP sessions.\n \n## Repository structure\n\n### Main directory (SEP rate/)\nContains metadata files in the BIDS standard about the participants and the study. Folders are explained below.\n\n### Subfolders\n* SEP rate/sub-**/\nContains folders for each subject, named sub-<subject number> and session information.\n* SEP rate/sub-**/ses-01/eeg\nContains the raw eeg data in .edf format for each subject. \nEach *eeg.edf file contains EEG data from one stimulation rate (see scans.tsv column stimRate).\nDetails about the channels are given in the corresponding .tsv file. \n* SEP rate/derivatives\nContains folders for each subject,named sub-<subject number> and session information that include processed data\n* SEP rate/derivatives/sub-**/ses-01/eeg/\nContains processed data for each subject.\n\n\n# Note from the paper\n\"The offline data processing used the continuous EEG that was recorded in parallel to the SEP recordings. \nData analysis was performed with custom scripts in Matlab (www.mathworks.com). To detect the SEP stimulation artefact, \nwe first filtered the EEG (high pass cutoff = 200 Hz) and performed local peak detection (minimum peak prominence between peaks = 30 ms,\nminimum peak width = 4 ms, samples = 0.2 ms). We used the times of the detected stimulus artifact as triggers to define sweeps with \npost-stimulus recording sweep length 50 ms for medianus SEP and 100 ms for tibial SEP. We resampled the data to sampling rate 1200 Hz before\nfurther processing. We classified sweeps with amplitude > 10 µV as artefact-ridden and excluded them from further analysis.\"\n\nBIDS Conversion\n---------------\nbids-starter-kid and custom Matlab scripts were used to convert the dataset into BIDS format. \n\n\nReferences\n----------\n[1] Dimakopoulos V, Selmin G, Regli L, Sarnthein J, Optimization of signal-to-noise ratio in short-duration SEP recordings by variation of stimulation rate, Clinical Neurophysiology, 2023, ISSN 1388-2457, https://doi.org/10.1016/j.clinph.2023.03.008.\n\n\n","bids_version":"1.4.0","sessions_count":4,"publish_date":null,"embedding_dirty":0,"license_tier":"public","zarr_status":"ready","zarr_converted_at":"2026-08-07 04:58:10","zarr_store_count":763,"zarr_index_etag":"5ad13ca9cc0b0867ea41f9337acef2fa","zarr_source_commit":"45c9a0385791a53454bc9fccf8aa397bfc17510d","archive_status":"ready","archive_size":6519931540,"archive_retry_count":0,"records_status":"ready","archive_skip_reason":null,"zarr_errors":7,"zarr_failure_count":7,"zarr_deterministic":1,"zarr_failed_at":"2026-08-07 04:58:10","num_dataset_citations":0,"num_datapaper_citations":5,"n_channels":4,"electrode_system":"other","has_hed":0,"hed_version":null,"is_exemplar":0,"bytes_present":8296260776,"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":72668,"recording_duration_min":22,"recording_duration_max":233,"recording_count":770,"recordings_unavailable":7,"recordings_measured":763,"channel_count_min":4,"channel_count_max":10,"sampling_frequency":20000,"power_line_frequency":50,"eeg_reference":"AFz","placement_scheme":null,"sweep_stamps":"{\"enrichment_updated_at\":\"2026-06-24 05:39:34\",\"metadata_updated_at\":\"2026-06-24 05:39:45\",\"archive_checked_at\":\"2026-06-24 05:46:58\",\"zarr_checked_at\":null,\"records_checked_at\":\"2026-06-24 05:40:21\",\"citations_updated_at\":\"2026-09-08 03:00:50\",\"channel_montage_checked_at\":\"2026-06-28 23:23:57\",\"hed_checked_at\":\"2026-06-30 04:57:57\",\"data_checked_at\":\"2026-08-09 03:00:44\",\"availability_report_at\":\"2026-07-23 01:18:29\",\"recording_stats_at\":\"2026-09-02 11:32:44\",\"signal_defaults_at\":\"2026-09-02 12:11:38\"}","participants":18,"num_citations":5,"latest_version":"v1.0.0","zarr_verify_status":null,"zarr_verified_at":null,"owner_username":"nemarAdmin","owner_github":"nemarAdmin","file_size_formatted":"12.36 GB","zarr_data_failures":{"count":7,"detail_ref":"zarr/index.json","compacted_by":"migration_0074"},"zarr_index_url":"https://zarr.nemar.org/on004381/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}}