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HED-SCORE example of EEG and iEEG data with annotations of artifacts, seizures and a modulator
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‎dataset_listing.tsv‎

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mrs_2dmrsi 2D sLASER MRSI data from 8 subjects [link](https://zenodo.org/records/7701228) [@markmikkelsen](https://github.com/markmikkelsen) anat, mrs T1w, mrsi
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mrs_biggaba MEGA-PRESS and PRESS MRS data from 12 subjects from one site from the Big GABA project [link](https://www.nitrc.org/projects/biggaba) [@markmikkelsen](https://github.com/markmikkelsen) anat, mrs T1w, mrsref, svs
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mrs_fmrs Functional MRS data involving a pain stimulus task from 15 subjects [link](https://www.nitrc.org/projects/fmrs_2020) [@markmikkelsen](https://github.com/markmikkelsen) anat, mrs T1w, events, mrsref, svs
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xeeg_hed_score EEG and iEEG data with annotations of artifacts, seizures and modulators using HED-SCORE [@dorahermes](https://github.com/dorahermes) eeg, anat, ieeg channels, coordsystem, electrodes, events, ieeg, eeg, T1w

‎xeeg_hed_score/README‎

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# BIDS example with HED-SCORE schema library annotations
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The HED schema library for the Standardized Computer-based Organized Reporting of EEG (SCORE) can be used to add annotations for BIDS datasets. The annotations are machine readable and validated with the BIDS and HED validators.
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The examples are related to the following preprint:
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Attia TP, Robbins K, Beniczky S, Bosch-Bayard J, Delorme A, Lundstrom BN, Rogers C, Rampp S, Valdes-Sosa P, Truong D, Worrell G, Makeig S, Hermes D. Hierarchical Event Descriptor library schema for EEG data annotation. arXiv preprint arXiv:2310.15173. 2023 Oct 4.
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# General information
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This BIDS example set includes 3 subjects where EEG data are annotated according to the HED-SCORE schema library:
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- Example subject with annotated Seizures.
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- Example subject with annotated Artifacts.
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- Example subject with an annotated Modulator (photic stimulation).
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Data are annotated by adding a column for annotations in the _events.tsv. This levels/annotations in this column are defined in the _events.json sidecar as HED tags. When annotations are observed in particular EEG channels, the relevant channels is annotated by including a channel column in the events.tsv file.
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# Source data
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Examples are based on original datasets:
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- sub-eegSeizureTUH The TUH EEG Seizure Corpus. Database: TUH EEG Seizure Corpus (TUSZ), Version: 1.5.3, Patient: 258, Session: s003 (../tuh_eeg_seizure/v1.5.3/edf/dev/01_tcp_ar/002/00000258/s003_2003_07_22)
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- sub-eegArtifactTUH The TUH EEG Artifact Corpus. Database: TUH EEG Artifact Corpus (TUAR), Version: v2.0.0, Patient: 715 , Session: s010 (../tuh_eeg_artifact/edf/01_tcp_ar/007/00000715/s010_2014_08_07)
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- sub-ieegModulator Intracranial EEG dataset collected at Mayo Clinic Rochester, MN during photic stimulation. The photic stimulation is annotated using the HED-SCORE modulator.
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# More information
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HED: https://www.hedtags.org/
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HED schema library for SCORE: https://github.com/hed-standard/hed-schema-library
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Temple University Hospital EEG Data Corpus: https://isip.piconepress.com/projects/tuh_eeg/
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# Contact
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Tal Pal Attia: [email protected]
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Dora Hermes: [email protected]

‎xeeg_hed_score/dataset_description.json‎

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{
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"Name": "HED schema library for SCORE annotations example",
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"BIDSVersion": "1.9.0",
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"HEDVersion": "score_2.0.0",
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"Authors": [
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"Tal Pal Attia",
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"Kay Robbins",
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"Dora Hermes"
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],
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"Acknowledgements": "Kay Robbins, Dung Truong, Arnaud Delorme, and Scott Makeig",
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"Funding": [
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"National Institute of Health Grant R01MH126700 (SM)",
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"National Institute of Health Grant R01MH122258 (DH)"
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],
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"SourceDatasets": [
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{
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"Name": "The TUH EEG Seizure Corpus. Database: TUH EEG Seizure Corpus (TUSZ).",
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"Version": "1.5.3",
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"URL": "https://isip.piconepress.com/projects/tuh_eeg/downloads/"
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},
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{
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"Name": "The TUH EEG Artifact Corpus. Database: TUH EEG Artifact Corpus (TUAR)",
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"Version": "2.0.0.",
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"URL": "https://isip.piconepress.com/projects/tuh_eeg/downloads/"
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}
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],
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"ReferencesAndLinks": ["https://github.com/hed-standard/hed-schema-library",
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"https://www.hedtags.org/",
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"Robbins, Kay, Dung Truong, Stefan Appelhoff, Arnaud Delorme, and Scott Makeig. 'Capturing the nature of events and event context using Hierarchical Event Descriptors (HED).' NeuroImage 245 (2021): 118766.",
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"Robbins, Kay, Dung Truong, Alexander Jones, Ian Callanan, and Scott Makeig. 'Building FAIR functionality: Annotating events in time series data using Hierarchical Event Descriptors (HED).' Neuroinformatics (2021): 1-19.",
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"Obeid, Iyad, and Joseph Picone. 'The temple university hospital EEG data corpus.' Frontiers in neuroscience 10 (2016): 196.",
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"Shah, Vinit, Eva Von Weltin, Silvia Lopez, James Riley McHugh, Lillian Veloso, Meysam Golmohammadi, Iyad Obeid, and Joseph Picone. 'The temple university hospital seizure detection corpus.' Frontiers in neuroinformatics 12 (2018): 83.",
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"Ochal, Domenic, Safwanur Rahman, Sean Ferrell, Tarek Elseify, Iyad Obeid, and Joseph Picone. 'The temple university hospital eeg corpus: Annotation guidelines.' Institute for Signal and Information Processing Report 1, no. 1 (2020).",
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"Buckwalter, G., S. Chhin, S. Rahman, I. Obeid, and J. Picone. 'Recent Advances in the TUH EEG Corpus: Improving the Interrater Agreement for Artifacts and Epileptiform Events.' In 2021 IEEE Signal Processing in Medicine and Biology Symposium (SPMB), pp. 1-3. IEEE, 2021.",
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"Hamid, Ahmed, Katherine Gagliano, Safwanur Rahman, Nikita Tulin, Vincent Tchiong, Iyad Obeid, and Joseph Picone. 'The temple university artifact corpus: An annotated corpus of EEG artifacts.' In 2020 IEEE Signal Processing in Medicine and Biology Symposium (SPMB), pp. 1-4. IEEE, 2020."
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]
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}

‎xeeg_hed_score/participants.json‎

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{
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"participant_id": {
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"LongName": "Participant identifier",
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"Description": "Unique subject identifier"
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}
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}

‎xeeg_hed_score/participants.tsv‎

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participant_id
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sub-ieegModulator
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sub-eegArtifactTUH
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sub-eegSeizureTUH

‎xeeg_hed_score/sub-eegArtifactTUH/ses-eeg01/eeg/.Rapp.history‎

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‎xeeg_hed_score/sub-eegArtifactTUH/ses-eeg01/eeg/sub-eegArtifactTUH_ses-eeg01_task-rest_channels.json‎

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{
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"name": {
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"Description": "REQUIRED. Label of the channel."
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},
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"type": {
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"Description": "REQUIRED. Type of channel; MUST use the channel types listed in bids-specification."
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},
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"units": {
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"Description": "REQUIRED. Physical unit of the value represented in this channel."
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}
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}

‎xeeg_hed_score/sub-eegArtifactTUH/ses-eeg01/eeg/sub-eegArtifactTUH_ses-eeg01_task-rest_channels.tsv‎

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name type units
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FP1-F7 EEG uV
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F7-T3 EEG uV
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T3-T5 EEG uV
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T5-O1 EEG uV
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FP2-F8 EEG uV
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F8-T4 EEG uV
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T4-T6 EEG uV
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T6-O2 EEG uV
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A1-T3 EEG uV
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T3-C3 EEG uV
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C3-CZ EEG uV
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CZ-C4 EEG uV
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C4-T4 EEG uV
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T4-A2 EEG uV
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FP1-F3 EEG uV
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F3-C3 EEG uV
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C3-P3 EEG uV
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P3-O1 EEG uV
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FP2-F4 EEG uV
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F4-C4 EEG uV
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C4-P4 EEG uV
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P4-O2 EEG uV

‎xeeg_hed_score/sub-eegArtifactTUH/ses-eeg01/eeg/sub-eegArtifactTUH_ses-eeg01_task-rest_run-000_eeg.edf‎

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‎xeeg_hed_score/sub-eegArtifactTUH/ses-eeg01/eeg/sub-eegArtifactTUH_ses-eeg01_task-rest_run-000_eeg.json‎

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{
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"TaskName": "rest",
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"TaskDescription": "Subject resting",
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"InstitutionName": "Temple University Hospital",
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"EEGReference": "bipolar banana montage",
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"SamplingFrequency": 250,
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"PowerLineFrequency": 60,
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"SoftwareFilters": "n/a"
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}

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