WRCC2023_MI_A/B/C from Harvard Dataverse, and the card at 32 datasets

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README.md

@@ -17,57 +17,64 @@ viewer: false
 
 Unmodified copies of public EEG motor imagery datasets in the [MOABB](https://moabb.neurotechx.com) cache layout. Files extracted from an upstream archive keep their bytes; Weibo2014's also take the names MOABB gives them. Zhou2016's saved Zenodo record is the one generated file; see its section.
 
-**29 datasets · 815 subjects · 1,891 sessions · 633 GB in 4,051 files · 10 original hosts**
+**32 datasets · 841 subjects · 1,917 sessions · 637 GB in 4,077 files · 10 original hosts**
 
 - [At a glance](#at-a-glance)
 - [Datasets](#datasets)
 - [Verification](#verification)
-- [Loading](#loading): [BNCI2014_001](#bnci2014_001) · [BNCI2014_002](#bnci2014_002) · [BNCI2014_004](#bnci2014_004) · [BNCI2015_001](#bnci2015_001) · [Beetl2021_A](#beetl2021_a) · [Brandl2020](#brandl2020) · [Cho2017](#cho2017) · [Dreyer2023](#dreyer2023) · [Farabbi2020](#farabbi2020) · [GrosseWentrup2009](#grossewentrup2009) · [GuttmannFlury2025_MI](#guttmannflury2025_mi) · [Jia2019](#jia2019) · [Kaya2018](#kaya2018) · [Kumar2024](#kumar2024) · [Lee2019_MI](#lee2019_mi) · [Leeuwis2021](#leeuwis2021) · [Liu2024](#liu2024) · [Pan2023](#pan2023) · [Pan2025](#pan2025) · [PhysionetMI](#physionetmi) · [Rozado2015](#rozado2015) · [Shin2022](#shin2022) · [Stieger2021](#stieger2021) · [Vagaja2023](#vagaja2023) · [Wang2025](#wang2025) · [Weibo2014](#weibo2014) · [Yang2025](#yang2025) · [Zhou2016](#zhou2016) · [Zhou2020](#zhou2020)
+- [Loading](#loading): [BNCI2014_001](#bnci2014_001) · [BNCI2014_002](#bnci2014_002) · [BNCI2014_004](#bnci2014_004) · [BNCI2015_001](#bnci2015_001) · [Beetl2021_A](#beetl2021_a) · [Brandl2020](#brandl2020) · [Cho2017](#cho2017) · [Dreyer2023](#dreyer2023) · [Farabbi2020](#farabbi2020) · [GrosseWentrup2009](#grossewentrup2009) · [GuttmannFlury2025_MI](#guttmannflury2025_mi) · [Jia2019](#jia2019) · [Kaya2018](#kaya2018) · [Kumar2024](#kumar2024) · [Lee2019_MI](#lee2019_mi) · [Leeuwis2021](#leeuwis2021) · [Liu2024](#liu2024) · [Pan2023](#pan2023) · [Pan2025](#pan2025) · [PhysionetMI](#physionetmi) · [Rozado2015](#rozado2015) · [Shin2022](#shin2022) · [Stieger2021](#stieger2021) · [Vagaja2023](#vagaja2023) · [WRCC2023_MI_A](#wrcc2023_mi_a) · [WRCC2023_MI_B](#wrcc2023_mi_b) · [WRCC2023_MI_C](#wrcc2023_mi_c) · [Wang2025](#wang2025) · [Weibo2014](#weibo2014) · [Yang2025](#yang2025) · [Zhou2016](#zhou2016) · [Zhou2020](#zhou2020)
 - [Citation](#citation)
 
 ## At a glance
 
-- **60%** of the bytes are one dataset: Stieger2021 is 377 GB and holds 62 of the 815 subjects (8%).
-- **25 GB** holds 449 subjects (55%), across the 15 datasets that take under 0.1 GB per subject: BNCI2014_001, BNCI2014_002, BNCI2014_004, Dreyer2023, Jia2019, Kaya2018, Leeuwis2021, Liu2024, Pan2023, Pan2025, PhysionetMI, Rozado2015, Shin2022, Vagaja2023 and Zhou2016.
-- **5 datasets** do not allow modified copies to be shared: BNCI2014_001, BNCI2014_002 and BNCI2014_004 (CC BY-ND 4.0; 001 and 004 are BCI Competition IV data sets 2a and 2b), and BNCI2015_001 and Brandl2020 (CC BY-NC-ND 4.0). A filtered or epoched copy of them may not be distributed. The other 24 allow it, with attribution (CC BY 4.0, ODC-By 1.0) or without conditions (CC0 1.0).
-- **7 datasets** keep the names MOABB caches them under, mostly their host's numeric file IDs with no extension: Jia2019, Kumar2024, Leeuwis2021, Liu2024, Pan2023, Pan2025 and Shin2022, 303 files in all. Searching the Files tab for an upstream file name will not find them.
+- **59%** of the bytes are one dataset: Stieger2021 is 377 GB and holds 62 of the 841 subjects (7%).
+- **25 GB** holds 449 subjects (53%), across the 15 datasets that take under 0.1 GB per subject: BNCI2014_001, BNCI2014_002, BNCI2014_004, Dreyer2023, Jia2019, Kaya2018, Leeuwis2021, Liu2024, Pan2023, Pan2025, PhysionetMI, Rozado2015, Shin2022, Vagaja2023 and Zhou2016.
+- **5 datasets** do not allow modified copies to be shared: BNCI2014_001, BNCI2014_002 and BNCI2014_004 (CC BY-ND 4.0; 001 and 004 are BCI Competition IV data sets 2a and 2b), and BNCI2015_001 and Brandl2020 (CC BY-NC-ND 4.0). A filtered or epoched copy of them may not be distributed. The other 27 allow it, with attribution (CC BY 4.0, ODC-By 1.0) or without conditions (CC0 1.0).
+- **10 datasets** keep the names MOABB caches them under, mostly their host's numeric file IDs with no extension: Jia2019, Kumar2024, Leeuwis2021, Liu2024, Pan2023, Pan2025, Shin2022 and the three WRCC2023 sets, 329 files in all. Searching the Files tab for an upstream file name will not find them.
 - **10 hosts** served the originals: BNCI Horizon, Zenodo, figshare, Harvard Dataverse, DataverseNL, GigaDB, OSF, PhysioNet, DepositOnce and Hugging Face. Files were checked against MD5, SHA-1, SHA-256, CRC-32 or S3 ETag checksums; see [Verification](#verification).
-- **3 to 128** EEG channels, from BNCI2014_004 to GrosseWentrup2009, sampled at 160 Hz (PhysionetMI) to 1000 Hz, across the 24 datasets the verification loaded. Recordings come in at least eight formats: MAT, EDF, BDF, EEGLAB, BrainVision, XDF, NumPy and CSV.
+- **3 to 128** EEG channels, from BNCI2014_004 to GrosseWentrup2009, sampled at 160 Hz (PhysionetMI) to 1000 Hz, across the 32 datasets the verification loaded. Recordings come in at least eight formats: MAT, EDF, BDF, EEGLAB, BrainVision, XDF, NumPy and CSV.
 - **9 of 106** motor imagery datasets in MOABB could not be fetched by a script on 7 Oct 2026: a 404, four Mendeley 403s, two licenses that must be accepted in code, a Harvard Dataverse 400 and a loader error. None of them is in this mirror.
 
 ## Datasets
 
-| # | Dataset | Subjects | Sessions | Size | Source | License |
-| ---: | --- | ---: | ---: | ---: | --- | --- |
-| 1 | BNCI2014_001 | 9 | 18 | 0.78 GB | [BNCI Horizon](https://bnci-horizon-2020.eu/database/data-sets) 001-2014 (BCI Competition IV, data set 2a) | [CC BY-ND 4.0](https://creativecommons.org/licenses/by-nd/4.0/), licensor: Institute for Knowledge Discovery, Graz University of Technology |
-| 2 | BNCI2014_002 | 14 | 14 | 0.89 GB | [BNCI Horizon](https://bnci-horizon-2020.eu/database/data-sets) 002-2014 | [CC BY-ND 4.0](https://creativecommons.org/licenses/by-nd/4.0/), licensor: Institute for Knowledge Discovery, Graz University of Technology |
-| 3 | BNCI2014_004 | 9 | 45 | 0.48 GB | [BNCI Horizon](https://bnci-horizon-2020.eu/database/data-sets) 004-2014 (BCI Competition IV, data set 2b) | [CC BY-ND 4.0](https://creativecommons.org/licenses/by-nd/4.0/), licensor: Institute for Knowledge Discovery, Graz University of Technology |
-| 4 | BNCI2015_001 | 12 | 28 | 1.83 GB | [BNCI Horizon](https://bnci-horizon-2020.eu/database/data-sets) 001-2015 | [CC BY-NC-ND 4.0](https://creativecommons.org/licenses/by-nc-nd/4.0/), licensor: Institute for Knowledge Discovery, Graz University of Technology |
-| 5 | Beetl2021_A | 3 | 3 | 0.45 GB | [figshare](https://doi.org/10.6084/m9.figshare.16586213.v1) `finalMI`, subjects 1–3 extracted from its single archive, and the [final-phase labels](https://doi.org/10.6084/m9.figshare.21602622.v1) | [CC BY 4.0](https://creativecommons.org/licenses/by/4.0/) |
-| 6 | Brandl2020 | 16 | 16 | 11.4 GB | [DepositOnce](https://doi.org/10.14279/depositonce-9827.2), TU Berlin | [CC BY-NC-ND 4.0](https://creativecommons.org/licenses/by-nc-nd/4.0/) |
-| 7 | Cho2017 | 52 | 52 | 10.7 GB | [GigaDB](https://doi.org/10.5524/100295) 100295 | [CC BY 4.0](https://creativecommons.org/licenses/by/4.0/) |
-| 8 | Dreyer2023 | 87 | 87 | 5.5 GB | [OSF](https://osf.io/8tdk5/), MOABB's BIDS copy of [Zenodo](https://doi.org/10.5281/zenodo.8089820) | [CC BY 4.0](https://creativecommons.org/licenses/by/4.0/) |
-| 9 | Farabbi2020 | 12 | 36 | 2.5 GB | [Zenodo](https://doi.org/10.5281/zenodo.5882500) | [CC BY 4.0](https://creativecommons.org/licenses/by/4.0/) |
-| 10 | GrosseWentrup2009 | 10 | 10 | 7.8 GB | [Zenodo](https://doi.org/10.5281/zenodo.1217449) | [CC BY 4.0](https://creativecommons.org/licenses/by/4.0/) |
-| 11 | GuttmannFlury2025_MI | 31 | 63 | 26.2 GB | MOABB's [Zenodo](https://zenodo.org/records/18970793) copy of [Synapse](https://doi.org/10.7303/syn64005218), motor imagery part | [CC0 1.0](https://creativecommons.org/publicdomain/zero/1.0/) |
-| 12 | Jia2019 | 15 | 15 | 1.3 GB | [figshare](https://doi.org/10.6084/m9.figshare.7636301), the 30 experiment 1 files MOABB loads | [CC BY 4.0](https://creativecommons.org/licenses/by/4.0/) |
-| 13 | Kaya2018 | 7 | 17 | 0.64 GB | [figshare](https://doi.org/10.6084/m9.figshare.c.3917698.v1), the 17 CLA recordings MOABB loads | [CC0 1.0](https://creativecommons.org/publicdomain/zero/1.0/) |
-| 14 | Kumar2024 | 18 | 108 | 4.5 GB | [Zenodo](https://doi.org/10.5281/zenodo.10694880), its single archive | [CC BY 4.0](https://creativecommons.org/licenses/by/4.0/) |
-| 15 | Lee2019_MI | 54 | 108 | 65 GB | [GigaDB](https://doi.org/10.5524/100542) 100542, motor imagery files only | [CC0 1.0](https://creativecommons.org/publicdomain/zero/1.0/) |
-| 16 | Leeuwis2021 | 55 | 55 | 5.1 GB | [DataverseNL](https://doi.org/10.34894/Z7ZVOD) version 1.0, the EEG files | [CC BY 4.0](https://creativecommons.org/licenses/by/4.0/) |
-| 17 | Liu2024 | 50 | 50 | 0.46 GB | [figshare](https://doi.org/10.6084/m9.figshare.21679035), the EDF archive and two BIDS tables | [CC BY 4.0](https://creativecommons.org/licenses/by/4.0/) |
-| 18 | Pan2023 | 14 | 28 | 0.74 GB | [Harvard Dataverse](https://doi.org/10.7910/DVN/251NOW) version 1.3 | [CC0 1.0](https://creativecommons.org/publicdomain/zero/1.0/) |
-| 19 | Pan2025 | 10 | 20 | 0.80 GB | [Harvard Dataverse](https://doi.org/10.7910/DVN/GH74ZG) version 1.0 | [CC0 1.0](https://creativecommons.org/publicdomain/zero/1.0/) |
-| 20 | PhysionetMI | 109 | 109 | 3.6 GB | [PhysioNet](https://doi.org/10.13026/C28G6P) eegmmidb 1.0.0, all 14 runs | [ODC-By 1.0](https://opendatacommons.org/licenses/by/1-0/) |
-| 21 | Rozado2015 | 30 | 30 | 2.4 GB | [Harvard Dataverse](https://doi.org/10.7910/DVN/28932), extracted from its two RAR archives | [CC0 1.0](https://creativecommons.org/publicdomain/zero/1.0/) |
-| 22 | Shin2022 | 10 | 10 | 0.35 GB | [figshare](https://doi.org/10.6084/m9.figshare.20383716.v1), its single archive | [CC BY 4.0](https://creativecommons.org/licenses/by/4.0/) |
-| 23 | Stieger2021 | 62 | 598 | 377 GB | [figshare](https://doi.org/10.6084/m9.figshare.13123148.v1) | [CC BY 4.0](https://creativecommons.org/licenses/by/4.0/) |
-| 24 | Vagaja2023 | 26 | 26 | 1.9 GB | [Zenodo](https://doi.org/10.5281/zenodo.8086086), the motor imagery recordings extracted from `GROUPS.zip` | [CC BY 4.0](https://creativecommons.org/licenses/by/4.0/) |
-| 25 | Wang2025 | 15 | 30 | 3.8 GB | [Hugging Face](https://huggingface.co/datasets/Jiaheng-Wang/ZJU-MI-EEG/tree/e60d6a740395cdedb18a621b8457aaf29f54037c/MI4) Jiaheng-Wang/ZJU-MI-EEG at `e60d6a7`, MI4 part | [ODC-By 1.0](https://opendatacommons.org/licenses/by/1-0/) |
-| 26 | Weibo2014 | 10 | 10 | 4.3 GB | [Harvard Dataverse](https://doi.org/10.7910/DVN/27306), extracted from its three archives | [CC0 1.0](https://creativecommons.org/publicdomain/zero/1.0/) |
-| 27 | Yang2025, two-class part | 51 | 153 | 74.6 GB | [figshare+](https://doi.org/10.25452/figshare.plus.22671172.v5), extracted from its single archive | [CC BY 4.0](https://creativecommons.org/licenses/by/4.0/) |
-| 28 | Zhou2016 | 4 | 12 | 0.13 GB | MOABB's [Zenodo](https://zenodo.org/records/16534752) BIDS copy of [figshare](https://doi.org/10.6084/m9.figshare.2061654.v2) | [CC BY 4.0](https://creativecommons.org/licenses/by/4.0/) |
-| 29 | Zhou2020 | 20 | 140 | 17.6 GB | MOABB's [Zenodo](https://zenodo.org/records/18988317) copy of [IEEE DataPort](https://doi.org/10.21227/f1c7-7x89) | [CC BY 4.0](https://creativecommons.org/licenses/by/4.0/) |
+| # | Dataset | Classes | Subjects | Sessions | Trials per class per session | EEG channels | Rate (Hz) | Participants | Size | Source | License |
+| ---: | --- | --- | ---: | ---: | --- | ---: | ---: | --- | ---: | --- | --- |
+| 1 | BNCI2014_001 | `left_hand`, `right_hand`, `feet`, `tongue` | 9 | 18 | 72 in subjects 1–2 | 22 | 250 | healthy | 0.78 GB | [BNCI Horizon](https://bnci-horizon-2020.eu/database/data-sets) 001-2014 (BCI Competition IV, data set 2a) | [CC BY-ND 4.0](https://creativecommons.org/licenses/by-nd/4.0/), licensor: Institute for Knowledge Discovery, Graz University of Technology |
+| 2 | BNCI2014_002 | `right_hand`, `feet` | 14 | 14 | 80 in subjects 1–2 | 15 | 512 |  | 0.89 GB | [BNCI Horizon](https://bnci-horizon-2020.eu/database/data-sets) 002-2014 | [CC BY-ND 4.0](https://creativecommons.org/licenses/by-nd/4.0/), licensor: Institute for Knowledge Discovery, Graz University of Technology |
+| 3 | BNCI2014_004 | `left_hand`, `right_hand` | 9 | 45 | 60–80 in subjects 1–2 | 3 | 250 | healthy | 0.48 GB | [BNCI Horizon](https://bnci-horizon-2020.eu/database/data-sets) 004-2014 (BCI Competition IV, data set 2b) | [CC BY-ND 4.0](https://creativecommons.org/licenses/by-nd/4.0/), licensor: Institute for Knowledge Discovery, Graz University of Technology |
+| 4 | BNCI2015_001 | `right_hand`, `feet` | 12 | 28 | 100 in subjects 1–2 | 13 | 512 |  | 1.83 GB | [BNCI Horizon](https://bnci-horizon-2020.eu/database/data-sets) 001-2015 | [CC BY-NC-ND 4.0](https://creativecommons.org/licenses/by-nc-nd/4.0/), licensor: Institute for Knowledge Discovery, Graz University of Technology |
+| 5 | Beetl2021_A | `left_hand`, `right_hand`, `feet`, `rest` | 3 | 3 | 74–75 `left_hand`, 124–125 `right_hand`, 24–25 `feet`, 73–75 `rest` | 63 | 500 | healthy | 0.45 GB | [figshare](https://doi.org/10.6084/m9.figshare.16586213.v1) `finalMI`, subjects 1–3 extracted from its single archive, and the [final-phase labels](https://doi.org/10.6084/m9.figshare.21602622.v1) | [CC BY 4.0](https://creativecommons.org/licenses/by/4.0/) |
+| 6 | Brandl2020 | `left_hand`, `right_hand` | 16 | 16 | 252 in subjects 1–2 | 63 | 1000 | healthy | 11.4 GB | [DepositOnce](https://doi.org/10.14279/depositonce-9827.2), TU Berlin | [CC BY-NC-ND 4.0](https://creativecommons.org/licenses/by-nc-nd/4.0/) |
+| 7 | Cho2017 | `left_hand`, `right_hand` | 52 | 52 | 100 in subjects 1–2 | 64 | 512 | healthy | 10.7 GB | [GigaDB](https://doi.org/10.5524/100295) 100295 | [CC BY 4.0](https://creativecommons.org/licenses/by/4.0/) |
+| 8 | Dreyer2023 | `left_hand`, `right_hand` | 87 | 87 | 120 in subjects 1–2 | 27 | 512 | healthy | 5.5 GB | [OSF](https://osf.io/8tdk5/), MOABB's BIDS copy of [Zenodo](https://doi.org/10.5281/zenodo.8089820) | [CC BY 4.0](https://creativecommons.org/licenses/by/4.0/) |
+| 9 | Farabbi2020 | `left_hand`, `right_hand` | 12 | 36 | 80 | 32 | 250 | healthy | 2.5 GB | [Zenodo](https://doi.org/10.5281/zenodo.5882500) | [CC BY 4.0](https://creativecommons.org/licenses/by/4.0/) |
+| 10 | GrosseWentrup2009 | `left_hand`, `right_hand` | 10 | 10 | 150 in subjects 1–2 | 128 | 500 | healthy | 7.8 GB | [Zenodo](https://doi.org/10.5281/zenodo.1217449) | [CC BY 4.0](https://creativecommons.org/licenses/by/4.0/) |
+| 11 | GuttmannFlury2025_MI | `left_hand`, `right_hand` | 31 | 63 | 20 in subjects 1–2 | 60 | 1000 | healthy | 26.2 GB | MOABB's [Zenodo](https://zenodo.org/records/18970793) copy of [Synapse](https://doi.org/10.7303/syn64005218), motor imagery part | [CC0 1.0](https://creativecommons.org/publicdomain/zero/1.0/) |
+| 12 | Jia2019 | `left_hand`, `right_hand` | 15 | 15 | 40 | 63 | 512 | stroke patients | 1.3 GB | [figshare](https://doi.org/10.6084/m9.figshare.7636301), the 30 experiment 1 files MOABB loads | [CC BY 4.0](https://creativecommons.org/licenses/by/4.0/) |
+| 13 | Kaya2018 | `left_hand`, `right_hand`, `passive` | 7 | 17 | 302–322 `left_hand`, 314–340 `right_hand`, 318–324 `passive` in subjects 1–2 | 19 | 200 |  | 0.64 GB | [figshare](https://doi.org/10.6084/m9.figshare.c.3917698.v1), the 17 CLA recordings MOABB loads | [CC0 1.0](https://creativecommons.org/publicdomain/zero/1.0/) |
+| 14 | Kumar2024 | `left_hand`, `right_hand` | 18 | 108 | 28–40 | 22 | 512 | healthy | 4.5 GB | [Zenodo](https://doi.org/10.5281/zenodo.10694880), its single archive | [CC BY 4.0](https://creativecommons.org/licenses/by/4.0/) |
+| 15 | Lee2019_MI | `left_hand`, `right_hand` | 54 | 108 | 50 in subjects 1–2 | 62 | 1000 | healthy | 65 GB | [GigaDB](https://doi.org/10.5524/100542) 100542, motor imagery files only | [CC0 1.0](https://creativecommons.org/publicdomain/zero/1.0/) |
+| 16 | Leeuwis2021 | `left_hand`, `right_hand` | 55 | 55 | 80 | 16 | 250 | healthy | 5.1 GB | [DataverseNL](https://doi.org/10.34894/Z7ZVOD) version 1.0, the EEG files | [CC BY 4.0](https://creativecommons.org/licenses/by/4.0/) |
+| 17 | Liu2024 | `left_hand`, `right_hand` | 50 | 50 | 20 | 29 | 500 | acute stroke patients | 0.46 GB | [figshare](https://doi.org/10.6084/m9.figshare.21679035), the EDF archive and two BIDS tables | [CC BY 4.0](https://creativecommons.org/licenses/by/4.0/) |
+| 18 | Pan2023 | `left_hand`, `right_hand` | 14 | 28 | 60 | 28 | 250 | healthy | 0.74 GB | [Harvard Dataverse](https://doi.org/10.7910/DVN/251NOW) version 1.3 | [CC0 1.0](https://creativecommons.org/publicdomain/zero/1.0/) |
+| 19 | Pan2025 | `left_hand`, `right_hand` | 10 | 20 | 62–95 `left_hand`, 87–138 `right_hand` | 28 | 250 | healthy | 0.80 GB | [Harvard Dataverse](https://doi.org/10.7910/DVN/GH74ZG) version 1.0 | [CC0 1.0](https://creativecommons.org/publicdomain/zero/1.0/) |
+| 20 | PhysionetMI | `left_hand`, `right_hand`, `feet`, `hands`, `rest` | 109 | 109 | 23 `left_hand`, 22 `right_hand`, 21–24 `feet`, 21–24 `hands`, 84 `rest` in subjects 1–2 | 64 | 160 | healthy | 3.6 GB | [PhysioNet](https://doi.org/10.13026/C28G6P) eegmmidb 1.0.0, all 14 runs | [ODC-By 1.0](https://opendatacommons.org/licenses/by/1-0/) |
+| 21 | Rozado2015 | `left_hand`, `rest` | 30 | 30 | 26 `left_hand`, 24 `rest` in subjects 1–2 | 32 | 512 |  | 2.4 GB | [Harvard Dataverse](https://doi.org/10.7910/DVN/28932), extracted from its two RAR archives | [CC0 1.0](https://creativecommons.org/publicdomain/zero/1.0/) |
+| 22 | Shin2022 | `left_hand`, `right_hand` | 10 | 10 | 127–132 `left_hand`, 126–132 `right_hand` | 16 | 250 | healthy | 0.35 GB | [figshare](https://doi.org/10.6084/m9.figshare.20383716.v1), its single archive | [CC BY 4.0](https://creativecommons.org/licenses/by/4.0/) |
+| 23 | Stieger2021 | `left_hand`, `right_hand`, `both_hand`, `rest` | 62 | 598 | 45–76 `left_hand`, 60–76 `right_hand`, 45–71 `both_hand`, 24–86 `rest` in subjects 1–2 | 60 | 1000 | healthy | 377 GB | [figshare](https://doi.org/10.6084/m9.figshare.13123148.v1) | [CC BY 4.0](https://creativecommons.org/licenses/by/4.0/) |
+| 24 | Vagaja2023 | `left_hand`, `right_hand` | 26 | 26 | 20 | 32 | 500 | healthy | 1.9 GB | [Zenodo](https://doi.org/10.5281/zenodo.8086086), the motor imagery recordings extracted from `GROUPS.zip` | [CC BY 4.0](https://creativecommons.org/licenses/by/4.0/) |
+| 25 | WRCC2023_MI_A | `left_hand`, `right_hand`, `feet` | 9 | 9 | 30 | 59 | 1000 | 2 stroke patients, not identified | 1.5 GB | [Harvard Dataverse](https://doi.org/10.7910/DVN/J9JFES) version 1.0 | [CC0 1.0](https://creativecommons.org/publicdomain/zero/1.0/) |
+| 26 | WRCC2023_MI_B | `left_hand`, `right_hand`, `feet` | 9 | 9 | 30 | 59 | 1000 | 2 stroke patients, not identified | 1.5 GB | [Harvard Dataverse](https://doi.org/10.7910/DVN/HFNWRX) version 1.0 | [CC0 1.0](https://creativecommons.org/publicdomain/zero/1.0/) |
+| 27 | WRCC2023_MI_C | `left_hand`, `right_hand`, `feet` | 8 | 8 | 30 | 59 | 1000 | 2 stroke patients, not identified | 1.4 GB | [Harvard Dataverse](https://doi.org/10.7910/DVN/G8FBHH) version 1.0 | [CC0 1.0](https://creativecommons.org/publicdomain/zero/1.0/) |
+| 28 | Wang2025 | `left_hand`, `right_hand`, `feet`, `tongue` | 15 | 30 | 100 | 62 | 256 | healthy | 3.8 GB | [Hugging Face](https://huggingface.co/datasets/Jiaheng-Wang/ZJU-MI-EEG/tree/e60d6a740395cdedb18a621b8457aaf29f54037c/MI4) Jiaheng-Wang/ZJU-MI-EEG at `e60d6a7`, MI4 part | [ODC-By 1.0](https://opendatacommons.org/licenses/by/1-0/) |
+| 29 | Weibo2014 | `left_hand`, `right_hand`, `feet`, `hands`, `left_hand_right_foot`, `rest`, `right_hand_left_foot` | 10 | 10 | 80 in subjects 1–2 | 60 | 200 | healthy | 4.3 GB | [Harvard Dataverse](https://doi.org/10.7910/DVN/27306), extracted from its three archives | [CC0 1.0](https://creativecommons.org/publicdomain/zero/1.0/) |
+| 30 | Yang2025, two-class part | `left_hand`, `right_hand` | 51 | 153 | 100 in subjects 1–2 | 59 | 1000 | healthy | 74.6 GB | [figshare+](https://doi.org/10.25452/figshare.plus.22671172.v5), extracted from its single archive | [CC BY 4.0](https://creativecommons.org/licenses/by/4.0/) |
+| 31 | Zhou2016 | `left_hand`, `right_hand`, `feet` | 4 | 12 | 45–60 `left_hand`, 45–59 `right_hand`, 45–60 `feet` in subjects 1–2 | 14 | 250 | healthy | 0.13 GB | MOABB's [Zenodo](https://zenodo.org/records/16534752) BIDS copy of [figshare](https://doi.org/10.6084/m9.figshare.2061654.v2) | [CC BY 4.0](https://creativecommons.org/licenses/by/4.0/) |
+| 32 | Zhou2020 | `left_hand`, `right_hand`, `feet`, `rest` | 20 | 140 | 50–70 in subjects 1–2 and 13 | 41 or 26 | 500 | healthy | 17.6 GB | MOABB's [Zenodo](https://zenodo.org/records/18988317) copy of [IEEE DataPort](https://doi.org/10.21227/f1c7-7x89) | [CC BY 4.0](https://creativecommons.org/licenses/by/4.0/) |
+
+Classes are MOABB's event names. Classes, trials, EEG channels and rate are what MOABB at commit `555d14a` loads, with downloads blocked, from these files: subjects 1–2 of every dataset on 10 Oct 2026, every subject of 11 datasets on 8–9 Oct 2026 and every subject of the three WRCC2023 sets. A trial count that names no subjects holds for every subject.
+
+In Beetl2021_A, MOABB loads the test run's "other" class, which is right hand or feet, as `right_hand`. Only 25 of each subject's `right_hand` trials are known to be right hand.
 
 ## Verification
 
@@ -75,6 +82,8 @@ Each file was checked as it was mirrored against the size and, where its host li
 
 On 8 Oct 2026, a fresh machine with no Hugging Face token restored every file of the 11 datasets added that day (Beetl2021_A, Farabbi2020, Jia2019, Kumar2024, Leeuwis2021, Liu2024, Pan2023, Pan2025, Shin2022, Vagaja2023 and Wang2025) and subjects 1–2 of 13 others. It checked each file again and loaded every one of those subjects with MOABB, with downloads blocked.
 
+On 10 Oct 2026, a second machine restored subjects 1–2 of the 29 datasets then in the mirror, 633 files and 35.6 GB, checked each file against its upstream checksum and the Hub's SHA-256, and loaded each of those subjects with MOABB, with downloads blocked. Every file matched except Zhou2016's saved Zenodo record: Zenodo now serves the record without two of its links, `archive` and `archive_media`. Its file list, the only part MOABB reads, is unchanged. The three WRCC2023 sets were checked against their upstream MD5 as they were downloaded, and every one of their subjects was loaded with MOABB from those files.
+
 ## Loading
 
 Every dataset loads the same way with MOABB at commit [`555d14a`](https://github.com/NeuroTechX/moabb/tree/555d14aebc1f1175e8476faeebabbfcafc522aba), to be released as 1.8.0. The 18 datasets mirrored before 8 Oct 2026 also load with MOABB 1.7.
@@ -553,6 +562,63 @@ moabb.set_download_provider("upstream")
 data = Vagaja2023().get_data(subjects=[3])
 ```
 
+### WRCC2023_MI_A
+
+One MAT file per subject, `subject1.mat` to `subject9.mat` upstream, stored as MOABB stores them, under their Harvard Dataverse file IDs in `api/access/datafile/`. MOABB's loader maps each subject to its ID: 10358829 for subject 1. Each file holds one session of 90 trials, 30 each of left hand, right hand and feet, with 59 channels at 1000 Hz. Two of the nine people had a stroke; the release does not say which. For all 9 subjects, use `allow_patterns="WRCC2023_MI_A/*"`.
+
+```python
+import os
+
+from huggingface_hub import snapshot_download
+
+path = snapshot_download("bkowshik/eeg-mi-datasets", repo_type="dataset", allow_patterns="WRCC2023_MI_A/*/datafile/10358829")
+os.environ["MNE_DATASETS_WRCC2023-MI-A_PATH"] = os.path.join(path, "WRCC2023_MI_A")
+
+import moabb
+from moabb.datasets import WRCC2023_MI_A
+
+moabb.set_download_provider("upstream")
+data = WRCC2023_MI_A(subjects=[1]).get_data()
+```
+
+### WRCC2023_MI_B
+
+As WRCC2023_MI_A, for the competition's second set: nine subjects, 10358839 for subject 1. For all 9 subjects, use `allow_patterns="WRCC2023_MI_B/*"`.
+
+```python
+import os
+
+from huggingface_hub import snapshot_download
+
+path = snapshot_download("bkowshik/eeg-mi-datasets", repo_type="dataset", allow_patterns="WRCC2023_MI_B/*/datafile/10358839")
+os.environ["MNE_DATASETS_WRCC2023-MI-B_PATH"] = os.path.join(path, "WRCC2023_MI_B")
+
+import moabb
+from moabb.datasets import WRCC2023_MI_B
+
+moabb.set_download_provider("upstream")
+data = WRCC2023_MI_B(subjects=[1]).get_data()
+```
+
+### WRCC2023_MI_C
+
+As WRCC2023_MI_A, for the competition's third set: eight subjects, 10358845 for subject 1. For all 8 subjects, use `allow_patterns="WRCC2023_MI_C/*"`.
+
+```python
+import os
+
+from huggingface_hub import snapshot_download
+
+path = snapshot_download("bkowshik/eeg-mi-datasets", repo_type="dataset", allow_patterns="WRCC2023_MI_C/*/datafile/10358845")
+os.environ["MNE_DATASETS_WRCC2023-MI-C_PATH"] = os.path.join(path, "WRCC2023_MI_C")
+
+import moabb
+from moabb.datasets import WRCC2023_MI_C
+
+moabb.set_download_provider("upstream")
+data = WRCC2023_MI_C(subjects=[1]).get_data()
+```
+
 ### Wang2025
 
 The MI4 part of the authors' Hugging Face repository at the revision MOABB's links served when mirrored, in the folder where MOABB keeps it: `sub-01/s1_calibration.mat`, `s1_feedback.mat`, `s2_calibration.mat` and `s2_feedback.mat` for subject 1, one calibration and one feedback file per session. For all 15 subjects, use `allow_patterns="Wang2025/*"`.
@@ -693,6 +759,9 @@ Cite the works listed for each dataset you use.
 - **Shin2022:** Shin, H., Suma, D., & He, B. (2022). Closed-loop motor imagery EEG simulation for brain-computer interfaces. *Frontiers in Human Neuroscience*, 16, 951591. https://doi.org/10.3389/fnhum.2022.951591
 - **Stieger2021:** Stieger, J. R., Engel, S. A., & He, B. (2021). Continuous sensorimotor rhythm based brain computer interface learning in a large population. *Scientific Data*, 8, 98. https://doi.org/10.1038/s41597-021-00883-1
 - **Vagaja2023:** Vagaja, K., & Vourvopoulos, A. (2023). Electrophysiological signals of embodiment and MI-BCI training in VR [Data set]. Zenodo. https://doi.org/10.5281/zenodo.8086086
+- **WRCC2023_MI_A:** WRCC2023. (2024). MI-A dataset of the BCI competition WRCC2023 (Version 1.0) [Data set]. Harvard Dataverse. https://doi.org/10.7910/DVN/J9JFES
+- **WRCC2023_MI_B:** WRCC2023. (2024). MI-B dataset of the BCI competition WRCC2023 (Version 1.0) [Data set]. Harvard Dataverse. https://doi.org/10.7910/DVN/HFNWRX
+- **WRCC2023_MI_C:** WRCC2023. (2024). MI-C dataset of the BCI competition WRCC2023 (Version 1.0) [Data set]. Harvard Dataverse. https://doi.org/10.7910/DVN/G8FBHH
 - **Wang2025:** Wang, J., Yao, L., & Wang, Y. (2025). Enhanced online continuous brain-control by deep learning-based EEG decoding. *IEEE Transactions on Neural Systems and Rehabilitation Engineering*, 33, 2834–2846. https://doi.org/10.1109/TNSRE.2025.3591254
 - **Weibo2014:** Yi, W., Qiu, S., Wang, K., Qi, H., Zhang, L., Zhou, P., He, F., & Ming, D. (2014). Evaluation of EEG oscillatory patterns and cognitive process during simple and compound limb motor imagery. *PLoS ONE*, 9(12), e114853. https://doi.org/10.1371/journal.pone.0114853
 - **Yang2025:** Yang, B., Rong, F., Xie, Y., Li, D., Zhang, J., Li, F., Shi, G., & Gao, X. (2025). A multi-day and high-quality EEG dataset for motor imagery brain-computer interface. *Scientific Data*, 12, 488. https://doi.org/10.1038/s41597-025-04826-y

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