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The dataset viewer is not available for this split.
Cannot load the dataset split (in streaming mode) to extract the first rows.
Error code:   StreamingRowsError
Exception:    ValueError
Message:      Dataset 'data' has length 10000 but expected 306
Traceback:    Traceback (most recent call last):
                File "/src/services/worker/src/worker/utils.py", line 147, in get_rows_or_raise
                  return get_rows(
                      dataset=dataset,
                  ...<4 lines>...
                      column_names=column_names,
                  )
                File "/src/libs/libcommon/src/libcommon/utils.py", line 272, in decorator
                  return func(*args, **kwargs)
                File "/src/services/worker/src/worker/utils.py", line 127, in get_rows
                  rows_plus_one = list(itertools.islice(safe_iter(ds, dataset=dataset), rows_max_number + 1))
                File "/src/services/worker/src/worker/utils.py", line 483, in safe_iter
                  yield from ds.decode(False) if ds.features else ds
                File "/usr/local/lib/python3.14/site-packages/datasets/iterable_dataset.py", line 2840, in __iter__
                  for key, example in ex_iterable:
                                      ^^^^^^^^^^^
                File "/usr/local/lib/python3.14/site-packages/datasets/iterable_dataset.py", line 2373, in __iter__
                  for key, pa_table in self._iter_arrow():
                                       ~~~~~~~~~~~~~~~~^^
                File "/usr/local/lib/python3.14/site-packages/datasets/iterable_dataset.py", line 2398, in _iter_arrow
                  for key, pa_table in self.ex_iterable._iter_arrow():
                                       ~~~~~~~~~~~~~~~~~~~~~~~~~~~~^^
                File "/usr/local/lib/python3.14/site-packages/datasets/iterable_dataset.py", line 536, in _iter_arrow
                  for key, pa_table in iterator:
                                       ^^^^^^^^
                File "/usr/local/lib/python3.14/site-packages/datasets/iterable_dataset.py", line 419, in _iter_arrow
                  for key, pa_table in self.generate_tables_fn(**gen_kwags):
                                       ~~~~~~~~~~~~~~~~~~~~~~~^^^^^^^^^^^^^
                File "/usr/local/lib/python3.14/site-packages/datasets/packaged_modules/hdf5/hdf5.py", line 76, in _generate_tables
                  num_rows = _check_dataset_lengths(h5, self.info.features)
                File "/usr/local/lib/python3.14/site-packages/datasets/packaged_modules/hdf5/hdf5.py", line 355, in _check_dataset_lengths
                  raise ValueError(f"Dataset '{path}' has length {dset.shape[0]} but expected {num_rows}")
              ValueError: Dataset 'data' has length 10000 but expected 306

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MegNIST

MegNIST is a magnetoencephalography (MEG) dataset for benchmarking non-invasive inner-speech decoding. The dataset contains recordings from a single participant performing repeated trials involving the digits 0–9.

The raw MEG data are organised according to the Brain Imaging Data Structure (BIDS). Processed data suitable for machine-learning analyses are provided separately in the derivatives/serialised/ directory.

Licence

MegNIST is licensed under the Creative Commons Attribution-NonCommercial 4.0 International (CC BY-NC 4.0) licence.

It is freely available for research and other non-commercial uses, subject to the terms of the licence. When sharing or redistributing MegNIST, including modified or derived versions, please credit the MegNIST authors, link to the dataset, and identify the CC BY-NC 4.0 licence. If you modify the dataset, please indicate that changes were made. For commercial licensing enquiries, please contact Oxford University Innovation (OUI).

Citation

If you use MegNIST, please cite:

Kwon, T., Somaiya, P., Elvers, G., Mantegna, F., Camera, A., Braeutigam, S., Woolrich, M. and Parker Jones, O. (2026). MegNIST: A Benchmark for Non-Invasive Inner Speech Decoding.

@misc{kwon2026megnist,
  title={{MegNIST}: A Benchmark for Non-Invasive Inner Speech Decoding},
  author={Kwon, Teyun and Somaiya, Pratik and Elvers, Gereon and Mantegna, Francesco and Camera, Anna and Braeutigam, Sven and Woolrich, Mark and Parker Jones, Oiwi},
  year={2026}
}
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