Authors: Amilleah Rodriguez, Dan Zhao, Kyra Wilson, Ritika Saboo, Sergey V Samsonau, Alec Marantz
TL;DR: We present NeuroMorph: neural data of 24 high-resolution MEG recordings capturing real-time processing of multi-morphemic words with over 17 hours of data from a lexical decision task, which can help improve cognitive modeling and NLP.
Keywords: natural language processing, morphemes, cognitive science, linguistics, magnetoencephalography, MEG
You can find the dataset on OpenNeuro
You can download the dataset from OpenNeuro using datalad:
pip install datalad
datalad install https://github.com/OpenNeuroDatasets/ds005241.git
datalad get .
The repository includes a few Jupyter notebooks to help you preprocess and analyze the data for both the lexical decision task and the functional localizer. It also includes ML modelling code for two classification tasks.
KIT/Yokogawa MEG system with 208 magnetometer channels 24 recordings amounting to over 17 hours of data stored in MEG-BIDS format (version 1.7.0) the dataset is published on OpenNeuro
https://mne.tools/stable/documentation/cookbook.html https://mne.tools/stable/documentation/glossary.html
Appelhoff, 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
Niso, 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.https://doi.org/10.1038/sdata.2018.110