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MIND DATA.

M.P. Weisend, F.M. Hanlon, R. Montaño, S.P. Ahlfors, A.C. Leuthold, D. Pantazis, J.C. Mosher, A.P. Georgopoulos, M.S. Hämäläinen, C.J. Aine,, V. (2007). Paving the way for cross-site pooling of magnetoencephalography (MEG) data. International Congress Series, Volume 1300, Pages 615-618.

Demonstrated features

Feature This example
MEG processing
EEG processing
Maxwell filter
Frequency filter
Artifact regression
SSP
ICA
Evoked contrasts
Time-by-time decoding
Time-generalization decoding
CSP decoding
Time-frequency analysis
BEM surface creation
Template MRI

Dataset source

This dataset was acquired from https://openneuro.org/datasets/ds004107

How to download this dataset

Run in your terminal:

Run in your terminal
openneuro-py download \
             --dataset=ds004107 \
             --include=sub-mind002/ses-01/meg/*coordsystem* \
             --include=sub-mind002/ses-01/meg/*auditory*

Configuration

Click to expand
Python
# This has auditory, median, indx, visual, rest, and emptyroom but let's just
# process the auditory (it's the smallest after rest)
bids_root = "~/mne_data/ds004107"
deriv_root = "~/mne_data/derivatives/mne-bids-pipeline/ds004107"
subjects = ["mind002"]
sessions = ["01"]
conditions = ["left", "right"]  # there are also tone and noise
task = "auditory"
ch_types = ["meg"]
crop_runs = (0, 120)  # to speed up computations
spatial_filter = "ssp"
l_freq = 1.0
h_freq = 40.0

Generated output

Summary reports

sub-average_ses-01_task-auditory_report.html

sub-mind002_ses-01_task-auditory_report.html