Mobile brain body imaging (MoBI) gait adaptation experiment.¶
See ds001971 on OpenNeuro: https://github.com/OpenNeuroDatasets/ds001971
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/ds001971
How to download this dataset
Run in your terminal:
Run in your terminal
openneuro-py download \
--dataset=ds001971 \
--include=sub-001/eeg/sub-001_task-AudioCueWalkingStudy_run-01_events.tsv \
--include=sub-001/eeg/sub-001_task-AudioCueWalkingStudy_run-01_eeg.set \
--include=sub-001/eeg/sub-001_task-AudioCueWalkingStudy_run-01_eeg.fdt \
--include=sub-001/eeg/sub-001_task-AudioCueWalkingStudy_run-01_eeg.json \
--include=sub-001/eeg/sub-001_task-AudioCueWalkingStudy_run-01_electrodes.tsv \
--include=sub-001/eeg/sub-001_task-AudioCueWalkingStudy_run-01_coordsystem.json \
--include=sub-001/eeg/sub-001_task-AudioCueWalkingStudy_run-01_channels.tsv
Configuration¶
Click to expand
Python
bids_root = "~/mne_data/ds001971"
deriv_root = "~/mne_data/derivatives/mne-bids-pipeline/ds001971"
task = "AudioCueWalkingStudy"
interactive = False
ch_types = ["eeg"]
reject = {"eeg": 150e-6}
conditions = ["AdvanceTempo", "DelayTempo"]
contrasts = [("AdvanceTempo", "DelayTempo")]
subjects = ["001"]
runs = ["01"]
epochs_decim = 5 # to 100 Hz
# This is mostly for testing purposes!
decode = True
decoding_time_generalization = True
decoding_time_generalization_decim = 2
decoding_csp = True
decoding_csp_freqs = {
"beta": [13, 20, 30],
}
decoding_csp_times = [-0.2, 0.0, 0.2, 0.4]
# Just to test that MD5 works
memory_file_method = "hash"