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

study_name = "ds001971"
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"