KIT phantom data.

https://mne.tools/dev/documentation/datasets.html#kit-phantom-dataset

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://mne.tools/dev/generated/mne.datasets.phantom_kit.data_path.html

Configuration

Click to expand

Python

study_name = "MNE-phantom-KIT-data"
bids_root = "~/mne_data/MNE-phantom-KIT-data"
deriv_root = "~/mne_data/derivatives/mne-bids-pipeline/MNE-phantom-KIT-data"
task = "phantom"
ch_types = ["meg"]

# Preprocessing
l_freq = None
h_freq = 40.0
regress_artifact = dict(
    picks="meg", picks_artifact=["MISC 001", "MISC 002", "MISC 003"]
)

# Epochs
epochs_tmin = -0.08
epochs_tmax = 0.18
epochs_decim = 10  # 2000->200 Hz
baseline = (None, 0)
conditions = ["dip01", "dip13", "dip25", "dip37", "dip49"]

# Decoding
decode = True  # should be very good performance