audiovisual | |||||||||
---|---|---|---|---|---|---|---|---|---|
trial_type | subject | run | Auditory/Left | Auditory/Right | Button | Smiley | Visual/Left | Visual/Right | |
01 | 01 | 72 | 73 | 16 | 15 | 73 | 71 |
1 rows × 8 columns
General | ||
---|---|---|
Filename(s) | sub-01_task-audiovisual_ave.fif | |
MNE object type | Evoked | |
Measurement date | 1921-08-16 at 19:01:10 UTC | |
Participant | sub-01 | |
Experimenter | mne_anonymize | |
Acquisition | ||
Aggregation | average of 1 epochs | |
Condition | Grand average: 0.50 × Auditory/Left + 0.50 × Auditory/Right | |
Time range | -0.200 – 0.499 s | |
Baseline | -0.200 – 0.000 s | |
Sampling frequency | 150.15 Hz | |
Time points | 106 | |
Channels | ||
Magnetometers | ||
Gradiometers | ||
EEG | ||
Head & sensor digitization | 146 points | |
Filters | ||
Highpass | 0.10 Hz | |
Lowpass | 40.00 Hz | |
Projections |
Average EEG reference (on)
meg-ECG--0.499-0.499)-PCA-01 (on) meg-EOG--0.499-0.499)-PCA-01 (on) eeg-EOG--0.499-0.499)-PCA-01 (on) |
General | ||
---|---|---|
Filename(s) | sub-01_task-audiovisual_ave.fif | |
MNE object type | Evoked | |
Measurement date | 1921-08-16 at 19:01:10 UTC | |
Participant | sub-01 | |
Experimenter | mne_anonymize | |
Acquisition | ||
Aggregation | average of 1 epochs | |
Condition | Grand average: 0.51 × Visual/Left + 0.49 × Visual/Right | |
Time range | -0.200 – 0.499 s | |
Baseline | -0.200 – 0.000 s | |
Sampling frequency | 150.15 Hz | |
Time points | 106 | |
Channels | ||
Magnetometers | ||
Gradiometers | ||
EEG | ||
Head & sensor digitization | 146 points | |
Filters | ||
Highpass | 0.10 Hz | |
Lowpass | 40.00 Hz | |
Projections |
Average EEG reference (on)
meg-ECG--0.499-0.499)-PCA-01 (on) meg-EOG--0.499-0.499)-PCA-01 (on) eeg-EOG--0.499-0.499)-PCA-01 (on) |
General | ||
---|---|---|
Filename(s) | sub-01_task-audiovisual_ave.fif | |
MNE object type | Evoked | |
Measurement date | 1921-08-16 at 19:01:10 UTC | |
Participant | sub-01 | |
Experimenter | mne_anonymize | |
Acquisition | ||
Aggregation | average of 1 epochs | |
Condition | Grand average: Auditory/Left | |
Time range | -0.200 – 0.499 s | |
Baseline | -0.200 – 0.000 s | |
Sampling frequency | 150.15 Hz | |
Time points | 106 | |
Channels | ||
Magnetometers | ||
Gradiometers | ||
EEG | ||
Head & sensor digitization | 146 points | |
Filters | ||
Highpass | 0.10 Hz | |
Lowpass | 40.00 Hz | |
Projections |
Average EEG reference (on)
meg-ECG--0.499-0.499)-PCA-01 (on) meg-EOG--0.499-0.499)-PCA-01 (on) eeg-EOG--0.499-0.499)-PCA-01 (on) |
General | ||
---|---|---|
Filename(s) | sub-01_task-audiovisual_ave.fif | |
MNE object type | Evoked | |
Measurement date | 1921-08-16 at 19:01:10 UTC | |
Participant | sub-01 | |
Experimenter | mne_anonymize | |
Acquisition | ||
Aggregation | average of 1 epochs | |
Condition | Grand average: Auditory/Right | |
Time range | -0.200 – 0.499 s | |
Baseline | -0.200 – 0.000 s | |
Sampling frequency | 150.15 Hz | |
Time points | 106 | |
Channels | ||
Magnetometers | ||
Gradiometers | ||
EEG | ||
Head & sensor digitization | 146 points | |
Filters | ||
Highpass | 0.10 Hz | |
Lowpass | 40.00 Hz | |
Projections |
Average EEG reference (on)
meg-ECG--0.499-0.499)-PCA-01 (on) meg-EOG--0.499-0.499)-PCA-01 (on) eeg-EOG--0.499-0.499)-PCA-01 (on) |
General | ||
---|---|---|
Filename(s) | sub-01_task-audiovisual_ave.fif | |
MNE object type | Evoked | |
Measurement date | 1921-08-16 at 19:01:10 UTC | |
Participant | sub-01 | |
Experimenter | mne_anonymize | |
Acquisition | ||
Aggregation | average of 1 epochs | |
Condition | Grand average: (0.51 × Visual/Left + 0.49 × Visual/Right) - (0.50 × Auditory/Left + 0.50 × Auditory/Right) | |
Time range | -0.200 – 0.499 s | |
Baseline | -0.200 – 0.000 s | |
Sampling frequency | 150.15 Hz | |
Time points | 106 | |
Channels | ||
Magnetometers | ||
Gradiometers | ||
EEG | ||
Head & sensor digitization | 146 points | |
Filters | ||
Highpass | 0.10 Hz | |
Lowpass | 40.00 Hz | |
Projections |
Average EEG reference (on)
meg-ECG--0.499-0.499)-PCA-01 (on) meg-EOG--0.499-0.499)-PCA-01 (on) eeg-EOG--0.499-0.499)-PCA-01 (on) |
General | ||
---|---|---|
Filename(s) | sub-01_task-audiovisual_ave.fif | |
MNE object type | Evoked | |
Measurement date | 1921-08-16 at 19:01:10 UTC | |
Participant | sub-01 | |
Experimenter | mne_anonymize | |
Acquisition | ||
Aggregation | average of 1 epochs | |
Condition | Grand average: Auditory/Right - Auditory/Left | |
Time range | -0.200 – 0.499 s | |
Baseline | -0.200 – 0.000 s | |
Sampling frequency | 150.15 Hz | |
Time points | 106 | |
Channels | ||
Magnetometers | ||
Gradiometers | ||
EEG | ||
Head & sensor digitization | 146 points | |
Filters | ||
Highpass | 0.10 Hz | |
Lowpass | 40.00 Hz | |
Projections |
Average EEG reference (on)
meg-ECG--0.499-0.499)-PCA-01 (on) meg-EOG--0.499-0.499)-PCA-01 (on) eeg-EOG--0.499-0.499)-PCA-01 (on) |
"""MNE Sample Data: M/EEG combined processing."""
import mne
bids_root = "~/mne_data/ds000248"
deriv_root = "~/mne_data/derivatives/mne-bids-pipeline/ds000248_base"
subjects_dir = f"{bids_root}/derivatives/freesurfer/subjects"
subjects = ["01"]
rename_events = {"Smiley": "Emoji", "Button": "Switch"}
conditions = ["Auditory", "Visual", "Auditory/Left", "Auditory/Right"]
epochs_metadata_query = "index > 0" # Just for testing!
contrasts = [("Visual", "Auditory"), ("Auditory/Right", "Auditory/Left")]
time_frequency_conditions = ["Auditory", "Visual"]
ch_types = ["meg", "eeg"]
mf_reference_run = "01"
find_flat_channels_meg = True
find_noisy_channels_meg = True
use_maxwell_filter = True
def noise_cov(bp):
"""Estimate the noise covariance."""
# Use pre-stimulus period as noise source
bp = bp.copy().update(suffix="epo")
if not bp.fpath.exists():
bp.update(split="01")
epo = mne.read_epochs(bp)
cov = mne.compute_covariance(epo, rank="info", tmax=0)
return cov
spatial_filter = "ssp"
n_proj_eog = dict(n_mag=1, n_grad=1, n_eeg=1)
n_proj_ecg = dict(n_mag=1, n_grad=1, n_eeg=0)
ssp_meg = "combined"
ecg_proj_from_average = True
eog_proj_from_average = False
epochs_decim = 4
bem_mri_images = "FLASH"
recreate_bem = True
n_jobs = 2
def mri_t1_path_generator(bids_path):
"""Return the path to a T1 image."""
# don't really do any modifications – just for testing!
return bids_path
Platform Linux-5.15.0-1057-aws-x86_64-with-glibc2.35
Python 3.10.12 (main, Nov 20 2023, 15:14:05) [GCC 11.4.0]
Executable /home/circleci/python_env/bin/python3.10
CPU x86_64 (36 cores)
Memory 68.6 GB
Core
├☑ mne 1.8.0.dev79+gcaba81b9f (devel, latest release is 1.7.1)
├☑ numpy 2.0.0 (OpenBLAS 0.3.27 with 2 threads)
├☑ scipy 1.13.1
└☑ matplotlib 3.9.0 (backend=agg)
Numerical (optional)
├☑ sklearn 1.5.0
├☑ numba 0.60.0
├☑ nibabel 5.2.1
├☑ pandas 2.2.2
├☑ h5io 0.2.3
├☑ h5py 3.11.0
└☐ unavailable nilearn, dipy, openmeeg, cupy
Visualization (optional)
├☑ pyvista 0.43.10 (OpenGL 4.5 (Core Profile) Mesa 23.2.1-1ubuntu3.1~22.04.2 via llvmpipe (LLVM 15.0.7, 256 bits))
├☑ pyvistaqt 0.11.1
├☑ vtk 9.3.0
├☑ qtpy 2.4.1 (PyQt6=6.7.1)
└☐ unavailable ipympl, pyqtgraph, mne-qt-browser, ipywidgets, trame_client, trame_server, trame_vtk, trame_vuetify
Ecosystem (optional)
├☑ mne-bids 0.16.0.dev3+g0e3cbc66a
├☑ mne-bids-pipeline 1.9.0
├☑ edfio 0.4.2
├☑ pybv 0.7.5
└☐ unavailable mne-nirs, mne-features, mne-connectivity, mne-icalabel, neo, eeglabio, mffpy