auditory | |||||||||||
---|---|---|---|---|---|---|---|---|---|---|---|
trial_type | subject | session | left/noise | left/tone/2500 | left/tone/4000 | left/tone/500 | right/noise | right/tone/2500 | right/tone/4000 | right/tone/500 | |
mind002 | 01 | 99 | 108 | 100 | 109 | 119 | 105 | 106 | 104 |
1 rows × 10 columns
General | ||
---|---|---|
Filename(s) | sub-mind002_ses-01_task-auditory_ave.fif | |
MNE object type | Evoked | |
Measurement date | 1912-10-26 at 16:30:04 UTC | |
Participant | sub-mind002 | |
Experimenter | mne_anonymize | |
Acquisition | ||
Aggregation | average of 1 epochs | |
Condition | Grand average: 0.29 × left/noise + 0.24 × left/tone/2500 + 0.15 × left/tone/4000 + 0.32 × left/tone/500 | |
Time range | -0.200 – 0.500 s | |
Baseline | -0.200 – 0.000 s | |
Sampling frequency | 1250.00 Hz | |
Time points | 876 | |
Channels | ||
Magnetometers | ||
Gradiometers | ||
Head & sensor digitization | 136 points | |
Filters | ||
Highpass | 1.00 Hz | |
Lowpass | 40.00 Hz | |
Projections |
PCA-v1 (on)
PCA-v2 (on) PCA-v3 (on) planar-ECG--0.500-0.500)-PCA-01 (on) axial-ECG--0.500-0.500)-PCA-01 (on) |
General | ||
---|---|---|
Filename(s) | sub-mind002_ses-01_task-auditory_ave.fif | |
MNE object type | Evoked | |
Measurement date | 1912-10-26 at 16:30:04 UTC | |
Participant | sub-mind002 | |
Experimenter | mne_anonymize | |
Acquisition | ||
Aggregation | average of 1 epochs | |
Condition | Grand average: 0.27 × right/noise + 0.18 × right/tone/2500 + 0.29 × right/tone/4000 + 0.27 × right/tone/500 | |
Time range | -0.200 – 0.500 s | |
Baseline | -0.200 – 0.000 s | |
Sampling frequency | 1250.00 Hz | |
Time points | 876 | |
Channels | ||
Magnetometers | ||
Gradiometers | ||
Head & sensor digitization | 136 points | |
Filters | ||
Highpass | 1.00 Hz | |
Lowpass | 40.00 Hz | |
Projections |
PCA-v1 (on)
PCA-v2 (on) PCA-v3 (on) planar-ECG--0.500-0.500)-PCA-01 (on) axial-ECG--0.500-0.500)-PCA-01 (on) |
"""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.
"""
# 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
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