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 600.61 Hz
Time points 421
Channels
Magnetometers
Gradiometers
Head & sensor digitization 146 points
Filters
Highpass 0.10 Hz
Lowpass 40.00 Hz
Projections PCA-v1 (on)
PCA-v2 (on)
PCA-v3 (on)
Time course (Magnetometers)
Time course (Gradiometers)
Global field power
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 600.61 Hz
Time points 421
Channels
Magnetometers
Gradiometers
Head & sensor digitization 146 points
Filters
Highpass 0.10 Hz
Lowpass 40.00 Hz
Projections PCA-v1 (on)
PCA-v2 (on)
PCA-v3 (on)
Global field power
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 600.61 Hz
Time points 421
Channels
Magnetometers
Gradiometers
Head & sensor digitization 146 points
Filters
Highpass 0.10 Hz
Lowpass 40.00 Hz
Projections PCA-v1 (on)
PCA-v2 (on)
PCA-v3 (on)
Time course (Magnetometers)
Time course (Gradiometers)
Global field power
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 600.61 Hz
Time points 421
Channels
Magnetometers
Gradiometers
Head & sensor digitization 146 points
Filters
Highpass 0.10 Hz
Lowpass 40.00 Hz
Projections PCA-v1 (on)
PCA-v2 (on)
PCA-v3 (on)
Time course (Magnetometers)
Time course (Gradiometers)
Global field power
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 600.61 Hz
Time points 421
Channels
Magnetometers
Gradiometers
Head & sensor digitization 146 points
Filters
Highpass 0.10 Hz
Lowpass 40.00 Hz
Projections PCA-v1 (on)
PCA-v2 (on)
PCA-v3 (on)
Time course (Magnetometers)
Time course (Gradiometers)
Global field power
Full-epochs decoding
Based on N=1 subjects. Each dot represents the mean cross-validation score for a single subject. The dashed line is expected chance performance.
  """MNE Sample Data: Using the `fsaverage` template MRI."""

bids_root = "~/mne_data/ds000248"
deriv_root = "~/mne_data/derivatives/mne-bids-pipeline/ds000248_no_mri"
subjects_dir = f"{bids_root}/derivatives/freesurfer/subjects"

subjects = ["01"]
rename_events = {"Smiley": "Emoji", "Button": "Switch"}
conditions = ["Auditory", "Visual", "Auditory/Left", "Auditory/Right"]
contrasts = [("Auditory/Right", "Auditory/Left")]

ch_types = ["meg"]
use_maxwell_filter = False
process_empty_room = False

use_template_mri = "fsaverage"
adjust_coreg = True

  Platform             Linux-5.15.0-1077-aws-x86_64-with-glibc2.35
Python               3.12.4 (main, Jun  8 2024, 23:40:19) [GCC 11.4.0]
Executable           /home/circleci/.pyenv/versions/3.12.4/bin/python3.12
CPU                  Intel(R) Xeon(R) Platinum 8223CL CPU @ 3.00GHz (36 cores)
Memory               69.1 GiB

Core
├☑ mne               1.10.0.dev67+gbe27cf8dd (devel, latest release is 1.9.0)
├☑ numpy             2.1.3 (OpenBLAS 0.3.27 with 2 threads)
├☑ scipy             1.15.2
└☑ matplotlib        3.10.1 (backend=agg)

Numerical (optional)
├☑ sklearn           1.6.1
├☑ numba             0.61.0
├☑ nibabel           5.3.2
├☑ pandas            2.2.3
├☑ h5io              0.2.4
├☑ h5py              3.13.0
└☐ unavailable       nilearn, dipy, openmeeg, cupy

Visualization (optional)
├☑ pyvista           0.44.2 (OpenGL 4.5 (Core Profile) Mesa 23.2.1-1ubuntu3.1~22.04.3 via llvmpipe (LLVM 15.0.7, 256 bits))
├☑ pyvistaqt         0.11.2
├☑ vtk               9.3.1
├☑ qtpy              2.4.3 (PyQt6=6.8.2)
└☐ unavailable       ipympl, pyqtgraph, mne-qt-browser, ipywidgets, trame_client, trame_server, trame_vtk, trame_vuetify

Ecosystem (optional)
├☑ mne-bids          0.17.0.dev32+g3a25345
├☑ mne-bids-pipeline 1.10.0.dev68+gb995b51
├☑ edfio             0.4.6
├☑ pybv              0.7.6
└☐ unavailable       mne-nirs, mne-features, mne-connectivity, mne-icalabel, neo, eeglabio, mffpy