tDCS EEG¶
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/ds001810
How to download this dataset
Run in your terminal:
Run in your terminal
openneuro-py download \
             --dataset=ds001810 \
             --include=sub-01
Configuration¶
Click to expand
Python
.
study_name = "ds001810"
bids_root = "~/mne_data/ds001810"
deriv_root = "~/mne_data/derivatives/mne-bids-pipeline/ds001810"
task = "attentionalblink"
interactive = False
ch_types = ["eeg"]
eeg_template_montage = "biosemi64"
reject = dict(eeg=100e-6)
baseline = (None, 0)
conditions = ["61450", "61511"]
contrasts = [("61450", "61511")]
decode = True
decoding_n_splits = 3  # only for testing, use 5 otherwise
l_freq = 0.3
subjects = ["01"]
sessions = "all"
interpolate_bads_grand_average = False
n_jobs = 4