- MNE version: e.g. 1.8.0
- operating system: e.g. macOS sequoia 15.1 (24B83)
i did epoch each subjects (1 till 79) into 3133 1 sec epochs across 18 channels for each individual subject. using Pycrostates, i observe putting clusters=4 topo plots for subject1, but i want to know whetehjr is it microstte A or B or C or D as in standard literature, how to template match, from where can i get this predefined template to say it belong to A or B or C or D , i want to know sequence of these states for all subkects 3133 epochs like A,B , c,d,a so on till 3133? how to do this guys, please help me
import pycrostates
from pycrostates.cluster import ModKMeans
Select the first subject’s data
first_subject_raw = raw_list[0]
first_subject_raw.set_montage(‘standard_1020’)
Create 1-second epochs for the first subject
epochs = mne.make_fixed_length_epochs(first_subject_raw, duration=1.0, preload=True)
print(f"Created {len(epochs)} 1-second epochs for the first subject.")
Define the number of microstates to cluster into
n_clusters = 4 # Adjust as needed
Initialize the modified K-means clustering
clustering = ModKMeans(n_clusters=n_clusters, random_state=42)
Fit the clustering on the data for the first subject’s epochs
clustering.fit(epochs, picks=‘eeg’, tmin=None, tmax=None, reject_by_annotation=True, n_jobs=5, verbose=None)
Access the derived cluster centers (microstate maps)
microstate_maps = clustering.cluster_centers_
print(“Derived microstate maps for the first subject:”)
clustering.rename_clusters(new_names=[‘A’,‘B’,‘C’,‘D’]
manually i did i feel this is wrong