Dear MNE users,
We are pleased to announce the release of Pycrostates 0.1.1
Pycrostates package aims to provide basic functions to perform EEG microstates analysis in Python.
The code can be found on GitHub and documentation and examples can be fond here.
The library is also available through PyPi
and the conda-forge
channel.
To make a long story short , Pycrostates implements several modules including:
-
the
cluster
module which supports the different clustering algorithms that find the optimal topographic maps that sparsely represent the EEG. -
the
segmentation
module which supports the study of microstates sequences and their summary measures. -
the
metrics
module which quantifies the quality of the fitted clustering algorithms. -
the
dataset
module which direct access to preprocessed data that can be used to test pipelines. As of writing, it supports the LEMON dataset comprising preprocessed EEG recordings of 227 healthy participants. -
the
viz
module which provides visualization tools for performing microstate analyses.
By design, Pycrostates supports natively data types from MNE-Python such as Raw
and Epochs
instances. Future improvements and additions such as different clustering algorithms or new tools for sequence analysis such as Markov chains are planned in further releases.
We hope that this will be helpful to some of you,
Mathieu & Victor