Abstract: Accurate localization of neural sources in Magnetoencephalography (MEG) and Electroencephalography (EEG) is essential for advancing clinical and research applications in neuroscience.

Explore the first part of our series on sleep stage classification using Python, EEG data, and powerful libraries like Sklearn and MNE. Perfect for data scientists and neuroscience enthusiasts!

Separate accounts, separate campaigns, or one shared setup? It’s often the first question marketers face when launching Google Ads in multiple countries or languages. The structure you choose lays the ...

1 Department of Biomedical Engineering, Tehran University of Medical Sciences, Tehran, Iran 2 Research Center for Biomedical Technologies and Robotics (RCBTR), Advanced Medical Technologies and ...

We introduce an open-source Python package for the analysis of large-scale electrophysiological data, named SyNCoPy, which stands for Systems Neuroscience Computing in Python. The package includes ...

To my knowledge, there is no way to display source space(s) in the MNE Report. I would be nice to be able to quickly visualize the source space distribution, especially when working with automated ...

I would like to morph my label source estimates to an average brain, but it does not seem possible with the current mne-python API. I have reconstructed surface sources using the ...