Understanding Brain-Computer Interfaces with Python
A technical approach to understanding BCIs
Something about the brain evokes intrigue from almost anyone who views it; it is both ambiguous in its intricacy and specific in its action. Further, the sophistication of the brain demands a level of ingenuity and creativity when studying it.
In my previous article, An Introduction to Brain-Computer Interfaces¹, I have detailed some of the complexities of the brain and the associated neurotechnologies. These complexities can be difficult to understand, but certain tools allow almost anyone to be able to work with neuroimaging data and replicate scientific experiments².
The MNE-Python³ module is an open-source python package used for viewing neurophysiological tools. It is one of the only accessible tools that allow for online sample data of EEG, ECoG, MEG, and other acquisition methods to be viewed, manipulated, and analyzed. This library is extremely helpful in visualizing many of the steps used in various BCI systems and better understand this emerging technology. This article will cover the capabilities of MNE and working with sample datasets to test some of these capabilities.
