The second part of this series demonstrate additional preprocessing steps. Specifically, it addresses the problem of eye artifacts which are omnipresent in EEG recordings. It also demonstartes a procedure for repairing and rejecting noise-contaminated channels and segments.

Preprocessing is an important and controversial topic in EEG research. Here, I discuss it’s necessity and present a minimal preprocessing pipeline that deals with the most common sources of noise while avoiding to distort the data. I demonstrate each step using publicly available data.

We established an experimental setup to study sound localization behavior in a controlled environment using arrays of loudspeakers, digital signal processors, infra-red cameras and custom Python code.

Slab was designed for creating and running experiments on acoustic perception while providing a good learning experience for users lacking prior experience in coding. It is routinely used by students and researchers in auditory neuroscience.