EEG Machine Learning #34
Description
Added as an issue for book keeping
Source:
https://brainhack-dallas.github.io/mini-brainhack-utd/#projects
Matt Kmiecik
Matthew.Kmiecik@utdallas.edu
Goal: Explore applications of machine learning to electrophysiological data
Description: Two participant groups (controls vs. individuals with alcoholism) were shown images that were either identical or different while their scalp EEG was recorded. This brainhack project will explore ways to visualize event-related potentials (ERPs) and identify features within electrophysiological signals that differentiate how alcoholic from non-alcoholic individuals identify similarities and differences in their visual field.
Tools: R, GitHub, EEGLAB, MATLAB