EEG-Notebooks is a Python-based library developed by the NeuroTechX community for running cognitive neuroscience experiments with low-cost mobile EEG devices. It is intended as a tool for research, medical applications, and education - with the goal of making cognitive neuroscience and neurotechnology more accessible, affordable, and scalable. EEG-Notebooks is built around the standard Scientific Python and Neuroimaging-in-Python software stack (numpy, scipy, pandas, scikit-learn, MNE), and uses Psychopy for stimulus delivery and programming of experimental paradigms.
This GSoC project will focus on extending the experiment repertoire of eeg-notebooks, by porting the high-quality research paradigm implementations (face perception, auditory oddball, visual search, word pair judgment, flanker task) from the ERP-core platform. Additionally, the project will also develop novel statistical data analysis and machine learning analyses of various datasets shipped with the library.
Candidates should have experience with Python, data analysis, and EEG and/or behavioural/psychological experiments. Access to EEG hardware is not essential. The project will provide excellent experience and training for students interested in pursuing research in human neuroimaging, cognitive and clinical neuroscience, and brain-computer interfaces.
Tags: Python, EEG, Neurotechnology, Data Analysis, Machine Learning, Cognitive Neuroscience, EEG-Notebooks, electrophysiology