EEG-ExPy: Democratizing the Cognitive Neuroscience Experiment

Poster Session C - Sunday, April 14, 2024, 5:00 – 7:00 pm EDT, Sheraton Hall ABC

John D Griffiths¹ (j.davidgriffiths@gmail.com), Taha Morshedzadeh¹, Sorenza Bastiaens¹, Ore Ogundipe², Erik Bjareholt³, Daniele Marinazzo⁴, Yannick Roy⁵, EEG-ExPy Team .⁶; ¹University of Toronto & Centre for Addiction & Mental Health, ²Fusion Research Inc., ³Lund University, ⁴Unversity of Ghent, ⁵McGill Universty, ⁶github.com/NeurotechX/EEG-ExPy

Cognitive neuroscience experiments using EEG and related techniques have traditionally been restricted to lab settings, with dedicated space, expensive hardware, and professional technical/academic/student staff. Fortunately however, it is now becoming possible to run a wide range of classic experimental paradigms in a highly affordable fashion with minimal specialist equipment and expertise. This shift represents to many a "democratizaton of the cognitive neuroscience experiment". It is in this spirit that we introduce EEG-ExPy (github.com/NeuroTechX/EEG-ExPy) - A Python-based platform for cognitive neuroscience experimentation and education. This new tool allows a variety of visual, auditory, and other tasks to be run using a personal computer and a minimal+affordable, wireless (bluetooth), consumer-grade EEG device (e.g. InteraXon Muse, Neurosity Crown, OpenBCI Cyton, G.tec Unicorn). It can also be used with research-grade systems (including concurrently with mobile devices) in a lab setting. EEG-ExPy offers a fully self-contained solution to running cognitive neuroscience studies, with functionality spanning the entire span of data recording/stimulus presentation/analysis, with setup times of <30 seconds. This ease of use makes it attractive for a wide audience, including research scientists, clinicians, educators, and hobbyists. Use cases to date span a wide range of settings, from high school outreach programs, hackathons, under/graduate-level neuroscience courses, brain stimulation clinical trials in psychiatry, and bedside recordings in neurology patients. Here we describe the motivation, design, and usage of EEG-ExPy, demonstrating data from several featured experiments, including face-selective N170 ERP components, visual and auditory oddball tasks, and frequency tagging with visual and steady-state evoked potentials.

Topic Area: METHODS: Neuroimaging