• Jasmine Kwasa, a Ph.D. student at Carnegie Mellon University, noticed that EEG technology had limited functionality with thick curly, kinky, and textured hair types, leading to potential exclusion from research.
• Biases against physical characteristics like dark skin and thick curly hair are baked into all major neuroimaging technologies, including EEG, fNIRS, and MRI.
• Neurobiological datasets are overwhelmingly white, with 95% of the data collected by the UK Biobank corresponding to white study subjects and the Human Connectome Project (HCP) being 76% white.
• Carla Bailey, a neurophysiologist at Groote Schuur Hospital in Cape Town, South Africa, says she only encounters issues with EEG and Black hair when people don’t remove hair extensions that obscure the scalp.
• Precision Neuroscopics is perfecting the Sevo clip, which holds electrodes against the scalp between cornrows braided to accommodate electrode placement, and collecting evidence that it improves the quality of EEG data.
• A 2022 study found that machine learning algorithms trained on large neuroimaging datasets that favor white populations inaccurately predicted the behavior of Black Americans.
Published February 15, 2023
Visit Nautilus to read Jackie Rocheleau’s original post Neuroscience Has a Race Problem
