Addressing Racial and Phenotypic Bias in Human Neuroscience Methods

Typical EEG systems, the standard of care for neurological monitoring and a popular modality for vision sciences, do not work well for individuals with the coarse, dense, and curly hair common in the Black population (Etienne et al., 2020; IEEE EMBC). With more than 1 billion individuals of African descent across the globe, this not only compromises neurological care for a significant portion of the population, but also excludes these groups from basic neuroscience research studies. Our team developed the first solution to this problem by creating Sèvo Systems, a simple yet effective set of devices that leverage the strength of braided hair to improve scalp contact during brain recordings in individuals with coarse, dense, and curly hair. In this talk, I will briefly describe the Sèvo system and outline our ongoing assessments of its effectiveness in both research and clinical settings. Our work is the first step towards mitigating phenotypic biases embedded in this popular technology that may lead to misunderstandings of brain science and the exclusion of marginalized groups in human neuroscience and psychology research. I will also speak to other examples of phenotypic bias in neurotechnologies that we are seeking to improve at Carnegie Mellon including functional near-infrared spectroscopy (fNIRS) and pulse oximetry. I will outline ways that vision scientists can join the cause and use equitable and inclusive methodologies based on published work (Webb et al, 2022; Nature Neuro) and my personal experience in preparing different hair textures for neuroscience research.