Diversity in Neuroscience
Diversity in Neuroscience
Diversity in neuroscience is crucial for advancing our understanding of the human brain in all its complexity and variation. One often overlooked aspect of diversity is hair texture and color. fNIRS relies on direct contact with the scalp for light to emit, which can be more challenging with different hair textures, particularly coarse, darker, curlier hair. Ensuring that neuroimaging technologies and methodologies are inclusive and effective for people with all hair types is essential for generating accurate, representative data. If unaddressed, there's a risk of reinforcing biases against specific demographic groups, specifically those with coarser and thicker hair. By prioritizing diversity in research participants and developing adaptable techniques, neuroscience can achieve more equitable, comprehensive insights that benefit everyone. Please check out the video below to learn about how our lab is taking steps towards developing novel techniques to bridge the gap.
There is an absence of adequate reporting of demographic data and hair phenotypes which highlights the need for researchers to be more transparent of data inclusivity (Kwasa et al., 2023).
Reference
Kwasa, J., Peterson, H. M., Karrobi, K., Jones, L., Parker, T., Nickerson, N., & Wood, S. (2023). Demographic reporting and phenotypic exclusion in fNIRS. Frontiers in neuroscience, 17, 1086208. https://doi.org/10.3389/fnins.2023.1086208
Conferences, Presentations, and Posters
Eng, C.M., Hassan, N., Kwasa, J., Wandless, E., Gao, Y., & Reiss, A.L. (2024). Phenotypic Inclusion using fNIRS and Increasing Equity in Basic Cognitive Developmental Neuroscience Research. The Cognitive Developmental Society Conference Symposium, Pasadena, CA. Flash Talk: https://www.youtube.com/watch?v=WpdTLdgYQg4
Hassan, N., Wandless, E., Moron, S., Gao, Y., Reiss, A.L., & Eng, C.M. (2023). Hair Me Out: Phenotypic Inclusion using fNIRS and Increasing Equity in Neuroscience. Wu Tsai Neurosciences Institute NeURO Fellowship Symposium, Stanford, CA.