Demographic Reporting and Phenotypic Exclusion in fNIRS

Abstract

Functional near-infrared spectroscopy (fNIRS) promises to be a leading non-invasive neuroimaging method due to its portability and low cost. However, concerns are rising over its inclusivity of all skin tones and hair types (Parker and Ricard 2022, Webb et al 2022). Functional NIRS relies on direct contact of light-emitting optodes to the scalp, which can be blocked more by longer, darker, and especially curlier hair. Additionally, NIR light can be attenuated by melanin, which is accounted for in neither fNIRS hardware nor analysis methods. Recent work has shown that overlooking these considerations in other modalities like EEG leads to the disproportionate exclusion of individuals with these phenotypes - especially Black people - in both clinical and research literature (Bradford et al 2022, Choy 2020). In this article, we sought to determine if (1) biomedical optics developers and researchers report fNIRS performance variability between skin tones and hair textures, (2a) fNIRS neuroscience practitioners report phenotypic and demographic details in their articles, and thus, (2b) is a similar pattern of participant exclusion found in EEG also present in the fNIRS literature. We present a literature review of top Biomedical Optics and Human Neuroscience journals, showing that demographic and phenotypic reporting is unpopular in both fNIRS development and neuroscience applications. We conclude with a list of recommendations to the fNIRS community including examples of Black researchers addressing these issues head-on, inclusive best practices for fNIRS researchers, and recommendations to funding and regulatory bodies to achieve an inclusive neuroscience enterprise in fNIRS and beyond.

Interdisciplinary views of fNIRS: Current advancements, equity challenges, and an agenda for future needs of a diverse fNIRS research community

“…As the technology continues to develop, some of the current high-end fNIRS devices already contain features that help optimize signal quality in the context of the challenging phenotypes of darker hair and skin, including dynamic range adjustment for each individual optode and more sensitive light detection technology. However, there is still much to do to make fNIRS accessible to all hairstyles, textures, and colors, which is why multiple studies have recently launched with the aim of characterizing performance systematically in across participants with different hair and skin types to better understand the current state of the issue, identify opportunities for improvement, and direct further technology development (Nagels-Coune et al, 2020;Kwasa et al, 2022).…”

“…We can look to the efforts made by the public health research and computer research communities to reduce the bias in their respective fields (e.g., Ford et al, 2018;Loi, 2021). Ethics committees and institutional review boards can require investigators to record the ways in which they are actively minimizing the bias in their work (Kwasa et al, 2022), such as Boston University and Boston Medical Center's Reducing Implicit and Explicit Bias in Research form (Boston University, 2022). Journals can reduce publication biases of prioritizing novelty, by accepting replication studies with more representative samples or modified methods and meriting participant diversity in the review process (Roberts et al, 2020).…”

“…Despite these improvements in fNIRS technology, a growing concern within the overall research community, especially in the field of neuroscience, is the presence of bias regarding the collection and diversity of data from limited populations (Webb et al, 2022). While technological advancements have allowed the exploration of new research spaces, the hardware itself makes it difficult to collect fNIRS data on certain populations including people with darker skin and hair (Kwasa et al, 2022) and those with sensorymotor issues (Arenth et al, 2007). Another avenue for bias is from prejudice and harmful views present in society that infiltrate this type of research in many ways (Roberts et al, 2020;Bradford et al, 2022), that will be explored later in the paper (see Section 4).…”

The Intersection of Racism and Neuroscience Technology: A Cautionary Tale for the Criminal Legal System

“…The phenotypic biases of current EEG technology are not unique; similar problems have been documented using other neuroscience methodologies, such as functional near-infrared spectroscopy (fNIRS). fNIRS uses near-infrared light to detect changes in brain activity through the skin, but in doing so, it imposes assumptions about light absorption that are based on individuals with low levels of melanin (i.e., light skin; Doherty et al, 2023; Kwasa et al, 2023; Ricard et al, 2023). fNIRS shows lower reliability and validity for participants with greater melanin concentrations (i.e., darker skin; Wassenaar & Van Den Brand, 2005).…”

“…fNIRS shows lower reliability and validity for participants with greater melanin concentrations (i.e., darker skin; Wassenaar & Van Den Brand, 2005). Further, like EEG, fNIRS relies on electrode–scalp contact, creating barriers for people with curly, tightly coiled, dense, or voluminous hair or weaves, dreadlocks, or braids (Doherty et al, 2023; Kwasa et al, 2023; Ricard et al, 2023).…”