Doherty Emily J, Spencer Cara A, Burnison Jeremy, Čeko Marta, Chin Jenna, Eloy Lucca, Haring Kerstin, Kim Pilyoung, Pittman Daniel, Powers Shannon, Pugh Samuel L, Roumis Demetris, Stephens Jaclyn A, Yeh Tom, Hirshfield Leanne
Department of Computer Science, University of Colorado Boulder, Boulder, CO, United States.
Institute of Cognitive Science, University of Colorado Boulder, Boulder, CO, United States.
Front Integr Neurosci. 2023 Feb 27;17:1059679. doi: 10.3389/fnint.2023.1059679. eCollection 2023.
Functional Near-Infrared Spectroscopy (fNIRS) is an innovative and promising neuroimaging modality for studying brain activity in real-world environments. While fNIRS has seen rapid advancements in hardware, software, and research applications since its emergence nearly 30 years ago, limitations still exist regarding all three areas, where existing practices contribute to greater bias within the neuroscience research community. We spotlight fNIRS through the lens of different end-application users, including the unique perspective of a fNIRS manufacturer, and report the challenges of using this technology across several research disciplines and populations. Through the review of different research domains where fNIRS is utilized, we identify and address the presence of bias, specifically due to the restraints of current fNIRS technology, limited diversity among sample populations, and the societal prejudice that infiltrates today's research. Finally, we provide resources for minimizing bias in neuroscience research and an application agenda for the future use of fNIRS that is equitable, diverse, and inclusive.
功能近红外光谱技术(fNIRS)是一种创新且颇具前景的神经成像方式,用于在现实环境中研究大脑活动。自近30年前出现以来,fNIRS在硬件、软件和研究应用方面取得了快速进展,但在这三个领域仍然存在局限性,现有做法在神经科学研究界造成了更大的偏差。我们从不同终端应用用户的角度,包括fNIRS制造商的独特视角,对fNIRS进行了聚焦,并报告了在多个研究学科和人群中使用该技术所面临的挑战。通过对fNIRS应用的不同研究领域的回顾,我们识别并解决了偏差的存在问题,特别是由于当前fNIRS技术的限制、样本群体多样性有限以及渗透到当今研究中的社会偏见。最后,我们提供了减少神经科学研究中偏差的资源以及fNIRS未来公平、多样和包容使用的应用议程。