Establishing an fNIRS Ecosystem for Open Software-Hardware Dissemination

建立开放软硬件传播的fNIRS生态系统

DAVID BOAS Show email (2018-01-01 to 2021-12-31) $1,100,042

Project ID: R24NS104096 (NINDS)

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Abstract

Functional near infrared spectroscopy (fNIRS) is a non-invasive brain imaging and monitoring modality that measures the changes in oxygenated and deoxygenated hemoglobin concentrations associated with brain activity. Over the past 20 years, there has been exponential growth in the number of publications utilizing fNIRS, demonstrating that the modality can measure cortical brain responses to varied stimuli relevant for investigations of both normal and pathological brain function and development, as well as for clinical applications. To facilitate and accelerate fNIRS adoption and impact, there is a great need for easy-to-use analysis software that can help standardize the analysis, presentation, and comparison and mining of results from across multiple labs, just as SPM did in the early days of fMRI. While there is currently limited availability of standardized tools, there are important advances in analysis software features (motion correction, cleaning of physiological contamination, group-level analysis, anatomically guided image reconstruction) that can be implemented in the next few years and disseminated to this rapidly growing community. In addition, the next big advance that will transform the technology is wearable fNIRS. By dispensing with optical fibers and placing light emitters (LED light sources) and receivers (photodiodes) directly on the head, wearable devices offer lower weight and higher flexibility than traditional fNIRS systems, with recent developments showing performance characteristics just as good as the standard non-portable systems. Wearable fNIRS will not only enable studies of brain activity associated with natural behaviors in natural settings, but it will also dramatically reduce the cost of fNIRS systems, making the technology accessible to a broader array of researchers and permitting scalability from simple to high-density fNIRS systems. Our vision is to create an open software-hardware ecosystem to promote and support the fNIRS community in the adoption and application of cutting-edge acquisition and analysis technology that meets the needs of our interested users. We will implement and disseminate software advances through our Homer software package and shared near infrared file format (SNIRF) facilitating the translation and utility of fNIRS. We also aim to expand the number of fNIRS researchers by broadly disseminating wearable fNIRS instrumentation that is significantly cheaper than current commercial systems and expands measurement capabilities while maintaining typical measurement performance specifications. Utilizing our decades of dissemination experience, we will establish this resource to rapidly grow the dissemination of fNIRS hardware and analysis software to a broader array of users groups. Further, our resource will become self-sustaining beyond the proposed 4 year grant lifetime. This will ensure a powerful impact on a broad range of applications pursued by our users including those studying normal and abnormal brain development, perception and cognition, neurological disorders, brain trauma, stroke, speech disorders, and motor control.

功能性近红外光谱（fNIRS）是一种非侵入性脑成像和监测模式，可测量与大脑活动相关的氧合和脱氧血红蛋白浓度的变化。在过去的20年中，利用fNIRS的出版物数量呈指数增长，证明该模式可以测量皮质脑对不同刺激的反应，这些刺激与正常和病理性脑功能和发育以及临床应用的研究相关。。为了促进和加速fNIRS的采用和影响，非常需要易于使用的分析软件，它可以帮助标准化分析，演示，比较和挖掘多个实验室的结果，就像SPM在早期所做的那样fMRI。虽然目前标准化工具的可用性有限，但分析软件功能（运动校正，生理污染清洁，组级分析，解剖学引导图像重建）的重要进展可以在未来几年内实施并传播到此快速发展的社区。此外，将改变技术的下一个重大进步是可穿戴的fNIRS。通过省去光纤并将光发射器（LED光源）和接收器（光电二极管）直接放在头上，可穿戴设备比传统的fNIRS系统具有更低的重量和更高的灵活性，最近的发展显示出与标准非传统性能特性一样好的性能特征。便携式系统。可穿戴式fNIRS不仅可以研究与自然环境中自然行为相关的大脑活动，还可以大大降低fNIRS系统的成本，使更多研究人员可以使用该技术，并允许从简单到高密度fNIRS的可扩展性系统。我们的愿景是创建一个开放的软件 - 硬件生态系统，以促进和支持fNIRS社区采用和应用最先进的采集和分析技术，以满足我们感兴趣的用户的需求。我们将通过我们的荷马软件包和共享近红外文件格式（SNIRF）实施和传播软件进展，以促进fNIRS的翻译和实用。我们还致力于通过广泛传播可穿戴的fNIRS仪器来扩大fNIRS研究人员的数量，这种仪器比现有的商用系统便宜得多，并且在保持典型测量性能规格的同时扩展了测量能力。利用我们数十年的传播经验，我们将建立这一资源，以便迅速将fNIRS硬件和分析软件的传播扩展到更广泛的用户群体。此外，我们的资源将超出拟议的4年授权期限内的自我维持。这将确保对我们的用户所追求的广泛应用产生强大影响，包括那些研究正常和异常大脑发育，感知和认知，神经障碍，脑外伤，中风，言语障碍和运动控制的应用。