Optical Tomography and Decoding for Communication via Brain-Computer Interface

项目概述：本研究的长期目标是开发一种新的、非侵入性的脑-计算机 脑机接口（BCI），将提供增强和替代通信（AAC）能力的患者， 由于严重的运动障碍，如完全闭锁综合征（CLIS）， 肌萎缩侧索硬化症（ALS）和严重脑瘫（CP）。拟议的研究项目将工作 通过开发基于来自高密度漫射光的脑成像信号的BCI， 断层扫描（HDDOT）。一些现有的BCI记录脑电图（EEG）或皮质电图 （ECoG）信号，然后将这些信号解码成用于操作ECoG系统的一些元件的指令。 外部世界，如屏幕上的光标、假肢或虚拟键盘。该功能可以使 通信然而，BCI通常在具有EEG或MRI的CLIS患者中具有有限的成功和能力。 依赖于侵入性技术，如ECoG或皮质内记录，这需要手术放置 大脑表面上或下的电极。虽然功能性磁共振成像（fMRI）最近取得了巨大的成功， 通过解码对象观看或听到的项目（例如，区别于>100个查看的图像），fMRI 需要笨重、昂贵的设备，不能用于严重运动神经功能障碍患者的常规BCI。 相关的沟通障碍。相比之下，光学成像方法，例如近红外光谱法， （NIRS），采用便携式可穿戴硬件。这些光学系统是非侵入性的并且使用非电离的， 近红外光来创建血液氧合的电影，从而提供生理信息 与功能性磁共振成像信号相当。NIRS最近已被应用作为EEG BCI的替代方案，用于解码简单的 CLIS患者的回答是/否。然而，NIRS系统的空间分辨率比fMRI低得多， 这使得近红外光谱不可能匹配功能磁共振成像的解码能力。高密度扩散光学层析成像 （HDDOT）结合了EEG和NIRS的轻便、低成本设备优势以及更高的空间分辨率 更接近于大脑表面的功能磁共振成像。HDDOT系统的最新进展使得平均空间分辨率成为可能。 定位误差<5 mm，空间分辨率<17-20 mm（远优于NIRS）。研究 展示了视觉和语言任务的详细地图。这些特性使HDDOT成为理想的 解码大脑功能的候选工具。该奖学金培训将提供一个坚实的基础，在光学 神经成像方法、机器学习和脑机接口。这些经验将使 申请人非常擅长生物医学工程研究和开发技术， 将改善这些患者的生活质量。

Project Summary: The long-term goal of this research is to develop a new, non-invasive brain-computer interface (BCI) that will provide augmentative and alternative communication (AAC) capabilities to patients who have lost these capabilities due to severe motor impairments, such as completely locked-in syndrome (CLIS), amyotrophic lateral sclerosis (ALS), and severe cerebral palsy (CP). The proposed research project will work towards a long-term goal by developing a BCI based on brain imaging signals from high-density diffuse optical tomography (HDDOT). Some existing BCIs record electroencephalography (EEG) or electrocorticography (ECoG) signals from patients and then decode these signals into instructions for operating some element of the outside world, such as a cursor on a screen, a prosthetic limb, or a virtual keyboard. This functionality can enable communication. However, BCI generally has had limited success and capabilities in CLIS patients with EEG or has relied on invasive technology such as ECoG or intracortical recordings, which require surgical placement of electrodes on or beneath the brain surface. Although functional MRI (fMRI) has recently achieved great success with decoding items viewed or heard by subjects (e.g., distinguishing from among >100 viewed images), fMRI requires bulky, expensive equipment that cannot be employed for routine BCI for patients with severe motor- related communication deficits. In contrast, optical imaging approaches, such as near-infrared spectroscopy (NIRS), employ portable, wearable hardware. These optical systems are non-invasive and use non-ionizing, near-infrared light to create movies of blood oxygenation and therefore provide physiological information comparable to the fMRI signal. NIRS has recently been applied as an alternative to EEG BCI for decoding simple yes/no responses in CLIS patients. However, NIRS systems suffer from much-lower spatial resolution than fMRI, which renders NIRS unlikely to match the decoding capabilities of fMRI. High-density diffuse optical tomography (HDDOT) combines the lightweight, low-cost equipment benefits of EEG and NIRS with higher spatial resolution closer to that of fMRI at the brain surface. Recent advances in HDDOT systems have enabled average spatial localization errors <5 mm and spatial resolution <17-20 mm (substantially better than NIRS). Studies have demonstrated detailed maps of both visual and language tasks. These properties make HDDOT an ideal candidate tool for decoding brain function. The fellowship training will provide a strong foundation in optical neuroimaging methods, machine learning, and brain-computer interface. These experiences will prepare the applicant exceptionally well for a career in biomedical engineering research and for developing technology that will improve these patients’ quality of life.