Optical Tomography and Decoding for Communication via Brain-Computer Interface
Optical Tomography and Decoding for Communication via Brain-Computer Interface
批准号:
9911583
负责人:
Zachary E Markow
金额:
$4.5万
依托单位:
依托单位国家:
美国
项目类别:
财政年份:
2020
资助国家:
美国
项目状态:
已结题
起止时间:
2020-01-01 至 2021-12-31
关键词:
AdultAmyotrophic Lateral SclerosisAugmentative and Alternative CommunicationBiomedical EngineeringBloodBrainBrain imagingBrain scanCerebral PalsyChildClipCollectionColorCommunicationComputersDataDevicesElectrocorticogramElectrodesElectroencephalographyElementsEquipmentEyeFellowshipFoundationsFrequenciesFunctional Magnetic Resonance ImagingGoalsHearingImageImaginationInstructionLanguageLearningLettersLightLimb ProsthesisLiteratureLocked-In SyndromeMachine LearningMapsMethodsModelingMotorMuscleNear-Infrared SpectroscopyOperative Surgical ProceduresOptical TomographyOpticsPatientsPatternPerformancePhasePhysiologicalPropertyPsyche structureQuality of lifeResearchResearch Project GrantsResolutionSemanticsShapesSignal TransductionSpeechStimulusSurfaceSystemTechnologyTemporal LobeTestingTrainingTravelVisualVisual CortexWorkbasebrain computer interfacecareercostdensitydiffuse optical tomographyexperienceexperimental studyextrastriate visual cortexfrontal lobehuman subjectimaging approachimaging systemimprovedlight weightmental imagerymotor impairmentmovieneuroimagingnon-invasive systemoptical imagingportabilityresponsesuccesstoolvirtual
中文摘要
项目概述:这项研究的长期目标是开发一种新的、非侵入性的脑计算机
接口(BCI)将为以下患者提供增强和替代通信(AAC)功能
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)。拟议的研究项目将会奏效。
通过开发基于来自高密度漫反射光学的脑成像信号的脑机接口来实现长期目标
断层扫描(HDDOT)。一些现有的BCI记录脑电(EEG)或皮层脑电图仪
(ECOG)来自患者的信号,然后将这些信号解码成用于操作
外部世界,如屏幕上的光标、假肢或虚拟键盘。此功能可以实现
沟通。然而,脑机接口在患有脑电或脑血管疾病的CLIS患者中的成功和能力通常有限。
依赖于侵入性技术,如ECoG或皮质内记录,这需要手术放置
大脑表面上或下面的电极。尽管功能磁共振成像(FMRI)最近取得了巨大的成功
通过对对象观看或听到的项目进行解码(例如,从100个观看的图像中区分),
需要笨重、昂贵的设备,而这些设备不能用于严重运动障碍患者的常规脑血流灌注。
相关的沟通障碍。相比之下,光学成像方法,如近红外光谱分析
(NIR),使用便携式、可穿戴硬件。这些光学系统是非侵入性的并且使用非电离,
近红外光产生血液氧合的电影,从而提供生理信息
与功能磁共振信号相当。NIRS最近已被应用为EEG BCI的替代方案,用于解码SIMPLE
CLIS患者的是/否反应。然而,近红外系统的空间分辨率比fMRI低得多,
这使得NIR不太可能与fMRI的解码能力相匹配。高密度漫反射光学层析成像
(HDDOT)结合了EEG和NIRS的轻量级、低成本设备优势和更高的空间分辨率
更接近大脑表面的功能磁共振成像。HDDOT系统的最新进展使平均空间
定位误差<;5 mm和空间分辨率<;17-20 mm(大大优于近红外光谱)。研究表明,
演示了视觉和语言任务的详细地图。这些特性使HDDOT成为理想的选择
破译大脑功能的候选工具。研究金培训将提供坚实的光学基础
神经成像方法、机器学习和脑机接口。这些经历将为
应聘者特别适合从事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。
英文摘要
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.
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Optical Tomography and Decoding for Communication via Brain-Computer Interface
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批准号:10078847
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项目类别:
-
资助金额:$2.95万
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财政年份:2020
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负责人:Zachary E Markow
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依托单位:
海外基金