Franceschini Maria Angela, Joseph Danny K, Huppert Theodore J, Diamond Solomon G, Boas David A
Massachusetts General Hospital, Athinoula A. Martinos Center for Biomedical Imaging, 13th Street, Bldg. 149 (RM 2301), Charlestown, Massachusetts 02129, USA.
J Biomed Opt. 2006 Sep-Oct;11(5):054007. doi: 10.1117/1.2363365.
Near-Infrared Spectroscopy (NIRS) and diffuse optical imaging (DOI) are increasingly used to detect hemodynamic changes in the cerebral cortex induced by brain activity. Until recently, the small number of optodes in NIRS instruments has hampered measurement of optical signals from diverse brain regions. Our new DOI system has 32 detectors and 32 sources; by arranging them in a specific pattern, we can cover most of the adult head. With the increased number of optodes, we can collect optical data from prefrontal, sensorimotor, and visual cortices in both hemispheres simultaneously. We describe the system and report system characterization measurements on phantoms as well as on human subjects at rest and during visual, motor, and cognitive stimulation. Taking advantage of the system's larger number of sources and detectors, we explored the spatiotemporal patterns of physiological signals during rest. These physiological signals, arising from cardiac, respiratory, and blood-pressure modulations, interfere with measurement of the hemodynamic response to brain stimulation. Whole-head optical measurements, in addition to providing maps of multiple brain regions' responses to brain activation, will enable better understandings of the physiological signals, ultimately leading to better signal processing algorithms to distinguish physiological signal clutter from brain activation signals.
近红外光谱(NIRS)和扩散光学成像(DOI)越来越多地用于检测大脑活动引起的大脑皮质血流动力学变化。直到最近,NIRS仪器中光探测器数量较少,限制了对不同脑区光信号的测量。我们的新型DOI系统有32个探测器和32个光源;通过以特定模式排列它们,我们可以覆盖大部分成人头部。随着光探测器数量的增加,我们可以同时从双侧半球的前额叶、感觉运动和视觉皮质收集光学数据。我们描述了该系统,并报告了在体模以及静息状态和视觉、运动及认知刺激期间人体受试者上的系统特性测量结果。利用该系统更多的光源和探测器,我们探索了静息期间生理信号的时空模式。这些由心脏、呼吸和血压调制产生的生理信号会干扰对大脑刺激的血流动力学反应的测量。全脑光学测量除了能提供多个脑区对大脑激活反应的图谱外,还将有助于更好地理解生理信号,最终带来更好的信号处理算法,以区分生理信号干扰和大脑激活信号。