活体人视网膜神经节细胞和受体细胞的渗透压对比功能成像
Functional imaging of ganglion and receptor cells in living human retina by osmotic contrast
摘要：
非侵入性地在体内成像神经元活动是巨大的兴趣，但目前的成像技术缺乏功能对比度或必要的显微分辨率。视网膜是中枢神经系统（CNS）中唯一允许我们直接进行光学访问的部分。不仅眼科疾病，而且许多中枢神经系统的退行性疾病都伴随着视网膜的病理变化。因此，视网膜神经元的功能分析可以导致这些疾病的早期和更好的诊断和理解。最近，我们表明，感光细胞的激活可以可视化在人类使用光学相干断层扫描数据的相位敏感评价。外段的光路长度响应于光刺激而改变几百纳米。在这里，我们显示感光细胞和神经节细胞的激活的同时成像。来自神经节细胞的信号比来自感光细胞的信号小十倍，并且只有使用抑制运动伪影的新算法才能看到。这使我们能够生成一个布线图，显示光感受器和神经节细胞之间的功能连接。我们提出了一个理论模型，解释了所观察到的内在光学信号的渗透体积的变化，诱导离子流入或流出。由于所有的神经元活动与离子通量，成像渗透诱导的尺寸变化与纳米精度应可视化激活任何神经元。
英文摘要：
Imaging neuronal activity non-invasively in vivo is of tremendous interest, but current imaging techniques lack either functional contrast or necessary microscopic resolution. The retina is the only part of the central nervous system (CNS) that allows us direct optical access. Not only ophthalmic diseases, but also many degenerative disorders of the CNS go along with pathological changes in the retina. Consequently, functional analysis of retinal neurons could lead to an earlier and better diagnosis and understanding of those diseases. Recently, we showed that an activation of photoreceptor cells could be visualized in humans using a phase sensitive evaluation of optical coherence tomography data. The optical path length of the outer segments changes by a few hundred nanometers in response to optical stimulation. Here, we show simultaneous imaging of the activation of photoreceptor and ganglion cells. The signals from the ganglion cells are ten-fold smaller than those from the photoreceptor cells and were only visible using new algorithms for suppressing motion artifacts. This allowed us to generate a wiring diagram showing functional connections between photoreceptors and ganglion cells. We present a theoretical model that explains the observed intrinsic optical signals by osmotic volume changes, induced by ion influx or efflux. Since all neuronal activity is associated with ion fluxes, imaging osmotic induced size changes with nanometer precision should visualize activation in any neuron.
机构、总结、中文摘要均由AI分析而来，可能存在错误，请以论文正文为准。
