Imaging and quantifying ganglion cells and other transparent neurons in the living human retina

dc.contributor.authorLiu, Zhuolin
dc.contributor.authorKurokawa, Kazuhiro
dc.contributor.authorZhang, Furu
dc.contributor.authorLee, John J.
dc.contributor.authorMiller, Donald T.
dc.contributor.departmentEngineering Technology, School of Engineering and Technologyen_US
dc.date.accessioned2018-06-13T18:04:53Z
dc.date.available2018-06-13T18:04:53Z
dc.date.issued2017-11-28
dc.description.abstractGanglion cells are the primary building block of retinal neural circuitry, but have been elusive to observe and quantify in the living human eye. Here, we show a light microscopy modality that reveals not only the somas of these cells, but also their 3D packing geometry, primary subtypes, and spatial projection to other neurons. The method provides a glimpse of the rich tapestry of neurons, glia, and blood vessels that compose the retina, thus exposing the anatomical substrate for neural processing of visual information. Clinically, high-resolution images of retinal neurons in living eyes hold promise for improved diagnosis and assessing treatment of ganglion cell and other neuron loss in retinal disease., Ganglion cells (GCs) are fundamental to retinal neural circuitry, processing photoreceptor signals for transmission to the brain via their axons. However, much remains unknown about their role in vision and their vulnerability to disease leading to blindness. A major bottleneck has been our inability to observe GCs and their degeneration in the living human eye. Despite two decades of development of optical technologies to image cells in the living human retina, GCs remain elusive due to their high optical translucency. Failure of conventional imaging—using predominately singly scattered light—to reveal GCs has led to a focus on multiply-scattered, fluorescence, two-photon, and phase imaging techniques to enhance GC contrast. Here, we show that singly scattered light actually carries substantial information that reveals GC somas, axons, and other retinal neurons and permits their quantitative analysis. We perform morphometry on GC layer somas, including projection of GCs onto photoreceptors and identification of the primary GC subtypes, even beneath nerve fibers. We obtained singly scattered images by: (i) marrying adaptive optics to optical coherence tomography to avoid optical blurring of the eye; (ii) performing 3D subcellular image registration to avoid motion blur; and (iii) using organelle motility inside somas as an intrinsic contrast agent. Moreover, through-focus imaging offers the potential to spatially map individual GCs to underlying amacrine, bipolar, horizontal, photoreceptor, and retinal pigment epithelium cells, thus exposing the anatomical substrate for neural processing of visual information. This imaging modality is also a tool for improving clinical diagnosis and assessing treatment of retinal disease.en_US
dc.eprint.versionFinal published versionen_US
dc.identifier.citationLiu, Z., Kurokawa, K., Zhang, F., Lee, J. J., & Miller, D. T. (2017). Imaging and quantifying ganglion cells and other transparent neurons in the living human retina. Proceedings of the National Academy of Sciences of the United States of America, 114(48), 12803–12808. https://doi.org/10.1073/pnas.1711734114en_US
dc.identifier.issn0027-8424en_US
dc.identifier.urihttps://hdl.handle.net/1805/16488
dc.language.isoen_USen_US
dc.publisherNational Academy of Sciencesen_US
dc.relation.isversionof10.1073/pnas.1711734114en_US
dc.relation.journalProceedings of the National Academy of Sciences of the United States of Americaen_US
dc.rightsAttribution-NonCommercial-NoDerivs 3.0 United States
dc.rights.urihttp://creativecommons.org/licenses/by-nc-nd/3.0/us/
dc.sourcePMCen_US
dc.subjectadaptive opticsen_US
dc.subjectoptical coherence tomographyen_US
dc.subjectorganelle motilityen_US
dc.subjectretinaen_US
dc.subjectretinal ganglion cellsen_US
dc.titleImaging and quantifying ganglion cells and other transparent neurons in the living human retinaen_US
dc.typeArticleen_US
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