Imaging and Analysis Techniques to Construct a Cell Census Atlas of the Human Brain Admin Supplement

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Abstract The ~86 billion neurons that form the human brain are organized at multiple scales, ranging from the fine details of an individual neuron’s dendritic arborization, to local circuits that are embedded within large-scale systems spanning the brain. In this project, we will image across this vast range of scales to create a multiscale atlas akin to Google Earth for the human brain that can visualize hemisphere-wide networks and then zoom in to see individual, labeled cells at micron resolution in the frontal temporal lobe. This dramatic advance will be made possible through the use of an array of imaging technologies, including light-sheet microscopy (LSM), tissue clearing, immunohistochemistry (IMH), magnetic resonance imaging (MRI) and newly developed techniques in Optical Coherence Tomography (OCT). OCT in particular is a potentially transformative technology as it provides micron resolution over large volumes of tissue, images all of the tissue (as opposed to fluorescence), does not require mounting and staining and hence can be automated, and is essentially distortion free as it images the tissue prior to cutting. LSM-based IMH will provide molecular, morphological and spatial properties of cells that will enable us to develop cellular classification systems, while OCT images of the same tissue will enable us to remove the distortions induced by cutting and clearing, and transfer information to whole-hemisphere MRI for atlasing and in vivo inference. This transfer of information depends critically on the ability to register images across a huge range of resolutions and contrast types. For this we propose to use the endogenous fiducial landmarks provided by the cerebral vasculature. To take full advantage of the vasculature using deep learning requires a training set of labeled vessels in each of our imaging modalities across an array of examples. The goal of this supplement is to provide these labelings including the assessment of intra- and inter-rater reliability.