Automated 3-D mapping of single neurons in the standard brain atlas using single brain slices

Abstract

11Recent breakthroughs in neuroanatomical tracing methods have helped unravel 12 complicated neural connectivity in whole brain tissue at a single cellular resolution. 13However, analysis of brain images remains dependent on highly subjective manual 14 processing. In the present study, we introduce AMaSiNe, a novel software for 15 automated mapping of single neurons in the standard mouse brain atlas. The AMaSiNe 16 automatically calibrates alignment angles of each brain slice to match the Allen 17Reference Atlas (ARA), locates labeled neurons from multiple brain samples in a 18 common brain space, and achieves a standardized 3D-rendered brain. Due to the high 19 fidelity and reliability of AMaSiNe, the retinotopic structures of neural projections to 20 the primary visual cortex (VISp) were determined from single and dual injections of the 21 rabies virus onto different visual areas. Our results demonstrate that distinct retinotopic 22 organization of bottom-up and top-down projections could be precisely mapped using 23AMaSiNe. 24

Bi-channel image registration and deep-learning segmentation (BIRDS) for efficient, versatile 3D mapping of mouse brain

“…Moreover, though registration-based methods can achieve full anatomical annotation in reference to a standard atlas for whole-brain datasets, their region-based 3D registration to a whole-brain atlas lacks the flexibility to analyze incomplete brain datasets or those focused on a certain volume of interest ( Song and Song, 2018 ), which is often the case in neuroscience research. Though some frameworks can register certain types of brain slabs that contain complete coronal outlines slice by slice ( Fürth et al, 2018 ; Song and Song, 2018 ; Ferrante and Paragios, 2017 ), it remains very difficult to register a small brain block without obvious anatomical outlines.…”

“…Moreover, though registration-based methods can achieve full anatomical annotation in reference to a standard atlas for whole-brain datasets, their region-based 3D registration to a whole-brain atlas lacks the flexibility to analyze incomplete brain datasets or those focused on a certain volume of interest ( Song and Song, 2018 ), which is often the case in neuroscience research. Though some frameworks can register certain types of brain slabs that contain complete coronal outlines slice by slice ( Fürth et al, 2018 ; Song and Song, 2018 ; Ferrante and Paragios, 2017 ), it remains very difficult to register a small brain block without obvious anatomical outlines. As neural networks have emerged as a technique of choice for image processing ( Long et al, 2015 ; Chen et al, 2018a ; He et al, 2019 ; Zhang et al, 2019 ), deep-learning-based brain mapping methods have also recently been reported to directly provide segmentation/annotation of primary regions for 3D brain datasets ( Iqbal et al, 2019 ; Akkus et al, 2017 ; Chen et al, 2018b ; Milletari et al, 2017 ; de Brebisson and Montana, 2015 ).…”

A tool for analyzing electrode tracks from slice histology

“…First, creating the transforms by manual input can be timeconsuming when an experiment involves many brain slices. In a future version, SHARP-Track's manual features could be combined with an algorithm to automatically register slices such as that found in Song et al, 2018. Second, we found that there remains some error and inconsistency in marking electrode trajectories (Figure 4).…”

“…We recommend prioritizing that the transform is accurate nearby the region of interest. An alternative approach could incorporate non-rigid transformations as in Fürth et al, 2018, Song et al, 2018, and Xiong et al, 2018 One feature generally lacking in electrodelocalization toolkits is the use of brain regions' distinct electrophysiological signatures. A future Figure 4.…”

“…Fürth et al, 2018 addresses the latter two problems with automated nonlinear slice registration and visualization tools but expects unangled coronal slices and a manual estimation of the anterior-posterior location. Song et al, 2018 andXiong et al, 2018 demonstrate automated registration of angled slices but do not yet provide an interface for registration and manual fine-tuning. Methods that produce volumetric images of the brain, such as serial-section two-photon imaging and light-sheet imaging of cleared brains, can resolve all three problems (Mayerich et al, 2008, Ragan et al, 2012, Renier et al, 2014, Niedworok et al, 2016, Vandenberghe et al, 2016 but can be impractical due to the extensive setup and expensive equipment required.…”