3D Reconstruction and Standardization of the Rat Vibrissal Cortex for Precise Registration of Single Neuron Morphology

Abstract Recent whole brain mapping projects are collecting large-scale 3D images using powerful and informative modalities, such as STPT, fMOST, VISoR, or MRI. Registration of these multi-dimensional whole-brain images onto a standard atlas is essential for characterizing neuron types and constructing brain wiring diagrams. However, cross-modality image registration is challenging due to intrinsic variations of brain anatomy and artifacts resulted from different sample preparation methods and imaging modalities. We introduced a cross-modality registration method, called mBrainAligner, which uses coherent landmark mapping as well as deep neural networks to align whole mouse brain images to the standard Allen Common Coordinate Framework atlas. We also built a single cell resolution atlas using the fMOST modality, and used our method to generate whole brain map of 3D full single neuron morphology and neuron cell types.

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Detection and skeletonization of single neurons and tracer injections using topological methods

10.1101/2020.03.21.000323 ◽

2020 ◽

Author(s):

Dingkang Wang ◽

Lucas Magee ◽

Bing-Xing Huo ◽

Samik Banerjee ◽

Xu Li ◽

...

Keyword(s):

Single Neuron ◽

Image Data ◽

Connectivity Matrix ◽

Consensus Tree ◽

Neuron Morphology ◽

Tracer Injection ◽

Topological Methods ◽

Global Properties ◽

Branching Patterns ◽

Performance Gains

Neuroscientific data analysis has traditionally relied on linear algebra and stochastic process theory. However, the tree-like shapes of neurons cannot be described easily as points in a vector space (the subtraction of two neuronal shapes is not a meaningful operation), and methods from computational topology are better suited to their analysis. Here we introduce methods from Discrete Morse (DM) Theory to extract the tree-skeletons of individual neurons from volumetric brain image data, and to summarize collections of neurons labelled by tracer injections. Since individual neurons are topologically trees, it is sensible to summarize the collection of neurons using a consensus tree-shape that provides a richer information summary than the traditional regional ‘connectivity matrix’ approach. The conceptually elegant DM approach lacks hand-tuned parameters and captures global properties of the data as opposed to previous approaches which are inherently local. For individual skeletonization of sparsely labelled neurons we obtain substantial performance gains over state-of-the-art non-topological methods (over 10% improvements in precision and faster proofreading). The consensus-tree summary of tracer injections incorporates the regional connectivity matrix information, but in addition captures the collective collateral branching patterns of the set of neurons connected to the injection site, and provides a bridge between single-neuron morphology and tracer-injection data.

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Single neuron morphology in vivo with confined primed conversion

Methods in Cell Biology - The Zebrafish - Cellular and Developmental Biology, Part A Cellular Biology ◽

10.1016/bs.mcb.2015.12.005 ◽

2016 ◽

pp. 125-138 ◽

Cited By ~ 5

Author(s):

M.A. Mohr ◽

P. Pantazis

Keyword(s):

Single Neuron ◽

Neuron Morphology

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Detection, Averaging, and 3D Reconstruction of Biological Specimens on Hypercubes (Transputer-based) Computers

Proceedings, annual meeting, Electron Microscopy Society of America ◽

10.1017/s0424820100181026 ◽

1990 ◽

Vol 48 (1) ◽

pp. 454-455

Author(s):

Jose-Maria Carazo ◽

I. Benavides ◽

S. Marco ◽

J.L. Carrascosa ◽

E.L. Zapata

Keyword(s):

3D Reconstruction ◽

3D Structure ◽

Three Dimensional ◽

Software Tools ◽

Mapping Method ◽

Computer Architectures ◽

Parallel Computer ◽

Reconstruction Process ◽

Computing Power ◽

Order Of Magnitude

Obtaining the three-dimensional (3D) structure of negatively stained biological specimens at a resolution of, typically, 2 - 4 nm is becoming a relatively common practice in an increasing number of laboratories. A combination of new conceptual approaches, new software tools, and faster computers have made this situation possible. However, all these 3D reconstruction processes are quite computer intensive, and the middle term future is full of suggestions entailing an even greater need of computing power. Up to now all published 3D reconstructions in this field have been performed on conventional (sequential) computers, but it is a fact that new parallel computer architectures represent the potential of order-of-magnitude increases in computing power and should, therefore, be considered for their possible application in the most computing intensive tasks.We have studied both shared-memory-based computer architectures, like the BBN Butterfly, and local-memory-based architectures, mainly hypercubes implemented on transputers, where we have used the algorithmic mapping method proposed by Zapata el at. In this work we have developed the basic software tools needed to obtain a 3D reconstruction from non-crystalline specimens (“single particles”) using the so-called Random Conical Tilt Series Method. We start from a pair of images presenting the same field, first tilted (by ≃55°) and then untilted. It is then assumed that we can supply the system with the image of the particle we are looking for (ideally, a 2D average from a previous study) and with a matrix describing the geometrical relationships between the tilted and untilted fields (this step is now accomplished by interactively marking a few pairs of corresponding features in the two fields). From here on the 3D reconstruction process may be run automatically.

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Structural Studies on the Eukaryotic Ribosome

Proceedings, annual meeting, Electron Microscopy Society of America ◽

10.1017/s0424820100180033 ◽

1990 ◽

Vol 48 (1) ◽

pp. 256-257

Author(s):

Adriana Verschoor ◽

Ronald Milligan ◽

Suman Srivastava ◽

Joachim Frank

Keyword(s):

Chick Embryo ◽

3D Reconstruction ◽

Single Particle ◽

Mass Density ◽

Particle Surface ◽

Uranyl Acetate ◽

Electron Microscopic ◽

Eukaryotic Ribosome ◽

Negative Stain ◽

Reconstruction Methods

We have studied the eukaryotic ribosome from two vertebrate species (rabbit reticulocyte and chick embryo ribosomes) in several different electron microscopic preparations (Fig. 1a-d), and we have applied image processing methods to two of the types of images. Reticulocyte ribosomes were examined in both negative stain (0.5% uranyl acetate, in a double-carbon preparation) and frozen hydrated preparation as single-particle specimens. In addition, chick embryo ribosomes in tetrameric and crystalline assemblies in frozen hydrated preparation have been examined. 2D averaging, multivariate statistical analysis, and classification methods have been applied to the negatively stained single-particle micrographs and the frozen hydrated tetramer micrographs to obtain statistically well defined projection images of the ribosome (Fig. 2a,c). 3D reconstruction methods, the random conical reconstruction scheme and weighted back projection, were applied to the negative-stain data, and several closely related reconstructions were obtained. The principal 3D reconstruction (Fig. 2b), which has a resolution of 3.7 nm according to the differential phase residual criterion, can be compared to the images of individual ribosomes in a 2D tetramer average (Fig. 2c) at a similar resolution, and a good agreement of the general morphology and of many of the characteristic features is seen.Both data sets show the ribosome in roughly the same ’view’ or orientation, with respect to the adsorptive surface in the electron microscopic preparation, as judged by the agreement in both the projected form and the distribution of characteristic density features. The negative-stain reconstruction reveals details of the ribosome morphology; the 2D frozen-hydrated average provides projection information on the native mass-density distribution within the structure. The 40S subunit appears to have an elongate core of higher density, while the 60S subunit shows a more complex pattern of dense features, comprising a rather globular core, locally extending close to the particle surface.

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