BigNeuron: a resource to benchmark and predict performance of algorithms for automated tracing of neurons in light microscopy datasets.

BigNeuron is an open community bench-testing platform with the goal of setting open standards for accurate and fast automatic neuron tracing. We gathered a diverse set of image volumes across several species that is representative of the data obtained in many neuroscience laboratories interested in neuron tracing. Here, we report generated gold standard manual annotations for a subset of the available imaging datasets and quantified tracing quality for 35 automatic tracing algorithms.

Vaa3D-x for cross-platform teravoxel-scale immersive exploration of multidimensional image data.

Summary: Vaa3D is a software package that has been widely used to visualize and analyze multidimensional microscopic images in a number of cutting edge bioimage informatics applications. However, due to many recent updates of both software development environments and operating systems, it was highly requested to maintain Vaa3D and disseminate it on latest operating systems. In addition, there has never been a showcase about how to use Vaa3D's cross-platform visualization and immersive exploration functions for multidimensional and teravoxel-scale images.

Functional Dissection of Protein Kinases in Sexual Development and Female Receptivity of .

Protein phosphorylation is crucial for a variety of biological functions, but how it is involved in sexual development and behavior is rarely known. In this study, we performed a screen of RNA interference targeting 177 protein kinases in and identified 13 kinases involved in sexual development in one or both sexes. We further identified that PKA and CASK promote female sexual behavior while not affecting female differentiation.

Petabyte-Scale Multi-Morphometry of Single Neurons for Whole Brains.

Recent advances in brain imaging allow producing large amounts of 3-D volumetric data from which morphometry data is reconstructed and measured. Fine detailed structural morphometry of individual neurons, including somata, dendrites, axons, and synaptic connectivity based on digitally reconstructed neurons, is essential for cataloging neuron types and their connectivity. To produce quality morphometry at large scale, it is highly desirable but extremely challenging to efficiently handle petabyte-scale high-resolution whole brain imaging database.

Morphological diversity of single neurons in molecularly defined cell types.

Dendritic and axonal morphology reflects the input and output of neurons and is a defining feature of neuronal types, yet our knowledge of its diversity remains limited. Here, to systematically examine complete single-neuron morphologies on a brain-wide scale, we established a pipeline encompassing sparse labelling, whole-brain imaging, reconstruction, registration and analysis. We fully reconstructed 1,741 neurons from cortex, claustrum, thalamus, striatum and other brain regions in mice.

TeraVR empowers precise reconstruction of complete 3-D neuronal morphology in the whole brain.

Neuron morphology is recognized as a key determinant of cell type, yet the quantitative profiling of a mammalian neuron's complete three-dimensional (3-D) morphology remains arduous when the neuron has complex arborization and long projection. Whole-brain reconstruction of neuron morphology is even more challenging as it involves processing tens of teravoxels of imaging data. Validating such reconstructions is extremely laborious.

Detecting abnormalities of corpus callosum connectivity in autism using magnetic resonance imaging and diffusion tensor tractography.

The corpus callosum (CC) has emerged as one of the primary targets of autism research. To detect aberrant CC interhemispheric connectivity in autism, we performed T1-weighted magnetic resonance imaging (MRI) and diffusion tensor imaging (DTI)-based tractography in 18 children with high functioning autism (HFA) and 16 well-matched typically developing (TD) children. We compared global and regional T1 measures (CC volume, and CC density), and the DTI measures [fractional anisotropy (FA), apparent diffusion coefficient (ADC), average fiber length (AFL), and fiber number (FN)] of transcallosal fibers, between the two groups.

Automatic reconstruction of 3D neuron structures using a graph-augmented deformable model.

Motivation: Digital reconstruction of 3D neuron structures is an important step toward reverse engineering the wiring and functions of a brain. However, despite a number of existing studies, this task is still challenging, especially when a 3D microscopic image has low single-to-noise ratio and discontinued segments of neurite patterns.

Results: We developed a graph-augmented deformable model (GD) to reconstruct (trace) the 3D structure of a neuron when it has a broken structure and/or fuzzy boundary.

V3D enables real-time 3D visualization and quantitative analysis of large-scale biological image data sets.

The V3D system provides three-dimensional (3D) visualization of gigabyte-sized microscopy image stacks in real time on current laptops and desktops. V3D streamlines the online analysis, measurement and proofreading of complicated image patterns by combining ergonomic functions for selecting a location in an image directly in 3D space and for displaying biological measurements, such as from fluorescent probes, using the overlaid surface objects. V3D runs on all major computer platforms and can be enhanced by software plug-ins to address specific biological problems.

Segmentation of center brains and optic lobes in 3D confocal images of adult fruit fly brains.

Automatic alignment (registration) of 3D images of adult fruit fly brains is often influenced by the significant displacement of the relative locations of the two optic lobes (OLs) and the center brain (CB). In one of our ongoing efforts to produce a better image alignment pipeline of adult fruit fly brains, we consider separating CB and OLs and align them independently. This paper reports our automatic method to segregate CB and OLs, in particular under conditions where the signal to noise ratio (SNR) is low, the variation of the image intensity is big, and the relative displacement of OLs and CB is substantial.

White matter impairments in autism, evidence from voxel-based morphometry and diffusion tensor imaging.

This study explored white matter abnormalities in a group of Chinese children with high functioning autism (HFA). Twelve male children with HFA and ten matched typically developing children underwent diffusion tensor imaging (DTI) as well three-dimensional T1-weighted MRI for voxel-based morphometry (VBM). We found a significant decrease of the white matter density in the right frontal lobe, left parietal lobe and right anterior cingulate and a significant increase in the right frontal lobe, left parietal lobe and left cingulate gyrus in the HFA group compared with the control group.

Voxel-based morphometry study on brain structure in children with high-functioning autism.

Earlier studies have suggested abnormal brain volumes in autism, but inconsistencies exist. Using voxel-based morphometry, we compared global and regional brain volumes in 17 high-functioning autistic children with 15 matched controls. We identified significant reduction in left white matter volume and white/gray matter ratio in autism.

Multicontext wavelet-based thresholding segmentation of brain tissues in magnetic resonance images.

A novel segmentation method based on wavelet transform is presented for gray matter, white matter and cerebrospinal fluid in thin-sliced single-channel brain magnetic resonance (MR) scans. On the basis of the local image model, multicontext wavelet-based thresholding segmentation (MCWT) is proposed to classify 2D MR data into tissues automatically. In MCWT, the wavelet multiscale transform of local image gray histogram is done, and the gray threshold is gradually revealed from large-scale to small-scale coefficients.

Brain magnetic resonance images segmentation based on wavelet method.

This paper focused on the brain magnetic resonance (MR) images, which is one of the key problems in image processing. A novel segmentation method based on watershed transform and wavelets transform is presented for white matter in thin sliced single-channel brain magnetic resonance scans. The original image is smoothed by using anisotropic filter and over-segmented by the watershed algorithm.

Gender difference in hemodynamic responses of prefrontal area to emotional stress by near-infrared spectroscopy.

Presentation of negative pictures was used as emotional stress to assess gender differences in prefrontal area activation in a functional near-infrared spectroscopy (NIRS) study. Compared with neutral condition, the response of oxy-HB for men yielded no significant difference during stress period, but the response induced by stress pictures for women showed significant enhancement. It was indicated that it is crucial to take gender difference into account when negative stimuli are used in functional brain imaging.