Advances in techniques to sparsely label neurons unlock the potential to reconstruct connectivity from 3D image stacks acquired by light microscopy. We present an application for semi-automated ...tracing of neurons to quickly annotate noisy datasets and construct complex neuronal topologies, which we call the Simple Neurite Tracer.
Simple Neurite Tracer is open source software, licensed under the GNU General Public Licence (GPL) and based on the public domain image processing software ImageJ. The software and further documentation are available via http://fiji.sc/Simple_Neurite_Tracer as part of the package Fiji, and can be used on Windows, Mac OS and Linux. Documentation and introductory screencasts are available at the same URL.
longair@ini.phys.ethz.ch; longair@ini.phys.ethz.ch.
Current imaging methods such as Magnetic Resonance Imaging (MRI), Confocal microscopy, Electron Microscopy (EM) or Selective Plane Illumination Microscopy (SPIM) yield three-dimensional (3D) data ...sets in need of appropriate computational methods for their analysis. The reconstruction, segmentation and registration are best approached from the 3D representation of the data set.
Here we present a platform-independent framework based on Java and Java 3D for accelerated rendering of biological images. Our framework is seamlessly integrated into ImageJ, a free image processing package with a vast collection of community-developed biological image analysis tools. Our framework enriches the ImageJ software libraries with methods that greatly reduce the complexity of developing image analysis tools in an interactive 3D visualization environment. In particular, we provide high-level access to volume rendering, volume editing, surface extraction, and image annotation. The ability to rely on a library that removes the low-level details enables concentrating software development efforts on the algorithm implementation parts.
Our framework enables biomedical image software development to be built with 3D visualization capabilities with very little effort. We offer the source code and convenient binary packages along with extensive documentation at http://3dviewer.neurofly.de.
A key challenge in neuroscience is the expeditious reconstruction of neuronal circuits. For model systems such as Drosophila and C. elegans, the limiting step is no longer the acquisition of imagery ...but the extraction of the circuit from images. For this purpose, we designed a software application, TrakEM2, that addresses the systematic reconstruction of neuronal circuits from large electron microscopical and optical image volumes. We address the challenges of image volume composition from individual, deformed images; of the reconstruction of neuronal arbors and annotation of synapses with fast manual and semi-automatic methods; and the management of large collections of both images and annotations. The output is a neural circuit of 3d arbors and synapses, encoded in NeuroML and other formats, ready for analysis.
Neuronal circuit mapping using electron microscopy demands laborious proofreading or reconciliation of multiple independent reconstructions. Here, we describe new methods to apply quantitative arbor ...and network context to iteratively proofread and reconstruct circuits and create anatomically enriched wiring diagrams. We measured the morphological underpinnings of connectivity in new and existing reconstructions of Drosophila sensorimotor (larva) and visual (adult) systems. Synaptic inputs were preferentially located on numerous small, microtubule-free 'twigs' which branch off a single microtubule-containing 'backbone'. Omission of individual twigs accounted for 96% of errors. However, the synapses of highly connected neurons were distributed across multiple twigs. Thus, the robustness of a strong connection to detailed twig anatomy was associated with robustness to reconstruction error. By comparing iterative reconstruction to the consensus of multiple reconstructions, we show that our method overcomes the need for redundant effort through the discovery and application of relationships between cellular neuroanatomy and synaptic connectivity.
Fiji is a distribution of the popular open-source software ImageJ focused on biological-image analysis. Fiji uses modern software engineering practices to combine powerful software libraries with a ...broad range of scripting languages to enable rapid prototyping of image-processing algorithms. Fiji facilitates the transformation of new algorithms into ImageJ plugins that can be shared with end users through an integrated update system. We propose Fiji as a platform for productive collaboration between computer science and biology research communities.
Protein-trap strains of Drosophila melanogaster provide a very useful tool for examining the 3D-expression patterns of proteins and purification of protein complexes. Here we present BrainTrap, ...available at http://fruitfly.inf.ed.ac.uk/braintrap, an online database of 3D confocal datasets showing reporter gene expression and protein localization in the adult brain of Drosophila. Full size images throughout the volume of the entire brain can be viewed interactively in a web browser. The database includes searchable annotations linked to the FlyBase Drosophila anatomy ontology. Anatomical search criteria can be specified using automatic completion and a hierarchical browser for the ontology. The provenance of all annotation is retained and the location where the annotator made the conclusion can be highlighted. Database URL: http://fruitfly.inf.ed.ac.uk/braintrap.
In many different insect species the highly conserved neuropil regions known as the central complex or central body complex have been shown to be important in behaviours such as locomotion, visual ...memory and courtship conditioning. The aim of this project is to generate accurate quantitative neuroanatomy of the central complex in the fruit fly Drosophila melanogaster. Much of the authoritative neuroanatomy of the fruit fly from past literature has been derived using Golgi stains, and in important cases these data are available only from 2D camera lucida drawings of the neurons and linguistic descriptions of connectivity. These cannot easily be mapped onto 3D template brains or compared directly to our own data. Using GAL4 driver and reporter constructs, some of the findings within these studies could be visualized using immunohistochemistry and confocal microscopy. A range of GAL4 driver lines were selected that particularly had prominent expression in the fan-shaped body. Images of brains from these lines were archived using a web-based 3D image stack archive developed for the sharing and backup of large confocal stacks. This is also the platform which we use to publish the data, so that other researchers can reuse this catalogue and compare their results directly. Each brain was annotated using desktop-based tools for labelling neuropil regions, locating landmarks in image stacks and tracing fine neuronal processes both manually and automatically. The development of the tracing and landmark annotation tools is described, and all of the tools used in this work are available as free software. In order to compare and aggregate these data, which are from many different brains, it is necessary to register each image stack onto some standard template brain. Although this is a well-studied problem in medical imaging, these high resolution scans of the central fly brain are unusual in a number of respects. The relative effectiveness of various methods currently available were tested on this data set. The best registrations were produced by a method that generates free-form deformations based on B-splines (the Computational Morphometry Toolkit), but for much faster registrations, the thin plate spline method based on manual landmarks may be sufficient. The annotated and registered data allows us to produce central complex template images and also files that accurately represent the possible central complex connectivity apparent in these images. One interesting result to arise from these efforts was evidence for a possible connection between the inferior region of the fan-shaped body and the beta lobe of the mushroom body which had previously been missed in these GAL4 lines. In addition, we can identify several connections which appear to be similar to those described in Hanesch et al., 1989, the canonical paper on the architecture of the Drosophila melanogaster central complex, and describe for the first time their variation statistically. This registered data was also used to suggest a method for classifying layers of expression within the fan-shaped body.
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