TrakEM2 Software for Neural Circuit Reconstruction

TLDR

Neuroscience faces a bottleneck in rapidly reconstructing neuronal circuits, especially for model organisms like Drosophila and C. elegans where image acquisition is no longer the limiting step but extracting circuits from images is. The authors developed TrakEM2, a software application designed to systematically reconstruct neuronal circuits from large electron microscopy and optical image volumes. TrakEM2 tackles image volume composition from deformed images, enables fast manual and semi‑automatic reconstruction of neuronal arbors and synapse annotation, and manages extensive image and annotation collections.

Abstract

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.