The neuroarchitecture of Acoela has been at the center of morphological debates. Some authors, using immunochemical tools, suggest that the nervous system in Acoela is organized as a commissural brain that bears little resemblance to the central, ganglionic type brain of other flatworms, and bilaterians in general. Others, who used histological staining on paraffin sections, conclude that it is a compact structure (an endonal brain; e.g., Raikova 2004; von Graff 1891; Delage Arch Zool Exp Gén 4:109-144, 1886). To address this question with modern tools, we have obtained images from serial transmission electron microscopic sections of the entire hatchling of Symsagittifera roscoffensis. In addition, we obtained data from wholemounts of hatchlings labeled with markers for serotonin and tyrosinated tubulin. Our data show that the central nervous system of a juvenile S. roscoffensis consists of an anterior compact brain, formed by a dense, bilobed mass of neuronal cell bodies surrounding a central neuropile. The neuropile flanks the median statocyst and contains several types of neurites, classified according to their types of synaptic vesicles. The neuropile issues three pairs of nerve cords that run at different dorso-ventral positions along the whole length of the body. Neuronal cell bodies flank the cords, and neuromuscular synapses are abundant. The TEM analysis also reveals different classes of peripheral sensory neurons and provides valuable information about the spatial relationships between neurites and other cell types within the brain and nerve cords. We conclude that the acoel S. roscoffensis has a central brain that is comparable in size and architecture to the brain of other (rhabditophoran) flatworms.

Tiled serial section Transmission Electron Microscopy (ssTEM) is increasingly used to describe high-resolution anatomy of large biological specimens. In particular in neurobiology, TEM is indispensable for analysis of synaptic connectivity in the brain. Registration of ssTEM image mosaics has to recover the 3D continuity and geometrical properties of the specimen in presence of various distortions that are applied to the tissue during sectioning, staining and imaging. These include staining artifacts, mechanical deformation, missing sections and the fact that structures may appear dissimilar in consecutive sections.

The Drosophila brain is formed by an invariant set of lineages, each of which is derived from a unique neural stem cell (neuroblast) and forms a genetic and structural unit of the brain. The task of reconstructing brain circuitry at the level of individual neurons can be made significantly easier by assigning neurons to their respective lineages. In this article we address the automation of neuron and lineage identification. We focused on the Drosophila brain lineages at the larval stage when they form easily recognizable secondary axon tracts (SATs) that were previously partially characterized. We now generated an annotated digital database containing all lineage tracts reconstructed from five registered wild-type brains, at higher resolution and including some that were previously not characterized. We developed a method for SAT structural comparisons based on a dynamic programming approach akin to nucleotide sequence alignment and a machine learning classifier trained on the annotated database of reference SATs. We quantified the stereotypy of SATs by measuring the residual variability of aligned wild-type SATs. Next, we used our method for the identification of SATs within wild-type larval brains, and found it highly accurate (93-99%). The method proved highly robust for the identification of lineages in mutant brains and in brains that differed in developmental time or labeling. We describe for the first time an algorithm that quantifies neuronal projection stereotypy in the Drosophila brain and use the algorithm for automatic neuron and lineage recognition.

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.

The analysis of microcircuitry (the connectivity at the level of individual neuronal processes and synapses), which is indispensable for our understanding of brain function, is based on serial transmission electron microscopy (TEM) or one of its modern variants. Due to technical limitations, most previous studies that used serial TEM recorded relatively small stacks of individual neurons. As a result, our knowledge of microcircuitry in any nervous system is very limited. We applied the software package TrakEM2 to reconstruct neuronal microcircuitry from TEM sections of a small brain, the early larval brain of Drosophila melanogaster. TrakEM2 enables us to embed the analysis of the TEM image volumes at the microcircuit level into a light microscopically derived neuro-anatomical framework, by registering confocal stacks containing sparsely labeled neural structures with the TEM image volume. We imaged two sets of serial TEM sections of the Drosophila first instar larval brain neuropile and one ventral nerve cord segment, and here report our first results pertaining to Drosophila brain microcircuitry. Terminal neurites fall into a small number of generic classes termed globular, varicose, axiform, and dendritiform. Globular and varicose neurites have large diameter segments that carry almost exclusively presynaptic sites. Dendritiform neurites are thin, highly branched processes that are almost exclusively postsynaptic. Due to the high branching density of dendritiform fibers and the fact that synapses are polyadic, neurites are highly interconnected even within small neuropile volumes. We describe the network motifs most frequently encountered in the Drosophila neuropile. Our study introduces an approach towards a comprehensive anatomical reconstruction of neuronal microcircuitry and delivers microcircuitry comparisons between vertebrate and insect neuropile.