A connectome and analysis of the adult Drosophila central brain.

The neural circuits responsible for animal behavior remain largely unknown. We summarize new methods and present the circuitry of a large fraction of the brain of the fruit fly Drosophila melanogaster. Improved methods include new procedures to prepare, image, align, segment, find synapses in, and proofread such large data sets. We define cell types, refine computational compartments, and provide an exhaustive atlas of cell examples and types, many of them novel. We provide detailed circuits consisting of neurons and their chemical synapses for most of the central brain. We make the data public and simplify access, reducing the effort needed to answer circuit questions, and provide procedures linking the neurons defined by our analysis with genetic reagents. Biologically, we examine distributions of connection strengths, neural motifs on different scales, electrical consequences of compartmentalization, and evidence that maximizing packing density is an important criterion in the evolution of the fly's brain.

Animal brains of all sizes, from the smallest to the largest, work in broadly similar ways. Studying the brain of any one animal in depth can thus reveal the general principles behind the workings of all brains. The fruit fly Drosophila is a popular choice for such research. With about 100,000 neurons ­ compared to some 86 billion in humans ­ the fly brain is small enough to study at the level of individual cells. But it nevertheless supports a range of complex behaviors, including navigation, courtship and learning. Thanks to decades of research, scientists now have a good understanding of which parts of the fruit fly brain support particular behaviors. But exactly how they do this is often unclear. This is because previous studies showing the connections between cells only covered small areas of the brain. This is like trying to understand a novel when all you can see is a few isolated paragraphs. To solve this problem, Scheffer, Xu, Januszewski, Lu, Takemura, Hayworth, Huang, Shinomiya et al. prepared the first complete map of the entire central region of the fruit fly brain. The central brain consists of approximately 25,000 neurons and around 20 million connections. To prepare the map ­ or connectome ­ the brain was cut into very thin 8nm slices and photographed with an electron microscope. A three-dimensional map of the neurons and connections in the brain was then reconstructed from these images using machine learning algorithms. Finally, Scheffer et al. used the new connectome to obtain further insights into the circuits that support specific fruit fly behaviors. The central brain connectome is freely available online for anyone to access. When used in combination with existing methods, the map will make it easier to understand how the fly brain works, and how and why it can fail to work correctly. Many of these findings will likely apply to larger brains, including our own. In the long run, studying the fly connectome may therefore lead to a better understanding of the human brain and its disorders. Performing a similar analysis on the brain of a small mammal, by scaling up the methods here, will be a likely next step along this path.

High-precision automated reconstruction of neurons with flood-filling networks.

Reconstruction of neural circuits from volume electron microscopy data requires the tracing of cells in their entirety, including all their neurites. Automated approaches have been developed for tracing, but their error rates are too high to generate reliable circuit diagrams without extensive human proofreading. We present flood-filling networks, a method for automated segmentation that, similar to most previous efforts, uses convolutional neural networks, but contains in addition a recurrent pathway that allows the iterative optimization and extension of individual neuronal processes. We used flood-filling networks to trace neurons in a dataset obtained by serial block-face electron microscopy of a zebra finch brain. Using our method, we achieved a mean error-free neurite path length of 1.1 mm, and we observed only four mergers in a test set with a path length of 97 mm. The performance of flood-filling networks was an order of magnitude better than that of previous approaches applied to this dataset, although with substantially increased computational costs.

Age and Long-Term Hormone Treatment Effects on the Ultrastructural Morphology of the Median Eminence of Female Rhesus Macaques.

The median eminence (ME) of the hypothalamus comprises the hypothalamic nerve terminals, glia (especially tanycytes) and the portal capillary vasculature that transports hypothalamic neurohormones to the anterior pituitary gland. The ultrastructure of the ME is dynamically regulated by hormones and undergoes organizational changes during development and reproductive cycles in adult females, but relatively little is known about the ME during aging, especially in nonhuman primates. Therefore, we used a novel transmission scanning electron microscopy technique to examine the cytoarchitecture of the ME of young and aged female rhesus macaques in a preclinical monkey model of menopausal hormone treatments. Rhesus macaques were ovariectomized and treated for 2 years with vehicle, estradiol (E2), or estradiol + progesterone (E2 + P4). While the overall cytoarchitecture of the ME underwent relatively few changes with age and hormones, changes to some features of neural and glial components near the portal capillaries were observed. Specifically, large neuroterminal size was greater in aged compared to young adult animals, an effect that was mitigated or reversed by E2 alone but not by E2 + P4 treatment. Overall glial size and the density and tissue fraction of the largest subset of glia were greater in aged monkeys, and in some cases reversed by E2 treatment. Mitochondrial size was decreased by E2, but not E2 + P4, only in aged macaques. These results contrast substantially with work in rodents, suggesting that the ME of aging macaques is less vulnerable to age-related disorganization, and that the effects of E2 on monkeys' ME are age specific.