CAVE: Connectome Annotation Versioning Engine.

Advances in Electron Microscopy, image segmentation and computational infrastructure have given rise to large-scale and richly annotated connectomic datasets which are increasingly shared across communities. To enable collaboration, users need to be able to concurrently create new annotations and correct errors in the automated segmentation by proofreading. In large datasets, every proofreading edit relabels cell identities of millions of voxels and thousands of annotations like synapses.

Integrating EM and Patch-seq data: Synaptic connectivity and target specificity of predicted Sst transcriptomic types.

Neural circuit function is shaped both by the cell types that comprise the circuit and the connections between those cell types . Neural cell types have previously been defined by morphology , electrophysiology , transcriptomic expression , connectivity , or even a combination of such modalities . More recently, the Patch-seq technique has enabled the characterization of morphology (M), electrophysiology (E), and transcriptomic (T) properties from individual cells .

NEURD offers automated proofreading and feature extraction for connectomics.

We are now in the era of millimeter-scale electron microscopy (EM) volumes collected at nanometer resolution. Dense reconstruction of cellular compartments in these EM volumes has been enabled by recent advances in Machine Learning (ML). Automated segmentation methods produce exceptionally accurate reconstructions of cells, but post-hoc proofreading is still required to generate large connectomes free of merge and split errors.

Cell-type-specific inhibitory circuitry from a connectomic census of mouse visual cortex.

Mammalian cortex features a vast diversity of neuronal cell types, each with characteristic anatomical, molecular and functional properties. Synaptic connectivity powerfully shapes how each cell type participates in the cortical circuit, but mapping connectivity rules at the resolution of distinct cell types remains difficult. Here, we used millimeter-scale volumetric electron microscopy to investigate the connectivity of all inhibitory neurons across a densely-segmented neuronal population of 1352 cells spanning all layers of mouse visual cortex, producing a wiring diagram of inhibitory connections with more than 70,000 synapses.

A scalable and modular automated pipeline for stitching of large electron microscopy datasets.

Serial-section electron microscopy (ssEM) is the method of choice for studying macroscopic biological samples at extremely high resolution in three dimensions. In the nervous system, nanometer-scale images are necessary to reconstruct dense neural wiring diagrams in the brain, so -called . The data that can comprise of up to 10 individual EM images must be assembled into a volume, requiring seamless 2D registration from physical section followed by 3D alignment of the stitched sections.

A petascale automated imaging pipeline for mapping neuronal circuits with high-throughput transmission electron microscopy.

Electron microscopy (EM) is widely used for studying cellular structure and network connectivity in the brain. We have built a parallel imaging pipeline using transmission electron microscopes that scales this technology, implements 24/7 continuous autonomous imaging, and enables the acquisition of petascale datasets. The suitability of this architecture for large-scale imaging was demonstrated by acquiring a volume of more than 1 mm of mouse neocortex, spanning four different visual areas at synaptic resolution, in less than 6 months.

Particle-physics implications of a recent test of the gravitational inverse-square law.

We use data from our recent search for violations of the gravitational inverse-square law to constrain dilaton, radion, and chameleon exchange forces as well as arbitrary vector or scalar Yukawa interactions. We test the interpretation of the PVLAS Collaboration effect and a conjectured "fat-graviton" scenario and constrain the gamma_{5} couplings of pseuodscalar bosons and arbitrary power-law interactions.

Tests of the gravitational inverse-square law below the dark-energy length scale.

We conducted three torsion-balance experiments to test the gravitational inverse-square law at separations between 9.53 mm and 55 microm, probing distances less than the dark-energy length scale lambda(d)=[4 -root](variant Planck's over 2pic/rho(d) approximately 85 microm. We find with 95% confidence that the inverse-square law holds (|alpha| View Article and Find Full Text PDF

Submillimeter test of the gravitational inverse-square law: a search for "large" extra dimensions.

Motivated by higher-dimensional theories that predict new effects, we tested the gravitational 1/r(2) law at separations ranging down to 218 microm using a 10-fold symmetric torsion pendulum and a rotating 10-fold symmetric attractor. We improved previous short-range constraints by up to a factor of 1000 and find no deviations from Newtonian physics.