High-resolution serial-section electron microscopy (ssEM) makes it possible to investigate the
dense meshwork of axons, dendrites, and synapses that form neuronal circuits 1 . However…

To the Editor—Recent technological developments, such as high-throughput imaging and
sequencing, enable experimentalists to collect increasingly large, complex, and …

We describe a scalable database cluster for the spatial analysis and annotation of high-throughput
brain imaging data, initially for 3-d electron microscopy image stacks, but for time-…

Reconstructing a map of neuronal connectivity is a critical challenge in contemporary
neuroscience. Recent advances in high-throughput serial section electron microscopy (EM) have …

Large volumetric neuroimaging datasets have grown in size over the past ten years from
gigabytes to terabytes, with petascale data becoming available and more common over the …

… Following [3], maps of the form \(\phi _{t_j 0}\) and \(\phi _{t_j 1}\) are computed using semi-Lagrangian
integrators while operators L and K are applied in the Fourier domain. Starting …

Object storage is a low-cost, scalable component of cloud ecosystems. However, interface
incompatibilities and performance limitations inhibit its adoption for emerging cloud-based …

We propose a new gradient-domain technique for processing registered EM image stacks
to remove inter-image discontinuities while preserving intra-image detail. To this end, we …

Object storage has emerged as a low-cost and hyper-scalable alternative to distributed file
systems. However, interface incompatibilities and performance limitations often compel users …

We describe NDStore, a scalable multi-hierarchical data storage deployment for spatial
analysis of neuroscience data on the AWS cloud. The system design is inspired by the …