504 citations · 2k across the 109 of their papers we have counts for
8 papers · 1 filter
Science In the Cloud (SIC): A use case in MRI Connectomics
Gregory Kiar, Krzysztof J. Gorgolewski, Dean Kleissas +8
Modern technologies are enabling scientists to collect extraordinary amounts of complex and sophisticated data across a huge range of scales like never before. With this onslaught…
Deformably Registering and Annotating Whole CLARITY Brains to an Atlas via Masked LDDMM
Kwame S. Kutten, Joshua T. Vogelstein, Nicolas Charon +3
The CLARITY method renders brains optically transparent to enable high-resolution imaging in the structurally intact brain. Anatomically annotating CLARITY brains is necessary for…
Quantifying mesoscale neuroanatomy using X-ray microtomography
Eva L. Dyer, William Gray Roncal, Hugo L. Fernandes +9
Methods for resolving the 3D microstructure of the brain typically start by thinly slicing and staining the brain, and then imaging each individual section with visible light photo…
An Automated Images-to-Graphs Framework for High Resolution Connectomics
William Gray Roncal, Dean M. Kleissas, Joshua T. Vogelstein +8
Reconstructing a map of neuronal connectivity is a critical challenge in contemporary neuroscience. Recent advances in high-throughput serial section electron microscopy (EM) have…
MIGRAINE: MRI Graph Reliability Analysis and Inference for Connectomics
William Gray Roncal, Zachary H. Koterba, Disa Mhembere +10
Currently, connectomes (e.g., functional or structural brain graphs) can be estimated in humans at scale using a combination of diffusion weighted magnetic resonan…
Multichannel Electrophysiological Spike Sorting via Joint Dictionary Learning & Mixture Modeling
David E. Carlson, Joshua T. Vogelstein, Qisong Wu +7
We propose a construction for joint feature learning and clustering of multichannel extracellular electrophysiological data across multiple recording periods for action potential d…