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Peale, D.

Publications and source records attributed to Peale, D..

3 recordsLinked to original sources

Accelerating Neuron Reconstruction with PATHFINDER

Comprehensive mapping of neural connections is essential for understanding brain function. Existing automated methods for connectome reconstruction from high-resolution images of brain tissue introduce errors that require extensive and time-consuming manual correction, a critical bottleneck in the field. To address this, we developed PATHFINDER, an AI system that segments volumetric image data, identifies potential ways to assemble neuron fragments, and evaluates the plausibility of resulting shapes to reconstruct complete neurons. Using a dataset of all axons in an IBEAM-mSEM volume of mouse cortex, we show that PATHFINDER reduces the error rate in axon reconstruction by an order of magnitude over previous state of the art, leading to an improvement in proofreading throughput of up to 84x relative to prior estimates in the context of a whole mouse brain. By drastically reducing the manual e"ort required for analysis, this advance unlocks the potential for both large-scale connectome mapping and routine investigation of smaller volumes.

neuroscience↗

Correlative three-dimensional super-resolution and block face electron microscopy of whole vitreously frozen cells

Living cells function through the spatial compartmentalization of thousands of distinct proteins serving a multitude of diverse biochemical needs. Correlative super-resolution (SR) fluorescence and electron microscopy (EM) has emerged as a pathway to directly view nanoscale protein relationships to the underlying global ultrastructure, but has traditionally suffered from tradeoffs of structure preservation, fluorescence retention, resolution, and field of view. We developed a platform for three-dimensional correlative cryogenic SR and focused ion beam milled block-face EM across entire vitreously frozen cells that addresses these issues by preserving native ultrastructure and enabling independent SR and EM workflow optimization. Application to a variety of biological systems revealed a number of unexpected protein-ultrastructure relationships and underscored the value of a comprehensive multimodal view of ultrastructural variability across whole cells.

cell biology↗

GCIB-SEM: A path to 10 nm isotropic imaging of cubic millimeter volumes

Focused Ion Beam Scanning Electron Microscopy (FIB-SEM) generates 3D datasets optimally suited for segmentation of cell ultrastructure and automated connectome tracing but is limited to small fields of view and is therefore incompatible with the new generation of ultrafast multibeam SEMs. In contrast, section-based techniques are multibeam-compatible but are limited in z-resolution making automatic segmentation of cellular ultrastructure difficult. Here we demonstrate a novel 3D electron microscopy technique, Gas Cluster Ion Beam SEM (GCIB-SEM), in which top-down, wide-area ion milling is performed on a series of thick sections, acquiring < 10 nm isotropic datasets of each which are then stitched together to span the full sectioned volume. Based on our results, incorporating GCIB-SEM into existing single beam and multibeam SEM workflows should be straightforward and should dramatically increase reliability while simultaneously improving z-resolution by a factor of 3 or more.

neuroscience↗