A Pipeline for Automated Assessment of Cell Location in 3D Mouse Brain Image Sets

Mapping the neuronal connectivity of the mouse brain has long been hampered by the laborious and time-consuming process of slicing, staining and imaging the brain tissue. Recent developments in automated 3D fluorescence microscopy, such as serial two- photon tomography (STP) and light sheet fluorescence microscopy, now allow for automated rapid 3D imaging of a complete mouse brain at cellular resolution. In combination with transsynaptic viral tracers, this paves the way for high-throughput brain mapping studies, which could greatly advance our understanding of the function of the brain. Because transsynaptic tracers label synaptically connected cells, the analysis of these whole-brain scans requires detection of fluorescently labelled cells and anatomical segmentation of the data, which are very labour- and time-intensive manual tasks and prevent high-throughput analysis. This thesis presents and validates two software tools to automate anatomical segmentation and cell detection in serial two photon (STP) scans of the mouse brain. Automated mouse atlas propagation (aMAP) segments the scans into anatomical regions by matching a 3D reference atlas to the data using affine and free-form image registration. The fast automated cell counting tool (FACCT) then detects fluorescently labelled cells in the dataset with a novel approach of stepwise data reduction combined with object detection using artificial neuronal networks. The tools are optimised for large datasets and are capable of processing a 2.5TB STP scan in under two days. The performance of aMAP and FACCT is evaluated on STP scans from retrograde connectivity tracing experiments using rabies virus injections in the primary visual corte

aMAP is a validated pipeline for registration and segmentation of high-resolution mouse brain data

AbstractThe validation of automated image registration and segmentation is crucial for accurate and reliable mapping of brain connectivity and function in three-dimensional (3D) data sets. While validation standards are necessarily high and routinely met in the clinical arena, they have to date been lacking for high-resolution microscopy data sets obtained from the rodent brain. Here we present a tool for optimized automated mouse atlas propagation (aMAP) based on clinical registration software (NiftyReg) for anatomical segmentation of high-resolution 3D fluorescence images of the adult mouse brain. We empirically evaluate aMAP as a method for registration and subsequent segmentation by validating it against the performance of expert human raters. This study therefore establishes a benchmark standard for mapping the molecular function and cellular connectivity of the rodent brain.</jats:p

The logic of single-cell projections from visual cortex

Neocortical areas communicate through extensive axonal projections, but the logic of information transfer remains poorly understood, because the projections of individual neurons have not been systematically characterized. It is not known whether individual neurons send projections only to single cortical areas or distribute signals across multiple targets. Here we determine the projection patterns of 591 individual neurons in the mouse primary visual cortex using whole-brain fluorescence-based axonal tracing and high-throughput DNA sequencing of genetically barcoded neurons (MAPseq). Projections were highly diverse and divergent, collectively targeting at least 18 cortical and subcortical areas. Most neurons targeted multiple cortical areas, often in non-random combinations, suggesting that sub-classes of intracortical projection neurons exist. Our results indicate that the dominant mode of intracortical information transfer is not based on 'one neuron-one target area' mapping. Instead, signals carried by individual cortical neurons are shared across subsets of target areas, and thus concurrently contribute to multiple functional pathways