Automated dense neuronal fiber tracing and connectivity mapping at cellular level

With the advancement of high throughput and high resolution volumetric brain imaging, there is an unmet need to trace dense neuron fibers and study long-range neuron connectivity. An initial pipeline is described for processing cellular-level neuronal fiber data acquired by a new super resolution imaging method called Magnified Analysis of the Proteome (MAP). First, a multiscale vessel enhancement filter is applied to segment fibers of different diameters. Morphological operations are then employed to extract the fiber centerlines, from which a 3D connectivity map is computed. Applying this approach to an initial data set yielded 2% equal error rate for segmentation and 92% accuracy for end-to-end fiber tracing (22 out of 24 hand-traced fibers). Future work calls for scaling up the algorithm to process much larger brain datasets (terabytes and above) and performing graph-based long-range connectivity analysis. This work has the potential to extend our knowledge on brain networks at the cellular level.