Interactive Visualization–A Key Prerequisite for Reconstruction and Analysis of Anatomically Realistic Neural Networks

Abstract

Recent progress in large-volume microscopy, tissue-staining, as well as in image processing methods and 3D anatomy reconstruction allow neuroscientists to extract previously inaccessible anatomical data with high precision. For instance, determination of neuron numbers, 3D distributions and 3D axonal and dendritic branching patterns support recently started efforts to reconstruct anatomically realistic network models of many thousand neurons. Such models aid in understanding neural network structure, and, by numerically simulating electro-physiological signaling, also to reveal their function.We illustrate the impact of visual computing on neurobiology at the example of important steps that are required for the reconstruction of large neural networks. In our case, the network to be reconstructed represents a single cortical column in the rat brain, which processes sensory information from its associated facial whisker hair. We demonstrate how analysis and reconstruction tasks, such as neuron somata counting and tracing of neuronal branches, have been incrementally acceleratedfinally leading to efficiency gains of orders of magnitude. We also show how steps that are difficult to automatize can now be solved interactively with visual support. Additionally, we illustrate how visualization techniques have aided computer scientists during algorithm development. Finally, we present visual analysis techniques allowing neuroscientists to explore morphology and function of 3D neural networks.Altogether, we demonstrate that visual computing techniques make an essential difference in terms of scientific output, both qualitatively, i.e., whether particular goals can be achieved at all, and quantitatively in terms of higher accuracy, faster work-flow and larger scale processing. Such techniques have therefore become essential in the daily work of neuroscientists.

Cell Type–Specific Three-Dimensional Structure of Thalamocortical Circuits in a Column of Rat Vibrissal Cortex

“…Axons were traced using an automated pipeline ( Oberlaender et al 2007 ; Oberlaender, Broser, et al 2009 ). Manual postprocessing of individual sections ( Dercksen et al 2012 ) and automated alignment of branches across sections ( Dercksen et al 2009 ), were performed in Amira visualization software ( Stalling et al 2005 ). Pia and barrel outlines were manually drawn on low resolution images (2×) and added to the tracings in Neurolucida software.…”

Sensory Experience Restructures Thalamocortical Axons during Adulthood

“…In each section, stacks of ~1.5 mm × 1.5 mm × 0.05 mm were imaged using optimized mosaic optical-sectioning microscopy (Oberlaender et al, 2009) and an oil-immersion objective (Olympus 100× UPLAN S APO, NA 1.4), yielding a voxel size of 0.184 μm × 0.184 μm × 0.5 μm. Manual postprocessing of individual sections (Dercksen et al, 2012), as well as automated alignment of reconstructed branches across sections (Dercksen et al, 2009), was performed using a custom-designed three-dimensional (3D) editing environment based on ZIBamira visualization software v2010.06 (Zuse Institute Berlin). Pia and barrel outlines were manually traced in each section at low resolution (Olympus 4× UPLAN S APO, NA 0.16) and added to the tracings in Neurolucida software (MicroBrightfield).…”

Three-dimensional axon morphologies of individual layer 5 neurons indicate cell type-specific intracortical pathways for whisker motion and touch

“…In cases in which neuronal branches reached the borders of the imaged volume, additional image stacks were taken at adjacent areas. Manual postprocessing of individual sections (62), as well as automated alignment of reconstructed branches across sections (63), were performed by using a custom-designed 3D editing environment based on Amira visualization software (64). Pia and barrel outlines were manually drawn on low-resolution images and added to the tracings in Neurolucida software (MicroBrightfield).…”