Abstract
The complexity of the human brain makes its understanding one of the biggest challenges that science is currently confronting. Due to its complexity, the brain has been studied at many different levels and from many disciplines and points of view, using a diversity of techniques for getting meaningful data at each specific level and perspective, producing sometimes data that are difficult to integrate. In order to advance understanding of the brain, scientists need new tools that can speed up this analysis process and that can facilitate integrating research results from different disciplines and techniques. Visualization has proved to be useful in the analysis of complex data, and this paper focuses on the design of visualization solutions adapted to the specific problems posed by brain research. In this paper, we propose a unified framework that allows the integration of specific tools to work together in a coordinated manner in a multiview environment, displaying information at different levels of abstraction and combining schematic and realistic representations. The two use cases presented here illustrate the capability of this approach for providing a visual environment that supports the exploration of the brain at all its organizational levels.
Highlights
IntroductionUnderstanding the human brain is one of the greatest challenges still open
Each of them addresses the visualization of data sets at different levels of abstraction and requires specific tools that can collaborate within the proposed framework, providing an environment that supports the visual analysis of neural morphology at different organizational scales
The first case study addresses the visual exploration of a set of cortical neurons. This task can be performed using the multilevel schematic cell depiction features provided by NeuroScheme, a tool for multilevel navigation around the neocortex designed for facilitating the analysis of the morphology, topology, and simulation results of relatively complex synthetic neocortical neuronal circuits [27]
Summary
Understanding the human brain is one of the greatest challenges still open. There are a number of factors that limit progress in this field. The first one is the brain’s overwhelming complexity, which comes from the combination of a set of factors: First, the number of significant components is huge (around 1011 neurons and 1015 synapses in the human brain [1]); other elements such as glia and vasculature are relevant. The morphology of each of these elements is far from trivial, as many details that determine important aspects of their behavior exist. Morphology alone is not enough, since it is necessary to understand each element’s function. It is necessary to consider a stationary network; its dynamic behavior is central for understanding the brain’s behavior and how it adapts to changing stimuli
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