Editorial: Anatomy and Plasticity in Large-Scale Brain Models

 What is your doctor and hospital doing to contact these supercomputing facilities for information on how these brain networks work in stroke damage?  ANYTHING AT ALL?
What is your doctor and hospital doing to contact these suphttp://journal.frontiersin.org/article/10.3389/fnana.2016.00108/full

Markus Butz¹, Wolfram Schenck² and Arjen van Ooyen^3*

• ¹Simulation Laboratory Neuroscience, Bernstein Facility for Simulation and Database Technology, Institute for Advanced Simulation, Jülich Aachen Research Alliance, Jülich Research Center, Jülich, Germany
• ²Faculty of Engineering and Mathematics, Bielefeld University of Applied Sciences, Bielefeld, Germany
• ³Department of Integrative Neurophysiology, VU University Amsterdam, Amsterdam, Netherlands

The Editorial on the Research Topic
Anatomy and Plasticity in Large-Scale Brain Models

Introduction

Supercomputing facilities are becoming increasingly available for simulating electrical activity in large-scale neuronal networks. On today's most advanced supercomputers, networks with up to a billion of neurons can be readily simulated. However, building biologically realistic, full-scale brain models requires more than just a huge number of neurons. In addition to network size, the detailed local and global anatomy of neuronal connections is of crucial importance. Moreover, anatomical connectivity is not fixed, but can rewire throughout life (structural plasticity; Butz et al., 2009)—an aspect that is missing in most current network models, in which plasticity is confined to changes in synaptic strength (synaptic plasticity).

The papers in this research topic, which may broadly be divided into three themes, aim to bring together high-performance computing with recent experimental and computational research in neuroanatomy. In the first theme (fiber connectivity), new methods are described for measuring and data-basing microscopic and macroscopic connectivity. In the second theme (structural plasticity), novel models are introduced that incorporate morphological plasticity and rewiring of anatomical connections. In the third theme (large-scale simulations), simulations of large-scale neuronal networks are presented with an emphasis on anatomical detail and plasticity mechanisms. Together, the papers in this research topic contribute to extending high-performance computing in neuroscience to encompass anatomical detail and plasticity.

Fiber Connectivity

Investigating the brain's connectivity requires multiscale approaches and hence strategies for integrating data across different spatial scales. Axer et al. demonstrate how to bridge microscopic visualizations of fibers obtained by 3D-PLI (polarized light imaging; Axer et al., 2011) to meso- or macro-scopic fiber orientations based on dMRI (diffusion magnetic resonance imaging). A relatively new technique, 3D-PLI is applicable to microtome sections of postmortem brains and uses birefringence of brain tissue, induced by optical anisotropy of the myelin sheaths around axons, to derive a 3D description of the underlying fiber architecture. To be able to link 3D-PLI to dMRI measurements, the authors introduce fiber orientation distribution functions (ODFs) extracted from 3D-PLI. They demonstrate the validity of their approach with simulated 3D-PLI data as well as real 3D-PLI data from the human brain and the brain of a hooded seal.

Capturing different aspects of brain organization, such as connectivity and molecular composition, necessitates the use of different neuroimaging techniques. To subsequently integrate the multiscale and multimodal data into a complete 3D brain model requires an accurate definition of the spatial positions of structural entities. Defined by MRI, the Waxholm Space (WHS) (http://software.incf.org/software/waxholm-space) provides such a reference space for rodent brain data. The aim of the study by Schubert et al. was to extend the WHS rat brain atlas with information about cytoarchitecture, receptor expression and spatial orientation of fiber tracts, derived from autoradiography and PLI images. To incorporate these distinct classes of information into the WHS, the authors improved currently available registration algorithms to align sections and to correct for deformations. The extended WHS rat brain atlas now enables combined studies on receptor and cell distributions as well as fiber densities in the same anatomical structures at microscopic scales. Furthermore, the methods developed facilitate future integration of data of other modalities.

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