Editorial: quantitative analysis of neuroanatomy

  • The true revolution in the age of digital neuroanatomy is the ability to extensively quantify anatomical structures and thus investigate structure-function relationships in great detail. Large-scale projects were recently launched with the aim of providing infrastructure for brain simulations. These projects will increase the need for a precise understanding of brain structure, e.g., through statistical analysis and models. From articles in this Research Topic, we identify three main themes that clearly illustrate how new quantitative approaches are helping advance our understanding of neural structure and function. First, new approaches to reconstruct neurons and circuits from empirical data are aiding neuroanatomical mapping. Second, methods are introduced to improve understanding of the underlying principles of organization. Third, by combining existing knowledge from lower levels of organization, models can be used to make testable predictions about a higher-level organization where knowledge is absent or poor. This latter approach is useful for examining statistical properties of specific network connectivity when current experimental methods have not yet been able to fully reconstruct whole circuits of more than a few hundred neurons.

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Author:Julian M. L. Budd, Hermann CuntzORCiDGND, Stephen J. Eglen, Patrik Krieger
Pubmed Id:https://pubmed.ncbi.nlm.nih.gov/26617494
Parent Title (English):Frontiers in neuroanatomy
Publisher:Frontiers Research Foundation
Place of publication:Lausanne
Document Type:Article
Date of Publication (online):2015/11/11
Date of first Publication:2015/11/11
Publishing Institution:Universitätsbibliothek Johann Christian Senckenberg
Release Date:2016/06/13
Tag:computational neuroscience; connectome; mathematical modeling; neuroinformatics; quantitative methods; statistical analysis
Issue:article 143
Page Number:4
Copyright © 2015 Budd, Cuntz, Eglen and Krieger. This is an open-access article distributed under the terms of the Creative Commons Attribution License (CC BY) http://creativecommons.org/licenses/by/4.0/ . The use, distribution or reproduction in other forums is permitted, provided the original author(s) or licensor are credited and that the original publication in this journal is cited, in accordance with accepted academic practice. No use, distribution or reproduction is permitted which does not comply with these terms.
Institutes:Wissenschaftliche Zentren und koordinierte Programme / Frankfurt Institute for Advanced Studies (FIAS)
Dewey Decimal Classification:6 Technik, Medizin, angewandte Wissenschaften / 61 Medizin und Gesundheit / 610 Medizin und Gesundheit
Licence (German):License LogoCreative Commons - Namensnennung 4.0