Statistical physics approach to quantifying differences in myelinated nerve fibers (Articolo in rivista)

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Label
  • Statistical physics approach to quantifying differences in myelinated nerve fibers (Articolo in rivista) (literal)
Anno
  • 2014-01-01T00:00:00+01:00 (literal)
Http://www.cnr.it/ontology/cnr/pubblicazioni.owl#doi
  • 10.1038/srep04511 (literal)
Alternative label
  • César H. Comin (1); João R. Santos (2); Dario Corradini (2,6); Will Morrison (2); Chester Curme (2); Douglas L. Rosene (3); Andrea Gabrielli (4,5); Luciano da F. Costa (1) H. Eugene Stanley (2) (2014)
    Statistical physics approach to quantifying differences in myelinated nerve fibers
    in Scientific reports (Nature Publishing Group)
    (literal)
Http://www.cnr.it/ontology/cnr/pubblicazioni.owl#autori
  • César H. Comin (1); João R. Santos (2); Dario Corradini (2,6); Will Morrison (2); Chester Curme (2); Douglas L. Rosene (3); Andrea Gabrielli (4,5); Luciano da F. Costa (1) H. Eugene Stanley (2) (literal)
Pagina inizio
  • 4511 (literal)
Http://www.cnr.it/ontology/cnr/pubblicazioni.owl#url
  • http://www.nature.com/srep/2014/140328/srep04511/full/srep04511.html#affil-auth (literal)
Http://www.cnr.it/ontology/cnr/pubblicazioni.owl#numeroVolume
  • 4 (literal)
Rivista
Note
  • ISI Web of Science (WOS) (literal)
  • Scopu (literal)
Http://www.cnr.it/ontology/cnr/pubblicazioni.owl#affiliazioni
  • (1) Institute of Physics at São Carlos, University of São Paulo, São Carlos, SP 13560-970, Brazil (2) Center for Polymer Studies and Department of Physics, Boston University, 590 Commonwealth Avenue, Boston, Massachusetts 02215, USA (3) Boston University, School of Medicine, Department of Anatomy & Neurobiology, Boston, Massachusetts 02118, USA (4) Istituto dei Sistemi Complessi (ISC) - CNR, UOS \"Sapienza\", Dipartimento di Fisica, \"Sapienza\" Università di Roma, Piazzale Aldo Moro 5, 00185 Rome, Italy (5) IMT Alti Studi Lucca, Piazza S. Ponziano 6, 55100 Lucca, Italy (6) Current address: Sorbonne Universités, UPMC Univ Paris 06, UMR 8234, PHENIX, Paris, France & CNRS, UMR 8234, PHENIX, Paris, France (literal)
Titolo
  • Statistical physics approach to quantifying differences in myelinated nerve fibers (literal)
Abstract
  • We present a new method to quantify differences in myelinated nerve fibers. These differences range from morphologic characteristics of individual fibers to differences in macroscopic properties of collections of fibers. Our method uses statistical physics tools to improve on traditional measures, such as fiber size and packing density. As a case study, we analyze cross-sectional electron micrographs from the fornix of young and old rhesus monkeys using a semi-automatic detection algorithm to identify and characterize myelinated axons. We then apply a feature selection approach to identify the features that best distinguish between the young and old age groups, achieving a maximum accuracy of 94% when assigning samples to their age groups. This analysis shows that the best discrimination is obtained using the combination of two features: the fraction of occupied axon area and the effective local density. The latter is a modified calculation of axon density, which reflects how closely axons are packed. Our feature analysis approach can be applied to characterize differences that result from biological processes such as aging, damage from trauma or disease or developmental differences, as well as differences between anatomical regions such as the fornix and the cingulum bundle or corpus callosum. (literal)
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