Literature DB >> 21286814

Minimum spanning tree reflects the alterations of the default mode network during Alzheimer's disease.

Koray Ciftçi1.   

Abstract

This study analyzes the connectivity pattern of the default mode network (DMN) in patients with Alzheimer's disease (AD) in comparison with young and elderly controls using the minimum spanning tree (MST). This tree is a tool from graph theory and connects all the nodes of a graph with the minimum cost. The findings revealed that the alterations of the basic structure represented by the MST might provide valuable insights about the physiopathology of the disease. Additionally, by making use of the MST for functionally clustering the DMN, it was shown that the functional subnetworks comprising the DMN differed among the three subject groups. Nonetheless, there were intact prefrontal and temporal networks in elderly controls and AD patients, as well. The analysis shows that although the topologies of the MST characterized by the degree distributions do not differ significantly among the groups, the DMN of the AD patients exhibits a higher segregation, insomuch that posterior cingulate/precuneus and hippocampus/parahippocampus are heavily isolated from rest of the network. We conclude that the MST can be used effectively for analyzing cortical networks.

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Year:  2011        PMID: 21286814     DOI: 10.1007/s10439-011-0258-9

Source DB:  PubMed          Journal:  Ann Biomed Eng        ISSN: 0090-6964            Impact factor:   3.934


  28 in total

1.  Default mode network in concussed individuals in response to the YMCA physical stress test.

Authors:  Kai Zhang; Brian Johnson; Michael Gay; Silvina G Horovitz; Mark Hallett; Wayne Sebastianelli; Semyon Slobounov
Journal:  J Neurotrauma       Date:  2012-03-20       Impact factor: 5.269

Review 2.  [Default mode network of the brain. Neurobiology and clinical significance].

Authors:  A Otti; H Gündel; A Wohlschläger; C Zimmer; C Sorg; M Noll-Hussong
Journal:  Nervenarzt       Date:  2012-01       Impact factor: 1.214

Review 3.  Network dysfunction in Alzheimer's disease: refining the disconnection hypothesis.

Authors:  Matthew R Brier; Jewell B Thomas; Beau M Ances
Journal:  Brain Connect       Date:  2014-06

4.  Network Optimization of Functional Connectivity Within Default Mode Network Regions to Detect Cognitive Decline.

Authors:  W Art Chaovalitwongse; Daehan Won; Onur Seref; Paul Borghesani; M Katie Askren; Sherry Willis; Thomas J Grabowski
Journal:  IEEE Trans Neural Syst Rehabil Eng       Date:  2017-03-07       Impact factor: 3.802

5.  On the Extraction and Analysis of Graphs From Resting-State fMRI to Support a Correct and Robust Diagnostic Tool for Alzheimer's Disease.

Authors:  Claudia Bachmann; Heidi I L Jacobs; PierGianLuca Porta Mana; Kim Dillen; Nils Richter; Boris von Reutern; Julian Dronse; Oezguer A Onur; Karl-Josef Langen; Gereon R Fink; Juraj Kukolja; Abigail Morrison
Journal:  Front Neurosci       Date:  2018-09-28       Impact factor: 4.677

6.  Functional connectivity and graph theory in preclinical Alzheimer's disease.

Authors:  Matthew R Brier; Jewell B Thomas; Anne M Fagan; Jason Hassenstab; David M Holtzman; Tammie L Benzinger; John C Morris; Beau M Ances
Journal:  Neurobiol Aging       Date:  2013-10-18       Impact factor: 4.673

7.  Brain networks engaged in audiovisual integration during speech perception revealed by persistent homology-based network filtration.

Authors:  Heejung Kim; Jarang Hahm; Hyekyoung Lee; Eunjoo Kang; Hyejin Kang; Dong Soo Lee
Journal:  Brain Connect       Date:  2015-03-02

8.  Uncertainty in Functional Network Representations of Brain Activity of Alcoholic Patients.

Authors:  Massimiliano Zanin; Seddik Belkoura; Javier Gomez; César Alfaro; Javier Cano
Journal:  Brain Topogr       Date:  2020-10-12       Impact factor: 3.020

9.  Fracturing ranked surfaces.

Authors:  K J Schrenk; N A M Araújo; J S Andrade; H J Herrmann
Journal:  Sci Rep       Date:  2012-04-02       Impact factor: 4.379

10.  Mapping the Alzheimer's brain with connectomics.

Authors:  Teng Xie; Yong He
Journal:  Front Psychiatry       Date:  2012-01-05       Impact factor: 4.157

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