Journal ArticleDOI
Alzheimer's disease: connecting findings from graph theoretical studies of brain networks
Betty M. Tijms,Alle Meije Wink,Willem de Haan,Wiesje M. van der Flier,Cornelis J. Stam,Philip Scheltens,Frederik Barkhof +6 more
TLDR
This work examined which graph properties have been consistently reported to be disturbed in AD studies, using a heuristically defined "graph space" to investigate which theoretical models can best explain graph alterations in AD.About:
This article is published in Neurobiology of Aging.The article was published on 2013-08-01. It has received 351 citations till now. The article focuses on the topics: Graph property & Graph theory.read more
Citations
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Modern network science of neurological disorders
TL;DR: Modern network science has revealed fundamental aspects of normal brain-network organization, such as small-world and scale-free patterns, hierarchical modularity, hubs and rich clubs, to use to gain a better understanding of brain disease.
Journal ArticleDOI
Focal brain lesions to critical locations cause widespread disruption of the modular organization of the brain
TL;DR: It is shown that focal damage to critical locations causes disruption of network organization throughout the brain and can have a widespread, nonlocal impact on brain network organization when there is damage to regions important for the communication between networks.
Journal ArticleDOI
Functional connectivity and graph theory in preclinical Alzheimer's disease
Matthew R. Brier,Jewell B. Thomas,Anne M. Fagan,Jason Hassenstab,David M. Holtzman,Tammie L.S. Benzinger,John C. Morris,Beau M. Ances +7 more
TL;DR: It is concluded that AD causes large-scale disconnection that is present before onset of symptoms, and has a particular effect on hub-like regions in the brain.
Journal ArticleDOI
The trees and the forest: Characterization of complex brain networks with minimum spanning trees.
Cornelis J. Stam,Prejaas Tewarie,E. van Dellen,E.C.W. van Straaten,Arjan Hillebrand,P. Van Mieghem +5 more
TL;DR: A minimum spanning tree (MST) is explained, a unique acyclic subgraph that connects all nodes and maximizes a property of interest such as synchronization between brain areas and how this may simplify the construction of simple generative models of normal and abnormal brain network organization.
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The minimum spanning tree: An unbiased method for brain network analysis
TL;DR: It is demonstrated that the MST is insensitive to alterations in connection strength or link density, and the behavior of MST and conventional network-characteristics for simulated regular and scale-free networks that were gradually rewired to random networks were explored.
References
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Journal ArticleDOI
“Mini-mental state”: A practical method for grading the cognitive state of patients for the clinician
Marshal F. Folstein,Marshal F. Folstein,Susan E B Folstein,Susan E B Folstein,Paul R. McHugh,Paul R. McHugh +5 more
TL;DR: A simplified, scored form of the cognitive mental status examination, the “Mini-Mental State” (MMS) which includes eleven questions, requires only 5-10 min to administer, and is therefore practical to use serially and routinely.
A practical method for grading the cognitive state of patients for the clinician
TL;DR: The Mini-Mental State (MMS) as mentioned in this paper is a simplified version of the standard WAIS with eleven questions and requires only 5-10 min to administer, and is therefore practical to use serially and routinely.
Journal ArticleDOI
Collective dynamics of small-world networks
TL;DR: Simple models of networks that can be tuned through this middle ground: regular networks ‘rewired’ to introduce increasing amounts of disorder are explored, finding that these systems can be highly clustered, like regular lattices, yet have small characteristic path lengths, like random graphs.
Journal ArticleDOI
Emergence of Scaling in Random Networks
TL;DR: A model based on these two ingredients reproduces the observed stationary scale-free distributions, which indicates that the development of large networks is governed by robust self-organizing phenomena that go beyond the particulars of the individual systems.
Journal ArticleDOI
The Structure and Function of Complex Networks
TL;DR: Developments in this field are reviewed, including such concepts as the small-world effect, degree distributions, clustering, network correlations, random graph models, models of network growth and preferential attachment, and dynamical processes taking place on networks.
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