Dynamical Graph Theory Networks Methods for the Analysis of Sparse Functional Connectivity Networks and for Determining Pinning Observability in Brain Networks

Anke Meyer-Baese; Rodney G. Roberts; Ignacio A. Illan; Uwe Meyer-Base; Marc Lobbes; Andreas Stadlbauer; Katja Pinker-Domenig

doi:10.3389/fncom.2017.00087

Dynamical Graph Theory Networks Methods for the Analysis of Sparse Functional Connectivity Networks and for Determining Pinning Observability in Brain Networks

Anke Meyer-Baese^*, Rodney G. Roberts, Ignacio A. Illan, Uwe Meyer-Base, Marc Lobbes, Andreas Stadlbauer, Katja Pinker-Domenig

^*Corresponding author for this work

Research output: Contribution to journal › Article › Academic › peer-review

9 Citations (Web of Science)

Original language	English
Article number	87
Number of pages	10
Journal	Frontiers in Computational Neuroscience
Volume	11
DOIs	https://doi.org/10.3389/fncom.2017.00087
Publication status	Published - 5 Oct 2017

Keywords

neurodegenerative disease
singular perturbations
area aggregation
multi-time-scale brain network
neural network
synchronization
pinning observability
COMPLEX NETWORKS
MODEL-REDUCTION
SYSTEMS
CONTROLLABILITY

Access to Document

10.3389/fncom.2017.00087

Cite this

Meyer-Baese, A., Roberts, R. G., Illan, I. A., Meyer-Base, U., Lobbes, M., Stadlbauer, A., & Pinker-Domenig, K. (2017). Dynamical Graph Theory Networks Methods for the Analysis of Sparse Functional Connectivity Networks and for Determining Pinning Observability in Brain Networks. Frontiers in Computational Neuroscience, 11, [87]. https://doi.org/10.3389/fncom.2017.00087

@article{62a2cc532685449a9a5d757ee827fe3c,

title = "Dynamical Graph Theory Networks Methods for the Analysis of Sparse Functional Connectivity Networks and for Determining Pinning Observability in Brain Networks",

keywords = "neurodegenerative disease, singular perturbations, area aggregation, multi-time-scale brain network, neural network, synchronization, pinning observability, COMPLEX NETWORKS, MODEL-REDUCTION, SYSTEMS, CONTROLLABILITY",

author = "Anke Meyer-Baese and Roberts, {Rodney G.} and Illan, {Ignacio A.} and Uwe Meyer-Base and Marc Lobbes and Andreas Stadlbauer and Katja Pinker-Domenig",

year = "2017",

month = oct,

day = "5",

doi = "10.3389/fncom.2017.00087",

language = "English",

volume = "11",

journal = "Frontiers in Computational Neuroscience",

issn = "1662-5188",

publisher = "Frontiers Media S.A.",

}

Dynamical Graph Theory Networks Methods for the Analysis of Sparse Functional Connectivity Networks and for Determining Pinning Observability in Brain Networks. / Meyer-Baese, Anke; Roberts, Rodney G.; Illan, Ignacio A.; Meyer-Base, Uwe; Lobbes, Marc; Stadlbauer, Andreas; Pinker-Domenig, Katja.

In: Frontiers in Computational Neuroscience, Vol. 11, 87, 05.10.2017.

Research output: Contribution to journal › Article › Academic › peer-review

TY - JOUR

T1 - Dynamical Graph Theory Networks Methods for the Analysis of Sparse Functional Connectivity Networks and for Determining Pinning Observability in Brain Networks

AU - Meyer-Baese, Anke

AU - Roberts, Rodney G.

AU - Illan, Ignacio A.

AU - Meyer-Base, Uwe

AU - Lobbes, Marc

AU - Stadlbauer, Andreas

AU - Pinker-Domenig, Katja

PY - 2017/10/5

Y1 - 2017/10/5

KW - neurodegenerative disease

KW - singular perturbations

KW - area aggregation

KW - multi-time-scale brain network

KW - neural network

KW - synchronization

KW - pinning observability

KW - COMPLEX NETWORKS

KW - MODEL-REDUCTION

KW - SYSTEMS

KW - CONTROLLABILITY

U2 - 10.3389/fncom.2017.00087

DO - 10.3389/fncom.2017.00087

M3 - Article

VL - 11

JO - Frontiers in Computational Neuroscience

JF - Frontiers in Computational Neuroscience

SN - 1662-5188

M1 - 87

ER -