scholarly journals Adaptive change point detection of dynamic functional connectivity networks

2016 ◽  
Author(s):  
Sadia Shakil ◽  
Sheila D Keilholz ◽  
Chin-Hui Lee
Keyword(s):  
Functional Connectivity ◽  
Change Point ◽  
Adaptive Change ◽  
Change Point Detection ◽  
Dynamic Functional Connectivity ◽  
Point Detection

Adaptive Change-Point Detection for Studying Human Locomotion

2021 ◽  
Author(s):  
Sylvain Jung ◽  
Laurent Oudre ◽  
Charles Truong ◽  
Eric Dorveaux ◽  
Louis Gorintin ◽  
...  
Keyword(s):  
Change Point ◽  
Human Locomotion ◽  
Adaptive Change ◽  
Change Point Detection ◽  
Point Detection

scholarly journals Network change point detection in resting-state functional connectivity dynamics of mild cognitive impairment patients

2020 ◽  
Vol 20 (3) ◽  
pp. 200-212
Author(s):  
Núria Mancho-Fora ◽  
Marc Montalà-Flaquer ◽  
Laia Farràs-Permanyer ◽  
Daniel Zarabozo-Hurtado ◽  
Geisa Bearitz Gallardo-Moreno ◽  
...  
Keyword(s):  
Cognitive Impairment ◽  
Mild Cognitive Impairment ◽  
Functional Connectivity ◽  
Resting State ◽  
Change Point ◽  
Change Point Detection ◽  
Resting State Functional Connectivity ◽  
Network Change ◽  
Point Detection

scholarly journals Adaptive change point detection algorithm for heart rate in children

2005 ◽  
Vol 52 (S1) ◽  
pp. A172-A172
Author(s):  
Mark Ansermino ◽  
Ping Yang ◽  
Joanne Lim ◽  
Guy Dumont ◽  
Craig R Ries
Keyword(s):  
Heart Rate ◽  
Change Point ◽  
Detection Algorithm ◽  
Adaptive Change ◽  
Change Point Detection ◽  
Point Detection

Resting-State Functional Connectivity Dynamics in Healthy Aging: An Approach Through Network Change Point Detection

2020 ◽  
Vol 10 (3) ◽  
pp. 134-142
Author(s):  
Núria Mancho-Fora ◽  
Marc Montalà-Flaquer ◽  
Laia Farràs-Permanyer ◽  
David Bartrés-Faz ◽  
Lídia Vaqué-Alcázar ◽  
...  
Keyword(s):  
Functional Connectivity ◽  
Resting State ◽  
Change Point ◽  
Healthy Aging ◽  
Change Point Detection ◽  
Resting State Functional Connectivity ◽  
Network Change ◽  
Point Detection

scholarly journals Dynamic Functional Connectivity Change-Point Detection With Random Matrix Theory Inference

2021 ◽  
Vol 15 ◽  
Author(s):  
Jaehee Kim ◽  
Woorim Jeong ◽  
Chun Kee Chung
Keyword(s):  
Functional Connectivity ◽  
Random Matrix Theory ◽  
Random Matrix ◽  
Change Point ◽  
Matrix Theory ◽  
Change Point Detection ◽  
Change Points ◽  
Point Problem ◽  
Change Point Problem ◽  
Point Detection

To study the dynamic nature of brain activity, functional magnetic resonance imaging (fMRI) data is useful including some temporal dependencies between the corresponding neural activity estimates. Recent studies have shown that the functional connectivity (FC) varies according to time and location which should be incorporated into the model. Modeling this dynamic FC (DFC) requires time-varying measures of spatial region of interest (ROI) sets. To know about the DFC, change-point detection in FC is of particular interest. In this paper, we propose a method of detecting a change-point based on the maximum of eigenvalues via random matrix theory (RMT). From covariance matrices for FC of all ROI's, the temporal change-point of FC is decided by an RMT approach. Simulation results show that our proposed method can detect meaningful FC change-points. We also illustrate the effectiveness of our FC detection approach by applying our method to epilepsy data where change-points detected are explained by the changes in memory capacity. Our study shows the possibility of RMT based approach in DFC change-point problem and in studying the complex dynamic pattern of functional brain interactions.

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