scholarly journals Functional connectivity analysis in resting state fMRI with echo-state networks and non-metric clustering for network structure recovery

2015 ◽  
Author(s):  
Axel Wismüller ◽  
Adora M. DSouza ◽  
Anas Z. Abidin ◽  
Xixi Wang ◽  
Susan K. Hobbs ◽  
...  
Keyword(s):  
Functional Connectivity ◽  
Network Structure ◽  
Resting State ◽  
Resting State Fmri ◽  
Connectivity Analysis ◽  
Functional Connectivity Analysis ◽  
Echo State Networks

scholarly journals Resting State fMRI Functional Connectivity Analysis Using Dynamic Time Warping

2017 ◽  
Vol 11 ◽  
Author(s):  
Regina J. Meszlényi ◽  
Petra Hermann ◽  
Krisztian Buza ◽  
Viktor Gál ◽  
Zoltán Vidnyánszky
Keyword(s):  
Functional Connectivity ◽  
Resting State ◽  
Dynamic Time Warping ◽  
Resting State Fmri ◽  
Connectivity Analysis ◽  
Time Warping ◽  
Functional Connectivity Analysis ◽  
Dynamic Time

scholarly journals An independent components and functional connectivity analysis of resting state fMRI data points to neural network dysregulation in adult ADHD

2013 ◽  
Vol 35 (4) ◽  
pp. 1261-1272 ◽  
Author(s):  
Elseline Hoekzema ◽  
Susana Carmona ◽  
J. Antoni Ramos-Quiroga ◽  
Vanesa Richarte Fernández ◽  
Rosa Bosch ◽  
...  
Keyword(s):  
Neural Network ◽  
Functional Connectivity ◽  
Resting State ◽  
Adult Adhd ◽  
Resting State Fmri ◽  
Fmri Data ◽  
Connectivity Analysis ◽  
Independent Components ◽  
Functional Connectivity Analysis ◽  
Data Points

SINGULAR SPECTRUM ANALYSIS AND ADAPTIVE FILTERING ENHANCE THE FUNCTIONAL CONNECTIVITY ANALYSIS OF RESTING STATE fMRI DATA

2014 ◽  
Vol 24 (03) ◽  
pp. 1450010 ◽  
Author(s):  
PAOLO PIAGGI ◽  
DANILO MENICUCCI ◽  
CLAUDIO GENTILI ◽  
GIACOMO HANDJARAS ◽  
ANGELO GEMIGNANI ◽  
...  
Keyword(s):  
Functional Connectivity ◽  
Adaptive Filtering ◽  
Spectrum Analysis ◽  
Resting State ◽  
Singular Spectrum Analysis ◽  
Resting State Fmri ◽  
Fmri Data ◽  
Connectivity Analysis ◽  
Singular Spectrum ◽  
Functional Connectivity Analysis

Sources of noise in resting-state fMRI experiments include instrumental and physiological noises, which need to be filtered before a functional connectivity analysis of brain regions is performed. These noisy components show autocorrelated and nonstationary properties that limit the efficacy of standard techniques (i.e. time filtering and general linear model). Herein we describe a novel approach based on the combination of singular spectrum analysis and adaptive filtering, which allows a greater noise reduction and yields better connectivity estimates between regions at rest, providing a new feasible procedure to analyze fMRI data.

The impact of “physiological correction” on functional connectivity analysis of pharmacological resting state fMRI

NeuroImage ◽  
2013 ◽  
Vol 65 ◽  
pp. 499-510 ◽  
Author(s):  
Najmeh Khalili-Mahani ◽  
Catie Chang ◽  
Matthias J. van Osch ◽  
Ilya M. Veer ◽  
Mark A. van Buchem ◽  
...  
Keyword(s):  
Functional Connectivity ◽  
Resting State ◽  
Resting State Fmri ◽  
Connectivity Analysis ◽  
Functional Connectivity Analysis ◽  
The Impact ◽  
Physiological Correction
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