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The effect of global signal regression on DCM estimates of noise and effective connectivity from resting state fMRI [article]

Hannes Almgren, Frederik Van de Steen, Adeel Razi, Karl Friston, Daniele Marinazzo
2019 bioRxiv   pre-print
In this study, we assessed the effects of global signal regression (GSR) on effective connectivity within and between resting-state networks; as estimated with dynamic causal modelling (DCM) for resting  ...  The influence of the global BOLD signal on resting state functional connectivity in fMRI data remains a topic of debate, with little consensus.  ...  In the present study, we assessed the effects of global signal regression on effective connectivity and noise parameters as estimated by (spectral) DCM for resting state fMRI (Friston, Kahan, Biswal,  ... 
doi:10.1101/634063 fatcat:mgogdkeb4jbfdi2uefqx4hpcgu

The effect of global signal regression on DCM estimates of noise and effective connectivity from resting state fMRI

Hannes Almgren, Frederik Van de Steen, Adeel Razi, Karl Friston, Daniele Marinazzo
2019 NeuroImage  
In this study, we assessed the effects of global signal regression (GSR) on effective connectivity within and between resting state networks (RSNs) - as estimated with dynamic causal modelling (DCM) for  ...  The influence of global BOLD fluctuations on resting state functional connectivity in fMRI data remains a topic of debate, with little consensus.  ...  In the present study, we assessed the effects of global signal regression on effective connectivity and noise parameters as estimated by (spectral) DCM for resting state fMRI (Friston et al., 2014; Razi  ... 
doi:10.1016/j.neuroimage.2019.116435 pmid:31816423 pmcid:PMC7014820 fatcat:da2ntxemlfenlbqfhcxkmypomq

Regression dynamic causal modeling for resting-state fMRI [article]

Stefan Frässle, Samuel J Harrison, Jakob Heinzle, Brett A Clementz, Carol A Tamminga, John A Sweeney, Elliot S Gershon, Matcheri S Keshavan, Godfrey D Pearlson, Albert Powers, Klaas E Stephan
2020 biorxiv/medrxiv   pre-print
"Resting-state" functional magnetic resonance imaging (rs-fMRI) is widely used to study brain connectivity.  ...  Second, we test construct validity of rDCM in relation to an established model of effective connectivity, spectral DCM.  ...  (a) Group-averaged posterior parameter estimates during the resting state as inferred with regression DCM (rDCM), and (b) spectral DCM (spDCM) F I G U R E 5 5 Effective connectivity among key brain regions  ... 
doi:10.1101/2020.08.12.247536 fatcat:ae6hv2kmbzahdf6f2chyvc7d7m

Variability and reliability of effective connectivity within the core default mode network: A longitudinal spectral DCM study [article]

Hannes B J Almgren, Frederik Van de Steen, Simone Kühn, Adeel Razi, Karl J Friston, Daniele Marinazzo
2018 bioRxiv   pre-print
We also found that various processing procedures (e.g. global signal regression and ROI size) had little effect on inference and reliability of connectivity for the majority of subjects.  ...  Most research applying spectral DCM has focused on group-averaged connectivity within large-scale intrinsic brain networks; however, the consistency of subject- and session-specific estimates of effective  ...  Global signal regression had no effect on hemispheric asymmetry for most subjects and did not alter the (within-subject) stability of effective connectivity.  ... 
doi:10.1101/273565 fatcat:r6e5ur3b2raijcqmoioh3dsg6a

Spectral Dynamic Causal Modelling of Resting-State fMRI: Relating Effective Brain Connectivity in the Default Mode Network to Genetics [article]

Yunlong Nie, Eugene Opoku, Laila Yasmin, Yin Song, Jie Wang, Sidi Wu, Vanessa Scarapicchia, Jodie Gawryluk, Liangliang Wang, Jiguo Cao, Farouk S. Nathoo
2020 arXiv   pre-print
We develop an analysis of longitudinal resting-state functional magnetic resonance imaging (rs-fMRI) and genetic data obtained from a sample of 111 subjects with a total of 319 rs-fMRI scans from the Alzheimer's  ...  A Dynamic Causal Model (DCM) is fit to the rs-fMRI scans to estimate effective brain connectivity within the DMN and related to a set of single nucleotide polymorphisms (SNPs) contained in an empirical  ...  Acknowledgements Research is supported by funding from the Natural Sciences and Engineering Research Council of Canada (NSERC) and the Canadian Statistical Sciences Institute. F.S. Nathoo  ... 
arXiv:1901.09975v8 fatcat:arew2726zvedjc4xr53yhua7ka

A blind deconvolution approach to recover effective connectivity brain networks from resting state fMRI data

Guo-Rong Wu, Wei Liao, Sebastiano Stramaglia, Ju-Rong Ding, Huafu Chen, Daniele Marinazzo
2013 Medical Image Analysis  
A great improvement to the insight on brain function that we can get from fMRI data can come from effective connectivity analysis, in which the flow of information between even remote brain regions is  ...  For task-related fMRI, neural population dynamics can be captured by modeling signal dynamics with explicit exogenous inputs; for resting-state fMRI on the other hand, the absence of explicit inputs makes  ...  Chen was supported by the Natural Science Foundation of China (No. 61125304 and No. 61035006). G.R. Wu gratefully acknowledges the financial support from China Scholarship Council (2011607033).  ... 
doi:10.1016/j.media.2013.01.003 pmid:23422254 fatcat:g6euzkyjmzbani62x5hhao2tfm

Test-retest reliability of regression dynamic causal modeling

Stefan Frässle, Klaas E. Stephan
2021 Network Neuroscience  
Generally, for all methods and metrics, task-based connectivity estimates showed greater reliability than those from the resting state.  ...  Regression dynamic causal modeling (rDCM) is a novel and computationally highly efficient method for inferring effective connectivity at the whole-brain level.  ...  First, we found connectivity estimates from task-based fMRI data to be consistently more reliable than those from resting-state fMRI data.  ... 
doi:10.1162/netn_a_00215 pmid:35356192 pmcid:PMC8959103 fatcat:tgkavkq3lfgl7obtsmgy47way4

A blind deconvolution approach to recover effective connectivity brain networks from resting state fMRI data [article]

G. Wu, W.Liao, S. Stramaglia, J. Ding, H. Chen, D. Marinazzo
2012 arXiv   pre-print
A great improvement to the insight on brain function that we can get from fMRI data can come from effective connectivity analysis, in which the flow of information between even remote brain regions is  ...  For task-related fMRI, neural population dynamics can be captured by modeling signal dynamics with explicit exogenous inputs; for resting-state fMRI on the other hand, the absence of explicit inputs makes  ...  Resting-State fMRI Datasets In order to investigate the role of repetition time (TR) on the deconvolution procedure and on the effective network reconstruction, our analyses were performed on a resting-state  ... 
arXiv:1208.3766v1 fatcat:mol4dnucordtbkzzoem4mondp4

Regression DCM for fMRI

Stefan Frässle, Ekaterina I. Lomakina, Adeel Razi, Karl J. Friston, Joachim M. Buhmann, Klaas E. Stephan
2017 NeuroImage  
The approach rests on translating a linear DCM into the frequency domain and reformulating it as a special case of Bayesian linear regression.  ...  The approach rests on translating a linear DCM into the frequency domain and reformulating it as a special case of Bayesian linear regression.  ...  University of Zurich (KES).  ... 
doi:10.1016/j.neuroimage.2017.02.090 pmid:28259780 fatcat:e2cvf6ta35duzmzmwjtg4eqbae

Enhancing Task fMRI Preprocessing via Individualized Model-Based Filtering of Intrinsic Activity Dynamics [article]

Matthew F Singh, Anxu Wang, Michael Cole, ShiNung Ching, Todd S Braver
2020 bioRxiv   pre-print
In the current work we describe a method to improve the estimation of task-evoked brain activity by first "filtering-out" the intrinsic propagation of pre-event activity from the BOLD signal.  ...  Results demonstrate that this simple operation significantly improves the statistical power and temporal precision of estimated group-level effects.  ...  The model predicts task-fMRI activation based upon the effective connectivity parameters estimated from resting-state.  ... 
doi:10.1101/2020.12.10.420273 fatcat:3263fmmbpregjdtkeoot7d2ds4

Variability and reliability of effective connectivity within the core default mode network: A multi-site longitudinal spectral DCM study

Hannes Almgren, Frederik Van de Steen, Simone Kühn, Adeel Razi, Karl Friston, Daniele Marinazzo
2018 NeuroImage  
We also found that various processing procedures (e.g. global signal regression and ROI size) had little effect on inference and the reliability of connectivity estimates for the majority of subjects.  ...  We also addressed the effects on consistency of standard data processing procedures. DCM analyses were applied to four longitudinal resting state fMRI datasets.  ...  FWO14/ASP/255 awarded to FvdS; http://www.fwo.be), and a fund from the Wellcome Trust (KF).  ... 
doi:10.1016/j.neuroimage.2018.08.053 pmid:30165254 pmcid:PMC6215332 fatcat:xfkaycw7snb3hlgcnm2hfox46u

Converging Resting State Networks Unravels Potential Remote Effects of Transcranial Magnetic Stimulation for Major Depression

Takuya Ishida, Thomas Dierks, Werner Strik, Yosuke Morishima
2020 Frontiers in Psychiatry  
In the current study, we investigated the resting-state fMRI data of 100 healthy subjects by exploring three overlapping functional networks associated with the psychopathologically MDD-related areas (  ...  The DCM results also suggested that most of the functional interactions between MDD-related areas and bilateral DLPFC, DMPFC, and bilateral insula can predominantly be explained by the effective connectivity  ...  Effective connectivity quantifies the directional causal relationship from one area to another (67) . We employed the spectral DCM implemented in SPM12 for resting-state fMRI data.  ... 
doi:10.3389/fpsyt.2020.00836 pmid:32973580 pmcid:PMC7468386 fatcat:54rl5ap65zftncanutcjrcipri

Reduced Dynamic Interactions Within Intrinsic Functional Brain Networks in Early Blind Patients

Xianglin Li, Ailing Wang, Junhai Xu, Zhenbo Sun, Jikai Xia, Peiyuan Wang, Bin Wang, Ming Zhang, Jie Tian
2019 Frontiers in Neuroscience  
In our study, we used spectral dynamic causal modeling (DCM) to estimate the causal interactions using resting-state data in a group of 20 EB patients and 20 healthy controls (HC).  ...  Statistical analyses found that all endogenous connections and the connections from the mPFC to bilateral IPCs in EB patients were significantly reduced within the DMN, and the effective connectivity from  ...  The spectral DCM is designed to estimate the intrinsic effective connectivity from resting state fMRI images with the crossspectra of the signals.  ... 
doi:10.3389/fnins.2019.00268 pmid:30983956 pmcid:PMC6448007 fatcat:brz6uarj2zbxjpfvy66jnbp6lm

Disentangling causal webs in the brain using functional Magnetic Resonance Imaging: A review of current approaches [article]

Natalia Z. Bielczyk, Sebo Uithol, Tim van Mourik, Paul Anderson, Jeffrey C. Glennon, Jan K. Buitelaar
2019 arXiv   pre-print
In the past two decades, functional Magnetic Resonance Imaging has been used to relate neuronal network activity to cognitive processing and behaviour.  ...  , and Transfer Entropy.  ...  Spectral DCM is then combined with functional connectivity priors in order to estimate the effective connectivity in the large-scale resting state networks.  ... 
arXiv:1708.04020v4 fatcat:r4jdjsl4qzdkriawdmuss2s7cq

Resting-state neural activity and connectivity associated with subjective happiness

Wataru Sato, Takanori Kochiyama, Shota Uono, Reiko Sawada, Yasutaka Kubota, Sayaka Yoshimura, Motomi Toichi
2019 Scientific Reports  
Furthermore, functional connectivity and spectral dynamic causal modeling analyses showed that both functional and effective connectivity of the right precuneus with the right amygdala were positively  ...  To investigate these issues, we performed resting-state functional magnetic resonance imaging and analyzed the fractional amplitude of low-frequency fluctuation (fALFF) in participants, whose subjective  ...  ), and the Research Complex Program from Japan Science and Technology Agency.  ... 
doi:10.1038/s41598-019-48510-9 pmid:31431639 pmcid:PMC6702218 fatcat:z3bezeid5bhhtig2ldgi3vyotq
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