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A DCM for resting state fMRI

Karl J. Friston, Joshua Kahan, Bharat Biswal, Adeel Razi
2014 NeuroImage  
This technical note introduces a dynamic causal model (DCM) for resting state fMRI time series based upon observed functional connectivity-as measured by the cross spectra among different brain regions  ...  This DCM is based upon a deterministic model that generates predicted crossed spectra from a biophysically plausible model of coupled neuronal fluctuations in a distributed neuronal network or graph.  ...  The first describes the generative model for resting state fMRI.  ... 
doi:10.1016/j.neuroimage.2013.12.009 pmid:24345387 pmcid:PMC4073651 fatcat:nftnds5uifbare552z3vm4yzge

Construct validation of a DCM for resting state fMRI

Adeel Razi, Joshua Kahan, Geraint Rees, Karl J. Friston
2015 NeuroImage  
This technical note addresses the validity of a recently proposed DCM for resting state fMRIas measured in terms of their complex cross spectral densityreferred to as spectral DCM.  ...  Recently, there has been a lot of interest in characterising the connectivity of resting state brain networks.  ...  from resting state fMRI datasets.  ... 
doi:10.1016/j.neuroimage.2014.11.027 pmid:25463471 pmcid:PMC4295921 fatcat:dvkqolvepjal3cskuyuiz4gopm

Mapping the smoking addiction using dynamic causal modelling at rest

Rongxiang Tang, Adeel Razi, Yi-Yuan Tang
2015 BMC Neuroscience  
Here we apply a dynamic causal modeling (DCM) in resting state fMRI [2] to demonstrate the causal relationships among the core regions in smoking addiction.  ...  Functional data were processed using the Data Processing Assistant for Resting-State fMRI, which is based on SPM (www.fil.ion.ucl.ac.uk/spm) and Resting-State fMRI Data Analysis Toolkit.  ...  Here we apply a dynamic causal modeling (DCM) in resting state fMRI [2] to demonstrate the causal relationships among the core regions in smoking addiction.  ... 
doi:10.1186/1471-2202-16-s1-p246 pmcid:PMC4699006 fatcat:qbb75ji2tnd37ly7yjq433n3ka

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.  ...  Here, we show that a method recently developed for task-fMRI - regression dynamic causal modeling (rDCM) - extends to rs-fMRI and offers both directional estimates and scalability to whole-brain networks  ...  ) , which represents an alternative variant of DCM for fMRI that is suited to model resting-state data.  ... 
doi:10.1101/2020.08.12.247536 fatcat:ae6hv2kmbzahdf6f2chyvc7d7m

Stochastic Dynamic Causal Modelling for resting-state fMRI [article]

Ged Ridgway
2017 Figshare  
2012 "GlaxoSmithKline - Neurophysics Workshop on Pharmacological MRI", an activity hosted at Warwick University and coordinated with the Neurophysics Marie Curie Initial Training Network of which GSK is a  ...  DCM and resting-state fMRI • Pros and cons of sDCM for rs-fMRI in pharma Bayesian model comparison • Can be extended to encompass -Random effects model selection over subjects, allowing heterogeneity  ...  Overview • Connectivity in the brain • Introduction to Dynamic Causal Modelling • Bayes, prior knowledge, and model evidence • Connectivity in disease • Motivation for resting-state fMRI in pharma • Stochastic  ... 
doi:10.6084/m9.figshare.5492731.v1 fatcat:yuzzaixpbvccxgyfdugsapaq7i

Brief mindfulness training alters causal brain connections in mTBI

Rongxiang Tang, Yi-Yuan Tang
2015 BMC Neuroscience  
Functional data were processed using the Data Processing Assistant for Resting-State fMRI, which is based on SPM and Resting-State fMRI Data Analysis Toolkit.  ...  Here we apply a dynamic causal modeling (DCM) in resting state fMRI [2] to demonstrate the causal relationships among the core regions involved in mTBI.  ...  Functional data were processed using the Data Processing Assistant for Resting-State fMRI, which is based on SPM and Resting-State fMRI Data Analysis Toolkit.  ... 
doi:10.1186/1471-2202-16-s1-p247 pmcid:PMC4699121 fatcat:wlzkdtfz5ve4xjgwwz4d7vuvvu

A Functional Data Method for Causal Dynamic Network Modeling of Task-Related fMRI

Xuefei Cao, Björn Sandstede, Xi Luo
2019 Frontiers in Neuroscience  
Though our method is developed for task-related fMRI, we also demonstrate the potential applicability of our method (with a simple modification) to resting-state fMRI, by analyzing both simulated and real  ...  Our method links the observed fMRI data with the latent neuronal states modeled by an ordinary differential equation (ODE) model.  ...  Application to Resting-State fMRI In this section, we test the applicability of our method for recovering a medium-sized network using resting-state fMRI.  ... 
doi:10.3389/fnins.2019.00127 pmid:30872989 pmcid:PMC6402339 fatcat:eigipqb32ngs3pbxloa5km5obm

Effective connectivity during working memory and resting states: A DCM study

Kyesam Jung, Karl J. Friston, Chongwon Pae, Hanseul H. Choi, Sungho Tak, Yoon Kyoung Choi, Bumhee Park, Chan-A Park, Chaejoon Cheong, Hae-Jeong Park
2018 NeuroImage  
We found a strong correlation between intrinsic effective connectivity in the resting and task states over subjects but a marked difference between task related changes in effective connectivity and resting-state  ...  This result implies that a greater change in context-sensitive couplingfrom resting state connectivity is associated with faster reaction times.  ...  Figure 1 1 summarizes the procedure for the current analysis. Figure 1 . 1 Procedure for DCM of resting-state and N-back task fMRI.  ... 
doi:10.1016/j.neuroimage.2017.12.067 pmid:29284140 fatcat:eofkdbweszhehaooqlzusnts2y

Causal Modelling and Brain Connectivity in Functional Magnetic Resonance Imaging

Karl Friston
2009 PLoS Biology  
Primers provide a concise introduction into an important aspect of biology highlighted by a current PLoS Biology research article.  ...  In DCM for fMRI, bilinear differential equations describe the changes in neuronal activity x(t) i in terms of linearly separable components that reflect the influence of other regional state variables.  ...  Conceptual Motivations for DCM, in Relation To GCM be interpreted in terms of causal interactions among neuronal states.  ... 
doi:10.1371/journal.pbio.1000033 pmid:19226186 pmcid:PMC2642881 fatcat:bkfidwukhbh2tm3lyoil3xh67y

Bridging the Gap: Dynamic Causal Modeling and Granger Causality Analysis of Resting State Functional Magnetic Resonance Imaging

Sahil Bajaj, Bhim M. Adhikari, Karl J. Friston, Mukesh Dhamala
2016 Brain Connectivity  
In this study, our objective was to establish construct validity between GC and DCM in the context of resting state functional magnetic resonance imaging (fMRI).  ...  These findings suggest that GC and DCM can be used to estimate directed functional and effective connectivity from fMRI measurements in a consistent manner.  ...  In the current study, we used the GC and DCM techniques to analyze resting state fMRI (rsfMRI) data and compared the resulting connectivity estimates.  ... 
doi:10.1089/brain.2016.0422 pmid:27506256 fatcat:qfffrk3fj5g7pp5pjpqrmhzhga

Effective Connectivity within the Default Mode Network: Dynamic Causal Modeling of Resting-State fMRI Data

Maksim G. Sharaev, Viktoria V. Zavyalova, Vadim L. Ushakov, Sergey I. Kartashov, Boris M. Velichkovsky
2016 Frontiers in Human Neuroscience  
For this purpose functional magnetic resonance imaging (fMRI) data from 30 healthy subjects (1000 time points from each one) was acquired and spectral dynamic causal modeling (DCM) on a resting-state fMRI  ...  The Default Mode Network (DMN) is a brain system that mediates internal modes of cognitive activity, showing higher neural activation when one is at rest.  ...  For this purpose functional magnetic resonance imaging (fMRI) data from 30 healthy subjects (1000 time points from each one) was acquired and spectral dynamic causal modeling (DCM) on a resting-state fMRI  ... 
doi:10.3389/fnhum.2016.00014 pmid:26869900 pmcid:PMC4740785 fatcat:2quv3rjcbjdmrjpmsd47w3ul2i

Dynamic and Static Amplitude of Low-Frequency Fluctuation Is a Potential Biomarker for Predicting Prognosis of Degenerative Cervical Myelopathy Patients: A Preliminary Resting-State fMRI Study

Ningjian Fan, Bing Zhao, LiYun Liu, WeiZhen Yang, Xian Chen, ZhanBin Lu
2022 Frontiers in Neurology  
) patients.MethodsVoxel-wise sALFF and dALFF of 47 DCM patients and 44 healthy controls were calculated using resting-state fMRI data, and an intergroup comparison was performed.  ...  Furthermore, the multivariate approach is a more sensitive method in exploring neuropathology and establishing a prognostic biomarker for DCM compared with the conventional univariate method.  ...  Resting-state fMRI was recently used to establish a prognostic biomarker for DCM patients (9–11).  ... 
doi:10.3389/fneur.2022.829714 pmid:35444605 pmcid:PMC9013796 fatcat:gndtm2r6mveujjyrd626lwkw2m

From descriptive connectome to mechanistic connectome: Generative modeling in functional magnetic resonance imaging analysis

Guoshi Li, Pew-Thian Yap
2022 Frontiers in Human Neuroscience  
Here we review the foundation and development of major generative modeling approaches for functional magnetic resonance imaging (fMRI) and survey their applications to cognitive or clinical neuroscience  ...  As a newly emerging field, connectomics has greatly advanced our understanding of the wiring diagram and organizational features of the human brain.  ...  In addition to task-fMRI, resting-state fMRI has been analyzed by DCM models to study the neural substrate of cognition.  ... 
doi:10.3389/fnhum.2022.940842 pmid:36061504 pmcid:PMC9428697 fatcat:oflaen765rdlljyyuhpsumcayu

fMRI in Non-human Primate: A Review on Factors That Can Affect Interpretation and Dynamic Causal Modeling Application

D. Blair Jovellar, Doris J. Doudet
2019 Frontiers in Neuroscience  
Dynamic causal modeling (DCM)-a framework for inferring hidden neuronal states from brain activity measurements (e. g., fMRI) and their context-dependent modulation-was developed for human neuroimaging  ...  Considering the factors that are relevant for DCM application to NHP neuroimaging, we propose a strategy for modeling effective connectivity under anesthesia using an integrated physiologic-stochastic  ...  ACKNOWLEDGMENTS We are grateful to Bernard Ng, Ph.D. and Rafael von Känel, Ph.D. for the stimulating discussions and the reviewers for their detailed comments.  ... 
doi:10.3389/fnins.2019.00973 pmid:31619951 pmcid:PMC6759819 fatcat:znwfnvyftbf5lksodas2kx37bq

Large-scale DCMs for resting-state fMRI

Adeel Razi, Mohamed L. Seghier, Yuan Zhou, Peter McColgan, Peter Zeidman, Hae-Jeong Park, Olaf Sporns, Geraint Rees, Karl J. Friston
2017 Network Neuroscience  
We show that spectral DCM-with functional connectivity priors-is ideally suited for directed graph theoretic analyses of resting-state fMRI.  ...  This paper considers the identification of large directed graphs for resting-state brain networks based on biophysical models of distributed neuronal activity, that is, effective connectivity.  ...  METHODS AND MATERIALS Dynamic Causal Modeling for Resting-State fMRI Resting-state fMRI is a paradigm that has become very popular during the past decade or so.  ... 
doi:10.1162/netn_a_00015 pmid:29400357 pmcid:PMC5796644 fatcat:k5ovly4t2netfkgdjo7joyuc3q
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