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Estimation of the Hemodynamic Response in Event-Related Functional MRI: Bayesian Networks as a Framework for Efficient Bayesian Modeling and Inference
2004
IEEE Transactions on Medical Imaging
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ACKNOWLEDGMENT The authors are grateful to Pr. J. Doyon (Institut de Gériatrie, Université de Montréal, Canada) for providing them with the data and to C. Posé for her technical support. ...
Estimation of the Hemodynamic Response in Event-Related Functional MRI: Bayesian Networks as a Framework for Efficient Bayesian Modeling and Inference Guillaume Marrelec*, Philippe Ciuciu, Member, IEEE ...
We finally apply this novel technique on both simulations and real data. Index Terms-Bayesian inference, Bayesian networks, functional MRI, hemodynamic response function.
I. ...
doi:10.1109/tmi.2004.831221
pmid:15338730
fatcat:t4hdvmix2fd63lp7rfj3ydrniu
Application of Spatial Bayesian Hierarchical Models to fMRI Data
[chapter]
2016
Assessment of Cellular and Organ Function and Dysfunction using Direct and Derived MRI Methodologies
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In this chapter, a spatial Bayesian hierarchical model is applied to an event-related fMRI study of cognitive control using the Simon test. ...
Bayesian modelling has attracted great interest in cognitive science and offered a flexible and interpretable way to study cognitive processes using functional magnetic resonance imaging data. ...
Acknowledgements This research was, in part, supported by the Ministry of Education, Taiwan, R.O.C. and National Cheng Kung University (the Aim for the Top University Project to National Cheng Kung University ...
doi:10.5772/64823
fatcat:2tyu76cetvgphffjqxs2btr24y
A deconvolution algorithm for multiecho functional MRI: Multiecho Sparse Paradigm Free Mapping
[article]
2019
biorxiv/medrxiv
pre-print
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This framework is a step towards deciphering the dynamic nature of brain activity in naturalistic paradigms, resting-state or experimental paradigms with unknown timing of the BOLD events. ...
Our results in multi-echo fMRI data collected during a multi-task event-related paradigm at 3 Tesla demonstrate that the maps of R2* changes obtained with ME-SPFM at the times of the stimulus trials show ...
Penny A. Gowland for helpful discussion regarding the contents of this manuscript, as well as the anonymous reviewers for their valuable comments and feedback. ...
doi:10.1101/558288
fatcat:3fymypki2rgu7npddhcaaacsqa
A deconvolution algorithm for multi-echo functional MRI: Multi-echo Sparse Paradigm Free Mapping
2019
NeuroImage
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This framework is a step towards deciphering the dynamic nature of brain activity in naturalistic paradigms, resting-state or experimental paradigms with unknown timing of the BOLD events. ...
Our results in multi-echo fMRI data collected during a multi-task event-related paradigm at 3 Tesla demonstrate that the maps of R2⁎ changes obtained with ME-SPFM at the times of the stimulus trials show ...
Penny A. Gowland for helpful discussion regarding the contents of this manuscript, as well as the anonymous reviewers for their valuable comments and feedback. ...
doi:10.1016/j.neuroimage.2019.116081
pmid:31419613
pmcid:PMC6819276
fatcat:sid3nqty2ba67l5jmhsu5aji7m
Partial correlation for functional brain interactivity investigation in functional MRI
2006
NeuroImage
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In the proposed framework, Bayesian analysis makes it possible to estimate and test the partial statistical dependencies between regions without any prior model on the underlying functional interactions ...
Partial correlation is more closely related to effective connectivity than marginal correlation and provides a convenient graphical representation for functional interactions. ...
Acknowledgments The authors are in debt to the two anonymous referees for significantly improving the quality of the original manuscript. ...
doi:10.1016/j.neuroimage.2005.12.057
pmid:16777436
fatcat:xpuqam6phjd7nndmlvvukk535y
Unsupervised learning and mapping of active brain functional MRI signals based on hidden semi-Markov event sequence models
2005
IEEE Transactions on Medical Imaging
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In this paper, a novel functional magnetic resonance imaging (fMRI) brain mapping method is presented within the statistical modeling framework of hidden semi-Markov event sequence models (HSMESMs). ...
Solving for the HSMESM Evaluation and Learning problems enables the model to automatically detect neural activation embedded in a given set of fMRI signals, without requiring any template basis function ...
Classical and Bayesian inference techniques applied to these models allow both to detect neural activation and estimate model parameters and hyperparameters. ...
doi:10.1109/tmi.2004.841225
pmid:15707252
fatcat:fhlkgeuciradlbrx2wyt7mg3ii
Multimodal Functional Neuroimaging: Integrating Functional MRI and EEG/MEG
2008
IEEE Reviews in Biomedical Engineering
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in the understanding and modeling of neurovascular coupling and in the methodologies for the fMRI-EEG/MEG simultaneous recording. ...
In this review, we start with an overview of the physiological origins of EEG/MEG and fMRI, as well as their fundamental biophysics and imaging principles, we proceed with a review of the major advances ...
Stimulus functions encoding the occurrence of a particular event or experimental state (e.g., boxcar-functions) are convolved with a hemodynamic response function (HRF) to form regressors in the GLM. ...
doi:10.1109/rbme.2008.2008233
pmid:20634915
pmcid:PMC2903760
fatcat:6hogffiwvrbonmxn2swkyqstde
Bayesian Treatments of Neuroimaging Data
[chapter]
2006
Bayesian Brain
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In summary, temporal basis functions offer useful constraints on the form of the estimated response that retain (i) the flexibility of FIR models and (ii) the efficiency of single regressor models. ...
In [13] the form of the hemodynamic impulse response function (HRF) was estimated using a least squares deconvolution and a time invariant model, where evoked neuronal responses are convolved with the ...
doi:10.7551/mitpress/9780262042383.003.0005
fatcat:iw2fqoge3bfvxpvqtcidvosptm
A Theoretical Investigation of the Relationship between Structural Equation Modeling and Partial Correlation in Functional MRI Effective Connectivity
2009
Computational Intelligence and Neuroscience
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In this paper, we provide theoretical fundaments explaining why and in what measure structural equation modeling and partial correlations are related. ...
We recently proposed a data-driven method based on the partial correlation matrix that could provide some insight regarding the pattern of functional interaction between brain regions as represented by ...
Inference of Π can be performed in a Bayesian framework using a numerical sampling scheme ( [11, 13] , see also the appendix). ...
doi:10.1155/2009/369341
pmid:19730736
pmcid:PMC2731937
fatcat:yypkvov44bainaqqzftgrvu2su
Decision-making under risk: A graph-based network analysis using functional MRI
2012
NeuroImage
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Regional response non-linearity was excluded as an artifactual basis to the observed effects, and directionality inferences were confirmed by comparison of dynamic causal models. ...
This study also has more general paradigmatic implications for neuroeconomics, demonstrating the value of explicit modeling of inter-regional interactions for understanding the neural substrates of decisional ...
Acknowledgments LM was wholly funded and employed by the Fondazione IRCCS Istituto Neurologico Carlo Besta (FINCB) during the core period of ...
doi:10.1016/j.neuroimage.2012.02.048
pmid:22387471
fatcat:u4rtcjqmand4zkfq5i5t2v3dpm
Independent component analysis of functional MRI: what is signal and what is noise?
2003
Current Opinion in Neurobiology
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Many sources of fluctuation contribute to the functional magnetic resonance imaging (fMRI) signal, complicating attempts to infer those changes that are truly related to brain activation. ...
Unlike methods of analysis of fMRI data that test the time course of each voxel against a hypothesized waveform, data-driven methods, such as independent component analysis and clustering, attempt to find ...
grant P20 EB 002013 to L Hansen, and both the Howard Hughes Medical Institute and a National Institutes of Health grant MH61619-03 to T Sejnowski. ...
doi:10.1016/j.conb.2003.09.012
pmid:14630228
pmcid:PMC2925426
fatcat:6qpybi2xzvexdi23ghce7tocem
Multi-Scale Information, Network, Causality, and Dynamics: Mathematical Computation and Bayesian Inference to Cognitive Neuroscience and Aging
[chapter]
2013
Functional Brain Mapping and the Endeavor to Understand the Working Brain
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Acknowledgements Preparation of this chapter is supported in part by a grant from the National Institute of Aging, K25AG033725. ...
Author details Michelle Yongmei Wang * Address all correspondence to: ymw@illinois.edu Departments of Statistics, Psychology, and Bioengineering, Beckman Institute, University of Illinois at Urbana-Champaign ...
A critical objective of neuroimaging data analysis is the inference of neural processes responsible for the observed data, that is, the estimation of the hemodynamic response functions. ...
doi:10.5772/55262
fatcat:go2r6jruyzdqrp4lqcnt64j7va
Incorporating priors for EEG source imaging and connectivity analysis
2015
Frontiers in Neuroscience
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Here, we review the available priors from such techniques as magnetic resonance imaging (MRI), functional MRI (fMRI), and positron emission tomography (PET). ...
For spatial priors, EEG-correlated fMRI, temporally coherent networks (TCNs) and resting-state fMRI are systematically introduced in the ESI. ...
Acknowledgments This research was supported by grants from the 863 project 2015AA020504 and the National Nature Science Foundation of China (31200857). ...
doi:10.3389/fnins.2015.00284
pmid:26347599
pmcid:PMC4539512
fatcat:dslnmr32h5cnzfz5u23eqi37xa
Hierarchical Bayesian Modeling of the Relationship between Task Related Hemodynamic Responses and Neuronal Excitability: a Simultaneous fNIRS/TMS Study
[article]
2021
bioRxiv
pre-print
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Here we proposed hierarchical Bayesian modeling to taking into account variability in the data at the individual and group levels, aiming to provide accurate and reliable statistical inferences on this ...
Conclusion: Benefiting from this original Bayesian data analysis, our results showed that PAS modulates task-related cortical hemodynamic responses in addition to M1 excitability. ...
Acknowledgments This work was supported by the Natural Sciences and Engineering Research Council of Canada Discovery Grant Program (CG and JML), an operating grant from the Canadian ...
doi:10.1101/2021.10.22.465452
fatcat:n57w2slr2fef5anjyd5p67p5rm
Large-scale DCMs for resting-state fMRI
2017
Network Neuroscience
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Furthermore, we show that the use of Bayesian model reduction to discover the most likely sparse graph (or model) from a parent (e.g., fully connected) graph eschews the arbitrary thresholding often applied ...
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. ...
The Bayesian framework used by DCM allows for an informed and graceful way of performing "network inference" via Bayesian model reduction to select or threshold out redundant edges . ...
doi:10.1162/netn_a_00015
pmid:29400357
pmcid:PMC5796644
fatcat:k5ovly4t2netfkgdjo7joyuc3q
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