A Bayesian spatial model for group fMRI studies 55
A BAYESIAN HIERARCHICAL FRAMEWORK FOR SPATIAL MODELING OF fMRI DATA
... activation studies often compare localized task-induced changes in brain activity between experimental ...a Bayesian exten- sion of voxel-level analyses that offers several notable ...our model using ...
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Bayesian fmri time series analysis with spatial priors
... the spatial prior underlying it are perhaps best understood with an example in which we compare VB with an L-prior to ...our model as ...used spatial precision parameters a 1 = a 2 = 1 and generated ...
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Group analysis based on multilevel Bayesian for FMRI data
... different studies compared by aligning them to standard space it can deal with different Talairach ...larger spatial SNR in spatial overlap by blurring over minor anatomical differences and ...
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Bayesian Spatial Modeling of fMRI data: A Multiple-Subject Analysis
... a spatial model for multi-subject fMRI ...on spatial modeling for single-subject data, there has been no work on spatial models that explicitly account for intersubject vari- ability in ...
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Bayesian model reduction and empirical Bayes for group (DCM) studies
... individual model are shown in the middle and lower left ...and Bayesian inference of the group level To illustrate the fundamental difference between classical and Bayesian inference at the ...
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Bayesian model reduction and empirical Bayes for group (DCM) studies
... reviews Bayesian model reduction and introduces its application in a hierarchical or empirical Bayesian ...to group studies, providing specific expressions for the procedures used in ...
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Search for patterns of functional specificity in the brain: A nonparametric hierarchical Bayesian model for group fMRI data
... MRI studies have uncovered a number of brain areas that demonstrate highly specific functional ...from fMRI data in a group of ...require spatial alignment of functional images from different ...
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A spatiotemporal nonparametric Bayesian model of multi-subject fMRI data
... multi-subject fMRI experi- ments. This is distinct from two-stage “group analysis” approaches tradition- ally considered in the fMRI literature, which separate the inference on the individual ...
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The impact of spatial scales and spatial smoothing on the outcome of Bayesian spatial model
... for Spatial Information, Melbourne, Victoria, Australia ∗ E-mail: ...in spatial analysis. There have been few studies into the impact of different geographical scales on the outcome of spatial ...
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A Constrained ICA-EMD Model for Group Level fMRI Analysis
... that spatial EMD can also be used to extract useful intrinsic patterns from functional MRI data, representing characteristic resting- state ...the spatial variant of this technique and to investigate other ...
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A group model for stable multi-subject ICA on fmri datasets
... and group-level independent components: subject components share the same set of independent spatial patterns and time courses for each spatial map, but the contribution of each independent pattern ...
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Model-Free Analysis of Single fMRI Time Series Based on Spatial Synchronization
... apply group independent component analysis (ICA) [19] on the group of subjects to extract the activation ...Recent studies showed that ICA can be used to separate fMRI data into meaningful ...
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Impact of the joint detection-estimation approach on random effects group studies in fMRI
... intra-subject studies, which are usually conducted using a massively univari- ate ...adaptive spatial correlation model en- ables the detection of activation clusters at voxel ...the group ...
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Spatial interactions in location decisions: Empirical evidence from a Bayesian spatial probit model
... DEPENDENTS’ measures how many of the ten nearest neighbors are independent stations. Assuming that independent competitors set prices more aggressively would suggest a positive impact of this variable on exit ...
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Data augmentation for a Bayesian spatial model involving censored observations
... Environmental studies often include some observations falling below a level of de- tection ...Censored spatial data are often analyzed by ignoring spatial correlation and using one of many methods ...
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Temporal-spatial modeling for fMRI data
... Event-related fMRI (ER-fMRI) has played an important role in many recent brain imaging studies to explore the relationship between recorded fMRI signals and neural ...block-design fMRI, ...
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Bayesian inference in camera trapping studies for a class of spatial capture-recapture models
... process model is a potential virtue of the Bayesian formulation of spatial capture–recapture models, we feel that the biggest practical advantage apparent at this time has to do with the validity of ...
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Generative models for group fMRI data
... contiguous spatial maps, despite the fact that our search does not con- strain the systems ...rating spatial information into our fMRI models. The spatial maps of our functional systems show ...
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A Bayesian Model Averaging Approach for Observational Gene Expression Studies
... microarray studies. As more and more studies are carried out with observational rather than well controlled experimental samples, it becomes important to evaluate and properly control the impact of sample ...
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How to avoid mismodelling in GLM-based fMRI data analysis: cross-validated Bayesian model selection
... informal model selection using classical significance ...arbitrary model differences and it delivers voxel-wise optimal ...each model separately without the possibility of only estimating one global ...
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