Bayesian inference has taken FMRI methods research into areas that frequentist statistics have struggled to reach. In this article we will consider some of the early forays into Bayes and what motivated its use. We shall see the impact that Bayes has had on haemodynamic modelling, spatial modelling, group analysis, model selection and brain connectivity analysis; and consider how these advancements have spun-off into related areas of neuroscience and some of the challenges that remain. Bayes has brought to the table inference flexibility, incorporation of prior information, adaptive regularisation and model selection. But perhaps more important than these things, is the ability of Bayes to empower the methods researcher with a mathematicall...
In this research work, I propose Bayesian nonparametric approaches to model functional magnetic reso...
Functional Magnetic Resonance Imaging (fMRI) is a powerful technique for studying the working of the...
In Friston et al. ((2002) Neuroimage 16: 465-483) we introduced empirical Bayes as a potentially use...
Bayesian inference has taken FMRI methods research into areas that frequentist statistics have strug...
Typically in neuroimaging we are looking to extract some pertinent information from imperfect, noisy...
Typically in neuroimaging we are looking to extract some pertinent information from imperfect, noisy...
models for functional magnetic resonance imaging data analysis Linlin Zhang,1 Michele Guindani2 and ...
Functional magnetic resonance imaging (fMRI), a noninvasive neuroimaging method that provides an ind...
Recent debates about the conventional traditional threshold used in the fields of neuroscience and p...
University of Minnesota Ph.D. dissertation. August 2010. Major: Statistics. Advisor: Jones, Galin. 1...
Functional magnetic resonance imaging (fMRI), a noninvasive neuroimaging method that provides an ind...
Functional magnetic resonance imaging (fMRI) is a non-invasive technique that measures the associate...
This paper aims to review state-of-the-art Bayesian-inference-based methods applied to functional ma...
Bayesian methods have proved powerful in many applications, including MRI, for the inference of mode...
This paper reviews hierarchical observation models, used in functional neuroimaging, in a Bayesian l...
In this research work, I propose Bayesian nonparametric approaches to model functional magnetic reso...
Functional Magnetic Resonance Imaging (fMRI) is a powerful technique for studying the working of the...
In Friston et al. ((2002) Neuroimage 16: 465-483) we introduced empirical Bayes as a potentially use...
Bayesian inference has taken FMRI methods research into areas that frequentist statistics have strug...
Typically in neuroimaging we are looking to extract some pertinent information from imperfect, noisy...
Typically in neuroimaging we are looking to extract some pertinent information from imperfect, noisy...
models for functional magnetic resonance imaging data analysis Linlin Zhang,1 Michele Guindani2 and ...
Functional magnetic resonance imaging (fMRI), a noninvasive neuroimaging method that provides an ind...
Recent debates about the conventional traditional threshold used in the fields of neuroscience and p...
University of Minnesota Ph.D. dissertation. August 2010. Major: Statistics. Advisor: Jones, Galin. 1...
Functional magnetic resonance imaging (fMRI), a noninvasive neuroimaging method that provides an ind...
Functional magnetic resonance imaging (fMRI) is a non-invasive technique that measures the associate...
This paper aims to review state-of-the-art Bayesian-inference-based methods applied to functional ma...
Bayesian methods have proved powerful in many applications, including MRI, for the inference of mode...
This paper reviews hierarchical observation models, used in functional neuroimaging, in a Bayesian l...
In this research work, I propose Bayesian nonparametric approaches to model functional magnetic reso...
Functional Magnetic Resonance Imaging (fMRI) is a powerful technique for studying the working of the...
In Friston et al. ((2002) Neuroimage 16: 465-483) we introduced empirical Bayes as a potentially use...