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An fMRI Investigation of Racial Paralysis
Behavior Race Characteristics Judgments Decision Choices and Conditions Personal Characteristics
2015/5/13
We explore the existence and underlying neural mechanism of a new norm endorsed by both black and white Americans for managing interracial interactions: "racial paralysis," the tendency to opt out of ...
HRF estimation improves sensitivity of fMRI encoding and decoding models
fMRI hemodynamic HRF GLM BOLD en-coding decoding
2013/6/14
Extracting activation patterns from functional Magnetic Resonance Images (fMRI) datasets remains challenging in rapid-event designs due to the inherent delay of blood oxygen level-dependent (BOLD) sig...
Fractal-driven distortion of resting state functional networks in fMRI: a simulation study
Fractal-driven distortion resting state functional networks simulation study
2012/9/17
Fractals are self-similar and scale-invariant patterns found ubiquitously in nature. A lot of evidences implying fractal properties such as 1/f power spectrums have been also observed in resting state...
Detecting sparse cone alternatives for Gaussian random fields, with an application to fMRI
random elds Euler characteristic kinematic formulae volumes of tubes expansion order-restricted inference multivari-ate one-sided hypotheses non-negative least squares.
2012/9/19
Our problem is to nd a good approximation to the P-value of the maximum of a random eld of test statistics for a cone alternative at each point in a sample of Gaussian random elds. These test stati...
Multi-scale Mining of fMRI data with Hierarchical Structured Sparsity
brain reading structured sparsity convex optimization sparse hierarchical models inter-subject validation proximal methods
2011/6/16
Inverse inference, or “brain reading”, is a recent paradigm for analyzing functional magnetic resonance imaging (fMRI) data, based on pattern recognition and statistical learning. By predicting some c...
Causality as a unifying approach between activation and connectivity analysis of fMRI data
Causality activations functional connectivity fMRI
2011/3/24
This paper indicates causality as the tool that unifies the analysis of both activations and connectivity of brain areas, obtained with fMRI data. Causality analysis is commonly applied to study conne...
Temporal and Spatial Independent Component Analysis for fMRI data sets embedded in a R package
Computation (stat.CO) Medical Physics (physics.med-ph) Applications (stat.AP)
2010/12/17
For statistical analysis of functional Magnetic Resonance Imaging (fMRI) data sets, we propose a data-driven approach based on Independent Component Analysis (ICA) implemented in a new version of the ...
SMART：A statistical framework for optimal design matrix generation with application to fMRI
statistical framework optimal design matrix generation fMRI
2010/3/18
The general linear model (GLM) is a well established tool for analyzing functional magnetic resonance imaging (fMRI) data. Most fMRI analyses via GLM proceed in a massively univariate
fashion where t...
ADIS——A robust pursuit algorithm for probabilistic，constrained and non-square blind source separation with application to fMRI
ADIS robust pursuit algorithm blind source separation fMRI
2010/3/18
In this article, we develop an algorithm for probabilistic and constrained projection pursuit.
Our algorithm called ADIS (automated decomposition into sources) accepts arbitrary non-linear
contrast ...
Semiparametric detection of significant activation for brain fMRI
deconvolution local polynomial regression nonparametrictest spatio-temporal data stimuli time resolution
2010/4/30
Functional magnetic resonance imaging (fMRI) aims to locate
activated regions in human brains when specific tasks are performed.
The conventional tool for analyzing fMRI data applies some variant
o...