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Information-based functional brain mapping.
The development of high-resolution neuroimaging and multielectrode electrophysiological recording provides neuroscientists with huge amounts of multivariate data. Expand
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Analysis of functional image analysis contest (FIAC) data with brainvoyager QX: From single‐subject to cortically aligned group general linear model analysis and self‐organizing group independent
We perform a standard analysis of the functional and anatomical data that includes preprocessing, spatial normalization into Talairach space, hypothesis‐driven statistics (one‐ and two‐factorial, single‐subject and group‐level random effects, General Linear Model [GLM]) of the block‐ and event‐related paradigms. Expand
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Mapping directed influence over the brain using Granger causality and fMRI
We propose Granger causality mapping (GCM) as an approach to explore directed influences between neuronal populations (effective connectivity) in fMRI data. Expand
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Investigating directed cortical interactions in time-resolved fMRI data using vector autoregressive modeling and Granger causality mapping.
We present a framework aimed to reveal directed interactions of activated brain areas using time-resolved fMRI and vector autoregressive (VAR) modeling in the context of Granger causality. Expand
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Mirror-Symmetric Tonotopic Maps in Human Primary Auditory Cortex
Understanding the functional organization of the human primary auditory cortex (PAC) is an essential step in elucidating the neural mechanisms underlying the perception of sound, including speech andExpand
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Localizing P300 Generators in Visual Target and Distractor Processing: A Combined Event-Related Potential and Functional Magnetic Resonance Imaging Study
Constraints from functional magnetic resonance imaging (fMRI) were used to identify the sources of the visual P300 event-related potential (ERP). Healthy subjects performed a visual three-stimulusExpand
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Individual faces elicit distinct response patterns in human anterior temporal cortex
Visual face identification requires distinguishing between thousands of faces we know. This computational feat involves a network of brain regions including the fusiform face area (FFA) and anteriorExpand
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Combining multivariate voxel selection and support vector machines for mapping and classification of fMRI spatial patterns
We propose a recursive algorithm for classifying functional imaging data based on a multivariate feature selection algorithm, Recursive Feature Elimination, that uses the training algorithm (support vector machine) recursively to eliminate irrelevant voxels and estimate informative spatial patterns. Expand
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7T vs. 4T: RF power, homogeneity, and signal‐to‐noise comparison in head images
Signal‐to‐noise ratio (SNR), RF field (B1), and RF power requirement for human head imaging were examined at 7T and 4T magnetic field strengths. The variation in B1 magnitude was nearly twofoldExpand
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Independent component analysis of fMRI group studies by self-organizing clustering
We exploit the application of similarity measures and a related visual tool to study the natural self-organizing clustering of many independent components from multiple individual data sets in the subject space. Expand
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