<p>(A) Case WithinSub: Classifiers are trained and tested for each subject separately; (B) Case AcrossSub: Classifiers are built across subjects, that is, leaving out the complete data of one subject for testing and using the data from all other subjects for training; (C) Case AvgItem: fMRI data are averaged over items and classifiers are built across subjects on the averaged data; (D) Case AvgSub: fMRI data are averaged over subjects and classifiers are built for this “averaged subject”. For each fMRI data analysis case, if a red rectangle contains only one subject, it indicates a within-subject analysis. Otherwise, the analysis is done across subjects.</p
A major goal of functional mri measurements is the localization of the neural correlates of sensory,...
International audienceIn brain imaging, solving learning problems in multi-subjects settings is diff...
Pattern recognition methods have shown that fMRI data can reveal signicant information about brain a...
The accuracies of the two-class, three-class and four-class classifications for the real fMRI data.<...
There are four datasets for total 18 subjects. The subject numbers are consistent across the four da...
A major goal of functional mri (fmri) measurements is the localization of the neural correlates of s...
Summarization: Functional magnetic resonance imaging (fMRI) is one of the most popular methods for s...
We present a new discriminant analysis (DA) method called Multiple Subject Barycentric Discriminant ...
Inter-subject correlation (ISC) analysis for functional magnetic resonance imaging (fMRI)is a data d...
Within functional magnetic resonance imaging (fMRI), the use of the traditional general linear model...
Within functional magnetic resonance imaging (fMRI), the use of the traditional general linear model...
Inter-subject correlation (ISC) analysis for functional magnetic resonance imaging (fMRI)is a data d...
<div><p>Within functional magnetic resonance imaging (fMRI), the use of the traditional general line...
fMRI is a powerful tool used in the study of brain function. it can non-invasively detect signal cha...
Machine learning and Pattern recognition techniques are being increasingly employed in Functional ma...
A major goal of functional mri measurements is the localization of the neural correlates of sensory,...
International audienceIn brain imaging, solving learning problems in multi-subjects settings is diff...
Pattern recognition methods have shown that fMRI data can reveal signicant information about brain a...
The accuracies of the two-class, three-class and four-class classifications for the real fMRI data.<...
There are four datasets for total 18 subjects. The subject numbers are consistent across the four da...
A major goal of functional mri (fmri) measurements is the localization of the neural correlates of s...
Summarization: Functional magnetic resonance imaging (fMRI) is one of the most popular methods for s...
We present a new discriminant analysis (DA) method called Multiple Subject Barycentric Discriminant ...
Inter-subject correlation (ISC) analysis for functional magnetic resonance imaging (fMRI)is a data d...
Within functional magnetic resonance imaging (fMRI), the use of the traditional general linear model...
Within functional magnetic resonance imaging (fMRI), the use of the traditional general linear model...
Inter-subject correlation (ISC) analysis for functional magnetic resonance imaging (fMRI)is a data d...
<div><p>Within functional magnetic resonance imaging (fMRI), the use of the traditional general line...
fMRI is a powerful tool used in the study of brain function. it can non-invasively detect signal cha...
Machine learning and Pattern recognition techniques are being increasingly employed in Functional ma...
A major goal of functional mri measurements is the localization of the neural correlates of sensory,...
International audienceIn brain imaging, solving learning problems in multi-subjects settings is diff...
Pattern recognition methods have shown that fMRI data can reveal signicant information about brain a...