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» An fMRI Activation Method Using Complex Data
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ICASSP
2011
IEEE
14 years 1 months ago
Data-driven fMRI group classification using connected components and Gaussian process classifiers
Functional magnetic resonance imaging (fMRI) is a popular tool for studying brain activity due to its non-invasiveness. Conventionally an expected response needs to be available f...
Sarah Lee, Fernando Zelaya, Yohan Samarasinghe, St...
73
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ISBI
2002
IEEE
15 years 10 months ago
A spatially robust ICA algorithm for multiple fMRI data sets
In this paper we derive an independent-component analysis (ICA) method for analyzing two or more data sets simultaneously. Our model extracts independent components common to all ...
Ana S. Lukic, Miles N. Wernick, Lars Kai Hansen, J...
TNN
2010
205views Management» more  TNN 2010»
14 years 4 months ago
Behavior-constrained support vector machines for fMRI data analysis
Statistical learning methods are emerging as a valuable tool for decoding information from neural imaging data. The noisy signal and the limited number of training patterns that ar...
Danmei Chen, Sheng Li, Zoe Kourtzi, Si Wu
MICCAI
2006
Springer
15 years 10 months ago
Anatomically Informed Convolution Kernels for the Projection of fMRI Data on the Cortical Surface
Abstract. We present here a method that aims at producing representations of functional brain data on the cortical surface from functional MRI volumes. Such representations are req...
Grégory Operto, Jean-Luc Anton, Olivier Cou...
ISBI
2006
IEEE
15 years 10 months ago
Sample dependence correction for order selection in fMRI analysis
Multivariate analysis methods such as independent component analysis (ICA) have been applied to the analysis of functional magnetic resonance imaging (fMRI) data to study the brai...
Tülay Adali, Vince D. Calhoun, Yi-Ou Li