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AIME
2007
Springer
13 years 11 months ago
Predictive Modeling of fMRI Brain States Using Functional Canonical Correlation Analysis
We present a novel method for predictive modeling of human brain states from functional neuroimaging (fMRI) data. Extending the traditional canonical correlation analysis of discre...
Sennay Ghebreab, Arnold W. M. Smeulders, Pieter W....
ISBI
2009
IEEE
14 years 11 hour ago
Detecting Maximal Directional Changes in Spatial fMRI Response Using Canonical Correlation Analysis
Traditional fMRI analysis has focused on modeling temporal changes in BOLD signals on a voxel-by-voxel basis to infer brain activation. To incorporate spatial information, we have...
Bernard Ng, Rafeef Abugharbieh, Martin McKeown
NIPS
2007
13 years 6 months ago
Predicting Brain States from fMRI Data: Incremental Functional Principal Component Regression
We propose a method for reconstruction of human brain states directly from functional neuroimaging data. The method extends the traditional multivariate regression analysis of dis...
Sennay Ghebreab, Arnold W. M. Smeulders, Pieter W....
ICASSP
2009
IEEE
13 years 12 months ago
Fusion of fMRI, sMRI, and EEG data using canonical correlation analysis
Typically data acquired through imaging techniques such as functional magnetic resonance imaging (fMRI), structural MRI (sMRI), and electroencephalography (EEG) are analyzed separ...
Nicolle M. Correa, Yi-Ou Li, Tülay Adali, Vin...
MICCAI
2010
Springer
13 years 3 months ago
Generalized Sparse Classifiers for Decoding Cognitive States in fMRI
The high dimensionality of functional magnetic resonance imaging (fMRI) data presents major challenges to fMRI pattern classification. Directly applying standard classifiers often ...
Bernard Ng, Arash Vahdat, Ghassan Hamarneh, Rafeef...