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» An fMRI Activation Method Using Complex Data
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EDM
2010
160views Data Mining» more  EDM 2010»
14 years 11 months ago
Using Neural Imaging and Cognitive Modeling to Infer Mental States while Using an Intelligent Tutoring System
Functional magnetic resonance imaging (fMRI) data were collected while students worked with a tutoring system that taught an algebra isomorph. A cognitive model predicted the distr...
Jon M. Fincham, John R. Anderson, Shawn Betts, Jen...
COMPIMAGE
2010
Springer
15 years 4 months ago
Surface-Based Imaging Methods for High-Resolution Functional Magnetic Resonance Imaging
Functional magnetic resonance imaging (fMRI) has become an exceedingly popular technique for studies of human brain activity. Typically, fMRI is performed with >3-mm sampling, s...
David Ress, Sankari Dhandapani, Sucharit Katyal, C...
ICASSP
2007
IEEE
15 years 4 months ago
Local Linear Discriminant Analysis (LLDA) for Inference of Multisubject FMRI Data
Large intersubject variability is a well-described feature of fMRI studies, making inter-group inference, of critical importance for biological interpretation, difficult. Therefor...
Martin J. McKeown, Junning Li, Xuemei Huang, Z. Ja...
CORR
2011
Springer
150views Education» more  CORR 2011»
14 years 4 months ago
Total variation regularization for fMRI-based prediction of behaviour
—While medical imaging typically provides massive amounts of data, the extraction of relevant information for predictive diagnosis remains a difficult challenge. Functional MRI ...
Vincent Michel, Alexandre Gramfort, Gaël Varo...
BC
2007
113views more  BC 2007»
14 years 9 months ago
Akaike causality in state space
We present a new approach of explaining partial causality in multivariate fMRI time series by a state space model. A given single time series can be divided into two noise-driven ...
Kin Foon Kevin Wong, Tohru Ozaki