A parametric empirical bayesian framework for the EEG/MEG inverse problem: Generative models for multi-subject and multi-modal integration

Frontiers in Human Neuroscience

Volumn , Issue AUGUST, 2011, Pages

  Henson, Richard N ^a   Wakeman, Daniel G ^a   Litvak, Vladimir ^b   Friston, Karl J ^b  

^a MRC COGNITION AND BRAIN SCIENCES UNIT   (United Kingdom)

^b UNIVERSITY COLLEGE LONDON   (United Kingdom)

Author keywords

Bioelectromagnetic signals; Data fusion; Neuroimaging; Source reconstruction

Indexed keywords

ANALYTICAL PARAMETERS; BAYES THEOREM; ELECTROENCEPHALOGRAM; EVOKED CORTICAL RESPONSE; FACE PROFILE; FREQUENCY MODULATION; FUNCTIONAL MAGNETIC RESONANCE IMAGING; IMAGE RECONSTRUCTION; INFORMATION PROCESSING; MAGNETOENCEPHALOGRAPHY; MATHEMATICAL ANALYSIS; MATHEMATICAL COMPUTING; MATHEMATICAL PARAMETERS; NUCLEAR MAGNETIC RESONANCE IMAGING; PERCEPTIVE DISCRIMINATION; REPRODUCIBILITY; REVIEW; STATISTICAL MODEL; VISUAL DISCRIMINATION;

EID: 84933671268     PISSN: 16625161     EISSN: 16625161     Source Type: Journal    
DOI: 10.3389/fnhum.2011.00076     Document Type: Review

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