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A probabilistic algorithm for MEG source reconstruction
Johanna M. Zumer
*
, Hagai T. Attias
, Kensuke Sekihara
, Srikantan S. Nagarajan
*
Corresponding author for this work
School of Psychology
College of Health and Life Sciences
Golden Metallic, Inc.
Tokyo Metropolitan University
University of California San Francisco
UCB
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Keyphrases
Dipole
100%
Source Reconstruction
100%
Probabilistic Algorithm
100%
Correlated Sources
66%
Sensor Noise
66%
Temporal Basis Function
66%
Background Activity
66%
Source Localization
33%
Expectation-maximization Algorithm
33%
Linear Combination
33%
Factor Analysis
33%
Probabilistic Model
33%
Computational Complexity
33%
Dipolar Sources
33%
Beamforming Technique
33%
Sensor Data
33%
EEG Data
33%
Novel Algorithm
33%
MEG Data
33%
Mixing Matrix
33%
Fitting Method
33%
Linear Mixture
33%
Noise Covariance
33%
Active Dipole
33%
MAP Estimate
33%
Multi-dipole
33%
Matrix Sensor
33%
Deep Sources
33%
Central Sulcus
33%
Lateral Sulcus
33%
MUSIC Technique
33%
Somatosensory Evoked Fields
33%
Auditory Evoked Field
33%
Computer Science
Basis Function
100%
Computational Complexity
33%
Source Localization
33%
Probabilistic Modeling
33%
Linear Combination
33%
Unknown Coefficient
33%
Background Model
33%
Linear Mixture
33%