Title :
Genetic algorithms for neuromagnetic source reconstruction
Author :
Lewis, Paul S. ; Mosher, John C.
Author_Institution :
Eng. Sci. and Appl. Div., Los Alamos Nat. Lab., NM, USA
Abstract :
Neuromagnetic source reconstruction is the process of deducing internal brain currents from the external magnetic fields they produce. Brain currents are the result of neural activity and a map of their distribution corresponds to a functional image of the brain. In this paper the reconstruction is formulated as an underdetermined linear inverse problem to which a minimal source solution is sought. The minimal source solution is defined by the minimization of a hybrid metric that accounts for both the sparseness of the reconstruction and its compatibility with the measured magnetic field. Genetic algorithms are employed as a robust means of computing this minimal source reconstruction
Keywords :
bioelectric phenomena; genetic algorithms; inverse problems; magnetoencephalography; brain functional image; external magnetic fields; hybrid metric minimization; internal brain currents deduction; minimal source solution; neural activity; neuromagnetic source reconstruction; reconstruction sparseness; underdetermined linear inverse problem; Genetic algorithms; High-resolution imaging; Image reconstruction; Image resolution; Laboratories; Magnetic analysis; Magnetic field measurement; Magnetic fields; Magnetic heads; Magnetic resonance imaging;
Conference_Titel :
Acoustics, Speech, and Signal Processing, 1994. ICASSP-94., 1994 IEEE International Conference on
Conference_Location :
Adelaide, SA
Print_ISBN :
0-7803-1775-0
DOI :
10.1109/ICASSP.1994.389474