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