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Titolo:
Multistart algorithms for MEG empirical data analysis reliably characterize locations and time courses of multiple sources
Autore:
Aine, C; Huang, M; Stephen, J; Christner, R;
Indirizzi:
Vet Adm Med Ctr, Ctr Funct Brain Imaging, Albuquerque, NM 87108 USA Vet Adm Med Ctr Albuquerque NM USA 87108 aging, Albuquerque, NM 87108 USA Univ New Mexico, Sch Med, Dept Radiol, Albuquerque, NM 87131 USA Univ New Mexico Albuquerque NM USA 87131 adiol, Albuquerque, NM 87131 USA Univ New Mexico, Sch Med, Dept Neurol, Albuquerque, NM 87131 USA Univ New Mexico Albuquerque NM USA 87131 eurol, Albuquerque, NM 87131 USA
Titolo Testata:
NEUROIMAGE
fascicolo: 2, volume: 12, anno: 2000,
pagine: 159 - 172
SICI:
1053-8119(200008)12:2<159:MAFMED>2.0.ZU;2-S
Fonte:
ISI
Lingua:
ENG
Soggetto:
MEDIAN NERVE-STIMULATION; HUMAN VISUAL-CORTEX; NEUROMAGNETIC RESPONSES; SOURCE LOCALIZATION; MAGNETIC-FIELDS; BRAIN; ORGANIZATION; MODEL; MAGNETOENCEPHALOGRAPHY; CONNECTIONS;
Keywords:
magnetoencephalography; MEG; functional brain mapping; neuroimaging; modeling; somatosensory; visual cortex;
Tipo documento:
Article
Natura:
Periodico
Settore Disciplinare:
Life Sciences
Citazioni:
41
Recensione:
Indirizzi per estratti:
Indirizzo: Aine, C Vet Adm Med Ctr, Ctr Funct Brain Imaging, 1501 San Pedro Dr SE,Bldg 49 114M, Albuquerque, NM 87108 USA Vet Adm Med Ctr 1501 San Pedro Dr SE,Bldg 49 114M Albuquerque NM USA 87108
Citazione:
C. Aine et al., "Multistart algorithms for MEG empirical data analysis reliably characterize locations and time courses of multiple sources", NEUROIMAGE, 12(2), 2000, pp. 159-172

Abstract

We applied our newly developed Multistart algorithm (M. Huang et al., 1998, Electroencephalogr. Clin. Neurophysiol. 108, 32-44) to high signal-to-noise ratio (SNR) somatosensory responses and low SNR visual data to demonstrate the reliability of this analysis tool for determining source locations and time courses of empirical multisource neuromagnetic data. This algorithmperforms a downhill simplex search hundreds to thousands of times with multiple, randomly selected initial starting parameters from within the head volume, in order to avoid problems of local minima. Two subjects participated in two studies: (1) somatosensory (left and right median nerves were stimulated using a square wave pulse of 0.2 ms duration) and (2) visual (small black and white bull's-eye patterns were presented to central and peripheral locations in four quadrants of the visual held). One subject participatedin both of the studies mentioned above and in a third study (i.e., simultaneous somatosensory/visual stimulation). The best-fitting solutions were tightly clustered in high SNR somatosensory data and all dominant regions of activity could be identified in some instances by using a single model order (e.g., six dipoles) applied to a single interval of time (e.g., 15-250 ms) that captured the entire somatosensory response. In low SNR visual data, solutions were obtained from several different model orders and time intervals in order to capture the dominant activity across the entire visual response (e.g., 60-300 ms). Our results demonstrate that Multistart MEG analysis procedures can localize multiple regions of activity and characterize their time courses in a reliable fashion. Sources for visual data were determined by comparing results across several different models, each of which wasbased on hundreds to thousands of different fits to the data.

ASDD Area Sistemi Dipartimentali e Documentali, Università di Bologna, Catalogo delle riviste ed altri periodici
Documento generato il 29/03/20 alle ore 14:24:26