Synchronous neural interactions assessed by magnetoencephalography: a functional biomarker for brain disorders

Georgopoulos, Apostolos P.; Karageorgiou, Elissaios; Leuthold, Arthur C.; Lewis, Scott M.; Lynch, Joshua; Alonso, Aurelio; Aslam, Zaheer; Carpenter, Adam F.; Georgopoulos, Angeliki; Hemmy, Laura S; Koutlas, Ioannis G.; Langheim, Frederick J. P.; McCarten, J. Riley; McPherson, Susan; Pardo, José V.; Pardo, Patricia J.; Parry, Gareth; Rottunda, Susan; Segal, Barbara; Sponheim, Scott R.; Stanwyck, John J.; Stephane, Massoud; Westermeyer, Joseph

doi:10.1088/1741-2560/4/4/001

Cited by 96 publications

(108 citation statements)

References 18 publications

(26 reference statements)

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“…We then used a stepwise linear discriminant analysis (17) to test how well patterns of MEG signals could classify periods of motion perception. To do this, we used the mean MEG signals from the epochs described above.…”

Section: Methodsmentioning

confidence: 99%

Differential brain activity states during the perception and nonperception of illusory motion as revealed by magnetoencephalography

Crowe¹,

Leuthold²,

Georgopoulos³

2010

Proc. Natl. Acad. Sci. U.S.A.

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We studied visual perception using an annular random-dot motion stimulus called the racetrack. We recorded neural activity using magnetoencephalography while subjects viewed variants of this stimulus that contained no inherent motion or various degrees of embedded motion. Subjects reported seeing rotary motion during viewing of all stimuli. We found that, in the absence of any motion signals, patterns of brain activity differed between states of motion perception and nonperception. Furthermore, when subjects perceived motion, activity states within the brain did not differ across stimuli of different amounts of embedded motion. In contrast, we found that during periods of nonperception brainactivity states varied with the amount of motion signal embedded in the stimulus. Taken together, these results suggest that during perception the brain may lock into a stable state in which lowerlevel signals are suppressed.racetrack illusion | visual motion perception

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Section: Methodsmentioning

confidence: 99%

Differential brain activity states during the perception and nonperception of illusory motion as revealed by magnetoencephalography

Crowe¹,

Leuthold²,

Georgopoulos³

2010

Proc. Natl. Acad. Sci. U.S.A.

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“…The results prove that our method is comparable with other methods in this area. In order to prove the effectiveness and compatibility of the proposed method, we have compared the proposed method with several state-of-the-art methods including, Ford et al [26], Pokrajac et al [27], and Georgopoulos et al [28] methods, and the results are shown in table 3. …”

Section: Case Number Diagnosismentioning

confidence: 99%

Feature selection using genetic algorithm for classification of schizophrenia using fMRI data

Shahamat

Pouyan

2015

JAIDM

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In this paper we propose a new method for classification of subjects into schizophrenia and control groups using functional magnetic resonance imaging (fMRI) data. In the preprocessing step, the number of fMRI time points is reduced using principal component analysis (PCA). Then, independent component analysis (ICA) is used for further data analysis. It estimates independent components (ICs) of PCA results. For feature extraction, local binary patterns (LBP) technique is used for the ICs. It transforms the ICs into spatial histograms of LBP values. For feature selection, the genetic algorithm (GA) is used to obtain a set of features with large discrimination power. In the next step of feature selection, linear discriminant analysis (LDA) is used for further extract features that maximize the ratio of between-class and within-class variability. Finally, a test subject is classified into schizophrenia or control group using a Euclidean distance based classifier and a majority vote method. In this paper, a leave-one-out cross validation method is used for performance evaluation. Experimental results prove that the proposed method has an acceptable accuracy.

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“…However, given the prevalence of ASD, the potential benefits of using MEG as a screening tool to allow early identification of the illness make the technique a valuable one. Georgopoulos et al (2007) made MEG recordings from 142 individuals whilst they fixated on a spot of light for 45-60 seconds. The analysis stream utilised the sensor information and assessed zero-lag cross-correlations in order to provide an estimate of synchronous coupling.…”

Section: Future Applicationsmentioning

confidence: 99%

Past, Current and Future Clinical Applications of MEG

Prendergast¹

2011

Magnetoencephalography

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Synchronous neural interactions assessed by magnetoencephalography: a functional biomarker for brain disorders

Cited by 96 publications

References 18 publications

Differential brain activity states during the perception and nonperception of illusory motion as revealed by magnetoencephalography

Differential brain activity states during the perception and nonperception of illusory motion as revealed by magnetoencephalography

Feature selection using genetic algorithm for classification of schizophrenia using fMRI data

Past, Current and Future Clinical Applications of MEG

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