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

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

Research output: Contribution to journalArticlepeer-review

75 Scopus citations

Abstract

We report on a test to assess the dynamic brain function at high temporal resolution using magnetoencephalography (MEG). The essence of the test is the measurement of the dynamic synchronous neural interactions, an essential aspect of the brain function. MEG signals were recorded from 248 axial gradiometers while 142 human subjects fixated a spot of light for 45-60 s. After fitting an autoregressive integrative moving average (ARIMA) model and taking the stationary residuals, all pairwise, zero-lag, partial cross-correlations (PCCij0) and their z-transforms (zij 0) between i and j sensors were calculated, providing estimates of the strength and sign (positive, negative) of direct synchronous coupling at 1 ms temporal resolution. We found that subsets of zij0 successfully classified individual subjects to their respective groups (multiple sclerosis, Alzheimer's disease, schizophrenia, Sjögren's syndrome, chronic alcoholism, facial pain, healthy controls) and gave excellent external cross-validation results.

Original languageEnglish (US)
Pages (from-to)349-355
Number of pages7
JournalJournal of neural engineering
Volume4
Issue number4
DOIs
StatePublished - Dec 1 2007

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