Canonical correlation analysis of
Synchronous Neural Interactions

Synchronous Neural Interactions (SNI)

Zero-lag partial correlations in pairs of MEG time series and denote the strength and polarity (positive or negative) of neuronal interactions. Anomalies in SNIs as assessed by MEG differentiate psychiatric disorders from healthy brain functioning and can discriminate among various brain diseases. From this research, a highly distinctive, unique PTSD SNI signature characterized by miscommunication of temporal and parietal and/or parieto-occipital right hemispheric areas with other brain areas has emerged. These findings, in addition to the growing research applying MEG to other psychiatric disorders, highlight the utility of MEG in identifying biomarkers of disease and underscore the potential for broader clinical applications of MEG.
and cognitive deficits in Alzheimer's dementia

Journal of Neural Engineering - 2012-08-07Karageorgiou E, Lewis S, McCarten JR, Leuthold A, Hemmy LS, McPherson SE, Rottunda SJ, Rubins D, Georgopoulos AP10.1088/1741-2560/9/5/056003
In previous work (Georgopoulos et al 2007 J. Neural Eng. 4 349-55) we reported on the use of magnetoencephalographic (
Magnetoencephalography

Magnetoencephalography (MEG)

A noninvasive technique that detects magnetic fields above the surface of the head produced by postsynaptic potentials in the brain.
)
Synchronous Neural Interactions

Synchronous Neural Interactions (SNI)

Zero-lag partial correlations in pairs of MEG time series and denote the strength and polarity (positive or negative) of neuronal interactions. Anomalies in SNIs as assessed by MEG differentiate psychiatric disorders from healthy brain functioning and can discriminate among various brain diseases. From this research, a highly distinctive, unique PTSD SNI signature characterized by miscommunication of temporal and parietal and/or parieto-occipital right hemispheric areas with other brain areas has emerged. These findings, in addition to the growing research applying MEG to other psychiatric disorders, highlight the utility of MEG in identifying biomarkers of disease and underscore the potential for broader clinical applications of MEG.
as a functional biomarker in Alzheimer's dementia (AD) diagnosis. Here we report on the application of canonical correlation analysis to investigate the relations between
SNI

Synchronous Neural Interactions (SNI)

Zero-lag partial correlations in pairs of MEG time series and denote the strength and polarity (positive or negative) of neuronal interactions. Anomalies in SNIs as assessed by MEG differentiate psychiatric disorders from healthy brain functioning and can discriminate among various brain diseases. From this research, a highly distinctive, unique PTSD SNI signature characterized by miscommunication of temporal and parietal and/or parieto-occipital right hemispheric areas with other brain areas has emerged. These findings, in addition to the growing research applying MEG to other psychiatric disorders, highlight the utility of MEG in identifying biomarkers of disease and underscore the potential for broader clinical applications of MEG.
and cognitive neuropsychological (NP) domains in AD patients. First, we performed individual correlations between each
SNI

Synchronous Neural Interactions (SNI)

Zero-lag partial correlations in pairs of MEG time series and denote the strength and polarity (positive or negative) of neuronal interactions. Anomalies in SNIs as assessed by MEG differentiate psychiatric disorders from healthy brain functioning and can discriminate among various brain diseases. From this research, a highly distinctive, unique PTSD SNI signature characterized by miscommunication of temporal and parietal and/or parieto-occipital right hemispheric areas with other brain areas has emerged. These findings, in addition to the growing research applying MEG to other psychiatric disorders, highlight the utility of MEG in identifying biomarkers of disease and underscore the potential for broader clinical applications of MEG.
and each NP, which provided an initial link between
SNI

Synchronous Neural Interactions (SNI)

Zero-lag partial correlations in pairs of MEG time series and denote the strength and polarity (positive or negative) of neuronal interactions. Anomalies in SNIs as assessed by MEG differentiate psychiatric disorders from healthy brain functioning and can discriminate among various brain diseases. From this research, a highly distinctive, unique PTSD SNI signature characterized by miscommunication of temporal and parietal and/or parieto-occipital right hemispheric areas with other brain areas has emerged. These findings, in addition to the growing research applying MEG to other psychiatric disorders, highlight the utility of MEG in identifying biomarkers of disease and underscore the potential for broader clinical applications of MEG.
and specific cognitive tests. Next, we performed factor analysis on each set, followed by a canonical correlation analysis between the derived
SNI

Synchronous Neural Interactions (SNI)

Zero-lag partial correlations in pairs of MEG time series and denote the strength and polarity (positive or negative) of neuronal interactions. Anomalies in SNIs as assessed by MEG differentiate psychiatric disorders from healthy brain functioning and can discriminate among various brain diseases. From this research, a highly distinctive, unique PTSD SNI signature characterized by miscommunication of temporal and parietal and/or parieto-occipital right hemispheric areas with other brain areas has emerged. These findings, in addition to the growing research applying MEG to other psychiatric disorders, highlight the utility of MEG in identifying biomarkers of disease and underscore the potential for broader clinical applications of MEG.
and NP factors. This last analysis optimally associated the entire
MEG

Magnetoencephalography (MEG)

A noninvasive technique that detects magnetic fields above the surface of the head produced by postsynaptic potentials in the brain.
signal with cognitive function. The results revealed that
SNI

Synchronous Neural Interactions (SNI)

Zero-lag partial correlations in pairs of MEG time series and denote the strength and polarity (positive or negative) of neuronal interactions. Anomalies in SNIs as assessed by MEG differentiate psychiatric disorders from healthy brain functioning and can discriminate among various brain diseases. From this research, a highly distinctive, unique PTSD SNI signature characterized by miscommunication of temporal and parietal and/or parieto-occipital right hemispheric areas with other brain areas has emerged. These findings, in addition to the growing research applying MEG to other psychiatric disorders, highlight the utility of MEG in identifying biomarkers of disease and underscore the potential for broader clinical applications of MEG.
as a whole were mostly associated with memory and language, and, slightly less, executive function, processing speed and visuospatial abilities, thus differentiating functions subserved by the frontoparietal and the temporal cortices. These findings provide a direct interpretation of the information carried by the
SNI

Synchronous Neural Interactions (SNI)

Zero-lag partial correlations in pairs of MEG time series and denote the strength and polarity (positive or negative) of neuronal interactions. Anomalies in SNIs as assessed by MEG differentiate psychiatric disorders from healthy brain functioning and can discriminate among various brain diseases. From this research, a highly distinctive, unique PTSD SNI signature characterized by miscommunication of temporal and parietal and/or parieto-occipital right hemispheric areas with other brain areas has emerged. These findings, in addition to the growing research applying MEG to other psychiatric disorders, highlight the utility of MEG in identifying biomarkers of disease and underscore the potential for broader clinical applications of MEG.
and set the basis for identifying specific neural disease phenotypes according to cognitive deficits.