TY - JOUR
T1 - Canonical correlation analysis of synchronous neural interactions and cognitive deficits in Alzheimer's dementia
AU - Karageorgiou, Elissaios
AU - Lewis, Scott M.
AU - McCarten, J. Riley
AU - Leuthold, Arthur C.
AU - Hemmy, Laura S.
AU - McPherson, Susan E.
AU - Rottunda, Susan J.
AU - Rubins, David M.
AU - Georgopoulos, Apostolos P.
N1 - Copyright:
Copyright 2013 Elsevier B.V., All rights reserved.
PY - 2012/10
Y1 - 2012/10
N2 - In previous work (Georgopoulos et al 2007 J. Neural Eng. 4 349-55) we reported on the use of magnetoencephalographic (MEG) synchronous neural interactions (SNI) 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 and cognitive neuropsychological (NP) domains in AD patients. First, we performed individual correlations between each SNI and each NP, which provided an initial link between SNI and specific cognitive tests. Next, we performed factor analysis on each set, followed by a canonical correlation analysis between the derived SNI and NP factors. This last analysis optimally associated the entire MEG signal with cognitive function. The results revealed that SNI 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 and set the basis for identifying specific neural disease phenotypes according to cognitive deficits.
AB - In previous work (Georgopoulos et al 2007 J. Neural Eng. 4 349-55) we reported on the use of magnetoencephalographic (MEG) synchronous neural interactions (SNI) 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 and cognitive neuropsychological (NP) domains in AD patients. First, we performed individual correlations between each SNI and each NP, which provided an initial link between SNI and specific cognitive tests. Next, we performed factor analysis on each set, followed by a canonical correlation analysis between the derived SNI and NP factors. This last analysis optimally associated the entire MEG signal with cognitive function. The results revealed that SNI 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 and set the basis for identifying specific neural disease phenotypes according to cognitive deficits.
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U2 - 10.1088/1741-2560/9/5/056003
DO - 10.1088/1741-2560/9/5/056003
M3 - Article
C2 - 22871558
AN - SCOPUS:84865955790
SN - 1741-2560
VL - 9
JO - Journal of neural engineering
JF - Journal of neural engineering
IS - 5
M1 - 056003
ER -