A Study of Dementia by Linear and Nonlinear Analyses of Electroencephalography and Electrocardiography
Date Issued
2010
Date
2010
Author(s)
Lin, Pei-Feng
Abstract
Introduction
The load of caring for demented patients is increasing globally very fast as eighty million demented population is expected in 2040. Alzheimer’s disease (AD) and vascular dementia (VD) are the two major causes of dementia. Since all current therapies for dementia depend on early diagnoses, risk and predicative factors for dementia are crucial. AD and VD share common risk factors as aging and vascular risks such as diabetes, hypertension, metabolic syndrome, homocystinemia, atrial fibrillation, and smoking. There are bidirectional connections between the heart and the brain. A neurovisceral integration model with laterality on the right prefrontal cortex was proposed to describe the pathways.
EEG and EKG are nonstationary and nonlinear signals. The traditional Fourier spectrum is too coarse and fails to represent instantaneous changes. Nonstaionary but linear methods such as Wigner-Ville distribution and Wavelet have other drawbacks that hinder its adaptivity to ever-changing signals. Methods based on theories of chaos, fractal and entropy, quantifying either similarity, disorder, or stability, are suitable for nonlinear but stationary data. The Hilbert–Huang transform(HHT) on the other hand, is adaptive to nonlinear and nonstationary signals. The advantages of the HHT over traditional Fourier-based methods have been appreciated in many studies of different physiological systems.
The study of heart rate variability (HRV), namely the variability of RR intervals (RRI), which reflects depolarization of the sinoatrial node, can monitor the autonomic system. The cholinergic deficits in the brain of dementia may affect the central autonomic network. Yet the HRV changes in dementia in previous reports were not congruent. A higher risk of dementia was shown in people with obstructive sleep apnea, which could be indicated by some newly developed methods of HRV analysis.
Understanding how functional interactions among different brain regions are crucial to the study of higher cortical functions. The cross correlation and coherence analysis are two of the classical methodologies of linear approach. While the synchronization likelihood, which calculates the probability of similarity between two signals in phase space is a nonlinear approach. From synchronization to the execution of particular tasks of the brain, there hide still many puzzles such as ‘binding problem’.
Social participation, exercise, smoking, and alcohol drinking may affect cognitive performance, while water intake insufficiency has yet to be proved.
Methods
This is a hospital-based, case control, and observational study with prospective follow-up of two groups (dementia and control). Various neuro-psychological and motility tests were performed in all subjects. As vascular risks are important in both types of dementia, carotid echosonography was also taken for each subject. Life style and eating behaviors were also compared. Both linear and nonlinear methods such as short time Fourier transform, spectral coherence, Hilbert Hung transform (HHT), multiscale entropy (MSE), and synchronization likelihood (SL) were performed for EEG signals. Heart rate variability was calculated individually in both awake and sleep EKG signals with linear analysis and MSE.
Results and Discussions
The demented group consists of 60 subjects (female/male=30/30, age 80.5±5.6, VD/AD=37/23, MMSE=19.8±6.9), while the control group consists of 29 subjects (female/male=13/16. age 75.3±6.4, MMSE=28.4±0.9).
Significant findings are as following: 1. The cross correlation coefficients of data decomposed by HHT suggest that the brain functions in a more holistic manner. 2. The phenomenon of ‘Vagal dominance during sleep’ was only shown in the demented group. 3. The values of all scales of MSE from a wide range of electrodes are positively correlated with scores of mental abilities or mobility. 4. The MSE of RRI showed no correlation to mental capacities, but it had significantly negative correlations to the MSE of EEG in multiple area. Interestingly, the EEGs of closed-eye resting were associated to the RRIs during the awake state, while the EEGs of photic stimulation were mostly associated to the RRIs during sleep. 5. The photic stimulation yielded the most copious results. 6. Word list, clock drawing, trail making, and number transcoding tests had better differentiating power than MMSE. 7. Subjects with positive Glabellar signs had a lower LF/HF during awake state. 8. Diabetic subjects had lower HF and LF during sleep, and HF during awake state. 9. There was no correlation among the severity of carotid atherosclerosis to either mental capacities, parameters of EEG or parameters of EKG. 10. EEG of Dementia showed loss of coupling, complexity and stationarity
Prospect
A community based design with long time following is the next plan. It aims at risk factors and markers for early diagnosis by the analysis of EEG. Therapy monitoring by EEG is an ongoing study with some promising primitive results. The cross-talk between the brain and the heart could be further explored noninvasively by the information hidden in EKG and EEG.
Key words: dementia, EKG, EEG, functional couplings, linear /nonlinear analysis, Multiscale Entropy, Hilbert- Huang Transformation
Subjects
dementia
EKG
EEG
functional couplings
linear /nonlinear analysis
Multiscale Entropy
Hilbert- Huang Transformation
SDGs
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