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Keywords:

  • Alzheimer's disease;
  • beamformer;
  • correlation analysis;
  • event-related synchronization;
  • frontal cortex;
  • magnetoencephalography;
  • Mini-Mental State Examination

Abstract

  1. Top of page
  2. Abstract
  3. INTRODUCTION
  4. METHODS
  5. RESULTS
  6. DISCUSSION
  7. REFERENCES

Background:  Induced-oscillatory activity is considered a key factor for understanding functional processes in the brain. Magnetoencephalography (MEG) can measure oscillatory activity non-invasively with higher spatial resolution than electroencephalography (EEG). However, MEG has rarely been used to explore functional abnormalities that may represent state markers in patients with Alzheimer's disease (AD).

Methods:  Thirteen patients with early AD and 14 age-matched normal controls participated in the present study. Magnetoencephalography activity was acquired during eyes-open and eyes-closed states. Alpha event-related synchronization (ERS) after eye closing was calculated and its cortical sources superimposed on each individual's magnetic resonance imaging (MRI) scan. The resulting functional image was converted into a Talairach-transformed anatomical brain image and group comparisons were made. We also assessed correlations between cortical ERS sources showing significant between-group differences in alpha activity and external clinical parameters, especially measures of cognitive function.

Results:  The averaged alpha ERS after eye closing appeared dominantly in posterior brain regions in both patients with AD and healthy controls. However, there was a significant increase in alpha ERS in frontal regions, maximal over the prefrontal cortex, in patients with AD relative to controls, indicating a frontal shift of the posterior dominant MEG alpha rhythm in AD patients. This frontal ERS source in the alpha band was negatively correlated with Mini-Mental State Examination scores in the AD patient group.

Conclusions:  The findings indicate that a frontal shift of alpha ERS elicited by an eyes-open/eyes-closed paradigm may be an early brain electromagnetic change in patients with AD, probably representing a physiological state marker of the disease. Furthermore, the results confirm that the beamformer with group comparison analysis is a useful tool with which to explore functional processes in the brain, as indicated by oscillatory activity changes.


INTRODUCTION

  1. Top of page
  2. Abstract
  3. INTRODUCTION
  4. METHODS
  5. RESULTS
  6. DISCUSSION
  7. REFERENCES

Alzheimer's disease (AD) is the most common neurodegenerative disorder; it is characterized mainly by cognitive and intellectual deficits. Electroencephalography (EEG) has long been used as a diagnostic tool in AD.1–3 Several EEG patterns of brain oscillatory activity have been reported in AD, including a slowing and diffusing of the posterior dominant alpha activity, an unclear alpha attenuation after eye opening, and an increase in delta and theta, as well as a decrease in beta and gamma, activities in certain cortical regions.1,2,4 However, in patients with early AD in particular, it is sometimes difficult to visualize these typical EEG findings.1,2 Although magnetoencephalography (MEG) measures neural activity non-invasively with higher spatial resolution than EEG, little has been reported regarding MEG abnormalities in patients with AD. Most of these studies have used a single dipole fitting,4,5 quantitative methods (e.g. frequency analysis approach),6 or connectivity analysis7 to explore brain abnormalities in AD.

Recently, with the advent of advanced time–frequency analysis, there interest has increased with regard to applying spatial filtering methods to analyze MEG data in several psychiatric and neurological disorders, including AD.8–10 In particular, the beamformer, one of the spatial filtering methods, has given us an important insight into the dynamics of oscillatory activity in the brain.11–14 We successfully used the beamformer for cortical mapping of source power changes after eye closing in patients with mild cognitive impairment (MCI) and AD, and found increased alpha event-related synchronization (ERS) in frontal regions specifically when comparing patients with early AD with healthy controls.15 However, it is not clear whether this frontal shift of MEG alpha activity in the eyes closed state could be considered as an indicator of the degree of cognitive impairment in patients with AD, thus representing a state effect of the disease. In the present study, we aimed to determine possible correlations between changes in alpha oscillatory activity after eye closing and measures of cognitive function in patients with early AD and healthy controls.

METHODS

  1. Top of page
  2. Abstract
  3. INTRODUCTION
  4. METHODS
  5. RESULTS
  6. DISCUSSION
  7. REFERENCES

Thirteen patients with early AD and 14 age-matched normal controls were enrolled in the study. All AD patients were recruited from the outpatient clinic of the Department of Psychiatry at Osaka University Hospital. The study was performed in accordance with the Declaration of Helsinki and was approved by the hospital's Ethics Committee. Written informed consent was obtained from all participants. A diagnosis of probable AD was established according to the National Institute of Neurological and Communicative Disorders and Stroke/the Alzheimer's Disease and Related Disorders Association (NINCDS-ADRDA) criteria.16 The normal controls were healthy volunteers who had neither cognitive disturbances nor a history of neurological or psychiatric disorders. Both patients and controls were not taking any medication that may have affected the central nervous system at the time of recruitment and all subjects underwent brain magnetic resonance imaging (MRI) screening to exclude organic lesions. In order to assess cognitive function, the Mini-Mental State Examination (MMSE)17 was performed on all patients and controls. In addition, the Alzheimer's Disease Assessment Scale-cognitive subscale (ADAS-J cog)18 and the Clinical Dementia Rating (CDR) scale19 were performed on the patients.

The MEG data were recorded using a 64-channel whole-head magnetometer (NeuroSQUID Model 100; VSM Medtech CTF Systems, Port Coquitlam, Canada) in a magnetically shielded room. The MEG signals were digitized at 625 Hz and filtered using a combined 60-Hz notch filter and a 200-Hz low pass filter. During the recording, the participants were seated comfortably with the head positioned in the helmet-shaped Dewar. The localization of the subject's head relative to the sensor array was measured with three coils affixed to the nasion and preauricular points. Participants were asked to alternatively open and close their eyes for 10 s, which resulted in alpha synchronization mainly over occipital channels (Fig. 1). A total of eight trials was collected for each participant. Artifact rejection was performed off-line and all trials containing eye blinks were excluded. Brain Electrical Source Analysis (BESA) software20 was used for source imaging of MEG data in the time-frequency domain. For each epoch, a 1-s MEG data interval in each condition was excluded from analysis to remove eye-blinking artifacts. Therefore, the event-related time frequency spectrum was calculated for a 9-s eyes-closed epoch (target interval) and compared with that of a 9-s eyes-open epoch (baseline interval; Fig. 2). The underlying cortical source was calculated using the Multiple Source Beamformer (MSBF) implemented in BESA (http://www.besa.de, accessed March 2008). This beamformer is a modified version of the linearly constrained minimum variance vector beamformer in the time-frequency domain, as described by Gross et al.21 The beamformer images were superimposed on the individual's brain MRI. This results in functional three-dimensional (3D) images that reveal the locations of changes in oscillatory activity (as a percentage) during the target interval relative to the baseline interval. Each acquired 3D image was imported into BrainVoyager QX (http://www.brainvoyager.com, accessed March 2008), transformed into a standardized Talairach brain (Talairach-transformed Montreal Neurological Institute (MNI) T1-weighted brain template; http://www.bic.mni.mcgill.ca, accessed March 2008), and superimposed on a standard anatomical brain image. BrainVoyager QX,22 originally developed for functional magnetic resonance imaging (fMRI) analysis, has been applied successfully to MEG data9,15 because it allows us to import data from BESA software to perform statistical analysis of functional 3D images between groups. The averaged ERS of alpha activity was calculated for each group. Statistical group comparisons of 3D images and clinical variables were performed using unpaired, two-tailed t-test. The Chi-squared test was performed for independence of group and gender. For correlation of cortical sources of oscillatory activity changes with external clinical variables, especially with measures of cognitive function, the coordinates at the voxel with t-maxima (peak ERS value) at locations with significant alpha activity changes in the statistical maps were obtained. Then, the value at these coordinates in each individual's functional 3D image was determined for further analysis using Pearson's correlation coefficient. Data are given as the mean±SD and the level of significance was set at P < 0.05.

image

Figure 1. Magnetoencephalography (MEG) waveforms of an example trial during eyes open and eyes closed conditions in one normal control. Only channels over the posterior regions are shown. Alpha synchronization can be seen during the eyes closed condition.

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image

Figure 2. Time-frequency plot for a magnetoencephalography (MEG) channel overlying the occipital region in one normal control. The vertical line indicates the time of eye closing (change from the eyes open to the eyes closed condition). In the spectrogram, the x-axis denotes the time relative to the beginning of eyes closed condition (in s) and the y-axis denotes the frequency of oscillatory activity (Hz). Sustained alpha event-related synchronization can be seen after eye closing.

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RESULTS

  1. Top of page
  2. Abstract
  3. INTRODUCTION
  4. METHODS
  5. RESULTS
  6. DISCUSSION
  7. REFERENCES

The demographic and clinical characteristics of patients with early AD and healthy controls are given in Table 1. There was no significant between-group difference in age and sex. Analysis of the results from neuropsychological tests revealed that patients with AD had a significantly lower MMSE scores compared with the control group. The peak frequency of alpha activity, as calculated by Fast Fourier Transform, was 9.3 ± 1.0 Hz in AD patients and 10.8 ± 1.3 Hz in controls. These findings indicate that neither patients nor controls showed slowing of the basic alpha rhythm.

Table 1.  Demographic and clinical characteristics of the patients with Alzheimer's disease and normal controls
 Early AD (n = 13)Healthy controls (n = 14)
  1. Unless noted otherwise, data are presented as the mean ± SD. **P < 0.001 compared with patients with AD (Alzheimer's disease).

  2. MMSE, Mini-Mental State Examination; ADAS-cog, Alzheimer's Disease Assessment Scale-cognitive subscale; CDR, Clinical Dementia Rating scale.

Age (years)75.6 ± 5.071.2 ± 6.8
Sex (F/M)9/48/6
MMSE score22.1 ± 2.628.6 ± 1.5**
ADAS-cog14.3 ± 3.3 
CDR score0.8 ± 0.2 

The averaged alpha ERS appeared dominantly in posterior regions in the two groups (Figs 3,4). Compared with controls, patients with AD showed significantly increased alpha ERS in a broader area involving the bilateral frontal cortex, which was maximal over the right superior frontal gyrus (t > 2.30, P < 0.05; Fig. 5).

image

Figure 3. Multiple source beamformer analysis of alpha frequency band in one normal control. Color-coded maps show a posterior dominant alpha rhythm. P, posterior; A, anterior; L, left; R, right.

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image

Figure 4. Averaged event-related synchronization of alpha activity in patients with Alzheimer's disease (AD) and normal controls (NC).

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image

Figure 5. Group comparison of alpha event-related synchronization sources between patients with Alzheimer's disease (AD) and normal controls (NC) using BrainVoyager QX (http://www.brainvoyager.com, accessed March 2008). The color maps show cortical regions with significant between-group differences in alpha activity (threshold: t > 2.30; P < 0.05). TRA, transverse; SAG, sagittal; COR, coronal.

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Correlation analysis of peak alpha ERS and clinical parameters and cognitive function measures indicated that, in the patient group, the MMSE score was negatively correlated with alpha ERS in the right prefrontal area, where significant between-group differences in oscillatory activity were found (r = −0.697, P < 0.001; Fig. 6). No significant correlation was observed between alpha ERS source in the frontal cortex and ADAS-J cog or CDR.

image

Figure 6. Correlation analysis between the peak alpha event-related synchronization (ERS) value (t-maxima) in the right prefrontal area and Mini-Mental State Examination (MMSE) scores in patients with Alzheimer's disease (AD; ●) and normal controls (○). A significant negative correlation was found for the AD patients (ρ = −0.697; P < 0.001).

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DISCUSSION

  1. Top of page
  2. Abstract
  3. INTRODUCTION
  4. METHODS
  5. RESULTS
  6. DISCUSSION
  7. REFERENCES

In the present study, changes in alpha oscillatory activity after eye closing were assessed in patients with early AD and age-matched healthy control subjects using MEG-beamformer and BrainVoyager for group comparisons. In addition, correlation analysis was performed between neural activity in cortical regions showing significant between-group differences and clinical parameters, including measures of cognitive function. Our findings revealed that although the averaged alpha ERS after eye closing appeared dominantly in posterior brain regions in both AD patients and healthy controls, there was increased alpha synchronization in frontal regions in AD patients, maximal over the right prefrontal cortex. Interestingly, this frontal ERS source in alpha band was negatively correlated with MMSE scores.

Eye opening/eye closing is deemed a simple task that induces modulation of EEG/MEG power. It is known that alpha reactivity or suppression during eye opening tends to decrease in several neurological disorders, including dementia.23 Hence, the fact that the averaged alpha ERS in AD patients and healthy controls had a similar pattern was an unexpected finding. This could be related to the existence of a slight difference in the degree of cognitive impairment between patients and controls, stemming from the enrollment of AD patients in the early stages of the disease, as indicated by the peak frequency of MEG alpha activity and the MMSE and CDR scores. The finding of a frontal shift of alpha ERS after eye closing characterizing patients with early AD in our study is consistent with previous EEG investigations reporting that anterior shift of alpha activity sources allowed for discrimination between patients with AD and those with MCI and healthy controls, despite the presence of decreased EEG alpha global field power in patients with AD.24

A striking finding with clinical implication is that the region with maximal alpha ERS in the frontal lobe, namely the right prefrontal cortex, showed a significant negative correlation with MMSE scores. This demonstrates an association of a frontal shift of the posterior alpha activity with cognitive impairment in AD. Thus, this abnormal oscillatory activity in frontal regions may represent a state effect of the disease. Recent evidence from a study of the functional significance of the frontal shift of event-related potential (ERP) amplitude with increasing age indicating that the elderly with most anterior distribution of neural activity showed the poorest recognition memory performance provides further support for our findings.25 Others have reported frontal shift of cortical activity as a positive change in response to pharmacotherapy rather than an abnormal phenomenon following the administration of atypical antipsychotic drugs.26 Surprisingly, unlike the MMSE, other measures of cognitive function, in particular the ADAS-J cognitive subscale and the CDR scale, were not correlated with the significant alpha ERS in the prefrontal cortex of patients with early AD. Although we do not have a clear explanation for this finding, it may indicate a higher sensitivity of the MMSE compared with the other two scales for the detection of early neurophysiological changes, such as abnormal alpha synchronization patterns in patients with AD.

In summary, the overall findings of the present study indicate that a frontal shift of alpha ERS may represent an early brain electromagnetic change in AD and suggest that a resting eyes open/eyes closed paradigm may elicit changes in alpha oscillatory power that could represent candidate physiological markers for this disorder. Moreover, our findings demonstrate that MEG-beamformer and group comparison analysis are useful tools with which to explore functional processes in the brain, as indicated by source-power changes in oscillatory activity. Further neurophysiological investigations will be required to confirm these findings.

REFERENCES

  1. Top of page
  2. Abstract
  3. INTRODUCTION
  4. METHODS
  5. RESULTS
  6. DISCUSSION
  7. REFERENCES
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