Evidence of biochemical and biomagnetic interactions in Alzheimer's disease: an MEG and MR spectroscopy study

An Overview of ICA/BSS-Based Application to Alzheimer's Brain Signal Processing

Alzheimer's disease (AD) is by far the most common cause of dementia associated with aging. Early and accurate diagnosis of AD and ability to track progression of the disease is increasingly important as potential disease-modifying therapies move through clinical trials. With the advent of biomedical techniques, such as computerized tomography (CT), electroencephalography (EEG), magnetoencephalography (MEG), positron emission tomography (PET), magnetic resonance imaging (MRI), and functional magnetic resonance imaging (fMRI), large amounts of data from Alzheimer's patients have been acquired and processed from which AD-related information or "signals" can be assessed for AD diagnosis. It remains unknown how best to mine complex information from these brain signals to aid in early diagnosis of AD. An increasingly popular technique for processing brain signals is independent component analysis or blind source separation (ICA/BSS) that separates blindly observed signals into original signals that are as independent as possible. This overview focuses on ICA/BSS-based applications to AD brain signal processing.

A Comprehensive Review of Magnetoencephalography (MEG) Studies for Brain Functionality in Healthy Aging and Alzheimer's Disease (AD)

Neural oscillations were established with their association with neurophysiological activities and the altered rhythmic patterns are believed to be linked directly to the progression of cognitive decline. Magnetoencephalography (MEG) is a non-invasive technique to record such neuronal activity due to excellent temporal and fair amount of spatial resolution. Single channel, connectivity as well as brain network analysis using MEG data in resting state and task-based experiments were analyzed from existing literature. Single channel analysis studies reported a less complex, more regular and predictable oscillations in Alzheimer's disease (AD) primarily in the left parietal, temporal and occipital regions. Investigations on both functional connectivity (FC) and effective (EC) connectivity analysis demonstrated a loss of connectivity in AD compared to healthy control (HC) subjects found in higher frequency bands. It has been reported from multiplex network of MEG study in AD in the affected regions of hippocampus, posterior default mode network (DMN) and occipital areas, however, conclusions cannot be drawn due to limited availability of clinical literature. Potential utilization of high spatial resolution in MEG likely to provide information related to in-depth brain functioning and underlying factors responsible for changes in neuronal waves in AD. This review is a comprehensive report to investigate diagnostic biomarkers for AD may be identified by from MEG data. It is also important to note that MEG data can also be utilized for the same pursuit in combination with other imaging modalities.

Alzheimer's disease: The state of the art in resting-state magnetoencephalography

Alzheimer's disease (AD) is accompanied by functional brain changes that can be detected in imaging studies, including electromagnetic activity recorded with magnetoencephalography (MEG). Here, we systematically review the studies that have examined resting-state MEG changes in AD and identify areas that lack scientific or clinical progress. Three levels of MEG analysis will be covered: (i) single-channel signal analysis, (ii) pairwise analyses over time series, which includes the study of interdependencies between two time series and (iii) global network analyses. We discuss the findings in the light of other functional modalities, such as electroencephalography (EEG) and functional magnetic resonance imaging (fMRI). Overall, single-channel MEG results show consistent changes in AD that are in line with EEG studies, but the full potential of the high spatial resolution of MEG and advanced functional connectivity and network analysis has yet to be fully exploited. Adding these features to the current knowledge will potentially aid in uncovering organizational patterns of brain function in AD and thereby aid the understanding of neuronal mechanisms leading to cognitive deficits.

Complex network analysis of resting state EEG in amnestic mild cognitive impairment patients with type 2 diabetes

Purpose: Diabetes is a great risk factor for dementia and mild cognitive impairment (MCI). This study investigates whether complex network-derived features in resting state EEG (rsEEG) could be applied as a biomarker to distinguish amnestic mild cognitive impairment (aMCI) from normal cognitive function in subjects with type 2 diabetes (T2D).

Method: In this study, EEG was recorded in 28 patients with T2D (16 aMCI patients and 12 controls) during a no-task eyes-closed resting state. Pair-wise synchronization of rsEEG signals were assessed in six frequency bands (delta, theta, lower alpha, upper alpha, beta, and gamma) using phase lag index (PLI) and grouped into long distance (intra- and inter-hemispheric) and short distance interactions. PLI-weighted connectivity networks were also constructed, and characterized by mean clustering coefficient and path length. The correlation of these features and Montreal Cognitive Assessment (MoCA) scores was assessed.

Results: Main findings of this study were as follows: (1) In comparison with controls, patients with aMCI had a significant decrease of global mean PLI in lower alpha, upper alpha, and beta bands. Lower functional connection at short and long intra-hemispheric distance mainly appeared on the left hemisphere. (2) In the lower alpha band, clustering coefficient was significantly lower in aMCI group, and the path length significantly increased. (3) Cognitive status measured by MoCA had a significant positive correlation with cluster coefficient and negative correlation with path length in lower alpha band.

Conclusions: The brain network of aMCI patients displayed a disconnection syndrome and a loss of small-world architecture. The correlation between cognitive states and network characteristics suggested that the more in deterioration of the diabetes patients' cognitive state, the less optimal the network organization become. Hence, the complex network-derived biomarkers based on EEG could be employed to track cognitive function of diabetic patients and provide a new diagnosis tool for aMCI.

Structural and functional patterns in healthy aging, mild cognitive impairment, and Alzheimer disease

The aim of this study was to analyze the combined contribution of magnetic resonance imaging and magnetoencephalography (MEG) to the diagnosis of mild cognitive impairment (MCI) and AD. To whole-head MEG recordings were obtained from three diagnosis groups: Alzheimer disease (AD), MCI, and control. Magnetic resonance imaging volumetric data of global brain, temporal lobe, and hippocampal volumes, were also obtained. Results indicated that a reduction of volume in the hippocampal structure allowed the discrimination between AD and MCI patients as compared with controls. The percentage of correct classification was 91.3% when AD versus controls was compared, and 83.3% when we compared MCI versus control. MEG data showed that AD patients exhibit higher theta and delta activity than MCI and controls. Such higher activity was significant in parietal, temporal, and occipital areas. Left parietal theta classified controls versus MCIs with 78.3% rate of correct classification. Right occipital theta and the left parietal delta allowed the discrimination of controls versus ADs, with 81.8% rate of correct classification. Left parietal theta discriminated between ADs and MCIs with 56.6% rate of correct classification. In addition, the combination of both techniques significantly improved the rate of correct classification, thus indicating that a multidisciplinary perspective of techniques may improve the diagnostic capabilities.

Biomagnetic profiles of verbal memory success in patients with mesial temporal lobe epilepsy

The risk of cognitive decline after mesial temporal lobe (MTL) resection in the dominant hemisphere for treatment of epilepsy has been assessed with the intracarotid amytal procedure and functional neuroimaging. In this study we used magnetoencephalography (MEG) to analyze memory profiles in patients with left hippocampal sclerosis (HS). Biomagnetic brain activity related to successful memory was compared in nine patients with left HS and nine age-matched controls. Patients manifested a higher number of activity sources over the right inferior parietal lobe in the late portion of the time window, and higher activity in the right than in the left MTL between 400 and 800 ms. This was reinforced by a -0.46 MTL laterality index, which indicates right MTL dominance. Controls showed a higher number of dipoles in the left anterior ventral prefrontal region, between 400 and 600 ms, and in the left MTL across the whole time window. Three patients who underwent a left temporal lobectomy, were seizure free, and who did not exhibit memory impairment after left temporal lobectomy, showed no activity in the left MTL presurgically. These results could support the ability of MEG to describe the time-modulated brain activity related to memory success in patients with epilepsy with left HS.

Use of magnetoencephalography (MEG) to study functional brain networks in neurodegenerative disorders

The pathophysiological mechanisms underlying clinical symptoms in neurodegenerative disorders such as Parkinson's disease (PD) and Alzheimer's disease (AD) are incompletely understood. Magnetoencephalography (MEG) is a relatively new functional neuroimaging technique, which allows the simultaneous recording of the brain's magnetic activity from large arrays of sensors covering the whole head. MEG studies in PD and AD have identified characteristic patterns of abnormal oscillatory activity in different frequency bands. Furthermore, MEG studies aimed at the characterization of distributed functional networks have demonstrated distinct patterns of abnormal connectivity in demented and non-demented PD, as well as in AD. In PD abnormal oscillatory activity and disturbed connectivity may respond differently to dopaminergic treatment. Further studies in this field could benefit from new technological developments such as ultra low field MRI and from the application of a well-defined theoretical framework such as graph theory to the study of disturbed brain networks.

Modulation of medial temporal lobe activity in epilepsy patients with hippocampal sclerosis during verbal working memory

It has been traditionally assumed that medial temporal lobe (MTL) is not required for working memory (WM). However, animal lesion and electrophysiological studies and human neuropsychological and neuroimaging studies have provided increasing evidences of a critical involvement of MTL in WM. Based on previous findings, the central aim of this study was to investigate the contribution of the MTL to verbal WM encoding. Here, we used magnetoencephalography (MEG) to compare the patterns of MTL activation of 9 epilepsy patients suffering from left hippocampal sclerosis with those of 10 healthy matched controls while they performed a verbal WM task. MEG recordings allow detailed tracking of the time course of MTL activation. We observed impaired WM performance associated with changes in the dynamics of MTL activity in epilepsy patients. Specifically, whereas patients showed decreased activity in damaged MTL, activity in the contralateral MTL was enhanced, an effect that became significant in the 600- to 700-ms interval after stimulus presentation. These findings strongly support the crucial contribution of MTL to verbal WM encoding and provide compelling evidence for the proposal that MTL contributes to both episodic memory and WM. Whether this pattern is signaling reorganization or a normal use of a damaged structure is discussed.

Magnetic resonance spectroscopy performance for detection of dementia, Alzheimer's disease and mild cognitive impairment in a community-based survey

BACKGROUND/AIMS

To evaluate (1)H-labelled magnetic resonance spectroscopy (MRS) in patients with a low Mini Mental State Examination (MMSE) score identified during a dementia community-based survey.

METHODS

A population sample of 1,500 individuals (>64 years old) was randomly selected. Two hundred and fifteen individuals (MMSE < or =24) were sorted into clinical groups: dementia, Alzheimer's disease, mild cognitive impairment (MCI), normal. Up to 56 of these individuals attended the MRS appointment. Two single-voxel sequences (TR 1,500, TE 35/144 ms) were carried out in the posterior cingulate gyrus of each individual, and the ratios N-acetylaspartate (NAA)/creatine (Cr), choline (Cho)/Cr, myo-inositol (mI)/Cr, NAA/mI and NAA/Cho were compared statistically. The ability of MRS to distinguish clinical groups was assessed by receiver-operating characteristics analysis. Cognition effects on metabolite ratios were estimated, with gender and cognition as categorical variables and age as a continuous covariate.

RESULTS

NAA/Cr and NAA/Cho ratios were lower in dementia or Alzheimer's disease than in MCI and normal groups. The NAA/Cr ratio at TE 35 ms performed best when distinguishing dementia or Alzheimer's disease from non-demented subjects (cut-off point 1.40). MRS could not distinguish between MCI patients and normal subjects. Dementia was an independent predictor of metabolite values.

CONCLUSION

In a population sample, conventional MRS still proved to be a useful tool for dementia discrimination, but it is potentially far less useful as a surrogate marker for MCI.

Magnetoencephalographic evaluation of resting-state functional connectivity in Alzheimer's disease

Statistical interdependencies between magnetoencephalographic signals recorded over different brain regions may reflect the functional connectivity of the resting-state networks. We investigated topographic characteristics of disturbed resting-state networks in Alzheimer's disease patients in different frequency bands. Whole-head 151-channel MEG was recorded in 18 Alzheimer patients (mean age 72.1 years, SD 5.6; 11 males) and 18 healthy controls (mean age 69.1 years, SD 6.8; 7 males) during a no-task eyes-closed resting state. Pair-wise interdependencies of MEG signals were computed in six frequency bands (delta, theta, alpha1, alpha2, beta and gamma) with the synchronization likelihood (a nonlinear measure) and coherence and grouped into long distance (intra- and interhemispheric) and short distance interactions. In the alpha1 and beta band, Alzheimer patients showed a loss of long distance intrahemispheric interactions, with a focus on left fronto-temporal/parietal connections. Functional connectivity was increased in Alzheimer patients locally in the theta band (centro-parietal regions) and the beta and gamma band (occipito-parietal regions). In the Alzheimer group, positive correlations were found between alpha1, alpha2 and beta band synchronization likelihood and MMSE score. Resting-state functional connectivity in Alzheimer's disease is characterized by specific changes of long and short distance interactions in the theta, alpha1, beta and gamma bands. These changes may reflect loss of anatomical connections and/or reduced central cholinergic activity and could underlie part of the cognitive impairment.

Medial temporal lobe neuromagnetic hypoactivation and risk for developing cognitive decline in elderly population: A 2-year follow-up study

Cognition declines as a function of age. However, some elders could develop more severe status such as mild cognitive impairment (MCI). The aim of this study was the early detection of neurophysiological patterns of brain activity that may predict the possibility of certain subjects to develop MCI. Brain magnetic activity was recorded from 15 healthy subjects during a memory task by means of magnetoencephalography. None of the participants could be considered as MCI at the time of the first clinical evaluation. After 2-year follow-up, five subjects developed MCI and 10 maintained their cognitive status across time. The subjects who developed cognitive decline showed a lower number of activity sources in the left medial temporal lobe between 400 and 800 ms after stimulus onset, as compared to the non-cognitive decline group. These findings may help with the early identification of elderly subjects at high risk of cognitive decline, allowing the possibility of neuropsychological or pharmaceutical treatment that delay or prevent the progression of the cognitive impairment.