Gray and White Matter Voxel-Based Morphometry of Alzheimer's Disease With and Without Significant Cerebrovascular Pathologies.

Alzheimer's disease (AD) is the most common type of dementia, and AD individuals often present significant cerebrovascular disease (CVD) symptomology. AD with significant levels of CVD is frequently labeled mixed dementia (or sometimes AD-CVD), and the differentiation of these two neuropathologies (AD, AD-CVD) from each other is challenging, especially at early stages. In this study, we compared the gray matter (GM) and white matter (WM) volumes in AD (n = 83) and AD-CVD (n = 37) individuals compared with those of cognitively healthy controls (n = 85) using voxel-based morphometry (VBM) of their MRI scans. The control individuals, matched for age and sex with our two dementia groups, were taken from the ADNI. The VBM analysis showed widespread patterns of significantly lower GM and WM volume in both dementia groups compared to the control group (P < .05, family-wise error corrected). While comparing with AD-CVD, the AD group mainly demonstrated a trend of lower volumes in the GM of the left putamen and right hippocampus and WM of the right thalamus (uncorrected P < .005 with cluster threshold, K = 10). The AD-CVD group relative to AD tended to present lower GM and WM volumes, mainly in the cerebellar lobules and right brainstem regions, respectively (uncorrected P < .005 with cluster threshold, K = 10). Although finding a discriminatory feature in structural MRI data between AD and AD-CVD neuropathologies is challenging, these results provide preliminary evidence that demands further investigation in a larger sample size.

Evaluating the Diagnostic Value of Electrovestibulography (EVestG) in Alzheimer's Patients with Mixed Pathology: A Pilot Study.

Background and Objectives: Diagnosis of dementia subtypes caused by different brain pathophysiologies, particularly Alzheimer's disease (AD) from AD mixed with levels of cerebrovascular disease (CVD) symptomology (AD-CVD), is challenging due to overlapping symptoms. In this pilot study, the potential of Electrovestibulography (EVestG) for identifying AD, AD-CVD, and healthy control populations was investigated. Materials and Methods: A novel hierarchical multiclass diagnostic algorithm based on the outcomes of its lower levels of binary classifications was developed using data of 16 patients with AD, 13 with AD-CVD, and 24 healthy age-matched controls, and then evaluated on a blind testing dataset made up of a new population of 12 patients diagnosed with AD, 9 with AD-CVD, and 8 healthy controls. Multivariate analysis was run to test the between population differences while controlling for sex and age covariates. Results: The accuracies of the multiclass diagnostic algorithm were found to be 85.7% and 79.6% for the training and blind testing datasets, respectively. While a statistically significant difference was found between the populations after accounting for sex and age, no significant effect was found for sex or age covariates. The best characteristic EVestG features were extracted from the upright sitting and supine up/down stimulus responses. Conclusions: Two EVestG movements (stimuli) and their most informative features that are best selective of the above-populations' separations were identified, and a hierarchy diagnostic algorithm was developed for three-way classification. Given that the two stimuli predominantly stimulate the otholithic organs, physiological and experimental evidence supportive of the results are presented. Disruptions of inhibition associated with GABAergic activity might be responsible for the changes in the EVestG features.

An unbiased algorithm for objective separation of Alzheimer's, Alzheimer's mixed with cerebrovascular symptomology, and healthy controls from one another using electrovestibulography (EVestG).

Diagnosis of Alzheimer's disease (AD) from AD with cerebrovascular disease pathology (AD-CVD) is a rising challenge. Using electrovestibulography (EVestG) measured signals, we develop an automated feature extraction and selection algorithm for an unbiased identification of AD and AD-CVD from healthy controls as well as their separation from each other. EVestG signals of 24 healthy controls, 16 individuals with AD, and 13 with AD-CVD were analyzed within two separate groupings: One-versus-One and One-versus-All. A multistage feature selection process was conducted over the training dataset using linear support vector machine (SVM) classification with 10-fold cross-validation, k nearest neighbors/averaging imputation, and exhaustive search. The most frequently selected features that achieved highest classification performance were selected. 10-fold cross-validation was applied via a linear SVM classification on the entire dataset. Multivariate analysis was run to test the between population differences while controlling for the covariates. Classification accuracies of ≥ 80% and 78% were achieved for the One-versus-All classification approach and AD versus AD-CVD separation, respectively. The results also held true after controlling for the effect of covariates. AD/AD-CVD participants showed smaller/larger EVestG averaged field potential signals compared to healthy controls and AD-CVD/AD participants. These characteristics are in line with our previous study results.

Baseline Prediction of rTMS efficacy in Alzheimer patients.

Repetitive transcranial magnetic stimulation (rTMS) with extensive 2-6-week protocols are applied to improve cognition and/or slow the cognitive decline seen in Alzheimer's Disease (AD). To date, there are no means to predict the response of a patient to rTMS treatment at baseline. Electrovestibulography (EVestG) biomarkers can be used to predict, at baseline, the efficacy of rTMS when applied to AD individuals. In a population of 27 AD patients (8 with significant cerebrovascular symptomatology, labelled ADcvd) EVestG signals were measured before and after rTMS treatment, and then compared with 16 age-matched healthy controls. MoCA was measured at baseline, whilst ADAS-Cog was the primary outcome measure. AD severity and comorbid cerebrovascular disease were treated as covariates. Using ADAS-Cog total score change, 13/27 AD/ADcvd patients improved with rTMS and 14/27 showed no-improvement. Leave-one-out-cross-validated linear-discriminant-analysis using two EVestG features yielded a blind accuracy of 75% for separating the improved and non-improved populations. Three-way separation of improved/non-improved/control accuracy was 91.9% using MoCA (67% alone) and one EVestG feature (66% alone). AD severity affects the rTMS treatment efficacy. The effect of existing significant cerebrovascular symptomatology on the efficacy of rTMS treatment remains unresolved. Baseline EVestG features can be predictive of the efficacy of rTMS treatment.

Physiological separation of Alzheimer's disease and Alzheimer's disease with significant levels of cerebrovascular symptomology and healthy controls.

Most dementia patients with a mixed dementia (MxD) diagnosis have a mix of Alzheimer's disease (AD) and vascular dementia. Electrovestibulography (EVestG) records vestibuloacoustic afferent activity. We hypothesize EVestG recordings of AD and MxD patients are different. All patients were assessed with the Montreal cognitive assessment (MoCA) and Hachinski ischemic scale (HIS) (> 4 HIS score < 7 is representative of MxD cerebrovascular symptomology). EVestG recordings were made from 26 AD, 21 MxD and 44 healthy (control) participants. Features were derived from the EVestG recordings of the average field potential and field potential interval histogram to classify the AD, MxD and control groups. Multivariate analysis was used to test the features' significance. Using a leave-one-out cross-validated linear discriminant analysis with 3 EVestG features yielded accuracies > 80% for separating pairs of AD/MxD/control. Using the MoCA assessment and 2 EVestG features, a best accuracy of 81 to 91% depending on the classifier was obtained for the 3-way identification of AD, MxD and controls. EVestG measures provide a physiological basis for identifying AD from MxD. EVestG measures are hypothesized to be partly related to channelopathies and changes in the descending input to the vestibular periphery. Four of the five AD or MxD versus control features used had significant correlations with the MoCA. This supports assertions that the pathologic changes associated with AD impact the vestibular system and further are suggestive that the postulated physiological changes behind these features have an association with cognitive decline severity.

Author Correction: Quantitative measurement of post-concussion syndrome Using Electrovestibulography.

An amendment to this paper has been published and can be accessed via a link at the top of the paper.

A Pilot Randomised Double-Blind Study of the Tolerability and efficacy of repetitive Transcranial Magnetic Stimulation on Persistent Post-Concussion Syndrome.

This study investigates the effect of Repetitive Transcranial Magnetic Stimulation (rTMS) on persistent post-concussion syndrome (PCS). The study design was a randomized (coin toss), placebo controlled, and double-blind study. Thirty-seven participants with PCS were assessed for eligibility; 22 were randomised and 18 completed the study requirements. Half the participants with PCS were given an Active rTMS intervention and the other half given Sham rTMS over 3 weeks. Follow ups were at the end of treatment and at 30 and 60 days. The primary outcome measure was the Rivermead Post-Concussion Symptoms Questionnaire (RPQ3 & RPQ13). The results indicate participants with more recent injuries (<12 month), who received Active rTMS, showed significant improvements compared to those of: 1) the same subgroup who received Sham, and 2) those with a longer duration of injury (>14 months) who received Active rTMS. This improvement predominantly manifested in RPQ13 in the follow up periods 1 and 2 months after the intervention (RPQ13 change (mean ± SD): at 1 month, Active = -21.8 ± 6.6, Sham = -2.2 ± 9.8; at 2 months, Active = -21.2 ± 5.3, Sham = -5.4 ± 13.7). No improvement was found in the subgroup with longer duration injuries. The results support rTMS as a tolerable and potentially effective treatment option for individuals with a recent (<1 year) concussion.

Quantitative measurement of post-concussion syndrome Using Electrovestibulography.

In this study, a noninvasive quantitative measure was used to identify short and long term post-concussion syndrome (PCS) both from each other and from healthy control populations. We used Electrovestibulography (EVestG) for detecting neurophysiological PCS consequent to a mild traumatic brain injury (mTBI) in both short-term (N = 8) and long-term (N = 30) (beyond the normal recovery period) symptomatic individuals. Peripheral, spontaneously evoked vestibuloacoustic signals incorporating - and modulated by - brainstem responses were recorded using EVestG, while individuals were stationary (no movement stimulus). Tested were 38 individuals with PCS in comparison to those of 33 age-and-gender-matched healthy controls. The extracted features were based on the shape of the averaged extracted field potentials (FPs) and their detected firing pattern. Linear discriminant analysis classification, incorporating a leave-one-out routine, resulted in (A) an unbiased 84% classification accuracy for separating healthy controls from a mix of long and short-term symptomatology PCS sufferers and (B) a 79% classification accuracy for separating between long and short-term symptomatology PCS sufferers. Comparatively, short-term symptomatology PCS was generally detected as more distal from controls. Based on the results, the EVestG recording shows promise as an assistive objective tool for detecting and monitoring individuals with PCS after normal recovery periods.

A new diagnostic vestibular evoked response.

OBJECTIVE: To describe the development of a new clinically applicable method for assessing vestibular function in humans with particular application in Meniere's disease. STUDY DESIGN: Sophisticated signal-processing techniques were applied to data from human subject undergoing tilts stimulating the otolith organs and semicircular canals. The most sensitive representatives of vestibular function were extracted as "features". METHODS: After careful consideration of expected response features, Electrovestibulography, a modified electrocochleography, recordings were performed on fourteen Meniere's patients and sixteen healthy controls undergoing controlled tilts. The data were subjected to multiple signal processing techniques to determine which "features" were most predictive of vestibular responses. RESULTS: Linear discriminant analysis and fractal dimension may allow data from a single tilt to be used to adequately characterize the vestibular system. CONCLUSION: Objective, physiologic assessment of vestibular function may become realistic with application of modern signal processing techniques.

Preliminary report: neural firing patterns specific for Meniere's disease.

OBJECTIVE: To describe the application of a new, objective diagnostic test for Meniere's disease. INTRODUCTION: Electrovestibulography (EVestG) is a complex, newly-developed test paradigm that searches for neural firing patterns that may be diagnostic for particular neural disorders. EVestG system was previously "trained" to distinguish Meniere's disease from other patients on a set of training data. In this paper we illustrate its diagnostic application in a new group of unknown subjects. SETTING: Collaborative Academic Bioengineering Research Centre. STUDY DESIGN: Prospective, blinded human Clinical Trial. METHODS: In an attempt to understand the specific neural firing patterns that may objectively characterize latent Meniere's disease, two hundred fifty-six consecutive patients who presented for electronystagmography testing were asked to undergo EVestG testing. Ten subjects actually completed testing but data were too noisy to permit analysis for one patient. Complete data were available for nine patients with either a clinical diagnosis of either Meniere's disease (4 patients) or some other vestibular disorder (2 vestibular neuritis, 2 benign positional vertigo and 1 non-specific dizziness). None of the patients were experiencing attacks of vertigo within a week of EVestG testing. Ten normal control subjects with no history or symptoms of ear disease were also tested. EVestG was performed in a separate engineering research facility by investigators who were unaware of their clinical diagnosis. If EVestG suggested that the probability of Meniere's disease was 0.5 or greater Meniere's disease was considered present by the objective testing. The objective and clinical diagnoses were compared. RESULTS: EVestG testing correctly identified three of four Meniere's disease patients and rejected the diagnosis in 9 of the 10 controls. Two of the 5 dizzy, non-Meniere's patients were incorrectly identified as Meniere's disease. The sensitivity and specificity of EvestG testing were 75% and 80%, respectively. EVestG results were statistically significantly different for Meniere's patients versus the other dizzy patients and controls (Univariate ANOVA difference contrasts p = 0.0340) even in this small sample. CONCLUSION: The EVestG protocol appeared to show promise as an objective, diagnostic test for Meniere's disease, but our sample size is too small to generalize widely. LEVEL OF EVIDENCE: N.A. Prospective Human clinical trial.

Intelligent arrhythmia detection and classification using ICA.

In this paper a novel approach for cardiac arrhythmias detection is proposed. The proposed method is based on using independent component analysis (ICA) and wavelet transform to extract important features. Using the extracted features different machine learning classification schemas, MLP and RBF neural networks and K-nearest neighbor, are used to classify 274 instance signals from the MIT-BIH database. Simulations show that multilayer neural networks with Levenberg-Marquardt (LM) back propagation algorithm provide the optimal learning system. We were able to obtain 98.5% accuracy, which is an improvement in comparison with the similar works.