Application of Vestibular Spontaneous Response as a Diagnostic Aid for Meniere's Disease

Using principal component analysis to determine which vestibular stimuli provide best biomarkers for separating Alzheimer's from mixed Alzheimer's disease

Alzheimer's disease (AD) is often mixed with cerebrovascular disease (AD-CVD). Heterogeneity of dementia etiology and the overlapping of neuropathological features of AD and AD-CVD make feature identification of the two challenging. Separation of AD from AD-CVD is important as the optimized treatment for each group may differ. Recent studies using vestibular responses recorded from electrovestibulography (EVestG™) have offered promising results for separating these two pathologies. An EVestG measurement records responses to several different physical stimuli (called tilts). In previous research, the number of EVestG features from different tilts was selected based on physiological intuition to classify AD from AD-CVD. As the number of potential characteristic features from all tilts can be very large, in this study, we used an algorithm based on principal component analysis (PCA) to rank the most effective vestibular stimuli for differentiating AD from AD-CVD. Analyses were performed on the EVestG signals of 28 individuals with AD and 24 with AD-CVD. The results of this study showed that tilts simulating the otolithic organs (utricle and saccule) generated the most characteristic features for separating AD from AD-CVD.

Adjunct Methods for Alzheimer's Disease Detection: A Review of Auditory Evoked Potentials

The auditory afferent pathway as a clinical marker of Alzheimer's disease (AD) has sparked interest in investigating the relationship between age-related hearing loss (ARHL) and AD. Given the earlier onset of ARHL compared to cognitive impairment caused by AD, there is a growing emphasis on early diagnosis and intervention to postpone or prevent the progression from ARHL to AD. In this context, auditory evoked potentials (AEPs) have emerged as a widely used objective auditory electrophysiological technique for both the clinical diagnosis and animal experimentation in ARHL due to their non-invasive and repeatable nature. This review focuses on the application of AEPs in AD detection and the auditory nerve system corresponding to different latencies of AEPs. Our objective was to establish AEPs as a systematic and non-invasive adjunct method for enhancing the diagnostic accuracy of AD. The success of AEPs in the early detection and prediction of AD in research settings underscores the need for further clinical application and study.

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.

Verification EVestG recordings are vestibuloacoustic signals

Introduction

Neural dysfunction is associated with aberrant nerve firing; thus, electrodiagnosis has the potential for objective diagnosis and quantification of neural dysfunction. Electrical stimulation alters nerve firing and may also have treatment potential. This article outlines some findings related to electrodiagnosis and electrical stimulation of the ear. The quasi‐synchronous firing of many vestibuloacoustic nerve fibers can produce an extracellular potential defined as a field potential (FP). Electrovestibulography (EVestG) is a method to record vestibuloacoustic signals and detect the associated FPs. A clear picture of the muscle‐, EEG‐, saccade‐related, or other artefactual origins, and the physiologic basis of FPs recorded with EVestG, is evolving. EVestG was applied to demonstrate the effect of electrical stimulation on spontaneous FPs in the ear canal.

Methods

Bilateral EVestG recordings were conducted on 14 guinea pigs before and after stimulation with 3–0.5 mA ipsilateral anodal electrical pulses before and after ablation via unilateral Scarpa's ganglionectomy to elucidate the origin of the EVestG recorded spontaneous FPs.

Results

Anodal electrical stimulation suppresses the recorded activity. There was a significant reduction of the level of recorded signal observed following anodal stimulation on the ablated but not the intact side.

Conclusion

Electrical stimulation of the external auditory canal reduces spontaneous electrical activity in the ear canal, some of which is due to central nervous system activity. The EVestG recorded FPs have a major vestibuloacoustic component.

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.

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.

Quantitative separation of the depressive phase of bipolar disorder and major depressive disorder using electrovestibulography

Objectives: No electrophysiological, neuroimaging or genetic markers have been established that strongly relate to the diagnostic separation of bipolar disorder (BD) and major depressive disorder (MDD). This paper's objective is to describe the potential of features, extracted from the recording of electrical activity from the outer ear canal, in a process called electrovestibulography (EVestG), for identifying depressed and partly remitted/remitted MDD and BD patients from each other.Methods: From EVestG data four sensory vestibulo-acoustic features were extracted from both background (no movement) and using a single supine-vertical translation stimulus to distinguish 27 controls, 39 MDD and 43 BD patients.Results: Using leave-one-out-cross-validation, unbiased parametric and non-parametric classification routines resulted in 78-83% (2-3 features), 80-81% (1-2 features) and 66-68% (3 features) accuracies for separation of MDD from BD, controls from depressed (BD & MDD) and the 3-way separation of BD from MDD from control groups, respectively. The main limitations of this study were the inability to fully disentangle the impact of prescribed medication from the responses and also the limited sample size.Conclusions: EVestG features can reliably identify depressed and partly remitted/remitted MDD and BD patients from each other.

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.

Electrophysiological Measurements of Peripheral Vestibular Function-A Review of Electrovestibulography

Electrocochleography (EcochG), incorporating the Cochlear Microphonic (CM), the Summating Potential (SP), and the cochlear Compound Action Potential (CAP), has been used to study cochlear function in humans and experimental animals since the 1930s, providing a simple objective tool to assess both hair cell (HC) and nerve sensitivity. The vestibular equivalent of ECochG, termed here Electrovestibulography (EVestG), incorporates responses of the vestibular HCs and nerve. Few research groups have utilized EVestG to study vestibular function. Arguably, this is because stimulating the cochlea in isolation with sound is a trivial matter, whereas stimulating the vestibular system in isolation requires significantly more technical effort. That is, the vestibular system is sensitive to both high-level sound and bone-conducted vibrations, but so is the cochlea, and gross electrical responses of the inner ear to such stimuli can be difficult to interpret. Fortunately, several simple techniques can be employed to isolate vestibular electrical responses. Here, we review the literature underpinning gross vestibular nerve and HC responses, and we discuss the nomenclature used in this field. We also discuss techniques for recording EVestG in experimental animals and humans and highlight how EVestG is furthering our understanding of the vestibular system.