Bipolar disorder in the balance

Measuring anxiety disorder in bipolar disorder using EVestG: broad impact of medication groups

Objectives

Anxiety disorder is present in approximately half of all bipolar disorder (BD) patients. There are neurologic bases for the comorbidity of balance (vestibular) disorders and anxiety. Our objective is to use electrovestibulography (EVestG), which is predominantly a measure of vestibular neural activity to not only quantitatively detect and measure comorbid anxiety disorder but also to quantitatively measure the impacts of anti-depressant, anti-psychotic, and mood stabilizer medication groups on anxiety measures in BD patients.

Methods

In a population of 50 (24 with anxiety disorder) depressive phase BD patients, EVestG signals were measured. Participants were labeled depression-wise as anxious or non-anxious using standard questionnaires. Analyses were conducted on the whole dataset as well as on matched (age/gender/MADRS) and "modeled medication-free" subsets. Modulations of the low-frequency EVestG firing pattern data were measured.

Findings

For BD, the main anxious minus non-anxious difference was the presence of an increase in spectral power proximal to 8-9 Hz, which was best attenuated by mood stabilizers.

Novelty

This is the first study to use an oto-acoustic physiological measure to quantify anxiety disorder in BD wherein it appears to manifest as a peak proximal to 8-9 Hz which we hypothesize as likely linked to hippocampal theta.

The Effect of Transcranial Alternating Current Stimulation With Cognitive Training on Executive Brain Function in Individuals With Dementia: Protocol for a Crossover Randomized Controlled Trial

BACKGROUND

Although memory and cognitive declines are associated with normal brain aging, they may also be precursors to dementia.

OBJECTIVE

We aim to offer a novel approach to prevent or slow the progress of neurodegenerative dementia, or plausibly, improve the cognitive functions of individuals with dementia.

METHODS

We will recruit and enroll 75 participants (older than 50 years old with either mild cognitive impairment or probable early or moderate dementia) for this double-blind randomized controlled study to estimate the efficacy of active transcranial alternating current stimulation with cognitive treatment (in comparison with sham transcranial alternating current stimulation). This will be a crossover study; a cycle consists of sham or active treatment for a period of 4 weeks (5 days per week, in two 30-minute sessions with a half-hour break in between), and participants are randomized into 2 groups, with stratification by age, sex, and cognitive level (measured with the Montreal Cognitive Assessment). Outcomes will be assessed before and after each treatment cycle. The primary outcomes are changes in Wechsler Memory Scale Older Adult Battery and Alzheimer Disease Assessment Scale scores. Secondary outcomes are changes in performance on tests of frontal lobe functioning (verbal fluency), neuropsychiatric symptoms (Neuropsychiatric Inventory Questionnaire), mood changes (Montgomery-Åsberg Depression Rating Scale), and short-term recall (visual 1-back task). Exploratory outcome measures will also be assessed: static and dynamic vestibular response using electrovestibulography, neuronal changes using functional near-infrared spectroscopy, and change in spatial orientation using virtual reality navigation.

RESULTS

As of February 10, 2022, the study is ongoing: 7 patients have been screened, and all were deemed eligible for and enrolled in the study; 4 participants have completed baseline assessments.

CONCLUSIONS

We anticipate that transcranial alternating current stimulation will be a well-tolerated treatment, with no serious side effects and with considerable short- and long-term cognitive improvements.

TRIAL REGISTRATION

Clinicaltrials.gov NCT05203523; https://clinicaltrials.gov/show/NCT05203523.

INTERNATIONAL REGISTERED REPORT IDENTIFIER (IRRID)

DERR1-10.2196/37282.

Comparing Vestibular Responses to Linear and Angular Whole-Body Accelerations in Real and Immersive Environments

The vestibular end organs differ in terms of anatomical and physiological characteristics. Sensory modalities' stimuli including visual stimuli and vestibular sensation can influence these organs differently. This paper explores differences between vestibular responses to axial tilts in physical and virtual environments. Four passive whole-body movements (linear: up-down, and angular: yaw, pitch, and roll) were applied to twenty-seven healthy participants once using a hydraulic chair (physical) and once visually using a head-mounted display (virtual). Electrovestibulography (EVestG) was used as the outcome measure to investigate the magnitude of vestibular-response-change in both ears for physical and virtual stimuli. Three features including average action potential (AP) area, AP amplitude, and mean detected firing rate change were used as indices of response. The results show that for both physical and virtual stimuli (1) generally the pitch and roll tilts produce the largest EVestG changes compared to other tilts (2) roll and pitch tilt responses are not significantly different from each other and (3) right side and left side roll tilts' responses are not significantly different. The findings indicate although visually- and physically-induced vestibular responses are different in terms of afferent activity, visual stimuli can still result in distinct responses when exposed to different axial tilts.

Machine learning approaches for prediction of bipolar disorder based on biological, clinical and neuropsychological markers: a systematic review and meta-analysis

Applying machine learning (ML) to objective markers may overcome prognosis uncertainty due to the subjective nature of the diagnosis of bipolar disorder (BD). This PRISMA-compliant meta-analysis provides new systematic evidence of the BD classification accuracy reached by different markers and ML algorithms. We focused on neuroimaging, electrophysiological techniques, peripheral biomarkers, genetic data, neuropsychological or clinical measures, and multimodal approaches. PubMed, Embase and Scopus were searched through 3^rd December 2020. Meta-analyses were performed using random-effect models. Overall, 81 studies were included in this systematic review and 65 in the meta-analysis (11,336 participants, 3,903 BD). The overall pooled classification accuracy was 0.77 (95%CI[0.75;0.80]). Despite subgroup analyses for diagnostic comparison group, psychiatric disorders, marker, ML algorithm, and validation procedure were not significant, linear discriminant analysis significantly outperformed support vector machine for peripheral biomarkers (p=0.03). Sample size was inversely related to accuracy. Evidence of publication bias was detected. Ultimately, although ML reached a high accuracy in differentiating BD from other psychiatric disorders, best practices in methodology are needed for the advancement of future studies.

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.

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.

Vestibular Rehabilitation after Vestibulopathy Focusing on the Application of Virtual Reality

Human postural control is regulated by the vestibular, somatosensory, and visual systems. These types of sensory information are integrated in the central nervous system to ascertain the body’s position in space. Proper functioning of the vestibular, somatosensory, and visual senses is necessary for the body to maintain equilibrium. Bilateral vestibulopathy (BVP) is a condition in which bilateral peripheral vestibular function is reduced. Its treatment includes vestibular rehabilitation (VeR), balance training, counseling, treating the underlying cause, and avoiding further damage to the vestibular system. As VeR is often tedious for patients, patient motivation is required or patients may drop out of the program. To solve this problem, in recent years, there have been increasing reports of VeR using virtual reality, which increases vestibulo-ocular reflex gain and decreased dizziness by inducing adaptation. In this review, we discuss VeR, particularly for BVP, and VeR using virtual reality.

Correlation between Ocular and Vestibular Abnormalities and Convergence Insufficiency in Post-Concussion Syndrome

The vestibular and oculomotor/visual systems are commonly affected in post-concussion syndrome (PCS). Convergence insufficiency (CI) is the most common ocular abnormality after concussion. Electrovestibulography (EVestG) is a relatively new non-invasive method that measures the peripheral vestibular responses; it has shown abnormal vestibular responses in a PCS. Here, we report the results of investigating the correlation between the vestibular and oculomotor systems in PCS population using EVestG and CI measures. Forty-eight PCS patients were tested using EVestG, out of which 20 also completed the Rivermead post-concussion questionnaire (RPQ). An EVestG feature (Field Potential (FP)-area) was extracted from the stationary part of the EVestG signals. A neuro-ophthalmologist (author BM) measured participants' CI at near vision using cross-cover examination and a prism-bar. Results indicate: (1) vestibular abnormality (i.e. FP-area) and CI values are significantly correlated in PCS (R = 0.68, p < .01), and (2) there are significant correlations between severity of concussion (i.e. RPQ3) and CI (R = 0.70, p < .01) and between RPQ3 and FP-area (R = -0.56, p < .02). To the best of our knowledge, this is the first study that objectively demonstrates a significant positive correlation between the CI and vestibular systems' abnormality. These findings are scientifically important as they help localise the pathology of PCS, and are clinically valuable as they help physicians in their decision-making about PCS diagnosis and rehabilitation strategies.

Differences Between Physical vs. Virtual Evoked Vestibular Responses

Electrovestibulography (EVestG), a technology purported to measure vestibular activity at the vestibular periphery, was used to compare the vestibular responses to two sensory inputs: (1) back-forward physical tilt (with eyes-open and eyes-closed) and (2) virtual reality replica of the back-forward tilt (eyes-open, physically static). Twenty-seven healthy participants (10 females) were tested. From each of the EVestG recordings, two feature curves: (1) average field potential (FP), and (2) distribution of time intervals between the detected FPs were extracted. For the eyes-closed physical tilt, except for the background segment, the FP response curve was generally wider compared to that evoked during the virtual replica tilt (p < 0.05). Moreover, the eyes-closed physical tilt produced longer time intervals between FP's compared to the virtual stimulus. For this measure, for the background segment, the eyes closed and open physical tilt responses were significantly different (p < 0.05) in both ears (repeated measure experimental design). The results support: (1) both vestibular and visual inputs evoking a measurably different EVestG response, (2) the differences between physical and virtual vestibular responses are dependent on the eyes being either open or closed, and (3) for the stimuli used, the modulation of vestibular afferent activity was measurably smaller for virtual than physical stimulation.

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.

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.

Investigating the validity and reliability of Electrovestibulography (EVestG) for detecting post-concussion syndrome (PCS) with and without comorbid depression

Features from Electrovestibulography (EVestG) recordings have been used to classify and measure the severity of both persistent post-concussion syndrome (PCS) and major depressive disorder. Herein, we examined the effect of comorbid depression on the detection of persistent PCS using EVestG. To validate our previously developed EVestG classifier for PCS detection, the classifier was tested with a new blind dataset (N = 21). The unbiased accuracy for identifying the new PCS from controls was found to be >90%. Next, the PCS group (N = 59) was divided into three subgroups: PCS with no-depression (n = 18), PCS with mild-depression (n = 27) and PCS with moderate/severe-depression (n = 14). When moderate/severe depression was present, PCS classification accuracy dropped to 83%. By adding an EVestG depression feature from a previous study, separation accuracy of each PCS subgroup from controls was >90%. A four and three-group (excluding mild-depression subgroup) classification, achieved an accuracy of 74% and 81%, respectively. Correlation analysis indicated a significant correlation (R = 0.67) between the depression feature and the MADRS depression score as well as between the PCS-specific feature and Rivermead Post-Concussion Questionnaire (RPQ) (R = −0.48). No significant correlation was found between the PCS-specific feature and the MADRS score (R = 0.20) or between RPQ and the depression feature (R = 0.12). The (PCS-specific and depression-specific) EVestG features used herein have the potential to robustly detect and monitor changes, relatively independently, in both persistent PCS and its depression comorbidity. Clinically, this can be particularly advantageous.