Quantitative Analysis of Factors of Attrition in a Double-blind rTMS Study for Alzheimer Treatment.

Attrition is a particular concern in studies examining the efficacy of a treatment for Alzheimer disease. Analyzing reasons for withdrawal in Alzheimer studies is crucial to ruling out attrition bias, which can undermine a study's validity. In contrast, attrition in studies using repetitive transcranial magnetic stimulation (rTMS) has received much less attention. Our goal was to identify any commonalities between participants who withdrew for the same reasons. Three independent coders rated each response concerning the reasons for withdrawal, and frequency tables were generated to characterize the participants within each category. This study was conducted on the 28 withdrawn cases from a 7-month study investigating the short-term and long-term therapeutic effects of rTMS for Alzheimer disease among 156 participants across 3 sites of the study. Seven reasons for withdrawal were identified, with health and medical changes being the most commonly reported reason (7 participants). Personal issues involving family or caregivers were the next most common (5 participants), and the remaining 5 categories consisted of 3 participants each. Although the limited sample size prevented the use of inferential statistics, our findings highlight the need for more transparent reporting of attrition rates and withdrawal reasons by rTMS researchers.

Design and Analysis of a Contact Piezo Microphone for Recording Tracheal Breathing Sounds.

Analysis of tracheal breathing sounds (TBS) is a significant area of study in medical diagnostics and monitoring for respiratory diseases and obstructive sleep apnea (OSA). Recorded at the suprasternal notch, TBS can provide detailed insights into the respiratory system's functioning and health. This method has been particularly useful for non-invasive assessments and is used in various clinical settings, such as OSA, asthma, respiratory infectious diseases, lung function, and detection during either wakefulness or sleep. One of the challenges and limitations of TBS recording is the background noise, including speech sound, movement, and even non-tracheal breathing sounds propagating in the air. The breathing sounds captured from the nose or mouth can interfere with the tracheal breathing sounds, making it difficult to isolate the sounds necessary for accurate diagnostics. In this study, two surface microphones are proposed to accurately record TBS acquired solely from the trachea. The frequency response of each microphone is compared with a reference microphone. Additionally, this study evaluates the tracheal and lung breathing sounds of six participants recorded using the proposed microphones versus a commercial omnidirectional microphone, both in environments with and without background white noise. The proposed microphones demonstrated reduced susceptibility to background noise particularly in the frequency ranges (1800-2199) Hz and (2200-2599) Hz with maximum deviation of 2 dB and 2.1 dB, respectively, compared to 9 dB observed in the commercial microphone. The findings of this study have potential implications for improving the accuracy and reliability of respiratory diagnostics in clinical practice.

1-Year Mortality Prediction through Artificial Intelligence Using Hemodynamic Trace Analysis among Patients with ST Elevation Myocardial Infarction.

Background and Objectives: Patients presenting with ST Elevation Myocardial Infarction (STEMI) due to occlusive coronary arteries remain at a higher risk of excess morbidity and mortality despite being treated with primary percutaneous coronary intervention (PPCI). Identifying high-risk patients is prudent so that close monitoring and timely interventions can improve outcomes. Materials and Methods: A cohort of 605 STEMI patients [64.2 ± 13.2 years, 432 (71.41%) males] treated with PPCI were recruited. Their arterial pressure (AP) wave recorded throughout the PPCI procedure was analyzed to extract features to predict 1-year mortality. After denoising and extracting features, we developed two distinct feature selection strategies. The first strategy uses linear discriminant analysis (LDA), and the second employs principal component analysis (PCA), with each method selecting the top five features. Then, three machine learning algorithms were employed: LDA, K-nearest neighbor (KNN), and support vector machine (SVM). Results: The performance of these algorithms, measured by the area under the curve (AUC), ranged from 0.73 to 0.77, with accuracy, specificity, and sensitivity ranging between 68% and 73%. Moreover, we extended the analysis by incorporating demographics, risk factors, and catheterization information. This significantly improved the overall accuracy and specificity to more than 76% while maintaining the same level of sensitivity. This resulted in an AUC greater than 0.80 for most models. Conclusions: Machine learning algorithms analyzing hemodynamic traces in STEMI patients identify high-risk patients at risk of mortality.

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.

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.

Bipolar disorder in the balance.

Bipolar disorder (BD) is a severe mood disorder that lacks established electrophysiological, neuroimaging or biological markers to assist with both diagnosis and monitoring disease severity. This study's aim is to describe the potential of new neurophysiological features assistive in BD diagnosis and severity measurement utilizing the recording of electrical activity from the outer ear canal called Electrovestibulography (EVestG). From EVestG data sensory vestibulo-acoustic features were extracted from a single supine-vertical translation stimulus to distinguish 50 depressed and partly remitted/remitted bipolar disorder patients [18 symptomatic (BD-S, MADRS > 19), 32 reduced symptomatic (BD-R, MADRS ≤ 19)] and 31 age and gender matched healthy individuals (controls). Six features were extracted from the measured firing pattern interval histogram and the extracted shape of the average field potential response. Five of the six features had low but significant correlations (p < 0.05) with the MADRS assessment. Using leave-one-out-cross-validation, unbiased parametric and non-parametric classification routines resulted in 75-79%, 84-86%, 76-85% and 79-82% accuracy for separation of control from BD, BD-S and BD-R as well as BD-S from BD-R groups, respectively. The main limitation of this study was the inability to fully disentangle the impact of prescribed medication from the responses recorded. A mix of stationary and movement evoked EVestG features produced good discrimination between control and BD patients whether BD-S or BD-R. Moreover, BD-S and BD-R appear to have measurably different pathophysiological manifestations. The firing pattern features used were dissimilar to those observed in a prior major depressive disorder study.

Effects of training with a neuro-mechano stimulator rehabilitation bicycle on functional recovery and paired-reflex depression of the soleus in individuals with incomplete paralysis: a proof-of-principle study.

Aim: The present study describes the training effects of a novel motorized bicycle-like device for individuals with incomplete spinal cord injury. Methods: Participants were five individuals with motor incomplete spinal cord injury (56 ± 7 years). Four of five participants received two 30-min sessions of training: one with, and one without, mechanical stimulation on the plantar surface of the foot; soleus paired H-reflex depression was examined before and after each session. Three of five participants received 24 sessions of 30-min of training (long-training). Following the long-training, balance, walking and spasticity improvements were assessed using validated clinical outcome measures, in addition to the H-reflex assessment. Results: One cycling session with mechanical stimulation yielded 14% and 32% more reflex depression in participants with moderate spasticity (n = 2/4). The same trend was not observed in non-spastic participants (n = 2/4). All participants who participated in the long-training had spasticity and showed reduced spasticity, improved walking speed, endurance and balance. Conclusions: Overall, participants with spasticity showed increased soleus H-reflex suppression after one training session with mechanical stimulation and reduced spasticity scores after long training. We interpret this as evidence that the training influenced both presynaptic and postsynaptic inhibitory mechanisms acting on soleus motoneurons. Therefore, this training has the potential to be a non-invasive complementary therapy to reduce spasticity after incomplete spinal cord injury.

Molybdenum coated SU-8 microneedle electrodes for transcutaneous electrical nerve stimulation.

Electrophysiological devices are connected to the body through electrodes. In some applications, such as nerve stimulation, it is needed to minimally pierce the skin and reach the underneath layers to bypass the impedance of the first layer called stratum corneum. In this study, we have designed and fabricated surface microneedle electrodes for applications such as electrical peripheral nerve stimulation. We used molybdenum for microneedle fabrication, which is a biocompatible metal; it was used for the conductive layer of the needle array. To evaluate the performance of the fabricated electrodes, they were compared with the conventional surface electrodes in nerve conduction velocity experiment. The recorded signals showed a much lower contact resistance and higher bandwidth in low frequencies for the fabricated microneedle electrodes compared to those of the conventional electrodes. These results indicate the electrode-tissue interface capacitance and charge transfer resistance have been increased in our designed electrodes, while the contact resistance decreased. These changes will lead to less harmful Faradaic current passing through the tissue during stimulation in different frequencies. We also compared the designed microneedle electrodes with conventional ones by a 3-dimensional finite element simulation. The results demonstrated that the current density in the deep layers of the skin and the directivity toward a target nerve for microneedle electrodes were much more than those for the conventional ones. Therefore, the designed electrodes are much more efficient than the conventional electrodes for superficial transcutaneous nerve stimulation purposes.

Physiological Differences in the Follicular, Luteal, and Menstrual Phases in Healthy Women Determined by Electrovestibulography: Depression, Anxiety, or Other Associations?

Electrovestibulography (EVestG) recordings have been previously applied toward classifying and/or measuring the severity of several neurological disorders including depression with and without anxiety. This study's objectives were to: (1) extract EVestG features representing physiological differences of healthy women during their menses, and follicular and luteal phases of their menstrual cycle, and (2) compare these features to those observed in previous studies for depression with and without anxiety. Three EVestG recordings were made on 15 young healthy menstruating females during menses, and follicular and luteal phases. Three features were extracted, using the shape and timing of the detected spontaneously evoked vestibulo-acoustic field potentials. Using these features, a 3-way separation of the 3 phases was achieved, with a leave-one-out cross-validation, resulting in accuracy of > 72%. Using an EVestG shape feature, separation of the follicular and luteal phases was achieved with a leave-one-out cross-validation accuracy of > 93%. The mechanism of separation was not like that in previous depression analyses, and is postulated to be more akin to a form of anxiety and/or progesterone sensitivity.

The efficacy of deep repetitive transcranial magnetic stimulation over the medial prefrontal cortex in obsessive compulsive disorder: results from an open-label study.

BACKGROUND: Significant numbers of patients with obsessive compulsive disorder (OCD) respond minimally to currently available treatments. Furthermore, the application of both high- and low-frequency repetitive transcranial magnetic stimulation (rTMS) to dorsolateral prefrontal cortex has shown to be ineffective in the reduction of OCD symptoms. In this study, we instead targeted the medial prefrontal cortex (mPFC) and applied low-frequency rTMS to patients with OCD and assessed their clinical response. METHODS: In an open-label design, 10 OCD patients with no other current axis I psychiatric disorders were recruited. Twelve hundred pulses of 1-Hz frequency were applied over the mPFC (Brodmann areas 24 and 32) using a double-cone coil for 10 days. Regions of interest were located on participants' MRIs using neuronavigation software. Patients' symptoms were rated using the Yale-Brown Obsessive Compulsive Scale (Y-BOCS). RESULTS: All patients demonstrated improvement in their OCD symptoms after 10 sessions of rTMS as shown by a mean improvement in Y-BOCS score of 39% (SD = 15%; P < .001, F = 62.95). This improvement persisted 1 month following the last session of rTMS. CONCLUSIONS: Our results suggest the use of low frequency deep rTMS as a promising and robust intervention in OCD symptom reduction. However, this study is limited by its open-label nature and its lack of a control group, so further randomized clinical trials are needed to confirm these results.

Development of an ultra low noise, miniature signal conditioning device for vestibular evoked response recordings.

BACKGROUND: Inner ear evoked potentials are small amplitude (<1 µVpk) signals that require a low noise signal acquisition protocol for successful extraction; an existing such technique is Electrocochleography (ECOG). A novel variant of ECOG called Electrovestibulography (EVestG) is currently investigated by our group, which captures vestibular responses to a whole body tilt. The objective is to design and implement a bio-signal amplifier optimized for ECOG and EVestG, which will be superior in noise performance compared to low noise, general purpose devices available commercially. METHOD: A high gain configuration is required (>85 dB) for such small signal recordings; thus, background power line interference (PLI) can have adverse effects. Active electrode shielding and driven-right-leg circuitry optimized for EVestG/ECOG recordings were investigated for PLI suppression. A parallel pre-amplifier design approach was investigated to realize low voltage, and current noise figures for the bio-signal amplifier. RESULTS: In comparison to the currently used device, PLI is significantly suppressed by the designed prototype (by >20 dB in specific test scenarios), and the prototype amplifier generated noise was measured to be 4.8 nV/Hz @ 1 kHz (0.45 µVRMS with bandwidth 10 Hz-10 kHz), which is lower than the currently used device generated noise of 7.8 nV/Hz @ 1 kHz (0.76 µVRMS). A low noise (<1 nV/Hz) radio frequency interference filter was realized to minimize noise contribution from the pre-amplifier, while maintaining the required bandwidth in high impedance measurements. Validation of the prototype device was conducted for actual ECOG recordings on humans that showed an increase (p < 0.05) of ~5 dB in Signal-to-Noise ratio (SNR), and for EVestG recordings using a synthetic ear model that showed a ~4% improvement (p < 0.01) over the currently used amplifier. CONCLUSION: This paper presents the design and evaluation of an ultra-low noise and miniaturized bio-signal amplifier tailored for EVestG and ECOG. The increase in SNR for the implemented amplifier will reduce variability associated with bio-features extracted from such recordings; hence sensitivity and specificity measures associated with disease classification are expected to increase. Furthermore, immunity to PLI has enabled EVestG and ECOG recordings to be carried out in a non-shielded clinical environment.

How accurate are coordinate systems being used for transcranial magnetic stimulation?

When applying transcranial magnetic stimulation (TMS) to the brain, it is desired to be as precise as possible to reach a target area in the brain. For that, neuronavigational system using individuals' MRI scans were developed to guide TMS pulses delivery. All neuronavigational systems need coordinates of the target area to guide the TMS coil. Talairach coordinate system, which uses the Talairach-Tournoux atlas, is the most common system used with TMS pulses. In this study we investigated how an average Talairach coordinate from 50 healthy individuals is close to the actual location of the hand area of the primary motor cortex to investigate if that elicit a motor response in the hand; thus, investigating the fitness and accuracy of the Talairach coordinate system. We performed this experiment on six individuals (ages 61-82). When applying TMS single pulses to hand area with the given Talairach coordinate system adjusted with the MRI of each participant, three participants had involuntary twitch and three participants had no consistent physical response, as corroborated by electromyography of the abductor pollicis brevis and first dorsal interosseous muscles at the resting motor threshold intensity. Subsequently, by trial-and-error, the hand area was successfully stimulated on those three non-responder participants. The largest deviation from the Talairach coordinates was found to be 19.5 mm, measured on the surface of the cranium, between the true hand area and the mean Talairach coordinate. This finding implies that using generalized coordinates might be misleading when choosing the optimal location for brain stimulation.

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.

iVR-fNIRS: studying brain functions in a fully immersive virtual environment.

Immersive virtual reality (iVR) employs head-mounted displays or cave-like environments to create a sensory-rich virtual experience that simulates the physical presence of a user in a digital space. The technology holds immense promise in neuroscience research and therapy. In particular, virtual reality (VR) technologies facilitate the development of diverse tasks and scenarios closely mirroring real-life situations to stimulate the brain within a controlled and secure setting. It also offers a cost-effective solution in providing a similar sense of interaction to users when conventional stimulation methods are limited or unfeasible. Although combining iVR with traditional brain imaging techniques may be difficult due to signal interference or instrumental issues, recent work has proposed the use of functional near infrared spectroscopy (fNIRS) in conjunction with iVR for versatile brain stimulation paradigms and flexible examination of brain responses. We present a comprehensive review of current research studies employing an iVR-fNIRS setup, covering device types, stimulation approaches, data analysis methods, and major scientific findings. The literature demonstrates a high potential for iVR-fNIRS to explore various types of cognitive, behavioral, and motor functions in a fully immersive VR (iVR) environment. Such studies should set a foundation for adaptive iVR programs for both training (e.g., in novel environments) and clinical therapeutics (e.g., pain, motor and sensory disorders and other psychiatric conditions).

Obstructive sleep apnea detection during wakefulness: a comprehensive methodological review.

Obstructive sleep apnea (OSA) is a chronic condition affecting up to 1 billion people, globally. Despite this spread, OSA is still thought to be underdiagnosed. Lack of diagnosis is largely attributed to the high cost, resource-intensive, and time-consuming nature of existing diagnostic technologies during sleep. As individuals with OSA do not show many symptoms other than daytime sleepiness, predicting OSA while the individual is awake (wakefulness) is quite challenging. However, research especially in the last decade has shown promising results for quick and accurate methodologies to predict OSA during wakefulness. Furthermore, advances in machine learning algorithms offer new ways to analyze the measured data with more precision. With a widening research outlook, the present review compares methodologies for OSA screening during wakefulness, and recommendations are made for avenues of future research and study designs.

Repetitive transcranial magnetic stimulation as a treatment for Alzheimer's disease: A randomized placebo-controlled double-blind clinical trial.

We report results of a large multisite double-blind randomized trial investigating the short and long-term efficacy of repetitive transcranial magnetic stimulation (rTMS) applied to patients with Alzheimer's disease (AD) at mild to moderate stages, in doses of either 2 or 4 weeks of treatment (5 days/week), whilst compared with 4 weeks of sham rTMS. Randomization to treatment group was stratified based on age and severity. The objectives of this study were to: 1) investigate the efficacy of active rTMS versus sham, 2) investigate the effect of dose of treatment (2 or 4 weeks), and 3) investigate the length of benefits from treatment. The rTMS pulses (20 â€‹Hz, 30 pulses/train, 25 trains, 10-s intertrain interval) were applied serially to the left and right dorsolateral prefrontal cortex using neuro-navigation. We compared the primary outcome measure's (ADAS-Cog) score changes from pre- to post-treatment, with assessments at baseline and 4 more times up to 6 months post-treatment. Data of 135 patients were analyzed. The mean total ADAS-Cog score at baseline did not differ between the active and sham treatment groups, nor across the three study sites. The overall results show significant cognitive improvement after treatment up to two months post-treatment with either sham or active coils. The results show both short and long-term benefits of active rTMS treatment but also show similar benefits for sham coil treatment of mild/moderate AD. We discuss this finding in the context of the existing literature on rTMS therapy for AD, as well as evidence of the sham coil's potential to induce a low-level current in the brain. TRIAL REGISTRATION: https://clinicaltrials.gov/ct2/show/NCT02908815.

Can Brain Volume-Driven Characteristic Features Predict the Response of Alzheimer's Patients to Repetitive Transcranial Magnetic Stimulation? A Pilot Study.

This study is a post-hoc examination of baseline MRI data from a clinical trial investigating the efficacy of repetitive transcranial magnetic stimulation (rTMS) as a treatment for patients with mild-moderate Alzheimer's disease (AD). Herein, we investigated whether the analysis of baseline MRI data could predict the response of patients to rTMS treatment. Whole-brain T1-weighted MRI scans of 75 participants collected at baseline were analyzed. The analyses were run on the gray matter (GM) and white matter (WM) of the left and right dorsolateral prefrontal cortex (DLPFC), as that was the rTMS application site. The primary outcome measure was the Alzheimer's disease assessment scale-cognitive subscale (ADAS-Cog). The response to treatment was determined based on ADAS-Cog scores and secondary outcome measures. The analysis of covariance showed that responders to active treatment had a significantly lower baseline GM volume in the right DLPFC and a higher GM asymmetry index in the DLPFC region compared to those in non-responders. Logistic regression with a repeated five-fold cross-validated analysis using the MRI-driven features of the initial 75 participants provided a mean accuracy of 0.69 and an area under the receiver operating characteristic curve of 0.74 for separating responders and non-responders. The results suggest that GM volume or asymmetry in the target area of active rTMS treatment (DLPFC region in this study) may be a weak predictor of rTMS treatment efficacy. These results need more data to draw more robust conclusions.

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.

Developing cognitive workload and performance evaluation models using functional brain network analysis.

Cognition, defined as the ability to learn, remember, sustain attention, make decisions, and solve problems, is essential in daily activities and in learning new skills. The purpose of this study was to develop cognitive workload and performance evaluation models using features that were extracted from Electroencephalogram (EEG) data through functional brain network and spectral analyses. The EEG data were recorded from 124 brain areas of 26 healthy participants conducting two cognitive tasks on a robot simulator. The functional brain network and Power Spectral Density features were extracted from EEG data using coherence and spectral analyses, respectively. Participants reported their perceived cognitive workload using the SURG-TLX questionnaire after each exercise, and the simulator generated actual performance scores. The extracted features, actual performance scores, and subjectively assessed cognitive workload values were used to develop linear models for evaluating performance and cognitive workload. Furthermore, the Pearson correlation was used to find the correlation between participants' age, performance, and cognitive workload. The findings demonstrated that combined EEG features retrieved from spectral analysis and functional brain networks can be used to evaluate cognitive workload and performance. The cognitive workload in conducting only Matchboard level 3, which is more challenging than Matchboard level 2, was correlated with age (0.54, p-value = 0.01). This finding may suggest playing more challenging computer games are more helpful in identifying changes in cognitive workload caused by aging. The findings could open the door for a new era of objective evaluation and monitoring of cognitive workload and performance.