Evaluation of Parkinson's disease early diagnosis using single-channel EEG features and auditory cognitive assessment.

Background: Parkinson's disease (PD) often presents with subtle early signs, making diagnosis difficult. F-DOPA PET imaging provides a reliable measure of dopaminergic function and is a primary tool for early PD diagnosis. This study aims to evaluate the ability of machine-learning (ML) extracted EEG features to predict F-DOPA results and distinguish between PD and non-PD patients. These features, extracted using a single-channel EEG during an auditory cognitive assessment, include EEG feature A0 associated with cognitive load in healthy subjects, and EEG feature L1 associated with cognitive task differentiation. Methods: Participants in this study are comprised of cognitively healthy patients who had undergone an F-DOPA PET scan as a part of their standard care (n = 32), and cognitively healthy controls (n = 20). EEG data collected using the Neurosteer system during an auditory cognitive task, was decomposed using wavelet-packet analysis and machine learning methods for feature extraction. These features were used in a connectivity analysis that was applied in a similar manner to fMRI connectivity. A preliminary model that relies on the features and their connectivity was used to predict initially unrevealed F-DOPA test results. Then, generalized linear mixed models (LMM) were used to discern between PD and non-PD subjects based on EEG variables. Results: The prediction model correctly classified patients with unrevealed scores as positive F-DOPA. EEG feature A0 and the Delta band revealed distinct activity patterns separating between study groups, with controls displaying higher activity than PD patients. In controls, EEG feature L1 showed variations between resting state and high-cognitive load, an effect lacking in PD patients. Conclusion: Our findings exhibit the potential of single-channel EEG technology in combination with an auditory cognitive assessment to distinguish positive from negative F-DOPA PET scores. This approach shows promise for early PD diagnosis. Additional studies are needed to further verify the utility of this tool as a potential biomarker for PD.

Single-Channel EEG Features Reveal an Association With Cognitive Decline in Seniors Performing Auditory Cognitive Assessment.

Background: Cognitive decline remains highly underdiagnosed despite efforts to find novel cognitive biomarkers. Electroencephalography (EEG) features based on machine-learning (ML) may offer a non-invasive, low-cost approach for identifying cognitive decline. However, most studies use cumbersome multi-electrode systems. This study aims to evaluate the ability to assess cognitive states using machine learning (ML)-based EEG features extracted from a single-channel EEG with an auditory cognitive assessment. Methods: This study included data collected from senior participants in different cognitive states (60) and healthy controls (22), performing an auditory cognitive assessment while being recorded with a single-channel EEG. Mini-Mental State Examination (MMSE) scores were used to designate groups, with cutoff scores of 24 and 27. EEG data processing included wavelet-packet decomposition and ML to extract EEG features. Data analysis included Pearson correlations and generalized linear mixed-models on several EEG variables: Delta and Theta frequency-bands and three ML-based EEG features: VC9, ST4, and A0, previously extracted from a different dataset and showed association with cognitive load. Results: MMSE scores significantly correlated with reaction times and EEG features A0 and ST4. The features also showed significant separation between study groups: A0 separated between the MMSE < 24 and MMSE ≥ 28 groups, in addition to separating between young participants and senior groups. ST4 differentiated between the MMSE < 24 group and all other groups (MMSE 24-27, MMSE ≥ 28 and healthy young groups), showing sensitivity to subtle changes in cognitive states. EEG features Theta, Delta, A0, and VC9 showed increased activity with higher cognitive load levels, present only in the healthy young group, indicating different activity patterns between young and senior participants in different cognitive states. Consisted with previous reports, this association was most prominent for VC9 which significantly separated between all level of cognitive load. Discussion: This study successfully demonstrated the ability to assess cognitive states with an easy-to-use single-channel EEG using an auditory cognitive assessment. The short set-up time and novel ML features enable objective and easy assessment of cognitive states. Future studies should explore the potential usefulness of this tool for characterizing changes in EEG patterns of cognitive decline over time, for detection of cognitive decline on a large scale in every clinic to potentially allow early intervention. Trial Registration: NIH Clinical Trials Registry [https://clinicaltrials.gov/ct2/show/results/NCT04386902], identifier [NCT04386902]; Israeli Ministry of Health registry [https://my.health.gov.il/CliniTrials/Pages/MOH_2019-10-07_007352.aspx], identifier [007352].

Description of the Method for Evaluating Digital Endpoints in Alzheimer Disease Study: Protocol for an Exploratory, Cross-sectional Study.

BACKGROUND: More sensitive and less burdensome efficacy end points are urgently needed to improve the effectiveness of clinical drug development for Alzheimer disease (AD). Although conventional end points lack sensitivity, digital technologies hold promise for amplifying the detection of treatment signals and capturing cognitive anomalies at earlier disease stages. Using digital technologies and combining several test modalities allow for the collection of richer information about cognitive and functional status, which is not ascertainable via conventional paper-and-pencil tests. OBJECTIVE: This study aimed to assess the psychometric properties, operational feasibility, and patient acceptance of 10 promising technologies that are to be used as efficacy end points to measure cognition in future clinical drug trials. METHODS: The Method for Evaluating Digital Endpoints in Alzheimer Disease study is an exploratory, cross-sectional, noninterventional study that will evaluate 10 digital technologies' ability to accurately classify participants into 4 cohorts according to the severity of cognitive impairment and dementia. Moreover, this study will assess the psychometric properties of each of the tested digital technologies, including the acceptable range to assess ceiling and floor effects, concurrent validity to correlate digital outcome measures to traditional paper-and-pencil tests in AD, reliability to compare test and retest, and responsiveness to evaluate the sensitivity to change in a mild cognitive challenge model. This study included 50 eligible male and female participants (aged between 60 and 80 years), of whom 13 (26%) were amyloid-negative, cognitively healthy participants (controls); 12 (24%) were amyloid-positive, cognitively healthy participants (presymptomatic); 13 (26%) had mild cognitive impairment (predementia); and 12 (24%) had mild AD (mild dementia). This study involved 4 in-clinic visits. During the initial visit, all participants completed all conventional paper-and-pencil assessments. During the following 3 visits, the participants underwent a series of novel digital assessments. RESULTS: Participant recruitment and data collection began in June 2020 and continued until June 2021. Hence, the data collection occurred during the COVID-19 pandemic (SARS-CoV-2 virus pandemic). Data were successfully collected from all digital technologies to evaluate statistical and operational performance and patient acceptance. This paper reports the baseline demographics and characteristics of the population studied as well as the study's progress during the pandemic. CONCLUSIONS: This study was designed to generate feasibility insights and validation data to help advance novel digital technologies in clinical drug development. The learnings from this study will help guide future methods for assessing novel digital technologies and inform clinical drug trials in early AD, aiming to enhance clinical end point strategies with digital technologies. INTERNATIONAL REGISTERED REPORT IDENTIFIER (IRRID): DERR1-10.2196/35442.

Continuous Monitoring of Mental Load During Virtual Simulator Training for Laparoscopic Surgery Reflects Laparoscopic Dexterity: A Comparative Study Using a Novel Wireless Device.

INTRODUCTION: Cognitive Load Theory (CLT) relates to the efficiency with which individuals manipulate the limited capacity of working memory load. Repeated training generally results in individual performance increase and cognitive load decrease, as measured by both behavioral and neuroimaging methods. One of the known biomarkers for cognitive load is frontal theta band, measured by an EEG. Simulation-based training is an effective tool for acquiring practical skills, specifically to train new surgeons in a controlled and hazard-free environment. Measuring the cognitive load of young surgeons undergoing such training can help to determine whether they are ready to take part in a real surgery. In this study, we measured the performance of medical students and interns in a surgery simulator, while their brain activity was monitored by a single-channel EEG. METHODS: A total of 38 medical students and interns were divided into three groups and underwent three experiments examining their behavioral performances. The participants were performing a task while being monitored by the Simbionix LAP MENTOR™. Their brain activity was simultaneously measured using a single-channel EEG with novel signal processing (Aurora by Neurosteer®). Each experiment included three trials of a simulator task performed with laparoscopic hands. The time retention between the tasks was different in each experiment, in order to examine changes in performance and cognitive load biomarkers that occurred during the task or as a result of nighttime sleep consolidation. RESULTS: The participants' behavioral performance improved with trial repetition in all three experiments. In Experiments 1 and 2, delta band and the novel VC9 biomarker (previously shown to correlate with cognitive load) exhibited a significant decrease in activity with trial repetition. Additionally, delta, VC9, and, to some extent, theta activity decreased with better individual performance. DISCUSSION: In correspondence with previous research, EEG markers delta, VC9, and theta (partially) decreased with lower cognitive load and higher performance; the novel biomarker, VC9, showed higher sensitivity to lower cognitive load levels. Together, these measurements may be used for the neuroimaging assessment of cognitive load while performing simulator laparoscopic tasks. This can potentially be expanded to evaluate the efficacy of different medical simulations to provide more efficient training to medical staff and measure cognitive and mental loads in real laparoscopic surgeries.

Postural control in karate practitioners: Does practice make perfect?

BACKGROUND: Karate training likely leads to enhanced postural control, however, previous studies did not always include a healthy, physically active comparison group and the findings are inconsistent. RESEARCH QUESTION: Will the postural control of experienced karate practitioners be better than that of experienced swimmers, i.e., athletes with similar characteristics who do not practice under conditions that require upright postural control? METHODS: In this cross-sectional study, 20 experienced, male karate practitioners and 20 experienced, male swimmers, ages 20-50, performed four standing postural control tasks of increasing difficulty: (a) two-legged stance with eyes open; (b) one-legged stance with eyes open; (c) one-legged stance with eyes closed, and (d) a dual-task, one-legged stance with eyes closed and a verbal fluency challenge. The primary outcome measure was a functional, behavioral measure that reflects the loss of balance. Specifically, in tasks that included one-legged stance, every touch of the raised foot to the floor was counted. Center-of-gravity movements were measured using a wearable sensor. RESULTS: Task-related differences were seen in all of the postural control measures. In the OneLegEyesClosed task, the median number of touches was 0.00 in the karate group and 6.50 in the swimming group (p < 0.001). In the OneLegEyesClosedWords task, the median number of touches was 0.00 in the karate group and 5.00 in the swimming group (p < 0.001). Shannon entropy, a measure of the complexity of the sway of the center-of-gravity, was lower in the karate group (p = 0.002), compared to the swimmers. SIGNIFICANCE: Karate training is associated with a higher level of postural control, even when compared to a physically active age-matched comparison group. In addition to supporting the specificity of exercise training principle, these findings raise the intriguing possibility that karate may be useful as a form of pre-habilitation, potentially aiding in the prevention of age-associated declines in balance control.

DJ-1 based peptide, ND-13, promote functional recovery in mouse model of focal ischemic injury.

Stroke is a leading cause of death worldwide and inflicts serious long-term damage and disability. The vasoconstrictor Endothelin-1, presenting long-term neurological deficits associated with excitotoxicity and oxidative stress is being increasingly used to induce focal ischemic injury as a model of stroke. A DJ-1 based peptide named ND-13 was shown to protect against glutamate toxicity, neurotoxic insults and oxidative stress in various animal models. Here we focus on the benefits of treatment with ND-13 on the functional outcome of focal ischemic injury. Wild type C57BL/6 mice treated with ND-13, after ischemic induction in this model, showed significant improvement in motor function, including improved body balance and motor coordination, and decreased motor asymmetry. We found that DJ-1 knockout mice are more sensitive to Endothelin-1 ischemic insult than wild type mice, contributing thereby additional evidence to the widely reported relevance of DJ-1 in neuroprotection. Furthermore, treatment of DJ-1 knockout mice with ND-13, following Endothelin-1 induced ischemia, resulted in significant improvement in motor functions, suggesting that ND-13 provides compensation for DJ-1 deficits. These preliminary results demonstrate a possible basis for clinical application of the ND-13 peptide to enhance neuroprotection in stroke patients.

Combined Gene Therapy to Reduce the Neuronal Damage in the Mouse Model of Focal Ischemic Injury.

Research into stroke is driven by frustration over the limited available therapeutics. Targeting a single aspect of this multifactorial disease contributes to the therapeutic boundaries. To overcome this, we devised a novel multifactorial-cocktail treatment, using lentiviruses encoding excitatory amino acid transporter 2 (EAAT2(, glutamate dehydrogenase 2 (GDH2), and nuclear factor E2-related factor 2 (Nrf2) genes, that acts synergistically to address the effected excito-oxidative axis. Here, we used the vasoconstrictor endothelin-1 (ET-1) to induce focal ischemic injury in mice by direct injection into the striatum. Mice treated with the mixture of these three genes show significant improvement in body balance, motor coordination, and decreased motor asymmetry compared to each gene separately. These results demonstrate that overexpression of the combined EAAT2, GDH2, and NRF2 genes can provide neuroprotection after ischemic injury.