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Early implantable epilepsy therapy devices provided open-loop electrical stimulation without brain sensing, computing, or an interface for synchronized behavioural inputs from patients. Recent epilepsy stimulation devices provide brain sensing but have not yet developed analytics for accurately tracking and quantifying behaviour and seizures. Here we describe a distributed brain co-processor providing an intuitive bi-directional interface between patient, implanted neural stimulation and sensing device, and local and distributed computing resources. Automated analysis of continuous streaming electrophysiology is synchronized with patient reports using a handheld device and integrated with distributed cloud computing resources for quantifying seizures, interictal epileptiform spikes and patient symptoms during therapeutic electrical brain stimulation. The classification algorithms for interictal epileptiform spikes and seizures were developed and parameterized using long-term ambulatory data from nine humans and eight canines with epilepsy, and then implemented prospectively in out-of-sample testing in two pet canines and four humans with drug-resistant epilepsy living in their natural environments. Accurate seizure diaries are needed as the primary clinical outcome measure of epilepsy therapy and to guide brain-stimulation optimization. The brain co-processor system described here enables tracking interictal epileptiform spikes, seizures and correlation with patient behavioural reports. In the future, correlation of spikes and seizures with behaviour will allow more detailed investigation of the clinical impact of spikes and seizures on patients.

The ability to identify individuals in the prodromal phase of Parkinson's disease has improved in recent years, raising the question of whether and how those affected should be informed about the risk of future disease. Several studies investigated prognostic counselling for individuals with isolated REM sleep behavior disorder and have shown that most patients want to receive information about prognosis, but autonomy and individual preferences must be respected. However, there are still many unanswered questions about risk disclosure or early diagnosis of PD, including the impact on personal circumstances, cultural preferences and specific challenges associated with different profiles of prodromal symptoms, genetic testing or biomarker assessments. This narrative review aims to summarize the current literature on prognostic counselling and risk disclosure in PD, as well as highlight future perspectives that may emerge with the development of new biomarkers and their anticipated impact on the definition of PD. Plain Language Summary: An important goal of Parkinson's disease research is to diagnose the disease at an earlier stage, even before the typical motor symptoms appear, in the so-called 'prodromal phase'. Currently, there are no treatments available that can slow down or prevent disease progression in this early phase, even though many of the early symptoms are treatable. This raises ethical questions about whether people want to know their future risk of Parkinson's and, if so, how this information should be given. This article summarizes the current state of knowledge, but also open questions about risk disclosure in the prodromal phase of Parkinson's. Previous studies have shown that many people with early symptoms of Parkinson's would like to know their risk, but that the individual's wish to know (or not to know) must first be ascertained and respected. Future studies need to find out whether very early diagnosis of Parkinson's might have an impact on people affected, for example in terms of psychological stress or anxiety, and whether cultural background might influence attitudes to risk disclosure. Furthermore, it is expected that in the future it will be possible to make an early diagnosis of Parkinson's using specific new techniques, e.g., by testing spinal fluid. It is of utmost importance to find out if and how test results of these new techniques should be communicated to patients, even if they do not lead to direct medical treatment. [ABSTRACT FROM AUTHOR]

Objective: We aim to analyze the efficacy and safety of TMS on cognition in mild cognitive impairment (MCI), Alzheimer's disease (AD), AD-related dementias, and nondementia conditions with comorbid cognitive impairment. Design: Systematic review, Meta-Analysis Setting: We searched MEDLINE, Embase, Cochrane database, APA PsycINFO, Web of Science, and Scopus from January 1, 2000, to February 9, 2023. Participants and interventions: RCTs, open-label, and case series studies reporting cognitive outcomes following TMS intervention were included. Measurement: Cognitive and safety outcomes were measured. Cochrane Risk of Bias for RCTs and MINORS (Methodological Index for Non-Randomized Studies) criteria were used to evaluate study quality. This study was registered with PROSPERO (CRD42022326423). Results: The systematic review included 143 studies (n = 5,800 participants) worldwide, encompassing 94 RCTs, 43 open-label prospective, 3 open-label retrospective, and 3 case series. The meta-analysis included 25 RCTs in MCI and AD. Collectively, these studies provide evidence of improved global and specific cognitive measures with TMS across diagnostic groups. Only 2 studies (among 143) reported 4 adverse events of seizures: 3 were deemed TMS unrelated and another resolved with coil repositioning. Meta-analysis showed large effect sizes on global cognition (Mini-Mental State Examination (SMD = 0.80 [0.26, 1.33], p = 0.003), Montreal Cognitive Assessment (SMD = 0.85 [0.26, 1.44], p = 0.005), Alzheimer's Disease Assessment Scale–Cognitive Subscale (SMD = −0.96 [−1.32, −0.60], p < 0.001)) in MCI and AD, although with significant heterogeneity. Conclusion: The reviewed studies provide favorable evidence of improved cognition with TMS across all groups with cognitive impairment. TMS was safe and well tolerated with infrequent serious adverse events. [ABSTRACT FROM AUTHOR]

Cognitive decline in Alzheimer's disease is associated with electroencephalographic (EEG) biosignatures even at early stages of mild cognitive impairment (MCI). The aim of this work is to provide a unified measure of cognitive decline by aggregating biosignatures from multiple EEG modalities and to evaluate repeatability of the composite measure at an individual level. These modalities included resting state EEG (eyes-closed) and two event-related potential (ERP) tasks on visual memory and attention. We compared individuals with MCI (n = 38) to age-matched healthy controls HC (n = 44). In resting state EEG, the MCI group exhibited higher power in Theta (3-7Hz) and lower power in Beta (13-20Hz) frequency bands. In both ERP tasks, the MCI group exhibited reduced ERP late positive potential (LPP), delayed ERP early component latency, slower reaction time, and decreased response accuracy. Cluster-based permutation analysis revealed significant clusters of difference between the MCI and HC groups in the frequency-channel and time-channel spaces. Cluster-based measures and performance measures (12 biosignatures in total) were selected as predictors of MCI. We trained a support vector machine (SVM) classifier achieving AUC = 0.89, accuracy = 77% in cross-validation using all data. Split-data validation resulted in (AUC = 0.87, accuracy = 76%) and (AUC = 0.75, accuracy = 70%) on testing data at baseline and follow-up visits, respectively. Classification scores at baseline and follow-up visits were correlated (r = 0.72, p<0.001, ICC = 0.84), supporting test-retest reliability of EEG biosignature. These results support the utility of EEG/ERP for prognostic testing, repeated assessments, and tracking potential treatment outcomes in the limited duration of clinical trials. [ABSTRACT FROM AUTHOR]

To investigate the feasibility and acceptability of SleepWell24, a multicomponent, evidence-based smartphone application, to improve positive airway pressure therapy (PAP) adherence, among patients with obstructive sleep apnea (OSA) naive to PAP. In a single-blind randomized controlled trial, SleepWell24, with a companion activity monitor was compared to usual care plus the activity monitor and its associated app. SleepWell24 provides objective feedback on PAP usage and sleep/physical activity patterns, and chronic disease management. Patients were recruited from two sleep medicine centers and followed over the first 60 days of PAP. Feasibility and acceptability were measured by recruitment/retention rates, app usage, differences in post-trial Treatment Evaluation Questionnaire (TEQ) scores, and patient interviews. Exploratory, intent-to-treat logistic and linear mixed models estimated PAP adherence and clinical outcomes. Of 103 eligible participants, 87 were enrolled (SleepWell24 n = 40, control n = 47; mean 57.6y [SD = 12.3], 44.8% female). Retention was ≥95% across arms. There were no significant differences in TEQ scores. SleepWell24 participants engaged with the app on 62.9% of trial days. PAP use was high across both arms (SleepWell24 vs. Control: mean hours 5.98 vs. 5.86). There were no differences in PAP adherence or clinical outcomes. SleepWell24 was feasible and acceptable among PAP-naive patients with OSA. NCT03156283 [ABSTRACT FROM AUTHOR]

When discussing AED conversion in the clinic, both the patient and physician perspectives on the goals and risks of this change are important to consider. To identify patient-reported and clinician-perceived concerns, a panel of epilepsy specialists was questioned about the topics discussed with patients and the clinician's perspective of patient concerns. Findings of a literature review of articles that report patient-expressed concerns regarding their epilepsy and treatment were also reviewed. Results showed that the specialist panel appropriately identified patient-reported concerns of driving ability, medication cost, seizure control, and medication side effects. Additionally, patient-reported concerns of independence, employment issues, social stigma, medication dependence, and undesirable cognitive effects are important to address when considering and initiating AED conversion.