Practicalities (and real-life experiences) of dementia in adults with Down syndrome.

Adults with down syndrome (DS) have a lifetime dementia risk in excess of 95%, with a median age of onset of 55 years, due to trisomy 21. Co-occurring Alzheimer's disease (AD) has increased morbidity and mortality, and it is now recommended to screen for AD in all adults with DS beginning at 40 years of age. In this manuscript, we present two clinical cases of adults with DS who developed AD summarizing their medical histories, presenting symptoms, path to diagnosis and psychosocial aspects of care collected from retrospective chart review with caregiver consent. These two cases were chosen due to their complexity and interwoven nature of the medical and psychosocial aspects, and highlight the complexity and nuance of caring for patients with DS and AD.

Sleep functional connectivity, hyperexcitability, and cognition in Alzheimer's disease.

INTRODUCTION: Sleep disturbances are common in Alzheimer's disease (AD) and may reflect pathologic changes in brain networks. To date, no studies have examined changes in sleep functional connectivity (FC) in AD or their relationship with network hyperexcitability and cognition. METHODS: We assessed electroencephalogram (EEG) sleep FC in 33 healthy controls, 36 individuals with AD without epilepsy, and 14 individuals with AD and epilepsy. RESULTS: AD participants showed increased gamma connectivity in stage 2 sleep (N2), which was associated with longitudinal cognitive decline. Network hyperexcitability in AD was associated with a distinct sleep connectivity signature, characterized by decreased N2 delta connectivity and reversal of several connectivity changes associated with AD. Machine learning algorithms using sleep connectivity features accurately distinguished diagnostic groups and identified "fast cognitive decliners" among study participants who had AD. DISCUSSION: Our findings reveal changes in sleep functional networks associated with cognitive decline in AD and may have implications for disease monitoring and therapeutic development. HIGHLIGHTS: Brain functional connectivity (FC) in Alzheimer's disease is altered during sleep. Sleep FC measures correlate with cognitive decline in AD. Network hyperexcitability in AD has a distinct sleep connectivity signature.

Epilepsy and sleep characteristics are associated with diminished 24-h memory retention in older adults with epilepsy.

OBJECTIVE: Individuals with epilepsy often have memory difficulties, and older adults with epilepsy are especially vulnerable, due to the additive effect of aging. The goal of this study was to assess factors that are associated with 24-h memory retention in older adults with epilepsy. METHODS: Fifty-five adults with epilepsy, all aged >50 years, performed a declarative memory task involving the recall of the positions of 15 card pairs on a computer screen prior to a 24-h ambulatory electroencephalogram (EEG). We assessed the percentage of encoded card pairs that were correctly recalled after 24 h (24-h retention rate). EEGs were evaluated for the presence and frequency of scalp interictal epileptiform activity (IEA) and scored for total sleep. Global slow wave activity (SWA) power during non-rapid eye movement sleep was also calculated. RESULTS: Forty-four participants successfully completed the memory task. Two were subsequently excluded due to seizures on EEG. The final cohort (n = 42) had a mean age of 64.3 ± 7.5 years, was 52% female, and had an average 24-h retention rate of 70.9% ± 30.2%. Predictors of 24-h retention based on multivariate regression analysis when controlling for age, sex, and education included number of antiseizure medications (ß = -.20, p = .013), IEA frequency (ß = -.08, p = .0094), and SWA power (ß = +.002, p = .02). SIGNIFICANCE: In older adults with epilepsy, greater frequency of IEA, reduced SWA power, and higher burden of antiseizure medications correlated with worse 24-h memory retention. These factors represent potential treatment targets to improve memory in older adults with epilepsy.

Interventions to Reduce Opioid Use in Youth At-Risk and in Treatment for Substance Use Disorders: A Scoping Review.

BACKGROUND: Youth and young adults have been significantly impacted by the opioid overdose and health crisis in North America. There is evidence of increasing morbidity and mortality due to opioids among those aged 15-29. Our review of key international reports indicates there are few youth-focused interventions and treatments for opioid use. Our scoping review sought to identify, characterize, and qualitatively evaluate the youth-specific clinical and pre-clinical interventions for opioid use among youth. METHOD: We searched MedLine and PsycInfo for articles that were published between 2013 and 2021. Previous reports published in 2015 and 2016 did not identify opioid-specific interventions for youth and we thus focused on the time period following the periods covered by these prior reports. We input three groups of relevant keywords in the aforementioned search engines. Specifically, articles were included if they targeted a youth population (ages 15-25), studied an intervention, and measured impacts on opioid use. RESULTS: We identified 21 studies that examined the impacts of heterogeneous interventions on youth opioid consumption. The studies were classified inductively as psycho-social-educational, pharmacological, or combined pharmacological-psycho-social-educational. Most studies focused on treatment of opioid use disorder among youth, with few studies focused on early or experimental stages of opioid use. A larger proportion of studies focused heavily on male participants (i.e., male gender and/or sex). Very few studies involved and/or included youth in treatment/program development, with one study premised on previous research about sexual minority youth. CONCLUSIONS: Research on treatments and interventions for youth using or at-risk of opioids appears to be sparse. More youth involvement in research and program development is vital. The intersectional and multi-factorial nature of youth opioid use and the youth opioid crisis necessitates the development and evaluation of novel treatments that address youth-specific contexts and needs (i.e., those that address socio-economic, neurobiological, psychological, and environmental factors that promote opioid use among youth).

SUDEP education among U.S. and international neurology trainees.

We evaluated baseline sudden unexpected death in epilepsy (SUDEP) knowledge and counseling practices among national and international adult neurology trainees with a 12-question online survey. The survey was emailed to all 169 U.S. neurology residency program directors and select international neurology/epilepsy program leaders. Program leaders were asked to distribute the survey link to adult neurology trainees. There were 161 respondents in the U.S. and 171 respondents outside the U.S. The latter were from 25 Latin American, European, Asian, and African countries. More than 90% of all trainees reported familiarity with SUDEP definition. Familiarity with SUDEP risk factors and mitigation measures ranged from 56% to 67% across these groups, with international trainees slightly more familiar with risk factors (67% vs. 61% in U.S.) but less familiar with mitigation measures (56% vs. 63% in U.S.). Approximately half of national (49%) and international (54%) trainees rarely or never counseled patients on SUDEP. Less than half of national (44%) and international (41%) trainees were educated about SUDEP. Many U.S. and adult neurology trainees remain unfamiliar with SUDEP risk factors and mitigation measures. Sudden unexpected death in epilepsy counseling falls below recommended standards. We suggest that worldwide neurology training programs' leaderships consider improving SUDEP education targeted at adult neurology trainees.

Measures of resting state EEG rhythms for clinical trials in Alzheimer's disease: Recommendations of an expert panel.

The Electrophysiology Professional Interest Area (EPIA) and Global Brain Consortium endorsed recommendations on candidate electroencephalography (EEG) measures for Alzheimer's disease (AD) clinical trials. The Panel reviewed the field literature. As most consistent findings, AD patients with mild cognitive impairment and dementia showed abnormalities in peak frequency, power, and "interrelatedness" at posterior alpha (8-12 Hz) and widespread delta (< 4 Hz) and theta (4-8 Hz) rhythms in relation to disease progression and interventions. The following consensus statements were subscribed: (1) Standardization of instructions to patients, resting state EEG (rsEEG) recording methods, and selection of artifact-free rsEEG periods are needed; (2) power density and "interrelatedness" rsEEG measures (e.g., directed transfer function, phase lag index, linear lagged connectivity, etc.) at delta, theta, and alpha frequency bands may be use for stratification of AD patients and monitoring of disease progression and intervention; and (3) international multisectoral initiatives are mandatory for regulatory purposes.

Widespread changes in network activity allow non-invasive detection of mesial temporal lobe seizures.

Decades of experience with intracranial recordings in patients with epilepsy have demonstrated that seizures can occur in deep cortical regions such as the mesial temporal lobes without showing any obvious signs of seizure activity on scalp electroencephalogram. Predicated on the idea that these seizures are purely focal, currently, the only way to detect these 'scalp-negative seizures' is with intracranial recordings. However, intracranial recordings are only rarely performed in patients with epilepsy, and are almost never performed outside of the context of epilepsy. As such, little is known about scalp-negative seizures and their role in the natural history of epilepsy, their effect on cognitive function, and their association with other neurological diseases. Here, we developed a novel approach to non-invasively identify scalp-negative seizures arising from the mesial temporal lobe based on scalp electroencephalogram network connectivity measures. We identified 25 scalp-negative mesial temporal lobe seizures in 10 patients and obtained control records from an additional 13 patients, all of whom underwent recordings with foramen ovale electrodes and scalp electroencephalogram. Scalp data from these records were used to train a scalp-negative seizure detector, which consisted of a pair of logistic regression classifiers that used scalp electroencephalogram coherence properties as input features. On cross-validation performance, this detector correctly identified scalp-negative seizures in 40% of patients, and correctly identified the side of seizure onset for each seizure detected. In comparison, routine clinical interpretation of these scalp electroencephalograms failed to identify any of the scalp-negative seizures. Among the patients in whom the detector raised seizure alarms, 80% had scalp-negative mesial temporal lobe seizures. The detector had a false alarm rate of only 0.31 per day and a positive predictive value of 75%. Of the 13 control patients, false seizure alarms were raised in only one patient. The fact that our detector specifically recognizes focal mesial temporal lobe seizures based on scalp electroencephalogram coherence features, lends weight to the hypothesis that even focal seizures are a network phenomenon that involve widespread neural connectivity. Our scalp-negative seizure detector has clear clinical utility in patients with temporal lobe epilepsy, and its potential easily translates to other neurological disorders, such as Alzheimer's disease, in which occult mesial temporal lobe seizures are suspected to play a significant role. Importantly, our work establishes a novel approach of using computational approaches to non-invasively detect deep seizure activity, without the need for invasive intracranial recordings.

Medication prescribing and patient-reported outcome measures in people with epilepsy in Bhutan.

OBJECTIVE: The aim of this study was to assess medication prescribing and patient-reported outcomes among people with epilepsy (PWE) in Bhutan and introduce criteria for evaluating unmet epilepsy care needs, particularly in resource-limited settings. METHODS: People with epilepsy in Bhutan (National Referral Hospital, 2014-2015) completed a questionnaire, the Quality of Life in Epilepsy Inventory (QOLIE-31), and an electroencephalogram (EEG). Management gap was the proportion of participants meeting any of six prespecified criteria based on best practices and the National Institute for Health and Care Excellence (NICE) guidelines. RESULTS: Among 253 participants (53% female, median: 24years), 93% (n=235) were treated with antiepileptic drugs (AEDs). Seventy-two percent (n=183) had active epilepsy (≥1 seizure in the prior year). At least one criterion was met by 55% (n=138) of participants, whereas the treatment gap encompassed only 5% (n=13). The criteria were the following: 1. Among 18 participants taking no AED, 72% (n=13) had active epilepsy. 2. Among 26 adults on subtherapeutic monotherapy, 46% (n=12) had active epilepsy. 3. Among 48 participants reporting staring spells, 56% (n=27) were treated with carbamazepine or phenytoin. 4. Among 101 female participants aged 14-40years, 23% (n=23) were treated with sodium valproate. 5. Among 67 participants reporting seizure-related injuries, 87% (n=58) had active epilepsy. 6. Among 111 participants with a QOLIE-31 score below 50/100, 77% (n=86) had active epilepsy. Years since first AED treatment (odds ratio: 1.07, 95% CI: 1.03, 1.12) and epileptiform discharges on EEG (odds ratio: 1.95, 95% CI: 1.15, 3.29) were significantly associated with more criteria met. CONCLUSIONS: By defining the management gap, subpopulations at greatest need for targeted interventions may be prioritized, including those already taking AEDs.

Differential interaction of tomosyn with syntaxin and SNAP25 depends on domains in the WD40 ß-propeller core and determines its inhibitory activity.

Neuronal exocytosis depends on efficient formation of soluble N-ethylmaleimide-sensitive factor attachment protein receptor (SNARE) complexes and is regulated by tomosyn, a SNARE-binding protein. To gain new information about tomosyn's activity, we characterized its mobility and organization on the plasma membrane (PM) in relation to other SNARE proteins and inhibition of exocytosis. By using direct stochastic optical reconstruction microscopy (dSTORM), we found tomosyn to be organized in small clusters adjacent to syntaxin clusters. In addition, we show that tomosyn is present in both syntaxin-tomosyn complexes and syntaxin-SNAP25-tomosyn complexes. Tomosyn mutants that lack residues 537-578 or 897-917 from its ß-propeller core diffused faster on the PM and exhibited reduced binding to SNAP25, suggesting that these mutants shift the equilibrium between tomosyn-syntaxin-SNAP25 complexes on the PM to tomosyn-syntaxin complexes. As these deletion mutants impose less inhibition on exocytosis, we suggest that tomosyn inhibition is mediated via tomosyn-syntaxin-SNAP25 complexes and not tomosyn-syntaxin complexes. These findings characterize, for the first time, tomosyn's dynamics at the PM and its relation to its inhibition of exocytosis.

Cell intrinsic mechanical regulation of plasma membrane accumulation at the cytokinetic furrow.

Cytokinesis is the process where the mother cell's cytoplasm separates into daughter cells. This is driven by an actomyosin contractile ring that produces cortical contractility and drives cleavage furrow ingression, resulting in the formation of a thin intercellular bridge. While cytoskeletal reorganization during cytokinesis has been extensively studied, little is known about the spatiotemporal dynamics of the plasma membrane. Here, we image and model plasma membrane lipid and protein dynamics on the cell surface during leukemia cell cytokinesis. We reveal an extensive accumulation and folding of plasma membrane at the cleavage furrow and the intercellular bridge, accompanied by a depletion and unfolding of plasma membrane at the cell poles. These membrane dynamics are caused by two actomyosin-driven biophysical mechanisms: the radial constriction of the cleavage furrow causes local compression of the apparent cell surface area and accumulation of the plasma membrane at the furrow, while actomyosin cortical flows drag the plasma membrane towards the cell division plane as the furrow ingresses. The magnitude of these effects depends on the plasma membrane fluidity, cortex adhesion and cortical contractility. Overall, our work reveals cell intrinsic mechanical regulation of plasma membrane accumulation at the cleavage furrow that is likely to generate localized differences in membrane tension across the cytokinetic cell. This may locally alter endocytosis, exocytosis and mechanotransduction, while also serving as a self-protecting mechanism against cytokinesis failures that arise from high membrane tension at the intercellular bridge.

Precision off-the-shelf natural killer cell therapies for oncology with logic-gated gene circuits.

Acute myeloid leukemia (AML) is an aggressive disease with a poor prognosis (5-year survival rate of 30.5% in the United States). Designing cell therapies to target AML is challenging because no single tumor-associated antigen (TAA) is highly expressed on all cancer subpopulations. Furthermore, TAAs are also expressed on healthy cells, leading to toxicity risk. To address these targeting challenges, we engineer natural killer (NK) cells with a multi-input gene circuit consisting of chimeric antigen receptors (CARs) controlled by OR and NOT logic gates. The OR gate kills a range of AML cells from leukemic stem cells to blasts using a bivalent CAR targeting FLT3 and/or CD33. The NOT gate protects healthy hematopoietic stem cells (HSCs) using an inhibitory CAR targeting endomucin, a protective antigen unique to healthy HSCs. NK cells with the combined OR-NOT gene circuit kill multiple AML subtypes and protect primary HSCs, and the circuit also works in vivo.

Investigating the relationship between feed and helminthic burden of captive birds of prey in Hong Kong.

The life cycle of most parasitic helminthes is related to their hosts feeding habits. Thus we need to investigate the impact of diet on the host's helminthic parasite burden. Not many studies in captive raptors have been conducted and published regarding parasitic infections. The aim of this study is to evaluate the helminthic burden of raptors kept in captivity and establish a relationship with the feed provided. A total of N = 51 different species of captive birds of prey were fed different diets consisting in different combinations of day old chicks, chicken breast, whole chicken carcass and mice. Their feces were sampled and the parasite burden was determined. A negative binomial model was successfully fitted to the data and the feeds "mice" (P < 0.001) and "whole chicken carcass" (P < 0.001) significantly contributed to an increase in the observed burden. Significant differences were also found between species (P < 0.001). Raptors fed adult animal carcasses and offal may explain the increase in the observed burden as these feeds have a larger probability of being contaminated by a larger variety of helminthic fauna.

Dementia detection from brain activity during sleep.

STUDY OBJECTIVES: Dementia is a growing cause of disability and loss of independence in the elderly, yet remains largely underdiagnosed. Early detection and classification of dementia can help close this diagnostic gap and improve management of disease progression. Altered oscillations in brain activity during sleep are an early feature of neurodegenerative diseases and be used to identify those on the verge of cognitive decline. METHODS: Our observational cross-sectional study used a clinical dataset of 10 784 polysomnography from 8044 participants. Sleep macro- and micro-structural features were extracted from the electroencephalogram (EEG). Microstructural features were engineered from spectral band powers, EEG coherence, spindle, and slow oscillations. Participants were classified as dementia (DEM), mild cognitive impairment (MCI), or cognitively normal (CN) based on clinical diagnosis, Montreal Cognitive Assessment, Mini-Mental State Exam scores, clinical dementia rating, and prescribed medications. We trained logistic regression, support vector machine, and random forest models to classify patients into DEM, MCI, and CN groups. RESULTS: For discriminating DEM versus CN, the best model achieved an area under receiver operating characteristic curve (AUROC) of 0.78 and area under precision-recall curve (AUPRC) of 0.22. For discriminating MCI versus CN, the best model achieved an AUROC of 0.73 and AUPRC of 0.18. For discriminating DEM or MCI versus CN, the best model achieved an AUROC of 0.76 and AUPRC of 0.32. CONCLUSIONS: Our dementia classification algorithms show promise for incorporating dementia screening techniques using routine sleep EEG. The findings strengthen the concept of sleep as a window into neurodegenerative diseases.

EEG Entropy in REM Sleep as a Physiologic Biomarker in Early Clinical Stages of Alzheimer's Disease.

BACKGROUND: Alzheimer's disease (AD) is associated with EEG changes across the sleep-wake cycle. As the brain is a non-linear system, non-linear EEG features across behavioral states may provide an informative physiologic biomarker of AD. Multiscale fluctuation dispersion entropy (MFDE) provides a sensitive non-linear measure of EEG information content across a range of biologically relevant time-scales. OBJECTIVE: To evaluate MFDE in awake and sleep EEGs as a potential biomarker for AD. METHODS: We analyzed overnight scalp EEGs from 35 cognitively normal healthy controls, 23 participants with mild cognitive impairment (MCI), and 19 participants with mild dementia due to AD. We examined measures of entropy in wake and sleep states, including a slow-to-fast-activity ratio of entropy (SFAR-entropy). We compared SFAR-entropy to linear EEG measures including a slow-to-fast-activity ratio of power spectral density (SFAR-PSD) and relative alpha power, as well as to cognitive function. RESULTS: SFAR-entropy differentiated dementia from MCI and controls. This effect was greatest in REM sleep, a state associated with high cholinergic activity. Differentiation was evident in the whole brain EEG and was most prominent in temporal and occipital regions. Five minutes of REM sleep was sufficient to distinguish dementia from MCI and controls. Higher SFAR-entropy during REM sleep was associated with worse performance on the Montreal Cognitive Assessment. Classifiers based on REM sleep SFAR-entropy distinguished dementia from MCI and controls with high accuracy, and outperformed classifiers based on SFAR-PSD and relative alpha power. CONCLUSION: SFAR-entropy measured in REM sleep robustly discriminates dementia in AD from MCI and healthy controls.

Altered Sleep Microarchitecture and Cognitive Impairment in Patients With Temporal Lobe Epilepsy.

BACKGROUND AND OBJECTIVES: To investigate the spatiotemporal characteristics of sleep waveforms in temporal lobe epilepsy (TLE) and examine their association with cognition. METHODS: In this retrospective, cross-sectional study, we examined overnight EEG data from adult patients with TLE and nonepilepsy comparisons (NECs) admitted to the epilepsy monitoring unit at Mass General Brigham hospitals. Automated algorithms were used to characterize sleep macroarchitecture (sleep stages) and microarchitecture (spindles, slow oscillations [SOs]) on scalp EEG and to detect hippocampal interictal epileptiform discharges (hIEDs) from foramen ovale electrodes simultaneously recorded in a subset of patients with TLE. We examined the association of sleep features and hIEDs with memory and executive function from clinical neuropsychological evaluations. RESULTS: A total of 81 adult patients with TLE and 28 NEC adult patients were included with similar mean ages. There were no significant differences in sleep macroarchitecture between groups, including relative time spent in each sleep stage, sleep efficiency, and sleep fragmentation. By contrast, the spatiotemporal characteristics of sleep microarchitecture were altered in TLE compared with NEC and were associated with cognitive impairments. Specifically, we observed a ∼30% reduction in spindle density in patients with TLE compared with NEC, which was significantly associated with worse memory performance. Spindle-SO coupling strength was also reduced in TLE and, in contrast to spindles, was associated with diminished executive function. We found no significant association between sleep macroarchitectural and microarchitectural parameters and hIEDs. DISCUSSION: There is a fundamental alteration of sleep microarchitecture in TLE, characterized by a reduction in spindle density and spindle-SO coupling, and these changes may contribute to neurocognitive comorbidity in this disorder.

Utility of Amyloid Positron Emission Tomography Imaging in Older Adults With Epilepsy and Cognitive Decline.

In older adults with cognitive decline and epilepsy, diagnosing the etiology of cognitive decline is challenging. We identified 6 subjects enrolled in the Imaging Dementia-Evidence of Amyloid Imaging Scanning (IDEAS) study and nonlesional epilepsy. Three cognitive neurologists reviewed each case to determine the likelihood of underlying Alzheimer's disease (AD) pathology. Their impressions were compared to amyloid PET findings. In 3 cases the impression was concordant with PET findings. In 2 cases "possibly suggestive," the PET reduced diagnostic uncertainty, with 1 having a PET without elevated amyloid and the other PET with intermediate amyloid. In the remaining case with lack of reviewer concordance, the significance of PET with elevated amyloid remains uncertain. This case series highlights that in individuals with a history of epilepsy and cognitive decline, amyloid PET can be a useful tool in evaluating the etiology of cognitive decline when used in an appropriate context.

Prevalence and localization of nocturnal epileptiform discharges in mild cognitive impairment.

Recent evidence shows that identifying and treating epileptiform abnormalities in patients with Alzheimer's disease could represent a potential avenue to improve clinical outcome. Specifically, animal and human studies have revealed that in the early phase of Alzheimer's disease, there is an increased risk of seizures. It has also been demonstrated that the administration of anti-seizure medications can slow the functional progression of the disease only in patients with EEG signs of cortical hyperexcitability. In addition, although it is not known at what disease stage hyperexcitability emerges, there remains no consensus regarding the imaging and diagnostic methods best able to detect interictal events to further distinguish different phenotypes of Alzheimer's disease. In this exploratory work, we studied 13 subjects with amnestic mild cognitive impairment and 20 healthy controls using overnight high-density EEG with 256 channels. All participants also underwent MRI and neuropsychological assessment. Electronic source reconstruction was also used to better select and localize spikes. We found spikes in six of 13 (46%) amnestic mild cognitive impairment compared with two of 20 (10%) healthy control participants (P = 0.035), representing a spike prevalence similar to that detected in previous studies of patients with early-stage Alzheimer's disease. The interictal events were low-amplitude temporal spikes more prevalent during non-rapid eye movement sleep. No statistically significant differences were found in cognitive performance between amnestic mild cognitive impairment patients with and without spikes, but a trend in immediate and delayed memory was observed. Moreover, no imaging findings of cortical and subcortical atrophy were found between amnestic mild cognitive impairment participants with and without epileptiform spikes. In summary, our exploratory study shows that patients with amnestic mild cognitive impairment reveal EEG signs of hyperexcitability early in the disease course, while no other significant differences in neuropsychological or imaging features were observed among the subgroups. If confirmed with longitudinal data, these exploratory findings could represent one of the first signatures of a preclinical epileptiform phenotype of amnestic mild cognitive impairment and its progression.

On-demand EEG education through competition - A novel, app-based approach to learning to identify interictal epileptiform discharges.

Objective: Misinterpretation of EEGs harms patients, yet few resources exist to help trainees practice interpreting EEGs. We therefore sought to evaluate a novel educational tool to teach trainees how to identify interictal epileptiform discharges (IEDs) on EEG. Methods: We created a public EEG test within the iOS app DiagnosUs using a pool of 13,262 candidate IEDs. Users were shown a candidate IED on EEG and asked to rate it as epileptiform (IED) or not (non-IED). They were given immediate feedback based on a gold standard. Learning was analyzed using a parametric model. We additionally analyzed IED features that best correlated with expert ratings. Results: Our analysis included 901 participants. Users achieved a mean improvement of 13% over 1,000 questions and an ending accuracy of 81%. Users and experts appeared to rely on a similar set of IED morphologic features when analyzing candidate IEDs. We additionally identified particular types of candidate EEGs that remained challenging for most users even after substantial practice. Conclusions: Users improved in their ability to properly classify candidate IEDs through repeated exposure and immediate feedback. Significance: This app-based learning activity has great potential to be an effective supplemental tool to teach neurology trainees how to accurately identify IEDs on EEG.

Decoding information about cognitive health from the brainwaves of sleep.

Sleep electroencephalogram (EEG) signals likely encode brain health information that may identify individuals at high risk for age-related brain diseases. Here, we evaluate the correlation of a previously proposed brain age biomarker, the "brain age index" (BAI), with cognitive test scores and use machine learning to develop and validate a series of new sleep EEG-based indices, termed "sleep cognitive indices" (SCIs), that are directly optimized to correlate with specific cognitive scores. Three overarching cognitive processes were examined: total, fluid (a measure of cognitive processes involved in reasoning-based problem solving and susceptible to aging and neuropathology), and crystallized cognition (a measure of cognitive processes involved in applying acquired knowledge toward problem-solving). We show that SCI decoded information about total cognition (Pearson's r = 0.37) and fluid cognition (Pearson's r = 0.56), while BAI correlated only with crystallized cognition (Pearson's r = - 0.25). Overall, these sleep EEG-derived biomarkers may provide accessible and clinically meaningful indicators of neurocognitive health.