Alden, Eva C

Abstract Temporal lobe epilepsy is a common neurological disease characterized by recurrent seizures that often originate within limbic networks involving amygdala and hippocampus. The limbic network is involved in crucial physiologic functions involving memory, emotion and sleep. Temporal lobe epilepsy is frequently drug-resistant, and people often experience comorbidities related to memory, mood and sleep. Deep brain stimulation targeting the anterior nucleus of the thalamus (ANT-DBS) is an established therapy for temporal lobe epilepsy. However, the optimal stimulation parameters and their impact on memory, mood and sleep comorbidities remain unclear. We used an investigational brain sensing-stimulation implanted device to accurately track seizures, interictal epileptiform spikes (IES), and memory, mood and sleep comorbidities in five ambulatory subjects. Wireless streaming of limbic network local field potentials (LFPs) and subject behaviour were captured on a mobile device integrated with a cloud environment. Automated algorithms applied to the continuous LFPs were used to accurately cataloged seizures, IES and sleep-wake brain state. Memory and mood assessments were remotely administered to densely sample cognitive and behavioural response during ANT-DBS in ambulatory subjects living in their natural home environment. We evaluated the effect of continuous low-frequency and duty cycle high-frequency ANT-DBS on epileptiform activity and memory, mood and sleep comorbidities. Both low-frequency and high-frequency ANT-DBS paradigms reduced seizures. However, continuous low-frequency ANT-DBS showed greater reductions in IES, electrographic seizures and better sleep and memory outcomes. These results highlight the potential of synchronized brain sensing and dense behavioural tracking during ANT-DBS for optimizing neuromodulation therapy. While studies with larger patient numbers are needed to validate the benefits of low-frequency ANT-DBS, these findings are potentially translatable to individuals currently implanted with ANT-DBS systems.

Abstract Introduction The aim of this study was to develop a conditional normative model for Rey's Auditory Verbal Learning Test (AVLT) that accounts for practice effects. Methods In our normative sample, robust conditional norms were derived from 1001 cognitively unimpaired (CU) adults ages 50 to 89 who completed the AVLT up to eight times. Linear mixed‐effects models adjusted for baseline performance, prior test exposures, time, demographics, and interaction terms. In our preliminary validation, mean performance on conditional and typical normative scores across two to four completed follow‐up tests in preclinical Alzheimer's disease participants at baseline with positive amyloid and tau positron emission ( n = 27 CU amyloid [A]+tau[T]+) was compared to biomarker negative individuals ( n = 269 CU A–T–). Results AVLT performance using typical norms did not differ across A+T+ and A–T– groups. Conditional norms z‐scores were lower in the A+T+ relative to the A–T– group for 30‐minute recall ( P = .033) and sum of trials ( P = .030). Discussion Conditional normative methods that account for practice effects show promise for identifying longitudinal cognitive decline.

Abstract Objective Individuals with early-onset dysexecutive Alzheimer’s disease (dAD) have high rates of failed performance validity testing (PVT), which can lead to symptom misinterpretation and misdiagnosis. Method The aim of this retrospective study is to evaluate rates of failure on a common PVT, the test of memory malingering (TOMM), in a sample of clinical patients with biomarker-confirmed early-onset dAD who completed neuropsychological testing. Results We identified seventeen patients with an average age of symptom onset at 52.25 years old. Nearly fifty percent of patients performed below recommended cut-offs on Trials 1 and 2 of the TOMM. Four of six patients who completed outside neuropsychological testing were misdiagnosed with alternative etiologies to explain their symptomatology, with two of these patients’ performances deemed unreliable based on the TOMM. Conclusions Low scores on the TOMM should be interpreted in light of contextual and optimally biological information and do not necessarily rule out a neurodegenerative etiology.

AbstractIntroductionThis study evaluated the diagnostic accuracy of the Cogstate Brief Battery (CBB) for mild cognitive impairment (MCI) and prodromal Alzheimer's disease (AD) in a population‐based sample.MethodsParticipants included adults ages 50+ classified as cognitively unimpaired (CU, n = 2866) or MCI (n = 226), and a subset with amyloid (A) and tau (T) positron emission tomography who were AD biomarker negative (A–T–) or had prodromal AD (A+T+).ResultsDiagnostic accuracy of the Learning/Working Memory Composite (Lrn/WM) for discriminating all CU and MCI was moderate (area under the curve [AUC] = 0.75), but improved when discriminating CU A–T– and MCI A+T+ (AUC = 0.93) and when differentiating MCI participants without AD biomarkers from those with prodromal AD (AUC = 0.86). Conventional cut‐offs yielded lower than expected sensitivity for both MCI (38%) and prodromal AD (73%).DiscussionClinical utility of the CBB for detecting MCI in a population‐based sample is lower than expected. Caution is needed when using currently available CBB normative data for clinical interpretation.