Abnormal gamma phase-amplitude coupling in the parahippocampal cortex is associated with network hyperexcitability in Alzheimer's disease.

While animal models of Alzheimer's disease (AD) have shown altered gamma oscillations (∼40 Hz) in local neural circuits, the low signal-to-noise ratio of gamma in the resting human brain precludes its quantification via conventional spectral estimates. Phase-amplitude coupling (PAC) indicating the dynamic integration between the gamma amplitude and the phase of low-frequency (4-12 Hz) oscillations is a useful alternative to capture local gamma activity. In addition, PAC is also an index of neuronal excitability as the phase of low-frequency oscillations that modulate gamma amplitude, effectively regulates the excitability of local neuronal firing. In this study, we sought to examine the local neuronal activity and excitability using gamma PAC, within brain regions vulnerable to early AD pathophysiology-entorhinal cortex and parahippocampus, in a clinical population of patients with AD and age-matched controls. Our clinical cohorts consisted of a well-characterized cohort of AD patients (n = 50; age, 60 ± 8 years) with positive AD biomarkers, and age-matched, cognitively unimpaired controls (n = 35; age, 63 ± 5.8 years). We identified the presence or the absence of epileptiform activity in AD patients (AD patients with epileptiform activity, AD-EPI+, n = 20; AD patients without epileptiform activity, AD-EPI-, n = 30) using long-term electroencephalography (LTM-EEG) and 1-hour long magnetoencephalography (MEG) with simultaneous EEG. Using the source reconstructed MEG data, we computed gamma PAC as the coupling between amplitude of the gamma frequency (30-40 Hz) with phase of the theta (4-8 Hz) and alpha (8-12 Hz) frequency oscillations, within entorhinal and parahippocampal cortices. We found that patients with AD have reduced gamma PAC in the left parahippocampal cortex, compared to age-matched controls. Furthermore, AD-EPI+ patients showed greater reductions in gamma PAC than AD-EPI- in bilateral parahippocampal cortices. In contrast, entorhinal cortices did not show gamma PAC abnormalities in patients with AD. Our findings demonstrate the spatial patterns of altered gamma oscillations indicating possible region-specific manifestations of network hyperexcitability within medial temporal lobe regions vulnerable to AD pathophysiology. Greater deficits in AD-EPI+ suggests that reduced gamma PAC is a sensitive index of network hyperexcitability in AD patients. Collectively, the current results emphasize the importance of investigating the role of neural circuit hyperexcitability in early AD pathophysiology and explore its potential as a modifiable contributor to AD pathobiology.

Neurophysiological trajectories in Alzheimer's disease progression.

Alzheimer's disease (AD) is characterized by the accumulation of amyloid-ß and misfolded tau proteins causing synaptic dysfunction, and progressive neurodegeneration and cognitive decline. Altered neural oscillations have been consistently demonstrated in AD. However, the trajectories of abnormal neural oscillations in AD progression and their relationship to neurodegeneration and cognitive decline are unknown. Here, we deployed robust event-based sequencing models (EBMs) to investigate the trajectories of long-range and local neural synchrony across AD stages, estimated from resting-state magnetoencephalography. The increases in neural synchrony in the delta-theta band and the decreases in the alpha and beta bands showed progressive changes throughout the stages of the EBM. Decreases in alpha and beta band synchrony preceded both neurodegeneration and cognitive decline, indicating that frequency-specific neuronal synchrony abnormalities are early manifestations of AD pathophysiology. The long-range synchrony effects were greater than the local synchrony, indicating a greater sensitivity of connectivity metrics involving multiple regions of the brain. These results demonstrate the evolution of functional neuronal deficits along the sequence of AD progression.

Spatiotemporal characteristics of neurophysiological changes in patients with four-repeat tauopathies.

INTRODUCTION: Progressive supranuclear palsy (PSP) and corticobasal degeneration (CBD), are the most common four-repeat tauopathies (4RT), and both frequently occur with varying degree of Alzheimer's disease (AD) copathology. Intriguingly, patients with 4RT and patients with AD are at opposite ends of the wakefulness spectrum-AD showing reduced wakefulness and excessive sleepiness whereas 4RT showing decreased homeostatic sleep. The neural mechanisms underlying these distinct phenotypes in the comorbid condition of 4RT and AD are unknown. The objective of the current study was to define the alpha oscillatory spectrum, which is prominent in the awake resting-state in the human brain, in patients with primary 4RT, and how it is modified in comorbid AD-pathology. METHOD: In an autopsy-confirmed case series of 4R-tauopathy patients (n = 10), whose primary neuropathological diagnosis was either PSP (n = 7) or CBD (n = 3), using high spatiotemporal resolution magnetoencephalography (MEG), we quantified the spectral power density within alpha-band (8-12 Hz) and examined how this pattern was modified in increasing AD-copathology. For each patient, their regional alpha power was compared to an age-matched normative control cohort (n = 35). RESULT: Patients with 4RT showed increased alpha power but in the presence of AD-copathology alpha power was reduced. CONCLUSIONS: Alpha power increase in PSP-tauopathy and reduction in the presence of AD-tauopathy is consistent with the observation that neurons activating wakefulness-promoting systems are preserved in PSP but degenerated in AD. These results highlight the selectively vulnerable impacts in 4RT versus AD-tauopathy that may have translational significance on disease-modifying therapies for specific proteinopathies.

Cortical Synchrony and Information Flow during Transition from Wakefulness to Light Non-Rapid Eye Movement Sleep.

Sleep is a highly stereotyped phenomenon, requiring robust spatiotemporal coordination of neural activity. Understanding how the brain coordinates neural activity with sleep onset can provide insights into the physiological functions subserved by sleep and the pathologic phenomena associated with sleep onset. We quantified whole-brain network changes in synchrony and information flow during the transition from wakefulness to light non-rapid eye movement (NREM) sleep, using MEG imaging in a convenient sample of 14 healthy human participants (11 female; mean 63.4 years [SD 11.8 years]). We furthermore performed computational modeling to infer excitatory and inhibitory properties of local neural activity. The transition from wakefulness to light NREM was identified to be encoded in spatially and temporally specific patterns of long-range synchrony. Within the delta band, there was a global increase in connectivity from wakefulness to light NREM, which was highest in frontoparietal regions. Within the theta band, there was an increase in connectivity in fronto-parieto-occipital regions and a decrease in temporal regions from wakefulness to Stage 1 sleep. Patterns of information flow revealed that mesial frontal regions receive hierarchically organized inputs from broad cortical regions upon sleep onset, including direct inflow from occipital regions and indirect inflow via parieto-temporal regions within the delta frequency band. Finally, biophysical neural mass modeling demonstrated changes in the anterior-to-posterior distribution of cortical excitation-to-inhibition with increased excitation-to-inhibition model parameters in anterior regions in light NREM compared with wakefulness. Together, these findings uncover whole-brain corticocortical structure and the orchestration of local and long-range, frequency-specific cortical interactions in the sleep-wake transition.SIGNIFICANCE STATEMENT Our work uncovers spatiotemporal cortical structure of neural synchrony and information flow upon the transition from wakefulness to light non-rapid eye movement sleep. Mesial frontal regions were identified to receive hierarchically organized inputs from broad cortical regions, including both direct inputs from occipital regions and indirect inputs via the parieto-temporal regions within the delta frequency range. Biophysical neural mass modeling revealed a spatially heterogeneous, anterior-posterior distribution of cortical excitation-to-inhibition. Our findings shed light on the orchestration of local and long-range cortical neural structure that is fundamental to sleep onset, and support an emerging view of cortically driven regulation of sleep homeostasis.

Neurophysiological trajectories in Alzheimer's disease progression.

Alzheimer's disease (AD) is characterized by the accumulation of amyloid-ß and misfolded tau proteins causing synaptic dysfunction and progressive neurodegeneration and cognitive decline. Altered neural oscillations have been consistently demonstrated in AD. However, the trajectories of abnormal neural oscillations in AD progression and their relationship to neurodegeneration and cognitive decline are unknown. Here, we deployed robust event-based sequencing models (EBMs) to investigate the trajectories of long-range and local neural synchrony across AD stages, estimated from resting-state magnetoencephalography. Increases in neural synchrony in the delta-theta band and decreases in the alpha and beta bands showed progressive changes along the EBM stages. Decreases in alpha and beta-band synchrony preceded both neurodegeneration and cognitive decline, indicating that frequency-specific neuronal synchrony abnormalities are early manifestations of AD pathophysiology. The long-range synchrony effects were greater than the local synchrony, indicating a greater sensitivity of connectivity metrics involving multiple regions of the brain. These results demonstrate the evolution of functional neuronal deficits along the sequence of AD progression.

Etiology and Clinical Significance of Network Hyperexcitability in Alzheimer's Disease: Unanswered Questions and Next Steps.

Cortical network hyperexcitability related to synaptic dysfunction in Alzheimer's disease (AD) is a potential target for therapeutic intervention. In recent years, there has been increased interest in the prevalence of silent seizures and interictal epileptiform discharges (IEDs, or seizure tendency), with both entities collectively termed "subclinical epileptiform activity" (SEA), on neurophysiologic studies in AD patients. SEA has been demonstrated to be common in AD, with prevalence estimates ranging between 22-54%. Converging lines of basic and clinical evidence imply that modifying a hyperexcitable state results in an improvement in cognition. In particular, though these results require further confirmation, post-hoc findings from a recent phase II clinical trial suggest a therapeutic effect with levetiracetam administration in patients with AD and IEDs. Here, we review key unanswered questions as well as potential clinical trial avenues. Specifically, we discuss postulated mechanisms and treatment of hyperexcitability in patients with AD, which are of interest in designing future disease-modifying therapies. Criteria to prompt screening and optimal screening methodology for hyperexcitability have yet to be defined, as does timing and personalization of therapeutic intervention.

Spike-Associated Networks Predict Postsurgical Outcomes in Children With Refractory Epilepsy.

PURPOSE: Up to half of the children undergoing epilepsy surgery will continue to have seizures (szs) despite a cortical resection or ablation. Functional connectivity has shown promise in better identifying the epileptogenic zone. We hypothesized that cortical areas showing high information outflow during interictal epileptiform discharges are part of the epileptogenic zone. METHODS: We identified 22 children with focal epilepsy who had undergone stereo electroencephalography, surgical resection or ablation, and had ≥1 year of postsurgical follow-up. The mean phase slope index, a directed measure of functional connectivity, was calculated for each electrode contact during interictal epileptiform discharges. The positive predictive value and negative predictive value for a sz-free outcome were calculated based on whether high information outflow brain regions were resected. RESULTS: Resection of high outflow (z-score ≥ 1) and very high outflow (z-score ≥ 2) electrode contacts was associated with higher sz freedom (high outflow: χ 2 statistic = 59.1; P < 0.001; very high outflow: χ 2 statistic = 31.3; P < 0.001). The positive predictive value and negative predictive value for sz freedom based on resection at the electrode level increased at higher z-score thresholds with a peak positive predictive value of 0.86 and a peak negative predictive value of 0.9. CONCLUSIONS: Better identification of the epileptogenic zone has the potential to improve epilepsy surgery outcomes. If the surgical plan can be modified to include these very high outflow areas, more children might achieve sz freedom. Conversely, if deficits from resecting these areas are unacceptable, ineffective surgeries could be avoided and alternative therapies offered.

Maintaining Medical Student Motivation During Remote Clinical Learning.

PURPOSE: Remote clinical learning (RCL) may result in learner disengagement. The factors that influence medical student motivation during RCL remain poorly understood. The authors aimed to explore factors that affect medical student motivation during RCL and determine potential strategies to optimize student motivation during RCL. METHOD: In December 2020, the authors conducted semistructured interviews with third- and fourth-year medical students at the University of California, San Francisco, who had experienced RCL. The authors coded transcripts and conducted an inductive thematic analysis using self-determination theory (SDT), which describes autonomy, competence, and relatedness as essential for motivation, as a sensitizing framework. RESULTS: Twelve students were interviewed. Four themes were identified and aligned with SDT: balancing flexibility and structure (autonomy), selecting appropriate resources (competence), setting reasonable expectations (competence), and building and maintaining community (relatedness). Students described a sense of tension between desiring flexibility and appreciating structure and accountability during RCL; a preference for high-yield, curated resources presented in an organized format during RCL; instances in which the remote curriculum fell short of their expectations or professional goals or in which they felt they had missed out on key clinical learning; and support sought from peers, mentors, and instructors during RCL, as well as the contribution of remote learning technology to a sense of community. CONCLUSIONS: The authors propose 4 guiding principles to address implementation of remote clinical curricula: provide students with choice within the bounds of a well-defined curriculum, curate and organize learning materials carefully and intentionally, orient students to the goals and objectives of the curriculum and discuss students' expectations for professional development, and incorporate structured opportunities for remote mentorship and peer-peer interaction and optimize these opportunities using technology. Educators can draw on the themes, guiding principles, and potential strategies identified to promote and maintain learner motivation during RCL.

What Is Different about Teratoma-Associated Anti-LGI1 Encephalitis? A Long-Term Clinical and Neuroimaging Case Series.

INTRODUCTION: Anti-leucine-rich glioma-inactivated 1 (LGI1) encephalitis is clinically heterogeneous, especially at presentation, and though it is sometimes found in association with tumor, this is by no means the rule. METHODS: Clinical data for 10 patients with anti-LGI1 encephalitis were collected including one case with teratoma and nine cases without and compared for clinical characteristics. Microscopic pathological examination and immunohistochemical assay of the LGI1 antibody were performed on teratoma tissue obtained by laparoscopic oophorocystectomy. RESULTS: In our teratoma-associated anti-LGI1 encephalitis case, teratoma pathology was characterized by mostly thyroid tissue and immunohistochemical assay confirmed positive nuclear staining of LGI1 in some tumor cells. The anti-LGl1 patient with teratoma was similar to the non-teratoma cases in many ways: age at onset (average 47.3 in non-teratoma cases); percent presenting with rapidly progressive dementia (67% of non-teratoma cases) and psychiatric symptoms (33%); hyponatremia (78%); normal cerebrospinal fluid results except for positive LGI1 antibody (78%); bilateral hippocampal hyperintensity on magnetic resonance imaging (44%); diffuse slow waves on electroencephalography (33%); good response to immunotherapy (67%); and mild residual cognitive deficit (22%). Her chronic anxiety and presentation with status epilepticus were the biggest differences compared with the non-teratoma cases. CONCLUSION: In our series, anti-LGI1 encephalitis included common clinical features in our series: rapidly progressive dementia, faciobrachial dystonic seizures, behavioral disorders, hyponatremia, hippocampal hyperintensity on magnetic resonance imaging, and residual cognitive deficit. We observed some differences (chronic anxiety and status epilepticus) in our case with teratoma, but a larger accumulation of cases is needed to improve our knowledge base.

Network connectivity predicts effectiveness of responsive neurostimulation in focal epilepsy.

Responsive neurostimulation is a promising treatment for drug-resistant focal epilepsy; however, clinical outcomes are highly variable across individuals. The therapeutic mechanism of responsive neurostimulation likely involves modulatory effects on brain networks; however, with no known biomarkers that predict clinical response, patient selection remains empiric. This study aimed to determine whether functional brain connectivity measured non-invasively prior to device implantation predicts clinical response to responsive neurostimulation therapy. Resting-state magnetoencephalography was obtained in 31 participants with subsequent responsive neurostimulation device implantation between 15 August 2014 and 1 October 2020. Functional connectivity was computed across multiple spatial scales (global, hemispheric, and lobar) using pre-implantation magnetoencephalography and normalized to maps of healthy controls. Normalized functional connectivity was investigated as a predictor of clinical response, defined as percent change in self-reported seizure frequency in the most recent year of clinic visits relative to pre-responsive neurostimulation baseline. Area under the receiver operating characteristic curve quantified the performance of functional connectivity in predicting responders (≥50% reduction in seizure frequency) and non-responders (<50%). Leave-one-out cross-validation was furthermore performed to characterize model performance. The relationship between seizure frequency reduction and frequency-specific functional connectivity was further assessed as a continuous measure. Across participants, stimulation was enabled for a median duration of 52.2 (interquartile range, 27.0-62.3) months. Demographics, seizure characteristics, and responsive neurostimulation lead configurations were matched across 22 responders and 9 non-responders. Global functional connectivity in the alpha and beta bands were lower in non-responders as compared with responders (alpha, pfdr < 0.001; beta, pfdr < 0.001). The classification of responsive neurostimulation outcome was improved by combining feature inputs; the best model incorporated four features (i.e. mean and dispersion of alpha and beta bands) and yielded an area under the receiver operating characteristic curve of 0.970 (0.919-1.00). The leave-one-out cross-validation analysis of this four-feature model yielded a sensitivity of 86.3%, specificity of 77.8%, positive predictive value of 90.5%, and negative predictive value of 70%. Global functional connectivity in alpha band correlated with seizure frequency reduction (alpha, P = 0.010). Global functional connectivity predicted responder status more strongly, as compared with hemispheric predictors. Lobar functional connectivity was not a predictor. These findings suggest that non-invasive functional connectivity may be a candidate personalized biomarker that has the potential to predict responsive neurostimulation effectiveness and to identify patients most likely to benefit from responsive neurostimulation therapy. Follow-up large-cohort, prospective studies are required to validate this biomarker. These findings furthermore support an emerging view that the therapeutic mechanism of responsive neurostimulation involves network-level effects in the brain.

"What is the mechanism?": Cues, barriers, and opportunities to discuss foundational science during internal medicine rounds.

BACKGROUND: Repeated application of foundational science (FS) during medical reasoning results in encapsulation of knowledge needed to develop clinical expertise. Despite proven benefit of educating learners using a FS framework to anchor clinical decision making, how FS is integrated on clinical rotations has not been well characterized. This study examines how and when FS discussion occurs on internal medicine teaching rounds. MATERIAL AND METHODS: We performed a convergent mixed method study. Six internal medicine teams at a quaternary hospital were observed during rounds and team members interviewed. Transcripts were analyzed using thematic analysis. Descriptive statistics provided a summary of the observations. RESULTS: Our study revealed that rounds used a teacher-centered model where FS knowledge was transmitted as pearls external to the clinical context. FS content arose primarily when the patient was complex. Barriers preventing FS discussion were lack of time and perceived lack of personal FS knowledge. CONCLUSION: Our study describes scenarios that commonly elicit discussion of FS on inpatient medicine rounds highlighting a 'transmission' model of FS knowledge. We suggest a learner-centered model that engages students in the practice of integrating FS into clinical reasoning.

Neuronal synchrony abnormalities associated with subclinical epileptiform activity in early-onset Alzheimer's disease.

Since the first demonstrations of network hyperexcitability in scientific models of Alzheimer's disease, a growing body of clinical studies have identified subclinical epileptiform activity and associated cognitive decline in patients with Alzheimer's disease. An obvious problem presented in these studies is lack of sensitive measures to detect and quantify network hyperexcitability in human subjects. In this study we examined whether altered neuronal synchrony can be a surrogate marker to quantify network hyperexcitability in patients with Alzheimer's disease. Using magnetoencephalography (MEG) at rest, we studied 30 Alzheimer's disease patients without subclinical epileptiform activity, 20 Alzheimer's disease patients with subclinical epileptiform activity and 35 age-matched controls. Presence of subclinical epileptiform activity was assessed in patients with Alzheimer's disease by long-term video-EEG and a 1-h resting MEG with simultaneous EEG. Using the resting-state source-space reconstructed MEG signal, in patients and controls we computed the global imaginary coherence in alpha (8-12 Hz) and delta-theta (2-8 Hz) oscillatory frequencies. We found that Alzheimer's disease patients with subclinical epileptiform activity have greater reductions in alpha imaginary coherence and greater enhancements in delta-theta imaginary coherence than Alzheimer's disease patients without subclinical epileptiform activity, and that these changes can distinguish between Alzheimer's disease patients with subclinical epileptiform activity and Alzheimer's disease patients without subclinical epileptiform activity with high accuracy. Finally, a principal component regression analysis showed that the variance of frequency-specific neuronal synchrony predicts longitudinal changes in Mini-Mental State Examination in patients and controls. Our results demonstrate that quantitative neurophysiological measures are sensitive biomarkers of network hyperexcitability and can be used to improve diagnosis and to select appropriate patients for the right therapy in the next-generation clinical trials. The current results provide an integrative framework for investigating network hyperexcitability and network dysfunction together with cognitive and clinical correlates in patients with Alzheimer's disease.

Investigation of the risk of valproic acid-induced tremor: clinical, neuroimaging, and genetic factors.

RATIONALE: Investigation of associated risk factors of valproic acid (VPA)-induced tremor helped in increasing tolerance and optimizing treatment scheme individually. OBJECTIVES: To determine the risk factors of VPA-induced tremor, with particular attention on identifying tremor-susceptible gene mutations. METHODS: Epileptic patients taking VPA were divided into a tremor and a non-tremor groups. A mutation of rs9652490 in the leucine-rich repeat and immunoglobulin domain-containing Nogo-receptor-interacting protein 1 (LINGO-1) gene was determined by Sanger sequencing. Cerebellar atrophy was assessed, and various cerebellar dimensions were measured on magnetic resonance imaging (MRI) scans. RESULTS: One hundred and eighty-one of 200 subjects were included. Multivariate regression analysis indicated several VPA-induced tremor-related factors: females (OR = 2.718, p = 0.014), family history of tremor (OR = 7.595, p = 0.003), treatment duration (> 24 months; OR = 3.294, p = 0.002), and daily dosage (> 1,000 mg/d; OR = 19.801, p = 0.008) of VPA. Chi-square tests revealed that treatment with VPA magnesium-ER (p = 0.030) and carbamazepine combination (p = 0.040) reduced the incidence of tremor. One hundred and seventy-six gene sequencing and 86 MRI results excluded any significant difference between the two groups in the mutation of rs9652490 within LINGO-1, the ratio of cerebellar atrophy or the cerebellar-dimension values (p > 0.05). However, mutation of rs9652490 within LINGO-1 was correlated with increased cerebellar atrophy (p = 0.001), reduced cerebellar hemisphere thickness (p = 0.025), and right cerebellar hemisphere longitudinal diameter (p = 0.047). CONCLUSIONS: Our cohort indicated risk (female, positive family history of tremor, daily dosage > 1000 mg and treatment duration > 24 months of VPA) and protective factors (VPA magnesium-ER and combination with CBZ) of VPA-induced tremor. Mutation of rs9652490 within LINGO-1 correlated with cerebellar atrophy, neither was correlated with VPA-induced tremor.

Clinical Validation of the Champagne Algorithm for Evoked Response Source Localization in Magnetoencephalography.

Magnetoencephalography (MEG) is a robust method for non-invasive functional brain mapping of sensory cortices due to its exceptional spatial and temporal resolution. The clinical standard for MEG source localization of functional landmarks from sensory evoked responses is the equivalent current dipole (ECD) localization algorithm, known to be sensitive to initialization, noise, and manual choice of the number of dipoles. Recently many automated and robust algorithms have been developed, including the Champagne algorithm, an empirical Bayesian algorithm, with powerful abilities for MEG source reconstruction and time course estimation (Wipf et al. 2010; Owen et al. 2012). Here, we evaluate automated Champagne performance in a clinical population of tumor patients where there was minimal failure in localizing sensory evoked responses using the clinical standard, ECD localization algorithm. MEG data of auditory evoked potentials and somatosensory evoked potentials from 21 brain tumor patients were analyzed using Champagne, and these results were compared with equivalent current dipole (ECD) fit. Across both somatosensory and auditory evoked field localization, we found there was a strong agreement between Champagne and ECD localizations in all cases. Given resolution of 8mm voxel size, peak source localizations from Champagne were below 10mm of ECD peak source localization. The Champagne algorithm provides a robust and automated alternative to manual ECD fits for clinical localization of sensory evoked potentials and can contribute to improved clinical MEG data processing workflows.

Magnetoencephalography Imaging Reveals Abnormal Information Flow in Temporal Lobe Epilepsy.

Background/Introduction: Widespread network disruption has been hypothesized to be an important predictor of outcomes in patients with refractory temporal lobe epilepsy (TLE). Most studies examining functional network disruption in epilepsy have largely focused on the symmetric bidirectional metrics of the strength of network connections. However, a more complete description of network dysfunction impacts in epilepsy requires an investigation of the potentially more sensitive directional metrics of information flow. Methods: This study describes a whole-brain magnetoencephalography-imaging approach to examine resting-state directional information flow networks, quantified by phase-transfer entropy (PTE), in patients with TLE compared with healthy controls (HCs). Associations between PTE and clinical characteristics of epilepsy syndrome are also investigated. Results: Deficits of information flow were specific to alpha-band frequencies. In alpha band, while HCs exhibit a clear posterior-to-anterior directionality of information flow, in patients with TLE, this pattern of regional information outflow and inflow was significantly altered in the frontal and occipital regions. The changes in information flow within the alpha band in selected brain regions were correlated with interictal spike frequency and duration of epilepsy. Conclusions: Impaired information flow is an important dimension of network dysfunction associated with the pathophysiological mechanisms of TLE.

Effect of Levetiracetam on Cognition in Patients With Alzheimer Disease With and Without Epileptiform Activity: A Randomized Clinical Trial.

Importance: Network hyperexcitability may contribute to cognitive dysfunction in patients with Alzheimer disease (AD). Objective: To determine the ability of the antiseizure drug levetiracetam to improve cognition in persons with AD. Design, Setting, and Participants: The Levetiracetam for Alzheimer's Disease-Associated Network Hyperexcitability (LEV-AD) study was a phase 2a randomized double-blinded placebo-controlled crossover clinical trial of 34 adults with AD that was conducted at the University of California, San Francisco, and the University of Minnesota, Twin Cities, between October 16, 2014, and July 21, 2020. Participants were adults 80 years and younger who had a Mini-Mental State Examination score of 18 points or higher and/or a Clinical Dementia Rating score of less than 2 points. Screening included overnight video electroencephalography and a 1-hour resting magnetoencephalography examination. Interventions: Group A received placebo twice daily for 4 weeks followed by a 4-week washout period, then oral levetiracetam, 125 mg, twice daily for 4 weeks. Group B received treatment using the reverse sequence. Main Outcomes and Measures: The primary outcome was the ability of levetiracetam treatment to improve executive function (measured by the National Institutes of Health Executive Abilities: Measures and Instruments for Neurobehavioral Evaluation and Research [NIH-EXAMINER] composite score). Secondary outcomes were cognition (measured by the Stroop Color and Word Test [Stroop] interference naming subscale and the Alzheimer's Disease Assessment Scale-Cognitive Subscale) and disability. Exploratory outcomes included performance on a virtual route learning test and scores on cognitive and functional tests among participants with epileptiform activity. Results: Of 54 adults assessed for eligibility, 11 did not meet study criteria, and 9 declined to participate. A total of 34 adults (21 women [61.8%]; mean [SD] age, 62.3 [7.7] years) with AD were enrolled and randomized (17 participants to group A and 17 participants to group B). Thirteen participants (38.2%) were categorized as having epileptiform activity. In total, 28 participants (82.4%) completed the study, 10 of whom (35.7%) had epileptiform activity. Overall, treatment with levetiracetam did not change NIH-EXAMINER composite scores (mean difference vs placebo, 0.07 points; 95% CI, -0.18 to 0.32 points; P = .55) or secondary measures. However, among participants with epileptiform activity, levetiracetam treatment improved performance on the Stroop interference naming subscale (net improvement vs placebo, 7.4 points; 95% CI, 0.2-14.7 points; P = .046) and the virtual route learning test (t = 2.36; Cohen f2 = 0.11; P = .02). There were no treatment discontinuations because of adverse events. Conclusions and Relevance: In this randomized clinical trial, levetiracetam was well tolerated and, although it did not improve the primary outcome, in prespecified analysis, levetiracetam improved performance on spatial memory and executive function tasks in patients with AD and epileptiform activity. These exploratory findings warrant further assessment of antiseizure approaches in AD. Trial Registration: ClinicalTrials.gov Identifier: NCT02002819.

Long QT syndrome with potassium voltage-gated channel subfamily H member 2 gene mutation mimicking refractory epilepsy: case report.

BACKGROUND: Epileptic seizures can be difficult to distinguish from other etiologies that cause cerebral hypoxia, especially cardiac diseases. Long QT syndrome (LQTS), especially LQTS type 2 (LQT2), frequently masquerades as seizures because of the transient cerebral hypoxia caused by ventricular arrhythmia. The high rate of sudden death in LQTS highlights the importance of accurate and early diagnosis; correct diagnosis of LQTS also prevents inappropriate treatment with anti-epileptic drugs (AEDs). CASE PRESENTATION: We report a case of congenital LQT2 with potassium voltage-gated channel subfamily H member 2 gene (KCNH2) mutation misdiagnosed as refractory epilepsy and treated with various AEDs for 22 years. The possibility of cardiac arrhythmia was suspected after the patient presented to the emergency room and the electrocardiograph (ECG) monitor showed paroxysmal ventricular tachycardia during attacks. Atypical seizure like attacks with prodromal uncomfortable chest sensation and palpitation, triggered by auditory stimulation, and typical ventricular tachycardia monitored by ECG raised suspicion for LQT2, which was confirmed by exome sequencing and epileptic seizure was ruled out by 24-h EEG monitoring. Although the patient rejected implantation of an implantable cardioverter defibrillator, ß blocker was given and the syncope only attacked 1-2 per year when there was an incentive during the 5 years follow up. CONCLUSIONS: Our case illustrates how long LQTS can masquerade convincingly as epilepsy and can be treated wrongly with AEDs, putting the patient at high risk of sudden cardiac death. Careful ECG evaluation is recommend for both patients with first seizure and those with refractory epilepsy.

Integrated in silico and experimental assessment of disease relevance of PCDH19 missense variants.

PCDH19 is a nonclustered protocadherin molecule involved in axon bundling, synapse function, and transcriptional coregulation. Pathogenic variants in PCDH19 cause infantile-onset epilepsy known as PCDH19-clustering epilepsy or PCDH19-CE. Recent advances in DNA-sequencing technologies have led to a significant increase in the number of reported PCDH19-CE variants, many of uncertain significance. We aimed to determine the best approaches for assessing the disease relevance of missense variants in PCDH19. The application of the American College of Medical Genetics and Association for Molecular Pathology (ACMG-AMP) guidelines was only 50% accurate. Using a training set of 322 known benign or pathogenic missense variants, we identified MutPred2, MutationAssessor, and GPP as the best performing in silico tools. We generated a protein structural model of the extracellular domain and assessed 24 missense variants. We also assessed 24 variants using an in vitro reporter assay. A combination of these tools was 93% accurate in assessing known pathogenic and benign PCDH19 variants. We increased the accuracy of the ACMG-AMP classification of 45 PCDH19 variants from 50% to 94%, using these tools. In summary, we have developed a robust toolbox for the assessment of PCDH19 variant pathogenicity to improve the accuracy of PCDH19-CE variant classification.

Clinical Validation of the Champagne Algorithm for Epilepsy Spike Localization.

Magnetoencephalography (MEG) is increasingly used for presurgical planning in people with medically refractory focal epilepsy. Localization of interictal epileptiform activity, a surrogate for the seizure onset zone whose removal may prevent seizures, is challenging and depends on the use of multiple complementary techniques. Accurate and reliable localization of epileptiform activity from spontaneous MEG data has been an elusive goal. One approach toward this goal is to use a novel Bayesian inference algorithm-the Champagne algorithm with noise learning-which has shown tremendous success in source reconstruction, especially for focal brain sources. In this study, we localized sources of manually identified MEG spikes using the Champagne algorithm in a cohort of 16 patients with medically refractory epilepsy collected in two consecutive series. To evaluate the reliability of this approach, we compared the performance to equivalent current dipole (ECD) modeling, a conventional source localization technique that is commonly used in clinical practice. Results suggest that Champagne may be a robust, automated, alternative to manual parametric dipole fitting methods for localization of interictal MEG spikes, in addition to its previously described clinical and research applications.

The 10 Common Evidence-Supported Indications for MEG in Epilepsy Surgery: An Illustrated Compendium.

Unfamiliarity with the indications for and benefits of magnetoencephalography (MEG) persists, even in the epilepsy community, and hinders its acceptance to clinical practice, despite the evidence. The wide treatment gap for patients with drug-resistant epilepsy and immense underutilization of epilepsy surgery had similar effects. Thus, educating referring physicians (epileptologists, neurologists, and neurosurgeons) both about the value of epilepsy surgery and about the potential benefits of MEG can achieve synergy and greatly improve the process of selecting surgical candidates. As a practical step toward a comprehensive educational process to benefit potential MEG users, current MEG referrers, and newcomers to MEG, the authors have elected to provide an illustrated guide to 10 everyday situations where MEG can help in the evaluation of people with drug-resistant epilepsy. They are as follows: (1) lacking or imprecise hypothesis regarding a seizure onset; (2) negative MRI with a mesial temporal onset suspected; (3) multiple lesions on MRI; (4) large lesion on MRI; (5) diagnostic or therapeutic reoperation; (6) ambiguous EEG findings suggestive of "bilateral" or "generalized" pattern; (7) intrasylvian onset suspected; (8) interhemispheric onset suspected; (9) insular onset suspected; and (10) negative (i.e., spikeless) EEG. Only their practical implementation and furtherance of personal and collective education will lead to the potentially impactful synergy of the two-MEG and epilepsy surgery. Thus, while fulfilling our mission as physicians, we must not forget that ignoring the wealth of evidence about the vast underutilization of epilepsy surgery - and about the usefulness and value of MEG in selecting surgical candidates - is far from benign neglect.