Neural circuit hyperexcitability and impaired excitation-to-inhibition (E/I) activity is believed to be a key contributor to synaptic and network degeneration in Alzheimer’s disease (AD). Extensive preclinical research on transgenic animal models of AD have demonstrated neuronal and circuit level E/I imbalance mediated by amyloid-beta (Aβ) and tau proteins. Synaptic and network deficits are also integral changes of aging. It is unknown whether the mechanisms of E/I imbalance in aging are distinct from that in AD. In this study we leveraged the aperiodic spectral slope measure, which represent the spontaneous neuronal firing, and which has been shown to indicate higher E/I as reduced slope values. We used source reconstructed, high spatiotemporal resolution signals, from magnetoencephalography (MEG) for the spectral analysis and used the neural mass model (NMM) to estimate excitatory and inhibitory neuronal parameters, in patients with AD (n = 85) and age-matched elderly-controls (n = 45). The NMM estimates the time constants of excitatory (t e ) and inhibitory (t i ) neuronal subpopulations and depicts E/I as 1/inhibitory-neural-gain (g ii ). We estimated the aperiodic slope from the spectral analysis (15-50 Hz) and examined the correlations with NMM parameters. In a subset of AD patients, we recorded the presence or absence of epileptiform activity (EPI) and examined the associations of neuronal-time-contents and inhibitory-neural-gain in AD-EPI+ (n = 20) vs. AD-EPI− (n = 30). AD patients showed reduced inhibitory-neural-gains compared to elderly-controls indicating increased E/I (Fig. 1.A). AD patients also showed increased neuronal-time-constants than controls (Fig. 1.B-C). The spatial patterns of reduced inhibitory-neural-gains overlapped with AD vulnerable anatomic regions showing a posterior temporo-parietal-occipital distribution (Fig. 1.D). Greater reductions of aperiodic-slope distinctly correlated with inhibitory-neural-gains in AD and with higher neuronal-time-constants in elderly-controls (Fig. 1.G-L). Moreover, AD-EPI+ showed greater reductions in inhibitory-neural-gains than AD-EPI−, but no differences in neuronal-time-constants (Fig. 1.M-O). Our findings identified impaired inhibitory synaptic activity as the strongest correlate of neural circuit hyperexcitability in AD. In contrast, impaired timing of both excitatory and inhibitory neurons were the best predictors of neural circuit hyperexcitability in aging. These results suggest different mechanisms of neural circuit hyperexcitability in AD vs. aging and have important implications to translational as well as clinical studies probing early network changes.

A growing body of evidence shows that epileptic activity is frequently observed in patients with Alzheimer's disease (AD), implicating underlying excitatory-inhibitory imbalance. The distinction of whether the AD-epileptic phenotype represents a subset of patients or an underdiagnosed manifestation holds major therapeutic implications. Here, we quantified the excitatory-inhibitory imbalance in AD patients using magnetoencephalography and examined the relationships to AD pathophysiology-amyloid-beta and tau, and to epileptic activity. We used two metrics to quantify regional excitatory-inhibitory imbalance distinguishing between local hyperexcitability (Neural excitability, quantified by regional aperiodic spectral slope) and aberrant long-range synaptic input integration (Neural fragility, quantified by regional linear dynamic instability). We found that amyloid-beta correlated with higher neural fragility and higher neural excitability, while tau and hypometabolism uniquely correlated with higher neural excitability. Importantly, the AD-epileptic phenotype showed a distinctive increase in neural fragility. Our findings demonstrate that AD pathophysiology is associated with diverse mechanisms of excitatory-inhibitory imbalance and that AD-epileptic phenotype represents a distinct group of patients with greater impairments in long-range synaptic input integration.

Abstract 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.

Alzheimer's disease (AD) is characterized by the accumulation of amyloid-β 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.

The measurement and understanding of brain activity time series is integral to epilepsy care and research. Brain signals may be acquired using external sensors, as with scalp electroencephalography (EEG) and magnetoencephalography (MEG), or using implanted internal sensors, as with intracranial EEG (iEEG). These techniques can provide high temporal resolution recordings of electrical or electromagnetic activity relevant to epilepsy, cognitive processing, and many other functions, but require data processing and cleaning ahead of analysis. We first describe how EEG and iEEG are acquired, discuss similarities and differences, and elaborate on fundamental data preprocessing steps. We next provide example MATLAB functions for the most common preprocessing steps. Subsequently, we provide an overview of why MEG recordings may be beneficial, discuss acquisition considerations, and review preprocessing steps. Finally, we comment on popular software toolboxes.

While animal models of Alzheimer's disease (AD) have shown altered gamma oscillations (similar to 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. Prabhu et al. examined phase-amplitude coupling between gamma amplitude and phase of lower frequencies in patients with Alzheimer's disease (AD) and their associations with network hyperexcitability. Theta-gamma coupling in AD was reduced in medial temporal regions (parahippocampus), which is the earliest affected region in AD, and was associated network hyperexcitability. Graphical abstract

Alzheimer’s disease (AD) carries an increased risk of seizures and subclinical epileptiform activity (Vossel et al. 2016). Network hyperexcitability which is the underlying phenomenon of epileptic manifestations is thought to contribute to AD pathophysiological processes. Recently we demonstrated that greater degree of neural synchronization deficits within 2-8Hz range of frequency oscillations are sensitive indicators of network hyperexcitability (Ranasinghe et al. 2021). Here, we sought to examine the high frequency gamma band deficits associated with network hyperexcitability in AD patients. Specifically, we quantified Phase Amplitude Coupling (PAC) between the amplitude of gamma oscillations (30-40Hz); with the phase of 2-8Hz oscillations) (Figure 1). We used 60s resting-state magnetoencephalography (MEG) recordings from 48 AD patients (n = 22, with subclinical epileptiform activity, AD-EPI+; n = 28 without subclinical epileptiform activity, AD-EPI-), and 35 age-matched controls. We computed PAC for each of 68 cortical regions (Desikan et al. 2006) on source-space reconstructed MEG signal using the mean vector length (Canolty et al. 2006). Permutation cluster test was performed for statistical comparisons between AD patients vs. age matched controls, and AD-EPI+ vs. AD-EPI-. Patients with AD showed significantly higher theta (4-8 Hz)-gamma coupling in the left parahippocampal and right caudal-middle frontal regions. Importantly, this increased left parahippocampal theta-gamma coupling was significantly higher in AD-EPI+ patients than in AD-EPI-. AD-EPI+ also showed higher alpha (8-12Hz)-gamma coupling in the right parahippocampal region compared to AD-EPI- (Figure 2). These results not only identify gamma band coupling deficits specifically localized to medial temporal regions which are the earliest affected regions in AD pathophysiology but also delineate the associated vulnerabilities of network hyperexcitability in AD.

Objective: Genetic diagnosis for epilepsy and other neurological disorders are not optimized to detect somatic mutations, representing a significant unsolved challenge in neurology. Our group identified candidate somatic variants from the Epi4K consortium, a large cohort of epilepsy trio exomes, using MosaicHunter, a sensitive framework to identify candidate somatic variants. Here, we analyze a specific loss-of-function somatic single nucleotide variant (sSNV) in ARHGAP31 to determine its functional effect as a potential novel epilepsy gene. Background: Once somatic variants have been identified and characterized in-silico, their functional and biological consequences must be experimentally validated. Here, we describe a clinical case with somatic candidate stop-gain variant in ARHGAP31, and use a patient cell line to investigate ARHGAP31, a gene that plays a key role in cellular signaling by regulating proteins Cdc42 and Rac1 (Lamarche-Vane and Hall, 1998). Design/Methods: To determine the effect of our ARHGAP31 variant on ARHGAP31 gene expression, concurrent genotyping and RNA expression analysis of individual patient-derived lymphoblasts was performed using a single-cell workflow with primers for Sanger sequencing and probes for digital droplet PCR (ddPCR). Additionally, we analyzed Epi25K, a cohort of exome sequencing data from epilepsy cases and controls, to determine whether ARHGAP31 somatic variants are preferentially present in epilepsy cohorts. Results: We hypothesized that wild-type cells express ARHGAP31 at a higher level than cells carrying the sSNV and report that in a population of 13 patient single-cells expressing ARHGAP31 at the highest level, 100% (13/13) were wild-type genotype (p-value = 0.00005). Additionally, we report several loss-of-function somatic variants in ARHGAP31 in large cohort analysis from Epi25K. Conclusions: Based upon single-cell gene expression data and large epilepsy cohort data, we present evidence for ARHGAP31 as a new epilepsy candidate gene. Clinically, this work is foundational to future efforts to determine additional somatic mutations which contribute to pediatric epilepsy. Disclosure: Mr. Cheng has nothing to disclose. An immediate family member of Mr. Chen has received personal compensation for serving as an employee of Lathrop & Gage. Dr. Huang has nothing to disclose. Junseok Park has nothing to disclose. The institution of Dr. Kirsch has received research support from Ricoh, Inc. Dr. Walsh has received personal compensation in the range of $10,000-$49,999 for serving as a Consultant for Maze therapeutics. Dr. Walsh has received personal compensation in the range of $10,000-$49,999 for serving as a Consultant for Third Rock Ventures. Dr. Walsh has received personal compensation in the range of $5,000-$9,999 for serving as a Consultant for Flagship Pioneering. Dr. Walsh has received personal compensation in the range of $10,000-$49,999 for serving as an Editor, Associate Editor, or Editorial Advisory Board Member for Annals of Neurology. Dr. Shao has nothing to disclose.

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.

PURPOSE: Increasingly, research or scientific method knowledge and skills are relevant and essential requisites for physicians.However, while the inclusion of research related activities in the curriculum of U.S. medical schools is growing, the importance of research experience in obtaining medical residency positions is not fully examined.METHODS: This study reviewed the importance of student involvement in research among other factors, from residency program directors' perspectives in the selection of applicants for interview and subsequent ranking for residency match.This study reviewed and analyzed secondary database of the Program Director Surveys published by the National Resident Matching Program from 2018 to 2021.RESULTS: For all residency specialties, between 2018 and 2021, on average, 39% of the program directors cited research involvement as a factor for selection for interview and 29% ranking the applicant for the match.In 2018, the mean ratings of importance for research involvement as a factor for interview invitation and ranking for residency match were similar.However, the mean importance ratings were higher for applicant rankings for residency match compared with those for interview invitation in 2020 and 2021.In 2018 and 2020 surveys, the percentage of program directors who reported involvement in research as a factor in selecting an applicant for interview varied widely among the specialties.The percentage of program directors who cited involvement in research as a factor for ranking the applicants was generally lower than those for invitation for interview among most of the specialties, but Internal Medicine Pediatric in 2018 as well as Psychiatry, Pediatrics, and Radiology-Diagnostic in 2020 showed an opposite trend.CONCLUSION: In conclusion, while medical residency program directors recognize the importance of research involvement in selecting applicant for the match, there is a wide variation among specialties.Future studies should be directed at understanding the reasons and effects of these variations.

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.

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.

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.

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.

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.

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.

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.

11028 Background: Cognitive integration (CI) connects foundational science (FS) to medical practice and improves clinical reasoning. While evidence supports CI in medical training, the clinical relevance of FS is often obscure to medical students, particularly in oncology, and few learning materials exist to support CI during clerkships. Providing effective and engaging tools to promote CI may enhance understanding of FS relevance to clinical medicine. We therefore aimed to create an online module to integrate FS into clerkships. Methods: Previous student feedback at our institution advocated for clinically relevant FS content. Applying Cognitive Theory of Multimedia Learning principles, we (an oncologist, a biochemist, and an instructional designer) created a cancer module grounded in the hallmarks of cancer (HoC), a key FS principle. To emphasize clinical relevance, we recorded patient interviews incorporating FS. The module, composed in Qualtrics, includes an introduction and four cases, each starting with a brief patient interview, followed by clinical text, images, questions, and explanations. Content co-created by the oncologist and biochemist combined clinical and FS perspectives and referenced the HoC throughout. We piloted a draft with a focus group of four students. The evaluation plan includes written learner feedback, a case-based pre/post-test, and review of clerkship assessments for evidence of CI. Results: We produced an FS oncology module with an estimated engagement time of two hours, which students may complete over multiple sittings. The development team met monthly over the course of one year. Filming and editing cost $100/hour. Overall, the project required approximately 60 faculty person-hours and 12 instructional designer person-hours. The patients interviewed for the module expressed gratitude for sharing their stories with students. The student focus group yielded unanimously positive feedback about the content, the multimedia format, the level of FS covered, and the use of authentic patient videos to enhance clinical relevance. Students strongly preferred this module compared to prior online learning activities. Conclusions: This novel interactive module can serve as a model for development of clerkship curricula promoting CI. Module creation based on real patients resulted in authentic story-telling and enhanced FS relevance. Content development involving a clinician and a basic scientist aligned with CI goals. Limitations include the need for funding and instructional design assistance. A randomized controlled trial comparing a series of novel FS modules to older recorded lectures may demonstrate improved outcomes. Involving learners in curriculum development may decrease faculty burden and increase student interest in FS.

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, p(fdr) < 0.001; beta, p(fdr) < 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. To prognosticate outcomes with neurostimulation for epilepsy, Fan et al. investigate functional network connectivity measured non-invasively with magnetoencephalography as a novel biomarker for effectiveness of responsive neurostimulation (RNS) therapy. Resting-state functional connectivity in alpha and beta frequency bands predicted response to subsequent RNS therapy and correlated with seizure frequency reduction.

Sleep is a highly stereotyped phenomenon that is ubiquitous across species. Although behaviorally appearing as a homogeneous process, sleep has been recognized as cortically heterogenous and locally dynamic. PET/fMRI studies have provided key insights into regional activation and deactivation with sleep onset, but they lack the high temporal resolution and electrophysiology for understanding neural interactions. Using simultaneous electrocorticography (EEG) and magnetoencephalography (MEG) imaging, we systematically characterize whole-brain neural oscillations and identify frequency specific, cortically-based patterns associated with sleep onset. In this study, 14 healthy subjects underwent simultaneous EEG and MEG imaging. Sleep states were determined by scalp EEG. Eight 15s artifact-free epochs, e.g. 120s sensor time series, were selected to represent each behavioral state: N1, N2 and wake. Atlas-based source reconstruction was performed using adaptive beamforming methods. Functional connectivity measures were computed using imaginary coherence and across regions of interests (ROIs, segmentation of 210 cortical regions with Brainnetome Atlas) in multiple frequency bands, including delta (1-4Hz), theta (4-8Hz), alpha (8-12Hz), sigma (12-15Hz), beta (15-30Hz), and gamma (30-50Hz). Directional phase transfer entropy (PTE) was also evaluated to determine the direction of information flow with transition to sleep. We show that the transition to sleep is encoded in a spatially and temporally specific dynamic pattern of whole-brain functional connectivity. With sleep onset, there is increased functional connectivity diffusely within the delta frequency, while spatially specific profiles in other frequency bands, e.g. increased fronto-temporal connectivity in the alpha frequency band and fronto-occipital connectivity in the theta band. In addition, rather than a decoupling of anterior-posterior regions with transition to sleep, there is a spectral shift to delta frequencies observed in the synchrony and information flow of neural activity. Sleep onset is cortically heterogeneous, composed of spatially and temporally specific patterns of whole-brain functional connectivity, which may play an essential role in the transition to sleep. Research reported in this publication was supported by the National Center for Advancing Translational Sciences of the NIH under Award Number (5TL1TR001871-05 to JMF). Its contents are solely the responsibility of the authors and do not necessarily represent the official views of the NIH.