Faculty Bibliography

Antibiotic-induced microbiome injury, defined as a reduction of ecological diversity and obligate anaerobe taxa, is associated with negative health outcomes in hospitalized patients, and healthy individuals who received antibiotics in the past are at higher risk for autoimmune diseases. Postbiotics contain mixtures of bacterial fermentation metabolites and bacterial cell wall components that have the potential to modulate microbial communities. Yet, it is unknown if a fermentation-derived postbiotic can reduce antibiotic-induced microbiome injury. Here, we present the results from a single-center, randomized placebo-controlled trial involving 32 patients who received an oral, fermentation-derived postbiotic alongside oral antibiotic and probiotic therapy for non-gastrointestinal (GI) infections. At the end of the antibiotic course, patients receiving the postbiotic (n = 16) had significantly higher fecal bacterial alpha diversity (+40%, inverse Simpson index) compared to the placebo group (n = 16), and the treatment was well-tolerated. Analysis of 157 longitudinal fecal samples revealed that this increased diversity was driven by enrichment of health-associated taxa, notably obligate anaerobic Firmicutes, particularly Lachnospiraceae. In contrast, Escherichia/Shigella species, often linked to pathogenicity and antibiotic resistance, were reduced in postbiotic-treated patients at the end of antibiotic treatment and remained lower up to 10 days later. Our findings suggest that postbiotic co-administration during antibiotic therapy may augment health-associated gut microbiome composition and mitigate antibiotic-induced microbiome injury.Trial registration ISRCTN30327931 retrospectively registered.

Large Language Models (LLMs) offer a framework for understanding language processing in the human brain. Unlike traditional models, LLMs represent words and context through layered numerical embeddings. Here, we demonstrate that LLMs' layer hierarchy aligns with the temporal dynamics of language comprehension in the brain. Using electrocorticography (ECoG) data from participants listening to a 30-minute narrative, we show that deeper LLM layers correspond to later brain activity, particularly in Broca's area and other language-related regions. We extract contextual embeddings from GPT-2 XL and Llama-2 and use linear models to predict neural responses across time. Our results reveal a strong correlation between model depth and the brain's temporal receptive window during comprehension. We also compare LLM-based predictions with symbolic approaches, highlighting the advantages of deep learning models in capturing brain dynamics. We release our aligned neural and linguistic dataset as a public benchmark to test competing theories of language processing.

Hippocampal sharp-wave ripples (SPW-Rs) are high-frequency oscillations critical for memory consolidation. Despite extensive characterization in rodents, their detection in humans is limited by coarse spatial sampling, interictal epileptiform discharges (IEDs), and a lack of consensus on human ripple localization and morphology. Here, we demonstrate that mouse and human hippocampal ripples share spatial, spectral and temporal features, which are clearly distinct from IEDs. In recordings from male APP/PS1 mice, SPW-Rs were distinguishable from IEDs by multiple criteria. Hippocampal ripples recorded during NREM sleep in female and male surgical epilepsy patients exhibited similar narrowband frequency peaks and multiple ripple cycles in the CA1 and subiculum regions. Conversely, IEDs showed a broad spatial extent and wide-band frequency power. We developed a semi-automated, ripple curation toolbox (ripmap) to separate event waveforms by low-dimensional embedding to reduce false-positive rate in selected ripple channels. Our approach improves ripple detection and provides a firm foundation for future human memory research.

Consciousness Science is entering an age of unprecedented opportunity, thanks to recent empirical and theoretical advances, increasing interest in the topic, and technological advances in neuroscience. The role theories will play in a maturing science of consciousness deserves a closer look.

Carotid webs are increasingly recognized as an underdiagnosed etiology of ischemic stroke, especially in young, otherwise healthy patients. These fibrous intimal protrusions create regions of flow stasis within the internal carotid artery, predisposing to thromboembolism. Diagnosis remains challenging due to their subtle radiographic appearance and underappreciation in clinical practice. While antiplatelet therapy or anticoagulation used to be the cornerstone of management, medical therapy alone has been found to be insufficient for stroke prevention in symptomatic patients. Definitive intervention includes carotid artery stenting or carotid endarterectomy; both have demonstrated excellent safety and efficacy. Risk stratification for symptomatic and asymptomatic carotid webs remains an area of active research, with emerging evidence suggesting that specific anatomic features, termed the carotid web angioarchitecture, may help predict stroke risk. Further studies are needed to determine the role of preventative intervention. A deeper understanding of carotid web pathogenesis, natural history, and hemodynamic impact is critical for guiding clinical decision-making.

The 2024 revised McDonald criteria for multiple sclerosis recognize the optic nerve as a topography for dissemination in space. Optical coherence tomography-derived inter-eye differences in peri-papillary retinal nerve fiber layer or ganglion cell-inner plexiform layer thicknesses (≥6μm or ≥4μm, respectively) are proposed for identifying unilateral optic nerve involvement. However, the value of combining inter-eye difference measures and optimal temporal-quadrant peri-papillary retinal nerve fiber layer inter-eye differences remains unclear. We investigated the diagnostic performance of combined inter-eye differences, optimal temporal-quadrant peri-papillary retinal nerve fiber layer inter-eye differences, and examined the effects of time, prior optic neuritis frequency, sex, and race on inter-eye differences. Retinal optical coherence tomography images from all study participants underwent rigorous quality control. Receiver operating characteristic analyses and area under the receiver operating characteristic curves (AUC) were used to determine optimal inter-eye differences of individual and combined measures to distinguish eyes with, from without, prior optic neuritis in people with multiple sclerosis. Mixed-effects models were used to assess impact of time, prior optic neuritis events, sex, and race on inter-eye differences. An independent multiple sclerosis cohort from a second center was examined for external validation. Among 1854 people with multiple sclerosis, optimal inter-eye difference thresholds for identifying unilateral optic nerve involvement were 6μm for peri-papillary retinal nerve fiber layer (AUC=0.80), 4μm for ganglion cell-inner plexiform layer (AUC=0.83), and 8μm for temporal-quadrant peri-papillary retinal nerve fiber layer (AUC=0.71) thicknesses. Peri-papillary retinal nerve fiber layer inter-eye differences ≥6μm or ganglion cell-inner plexiform layer inter-eye differences ≥4μm yielded 87.6% sensitivity, 70.0% specificity, and 64.0% positive predictive value. Concurrent inter-eye differences at lower thresholds (≥5μm peri-papillary retinal nerve fiber layer, ≥3μm ganglion cell-inner plexiform layer) reduced sensitivity to 72.5%, but improved specificity (86.6%) and positive predictive value (76.7%), while maintaining accuracy and negative predictive value. Temporal-quadrant peri-papillary retinal nerve fiber layer inter-eye differences did not improve diagnostic performance. Over a median of 5.1 years, ganglion cell-inner plexiform layer and peri-papillary retinal nerve fiber layer inter-eye differences remained stable. Prior optic neuritis counts and sex did not affect inter-eye differences. Although Black Americans had higher inter-eye differences than White Americans, optimal thresholds were comparable across races. The validation cohort comprising 254 people with multiple sclerosis confirmed these findings. In conclusion, concurrent peri-papillary retinal nerve fiber layer (≥5μm) and ganglion cell-inner plexiform layer inter-eye differences (≥3μm) improve unilateral optic nerve involvement detection versus either alone (≥6μm or ≥4μm, respectively), while temporal-quadrant peri-papillary retinal nerve fiber layer inter-eye differences offer limited benefit. Inter-eye differences remain stable longitudinally and unaffected by prior optic neuritis frequency.

BACKGROUND AND OBJECTIVES/OBJECTIVE:Vascular dysfunction contributes to Alzheimer disease (AD) and related dementias (ADRDs), but the underlying mechanisms remain unclear. Previous studies link midlife hemostasis and platelet aggregation measures to late-life dementia risk. We aimed to determine whether platelet aggregation in midlife is associated with imaging markers of AD pathology. METHODS:F-flortaucipir) PET uptake in dementia-free, middle-aged adults from the Framingham Heart Study. Co-primary outcomes included amyloid and tau uptake in AD-vulnerable regions. We also examined an MRI-based cortical thickness signature of AD risk as a secondary outcome. We used multivariable regression models adjusted for demographic and clinical factors, considering potential nonlinear associations. RESULTS:< 0.035), consistent with a neurodegenerative pattern. DISCUSSION/CONCLUSIONS:Our findings indicate that platelet aggregation is linked to PET and MRI markers of AD pathology as early as midlife. These findings support further investigation of platelet-mediated mechanisms in AD pathogenesis.

This position statement provides updated member guidance from the American Academy of Neurology (AAN) regarding (1) communication with surrogate decision makers about brain death/death by neurologic criteria (BD/DNC), (2) management of surrogate decision-maker objections to BD/DNC, (3) the ethical considerations associated with BD/DNC determination in a pregnant person, and (4) enhancing public trust in BD/DNC. This position statement is intended to complement recommendations in the 2023 "Pediatric and Adult Brain Death/Death by Neurologic Criteria Consensus Guideline" published by the AAN, American Academy of Pediatrics, Child Neurology Society, and Society of Critical Care Medicine, as well as the 2021 AAN Code of Professional Conduct. It replaces the 2019 AAN position statement, "Brain death, the determination of brain death, and member guidance for brain death accommodation requests."

BACKGROUND AND OBJECTIVES/OBJECTIVE:Epilepsy is a common neurologic disorder. Although antiseizure medications (ASMs) are the first-line treatment, identifying the most effective ASM for each individual remains a trial-and-error process. Genetic variation may influence treatment response. We aimed to develop and validate a multimodal deep learning model that integrates clinical and genomic features to predict response to the initial ASM in people with newly diagnosed epilepsy. METHODS:We used data from individuals with newly diagnosed epilepsy in Australia as the development cohort and participants from the Human Epilepsy Project 1 (recruited in the United States, Europe, and Australia) as the external validation cohort. All participants initiated ASM treatment and were followed prospectively for at least 1 year. We included 16 clinical factors and constructed 4 genomic feature types related to epilepsy and ASM pharmacogenomics, with and without functional impact annotations. We evaluated various machine learning architectures and multimodal fusion strategies to predict seizure freedom while taking the initial ASM at 1 year. RESULTS:< 0.05). Applying this model to the development cohort, if all participants took the highest ranked ASMs, the mean predicted seizure-free probability would be 68.05% (95% CI 65.79%-70.35%) compared with the observed seizure-free rate of 47.2% (95% CI 41.3%-53.2%). DISCUSSION/CONCLUSIONS:Integrating genomic data with clinical features enhances the ability of deep learning models in predicting ASM response in newly diagnosed epilepsy. This approach may support personalized treatment selection and improve clinical outcomes.

This guideline summarizes updated safety data (2017-2025) and provides expert recommendations on the use of low intensity transcranial electrical stimulation (tES) in humans. tES encompasses several techniques including transcranial direct current stimulation (tDCS), oscillatory transcranial direct current stimulation (otDCS), transcranial alternating current stimulation (tACS), transcranial random noise stimulation (tRNS), transcranial temporal interference stimulation (tTIS), and their combinations or variations. Across over 300,000 sessions involving healthy individuals, patients with neuropsychiatric conditions, and other clinical populations, no tES-related serious adverse events (AEs) have been reported. Moderate AEs are rare and limited to a small range of specific applications. Mild AEs are common and include transient symptoms such as localized sensations (e.g., tingling or burning), headaches, and fatigue. Similar mild AEs are also reported by individuals receiving placebo stimulation. The frequency, magnitude, and type of AEs are comparable across healthy, clinical, and vulnerable groups, including children, elderly, or pregnant women. Combined interventions (e.g., co-application with EEG, TMS, or neuroimaging) have not shown increased safety risks. Safety is well-established for both bipolar and multichannel tES when applied up to 4 mA and up to 60 min per day. Higher intensities and longer stimulation durations may also be safe. Nevertheless, the number of studies using intensities above 4 mA or stimulating longer than 60 min is low. Home-based use of treatments is growing rapidly, leveraging remote supervision to provide patients with greater access and enable repeated, sustained dosing paradigms. We recommend using screening and AE questionnaires in future controlled studies, in particular when planning to extend the stimulation parameters applied. We discuss recent regulatory and ethical issues.