Faculty Bibliography

BACKGROUND AND OBJECTIVES/OBJECTIVE:The aim of this study was to identify distinct inflammatory response subtypes in patients with c-NORSE by analyzing their cytokine profiles. Insights into underlying mechanisms were sought to understand the pathophysiology and guide personalized therapies to improve patient outcomes. METHODS:Sixty-two patients with c-NORSE were included. A comprehensive panel of 96 cytokines was analyzed in serum samples. Patients were clustered based on their cytokine profiles using the Louvain algorithm, an unsupervised graph-based clustering method. The identified clusters of patients were compared regarding cytokine levels and clinical features. Protein pathway analysis was used to explore the biological relevance of the inflammatory markers within each cluster. Patients with c-NORSE were compared with control patients (n = 18) and patients with other forms of refractory SE (n = 45). RESULTS:Compared with controls, patients with c-NORSE exhibited significant differences in 33 cytokines. Pathway analysis revealed dysregulations in chemotaxis and neutrophil recruitment and migration, highlighting the importance of innate immunity in patients with c-NORSE. Within the c-NORSE cohort, 3 clusters of patients emerged: cluster A, lacking specific inflammatory markers; cluster B, with a much stronger innate-immunity cytokine-driven inflammatory response compared with clusters A and C; and cluster C, defined by dysregulated autoimmune processes. Notably, patients in cluster B showed a statistically significant elevation of innate immune-related proinflammatory cytokines associated with leukocyte recruitment and degranulation. By contrast, those in cluster C showed activation of Janus kinase signal transducer and activator of transcription (JAK-STAT) pathways, suggesting autoimmune mechanisms. Patients in clusters B and C demonstrated varied responses to immunotherapies, with cluster C patients showing favorable outcomes after multiple immunotherapies. DISCUSSION/CONCLUSIONS:The identification of distinct inflammatory subgroups in c-NORSE suggests that variations in the underlying immune mechanisms contribute to differential treatment responses. These findings underscore the importance of personalized therapeutic strategies, potentially targeting specific inflammatory pathways, to optimize clinical outcomes in this challenging condition.

Neuronal oscillations at about 10 Hz, called alpha oscillations, are often thought to arise from synchronous activity across the occipital cortex and are usually largest when the cortex is inactive. However, recent studies measuring visual receptive fields have reported that local alpha power increases when cortex is excited by visual stimulation. This contrasts with the expectation that alpha oscillations are associated with cortical inactivity. Here, we used intracranial electrodes in human patients to measure alpha oscillations in response to visual stimuli whose location varied systematically across the visual field. We hypothesized that stimulus-driven local increases in alpha power result from a mixture of two effects: a reduction in alpha oscillatory power and a simultaneous increase in broadband power. To test this, we implemented a model to separate these components. The two components were then independently fit by population receptive field (pRF) models. We find that the alpha pRFs have similar center locations to pRFs estimated from broadband power but are several times larger and exhibit the opposite effect: alpha oscillatory power decreases in response to stimuli within the receptive field, reinforcing the link between alpha oscillations and cortical inactivity, whereas broadband power increases. The results demonstrate that alpha suppression in the human visual cortex can be precisely tuned, but that to measure these effects, it is essential to separate the oscillatory signal from broadband power changes. Finally, we show how the large size and the negative valence of alpha pRFs can explain key features of exogenous visual attention.

Sleep disturbances are prominent across neurodevelopmental disorders (NDDs) and may reflect specific abnormalities in brain development and function. Overnight polysomnography (PSG) allows for detailed investigation of sleep architecture, offering a unique window into neurocircuit function. Analysis of existing pediatric PSGs from clinical studies could enhance the availability of sleep studies in pediatric patients with NDDs towards a better understanding of mechanisms underlying abnormal development in NDDs. Here, we introduce and characterize a retrospective collection of 1527 clinical pediatric overnight PSGs across five different sites. We first developed an automated stager trained on independent pediatric sleep data, which yielded better performance compared to a generic stager trained primarily on adults. Using consistent staging across cohorts, we derived a panel of EEG micro-architectural features. This unbiased approach replicated broad trajectories previously described in typically developing sleep architecture. Further, we found sleep architecture disruptions in children with Down's Syndrome (DS) that were consistent across independent cohorts. Finally, we built and evaluated a model to predict age from sleep EEG metrics, which recapitulated our previous findings of younger predicted brain age in children with DS. Altogether, by creating a resource pooled from existing clinical data we expanded the available datasets and computational resources to study sleep in pediatric populations, specifically towards a better understanding of sleep in NDDs. This Retrospective Analysis of Sleep in Pediatric (RASP) cohorts dataset, including staging annotation derived from our automated stager, is deposited at https://sleepdata.org/datasets/rasp.

Sentence production is the uniquely human ability to transform complex thoughts into strings of words. Despite the importance of this process, language production research has primarily focused on single words. It remains a largely untested assumption that the principles of word production generalize to more naturalistic utterances like sentences. Here, we investigate this using high-resolution neurosurgical recordings (ECoG) and an overt production experiment where ten patients produced six words in isolation (picture naming) and in sentences (scene description). We trained machine learning classifiers to identify the unique brain activity patterns for each word during picture naming, and used these patterns to decode which words patients were processing while they produced sentences. Our findings confirm that words share cortical representations across tasks, but reveal a division of labor within the language network. In sensorimotor cortex, words were consistently activated in the order in which they were said in the sentence. However, in prefrontal cortex, the order in which words were processed depended on the syntactic structure of the sentence. In non-canonical sentences (passives), we further observed a spatial code for syntactic roles, with subjects selectively encoded in inferior frontal gyrus (IFG) and objects selectively encoded in middle frontal gyrus (MFG). We suggest that these complex dynamics of prefrontal cortex may impose a subtle pressure on language evolution, potentially explaining why nearly all the world's languages position subjects before objects.

BACKGROUND AND OBJECTIVES/OBJECTIVE:Disturbances in brain catecholamine activity may be associated with symptoms after exposure to repetitive head impacts (RHIs) or related chronic traumatic encephalopathy (CTE). In this article, we studied CSF catecholamines in former professional and college American football players and examined the relationship with football proxies of RHI exposure, CTE probability, cognitive performance, neuropsychiatric symptoms, and parkinsonism. METHODS:In this observational cross-sectional study, we examined male former American football players, professional ("PRO") or college ("COL") level, and asymptomatic unexposed male ("UE") individuals from the DIAGNOSE CTE Research Project. Catecholamines-norepinephrine (NE) and its metabolite, 3,4-dihydroxyphenylglycol (DHPG), and dopamine (DA) and its precursor, 3,4-dihydroxyphenylalanine (l-DOPA), and metabolite, 3,4-dihydroxyphenylacetic acid (DOPAC)-were measured in CSF with high-performance liquid chromatography and compared across groups with analysis of covariance. Multivariable linear regression models tested the relationship between CSF catecholamines and proxies of RHI exposure (e.g., total years of playing American football), factor scores for cognition, and neurobehavioral dysregulation (explosivity, emotional dyscontrol, impulsivity, affective lability), as well as depressive/anxiety symptoms, measured with the Beck Depression/Anxiety Inventories. CTE probability and parkinsonism were assessed using the National Institute of Neurological Disorders and Stroke consensus diagnostic criteria for traumatic encephalopathy syndrome (TES), and biomarkers were compared among different diagnostic groups. RESULTS:The cohort consisted of 120 former American football players (85 PRO players, 35 COL players) and 35 UE participants (age 45-75). Former players had significantly lower levels of NE (mean difference = -0.114, 95% CI -0.190 to -0.038), l-DOPA (-0.121, 95% CI -0.109 to -0.027), and DOPAC (-0.116, 95% CI -0.177 to -0.054) than UE participants. For NE and DOPAC, these overall group differences were primarily due to differences between the PRO and UE cohorts. No significant differences were found across TES-CTE probability subgroups or TES-parkinsonism diagnostic groups. Within the COL cohort, tested as post hoc analyses, higher CSF NE and l-DOPA were associated with higher neurobehavioral dysregulation factor scores, BAI total score, and worse executive functioning and processing speed. CSF DHPG and DOPAC were associated with impulsivity only in this subgroup. DISCUSSION/CONCLUSIONS:We observed reduced CSF catecholamine concentrations in former elite American football players, although the relationship with degree of RHI exposure and the clinical impact needs further study.

We introduce an intracranial EEG (iEEG) dataset collected as part of an adversarial collaboration between proponents of two theories of consciousness: Global Neuronal Workspace Theory and Integrated Information Theory. The data were recorded from 38 patients undergoing intracranial monitoring of epileptic seizures across three research centers using the same experimental protocol. Participants were presented with suprathreshold visual stimuli belonging to four different categories (faces, objects, letters, false fonts) in three orientations (front, left, right view), and for three durations (0.5, 1.0, 1.5 s). Participants engaged in a non-speeded Go/No-Go target detection task to identify infrequent targets with some stimuli becoming task-relevant and others task-irrelevant. Participants also engaged in a motor localizer task. The data were checked for its quality and converted to Brain Imaging Data Structure (BIDS). The de-identified dataset contains demographics, clinical information, electrode reconstruction, behavioral performance, and eye-tracking data. We also provide code to preprocess and analyze the data. This dataset holds promise for reuse in consciousness science and vision neuroscience to answer questions related to stimulus processing, target detection, and task-relevance, among many others.

OBJECTIVE:New-onset refractory status epilepticus (NORSE) occurs in people without pre-existing epilepsy or a rapidly identified structural, toxic, metabolic, or other cause. NORSE is a rare disorder with high morbidity and mortality rates and limited evidence for effective therapies. We aimed to assess whether the gut microbiome of NORSE and status epilepticus (SE) differs from that of chronic epilepsy, whether NORSE differs from SE at different disease time points, and to examine the correlations between specific gut microbiota and cytokines in NORSE and SE. METHODS:This longitudinal cohort study observed patients with NORSE (n = 15), SE (n = 17), and chronic epilepsy who were not in SE (n = 12). NORSE patients were recruited through the NORSE Consortium. Patients with NORSE and SE underwent longitudinal serial biospecimen collection. Fecal samples were subjected to whole-community shotgun metagenomics to characterize microbiome features. Cohorts were evaluated for prokaryotic, eukaryotic, and functional diversity. Correlations between blood inflammatory cytokine levels and microbiome features and covariate analysis with critical illness and clinical treatments were examined for NORSE and SE patients during and after SE resolution. RESULTS:During SE, NORSE and SE patients had significantly different prokaryotic, eukaryotic, and functional microbiome levels compared to chronic epilepsy patients without SE. Limited microbiome differences were observed within and between NORSE and SE, although these groups displayed differing correlation patterns between microbial species and cytokines. Patients who later died or were tube-fed harbored significantly different microbiomes than those who survived or were orally fed. SIGNIFICANCE/CONCLUSIONS:NORSE and SE patients present with a more variable and dramatically different fecal microbiome than chronic epilepsy patients, which may indicate gut dysbiosis that may be reciprocally linked to inflammatory responses. Although NORSE and SE patients had similar microbiome structures, fungal and bacterial correlates with inflammatory cytokines differed between NORSE and SE, with confounding factors influencing microbiome structure. Our data suggest a microbiome-specific response to NORSE and SE, with implications for future treatment strategies.

OBJECTIVE:In traditionally designed randomized clinical trials of antiseizure medications, participants take a blinded treatment for a prespecified number of weeks, irrespective of continued seizures. The alternative design time to prerandomization monthly seizure count (T-PSC) allows participants to end the blinded treatment after an individually prespecified number of seizures, which shortens exposure to placebo and ineffective treatment. Previous reanalyses have shown that T-PSC replicated the efficacy conclusions of trials; therefore, we evaluated whether T-PSC also could replicate tolerability and safety conclusions. METHODS:We retrospectively applied the T-PSC design to analyze treatment-emergent adverse events (TEAEs) from three blinded, placebo-controlled trials of perampanel for focal onset seizures (NCT00699972, NCT00699582, NCT00700310). We evaluated the incidences of TEAEs, treatment-related TEAEs, serious TEAEs, and TEAEs that prompted medication adjustment compared to those observed during the full-length trial. RESULTS:Of the 1480 participants in the three trials, 1093 experienced any TEAE, of whom 1006 (92%) had onset prior to T-PSC. When evaluating the differences in each type of TEAE for each dose of perampanel from placebo within each trial, there was no consistent pattern of under- or overestimation. Across the three studies, 23 of 79 (29%) serious TEAEs, most requiring hospitalization, occurred after T-PSC. SIGNIFICANCE/CONCLUSIONS:Almost all TEAEs occurred before T-PSC. Similar conclusions regarding the tolerability and safety of perampanel would have been reached if the T-PSC design had been used. This suggests that the T-PSC design may potentially benefit participants by allowing earlier change from an ineffective treatment to an alternate treatment, which could reduce the risk of serious consequences of ineffective treatment, such as hospitalization.

Tractography is a unique modality for the in vivo measurement of structural connectivity, crucial for understanding brain networks and neurological conditions. With increasing b-value, the diffusion-weighting signal becomes primarily sensitive to the intra-axonal signal. However, it remains unclear how tractography is affected by this observation. Here, using open-source datasets, we showed that at high b-values, DWI reduces the uncertainty in estimating fiber orientations. Specifically, we found the ratio of biologically-meaningful longer-range connections increases, accompanied with downstream impact of redistribution of connectome and network metrics. However, when going beyond b = 6000 s/mm², the loss of SNR imposed a penalty. Lastly, we showed that the data reaches satisfactory reproducibility with b-values above 1200 s/mm². Overall, the results suggest that using b-values above 2500 s/mm² is essential for more accurate connectome reconstruction by reducing uncertainty in fiber orientation estimation, supporting the use of higher b-value protocols in standard diffusion MRI scans and pipelines.

The ability to connect the form and meaning of a concept, known as word retrieval, is fundamental to human communication. While various input modalities could lead to identical word retrieval, the exact neural dynamics supporting this process relevant to daily auditory discourse remain poorly understood. Here, we recorded neurosurgical electrocorticography (ECoG) data from 48 patients and dissociated two key language networks that highly overlap in time and space, critical for word retrieval. Using unsupervised temporal clustering techniques, we found a semantic processing network located in the middle and inferior frontal gyri. This network was distinct from an articulatory planning network in the inferior frontal and precentral gyri, which was invariant to input modalities. Functionally, we confirmed that the semantic processing network encodes word surprisal during sentence perception. These findings elucidate neurophysiological mechanisms underlying the processing of semantic auditory inputs ranging from passive language comprehension to conversational speech.