Faculty Bibliography

BACKGROUND:Isolated psychiatric symptoms can be the initial symptom of pediatric anti-N-methyl-d-aspartate (NMDA) receptor autoimmune encephalitis (pNMDARE). Here we report on the prevalence of isolated psychiatric symptoms in pNMDARE. We also assess whether initial neurodiagnostic tests (brain magnetic resonance imaging [MRI], electroencephalography [EEG], and/or cerebrospinal fluid [CSF] white blood cell count) are abnormal in children with isolated psychiatric symptoms and pNMDARE. METHODS:This multicenter retrospective cohort study from CONNECT (Conquering Neuroinflammation and Epilepsies Consortium) from 14 institutions included children under age 18 years who were diagnosed with pNMDARE. Descriptive statistics using means, medians, and comparisons for continuous versus discrete data was performed. RESULTS:Of 249 children included, 12 (5%) had only psychiatric symptoms without other typical clinical features of autoimmune encephalitis at presentation. All but one (11 of 12 = 92%) had at least one abnormal finding on initial ancillary testing: eight of 12 (67%) had an abnormal EEG, six of 12 (50%) had an abnormal MRI, and five of 12 (42%) demonstrated CSF pleocytosis. The single patient with a normal MRI, EEG, and CSF profile had low positive CSF NMDA antibody (titer of 1:1), and symptoms improved without immunotherapy. CONCLUSIONS:Isolated first-episode psychiatric symptoms in pNMDARE are uncommon, and the majority of children will exhibit additional neurodiagnostic abnormalities. Delaying immunotherapy in a child with isolated psychiatric symptoms and normal neurodiagnostic testing may be warranted while awaiting confirmatory antibody testing.

Cenobamate has demonstrated efficacy in patients with treatment-resistant epilepsy, including patients who continued to have seizures after epilepsy surgery. This article provides recommendations for cenobamate use in patients referred for epilepsy surgery evaluation. A panel of six senior epileptologists from the United States and Europe with experience in presurgical evaluation of patients with epilepsy and in the use of antiseizure medications (ASMs) was convened to provide consensus recommendations for the use of cenobamate in patients referred for epilepsy surgery evaluation. Many patients referred for surgical evaluation may benefit from ASM optimization; both ASM and surgical treatment should be individualized. Based on previous clinical studies and the authors' clinical experience with cenobamate, a substantial proportion of patients with treatment-resistant epilepsy can become seizure-free with cenobamate. We recommend a cenobamate trial and ASM optimization in parallel with presurgical evaluations. Cenobamate can be started before phase two monitoring, especially in patients who are found to be suboptimal surgery candidates. As neurostimulation therapies are generally palliative, we recommend trying cenobamate before vagus nerve stimulation (VNS), deep brain stimulation, or responsive neurostimulation (RNS). In surgically remediable cases (mesial temporal sclerosis, benign discrete lesion in non-eloquent cortex, cavernous angioma, etc.), cenobamate use should not delay imminent surgery; however, a patient may decide to defer or even cancel surgery should they achieve sustained seizure freedom with cenobamate. This decision should be made on an individual, case-by-case basis based on seizure etiology, patient preferences, potential surgical risks (mortality and morbidity), and likely surgical outcome. The addition of cenobamate after unsuccessful surgery or palliative neuromodulation may also be associated with better outcomes.

Whether high-frequency phase-locked oscillations facilitate integration ('binding') of information across widespread cortical areas is controversial. Here we show with intracranial electroencephalography that cortico-cortical co-ripples (~100-ms-long ~90 Hz oscillations) increase during reading and semantic decisions, at the times and co-locations when and where binding should occur. Fusiform wordform areas co-ripple with virtually all language areas, maximally from 200 to 400 ms post-word-onset. Semantically specified target words evoke strong co-rippling between wordform, semantic, executive and response areas from 400 to 800 ms, with increased co-rippling between semantic, executive and response areas prior to correct responses. Co-ripples were phase-locked at zero lag over long distances (>12 cm), especially when many areas were co-rippling. General co-activation, indexed by non-oscillatory high gamma, was mainly confined to early latencies in fusiform and earlier visual areas, preceding co-ripples. These findings suggest that widespread synchronous co-ripples may assist the integration of multiple cortical areas for sustained periods during cognition.

OBJECTIVE:To characterize the experience of people with epilepsy and aligned healthcare workers (HCWs) during the first 18 months of the COVID-19 pandemic and compare experiences in high-income countries (HICs) with non-HICs. METHODS:Separate surveys for people with epilepsy and HCWs were distributed online in April 2020. Responses were collected to September 2021. Data were collected for COVID-19 infections, the effect of COVID-related restrictions, access to specialist help for epilepsy (people with epilepsy), and the impact of the pandemic on work productivity (HCWs). The frequency of responses for non-HICs and HICs were compared using non-parametric Chi-square tests. RESULTS:Two thousand one hundred and  five individuals with epilepsy from 53 countries and 392 HCWs from 26 countries provided data. The same proportion of people with epilepsy in non-HICs and HICs reported COVID-19 infection (7%). Those in HICs were more likely to report that COVID-19 measures had affected their health (32% vs. 23%; p < 0.001). There was no difference between non-HICs and HICs in the proportion who reported difficulty in obtaining help for epilepsy. HCWs in non-HICs were more likely to report COVID-19 infection than those in HICs (18% vs 6%; p = 0.001) and that their clinical work had been affected by concerns about contracting COVID-19, lack of personal protective equipment, and the impact of the pandemic on mental health (all p < 0.001). Compared to pre-pandemic practices, there was a significant shift to remote consultations in both non-HICs and HICs (p < 0.001). SIGNIFICANCE/CONCLUSIONS:While the frequency of COVID-19 infection was relatively low in these data from early in the pandemic, our findings suggest broader health consequences and an increased psychosocial burden, particularly among HCWs in non-HICs. Planning for future pandemics should prioritize mental healthcare alongside ensuring access to essential epilepsy services and expanding and enhancing access to remote consultations. PLAIN LANGUAGE SUMMARY/CONCLUSIONS:We asked people with epilepsy about the effects of COVID-19 on their health and healthcare. We wanted to compare responses from people in high-income countries and other countries. We found that people in high-income countries and other countries had similar levels of difficulty in getting help for their epilepsy. People in high-income countries were more likely to say that their general health had been affected. Healthcare workers in non-high-income settings were more likely to have contracted COVID-19 and have the care they deliver affected by the pandemic. Across all settings, COVID-19 associated with a large shift to remote consultations.

OBJECTIVE:The Human Epilepsy Project (HEP) is a large multinational cohort study of people with newly diagnosed and treated focal epilepsy. HEP utilized the Cogstate Brief Battery (CBB) as a self-directed online assessment to examine cognitive outcomes in study participants. The CBB has previously been validated in healthy individuals and people with various brain disorders, but its use in adults participating in HEP has not been assessed. In this study, we describe how the CBB was used in the HEP cohort and assess factors associated with test completion among study participants. METHODS:Enrollment data for HEP included 408 participants with comprehensive enrollment records, of whom 249 completed CBB assessments. HEP enrolled cognitively normal-range participants between the ages of 12 and 60 from June 29, 2012, to November 7, 2017, with newly diagnosed focal epilepsy and within 4 months of initial treatment. Baseline participant characteristics were analyzed, including demographics, pre-treatment seizure histories, MRI abnormalities, and the presence of any learning difficulties while in school, including formal learning disability diagnoses, repeated grades, and remediation. HEP participant characteristics for those who completed CBB testing were compared to those who did not using multiple logistic regression. RESULTS:The analysis of HEP participants who completed CBB testing showed that, after controlling for other factors, male participants were more likely to engage in testing (OR 2.14, 95 % CI 1.29 to 3.5, p < 0.01), Black subjects were less likely (OR 0.45, 95 % CI 0.22 to 0.9, p = 0.02), primary English speakers were more likely (OR 3.1, 95 % CI 1.21 to 7.96, p = 0.02), and those with a history of learning challenges were less likely (OR 0.69, 95 % CI 0.49 to 0.97, p = 0.03). There were no significant associations between completing CBB testing and age, employment (employed or student vs not), education (higher education vs not), diagnostic delay, pre-diagnostic seizure burden, or initial seizure semiology (motor vs non-motor). SIGNIFICANCE/CONCLUSIONS:The findings from this study highlight factors associated with the application of remote and unsupervised assessments of cognition in a prospective cohort of adults with focal epilepsy. These factors can be considered when interpreting performance on the CBB in HEP, as well as assisting the design of future studies that use similar approaches.

DHPS deficiency syndrome is an ultra-rare neurodevelopmental disorder (NDD) which results from biallelic mutations in the gene encoding the enzyme deoxyhypusine synthase (DHPS). DHPS is essential to synthesize hypusine, a rare amino acid formed by post-translational modification of a conserved lysine in eukaryotic initiation factor 5 A (eIF5A). DHPS deficiency syndrome causes epilepsy, cognitive and motor impairments, and mild facial dysmorphology. In mice, a brain-specific genetic deletion of Dhps at birth impairs eIF5A^HYP-dependent mRNA translation. This alters expression of proteins required for neuronal development and function, and phenotypically models features of human DHPS deficiency. We studied the role of DHPS in early brain development using a zebrafish loss-of-function model generated by knockdown of dhps expression with an antisense morpholino oligomer (MO) targeting the exon 2/intron 2 (E2I2) splice site of the dhps pre-mRNA. dhps knockdown embryos exhibited dose-dependent developmental delay and dysmorphology, including microcephaly, axis truncation, and body curvature. In dhps knockdown larvae, electrophysiological analysis showed increased epileptiform activity, and confocal microscopy analysis revealed reduced arborisation of GABAergic neurons. Our findings confirm that hypusination of eIF5A by DHPS is needed for early brain development, and zebrafish with an antisense knockdown of dhps model features of DHPS deficiency syndrome.

Effective communication hinges on a mutual understanding of word meaning in different contexts. We recorded brain activity using electrocorticography during spontaneous, face-to-face conversations in five pairs of epilepsy patients. We developed a model-based coupling framework that aligns brain activity in both speaker and listener to a shared embedding space from a large language model (LLM). The context-sensitive LLM embeddings allow us to track the exchange of linguistic information, word by word, from one brain to another in natural conversations. Linguistic content emerges in the speaker's brain before word articulation and rapidly re-emerges in the listener's brain after word articulation. The contextual embeddings better capture word-by-word neural alignment between speaker and listener than syntactic and articulatory models. Our findings indicate that the contextual embeddings learned by LLMs can serve as an explicit numerical model of the shared, context-rich meaning space humans use to communicate their thoughts to one another.

OBJECTIVE/UNASSIGNED:This study investigates speech decoding from neural signals captured by intracranial electrodes. Most prior works can only work with electrodes on a 2D grid (i.e., Electrocorticographic or ECoG array) and data from a single patient. We aim to design a deep-learning model architecture that can accommodate both surface (ECoG) and depth (stereotactic EEG or sEEG) electrodes. The architecture should allow training on data from multiple participants with large variability in electrode placements and the trained model should perform well on participants unseen during training. APPROACH/UNASSIGNED:We propose a novel transformer-based model architecture named SwinTW that can work with arbitrarily positioned electrodes, by leveraging their 3D locations on the cortex rather than their positions on a 2D grid. We train both subject-specific models using data from a single participant as well as multi-patient models exploiting data from multiple participants. MAIN RESULTS/UNASSIGNED:The subject-specific models using only low-density 8x8 ECoG data achieved high decoding Pearson Correlation Coefficient with ground truth spectrogram (PCC=0.817), over N=43 participants, outperforming our prior convolutional ResNet model and the 3D Swin transformer model. Incorporating additional strip, depth, and grid electrodes available in each participant (N=39) led to further improvement (PCC=0.838). For participants with only sEEG electrodes (N=9), subject-specific models still enjoy comparable performance with an average PCC=0.798. The multi-subject models achieved high performance on unseen participants, with an average PCC=0.765 in leave-one-out cross-validation. SIGNIFICANCE/UNASSIGNED:The proposed SwinTW decoder enables future speech neuroprostheses to utilize any electrode placement that is clinically optimal or feasible for a particular participant, including using only depth electrodes, which are more routinely implanted in chronic neurosurgical procedures. Importantly, the generalizability of the multi-patient models suggests the exciting possibility of developing speech neuroprostheses for people with speech disability without relying on their own neural data for training, which is not always feasible.

Sound structures such as phonemes and words have highly variable durations. Thus, there is a fundamental difference between integrating across absolute time (e.g., 100 ms) vs. sound structure (e.g., phonemes). Auditory and cognitive models have traditionally cast neural integration in terms of time and structure, respectively, but the extent to which cortical computations reflect time or structure remains unknown. To answer this question, we rescaled the duration of all speech structures using time stretching/compression and measured integration windows in the human auditory cortex using a new experimental/computational method applied to spatiotemporally precise intracranial recordings. We observed significantly longer integration windows for stretched speech, but this lengthening was very small (~5%) relative to the change in structure durations, even in non-primary regions strongly implicated in speech-specific processing. These findings demonstrate that time-yoked computations dominate throughout the human auditory cortex, placing important constraints on neurocomputational models of structure processing.