Faculty Bibliography

The cerebellum, a subcortical structure, is traditionally linked to sensorimotor integration and coordination, although its role in cognition and affective behavior, as well as epilepsy, is increasingly recognized. Cerebellar dysfunction in patients with epilepsy can result from genetic disorders, antiseizure medications, seizures, and seizure-related trauma. Impaired cerebellar function, regardless of cause, can cause ataxia (imbalance, impaired coordination, unsteady gait), tremor, gaze-evoked nystagmus, impaired slow gaze pursuit and saccade accuracy, as well as speech deficits (slurred, scanning, or staccato). We explore how cerebellar dysfunction can contribute to epilepsy, reviewing data on genetic, infectious, and neuroinflammatory disorders. Evidence of cerebellar dysfunction in epilepsy comes from animal studies as well as human neuropathology and structural magnetic resonance imaging (MRI), functional and diffusion tensor MRI, positron emission and single photon emission computerized tomography, and depth electrode electro-encephalography studies. Cerebellar lesions can infrequently cause epilepsy, with focal motor, autonomic, and focal to bilateral tonic-clonic seizures. Antiseizure medication-resistant epilepsy typically presents in infancy or before age 1 year with hemifacial clonic or tonic seizures ipsilateral to the cerebellar mass. Lesions are typically asymmetric benign or low-grade tumors in the floor of the fourth ventricle involving the cerebellar peduncles and extending to the cerebellar hemisphere. Electrical stimulation of the cerebellum has yielded conflicting results on efficacy, although methodological issues confound interpretation. Epilepsy-related comorbidities including cognitive and affective disorders, falls, and sudden unexpected death in epilepsy may also be impacted by cerebellar dysfunction. We discuss how cerebellar dysfunction may drive seizures and how genetic epilepsies, seizures and seizure therapies may drive cerebellar dysfunction, and how our understanding of epilepsy-related comorbidities through basic neuroscience, animals models and patient studies can advance our understanding and improve patient outcomes.

OBJECTIVE:Dravet syndrome (DS) is a severe developmental and epileptic encephalopathy caused by SCN1A haploinsufficiency in the majority of cases. Caregivers of adults with DS often complain about the loss of previously acquired skills. We set out to explore these perceptions and determine whether abnormalities reported were detectable in validated tests. We also investigated possible correlations between symptoms, age, and exposure to sodium channel blockers (SCBs). METHODS:This cross-sectional, multicenter study used the Vineland Adaptive Behavior Scales, 3rd edition (raw scores) for behavior analyses and Moss-Psychiatric Assessment Schedules checklist to screen for psychiatric symptoms. The Social Communication Questionnaire screened for social communication deficits. Parkinsonian features were evaluated with the modified Unified Parkinson's Disease Rating Scale. For gait evaluation, we validated the use of home videos, using instrumental gait analysis in a subgroup of patients, and then used the home videos for the remainder. RESULTS:A total of 92 patients were enrolled (age range = 18-51 years, mean = 27.93 ± 8.59 years). Sixty percent of caregivers observed a decline in previously acquired skills, including intelligence, speech, interaction with others, ability to climb stairs and walk without support, and hand coordination. Adaptive skills, parkinsonian symptoms, and gait were worse in older patients and those exposed to SCBs for longer periods of time. Fourteen percent of patients screened positive for affective disorders, 11.6% for dementia, and 10.5% for a psychotic disorder. Fifty-three percent screened positive for social communication deficits. SIGNIFICANCE/CONCLUSIONS:This is the largest group of adults with DS to be systematically evaluated. They had severe nonseizure symptoms. Older age and longer use of SCBs were associated with worse adaptive skills, gait, and parkinsonism. Some older adults screened positive for depression and dementia. Caregivers identified functional decline in activities of daily living (ADLs). Taken together, the risk of dementia, parkinsonian gait, and decline in ability to perform previously mastered ADLs support that some adults with DS may be developing a neurodegenerative disorder.

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.

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.

This study introduces a unified computational framework connecting acoustic, speech and word-level linguistic structures to study the neural basis of everyday conversations in the human brain. We used electrocorticography to record neural signals across 100 h of speech production and comprehension as participants engaged in open-ended real-life conversations. We extracted low-level acoustic, mid-level speech and contextual word embeddings from a multimodal speech-to-text model (Whisper). We developed encoding models that linearly map these embeddings onto brain activity during speech production and comprehension. Remarkably, this model accurately predicts neural activity at each level of the language processing hierarchy across hours of new conversations not used in training the model. The internal processing hierarchy in the model is aligned with the cortical hierarchy for speech and language processing, where sensory and motor regions better align with the model's speech embeddings, and higher-level language areas better align with the model's language embeddings. The Whisper model captures the temporal sequence of language-to-speech encoding before word articulation (speech production) and speech-to-language encoding post articulation (speech comprehension). The embeddings learned by this model outperform symbolic models in capturing neural activity supporting natural speech and language. These findings support a paradigm shift towards unified computational models that capture the entire processing hierarchy for speech comprehension and production in real-world conversations.

Presence of focal to bilateral tonic-clonic seizures (FBTCS) in focal epilepsy is associated with increased morbidity and mortality. Risk factors for FBTCS are poorly understood, and little is known regarding FBTCS recurrence after treatment initiation. This study aimed to investigate factors related to FBTCS in newly diagnosed focal epilepsy and their recurrence after starting antiseizure medications (ASMs) in the Human Epilepsy Project (HEP) cohort. HEP was an international, prospective cohort study that enrolled people with newly diagnosed focal epilepsy within 4 months of treatment initiation and followed them for up to 6 years. Baseline characteristics, treatment choices, and seizure outcomes were collected. Descriptive and inferential statistical analysis was conducted to assess the differences between study participants who had FBTCS and those who never experienced FBTCS. A total of 443 participants were included in this analysis; 77% (n = 342) had FBTCS at some point prior to or within the study period. In participants with FBTCS, regardless of initial seizure type, diagnosis was mostly made after FBTCS (335/342, 98%). After treatment initiation, FBTCS did not recur in 57% (n = 194/342) of cases. A higher number of total pretreatment seizures (median = 16 vs. 11, p = .048, Mann-Whitney U-test), predominantly focal aware seizures (FAS) or focal impaired awareness seizures (FIAS; median = 15 vs. 10, p = .049, Mann Whitney U-test), was associated with no recurrence in FBTCS after treatment initiation. Of 108 participants without FBTCS prior to treatment, only seven (6%) developed FBTCS after treatment initiation. There was no significant difference in choice of initial ASM class (levetiracetam vs. sodium channel blockers) between participants who experienced FBTCS and those who did not. This study highlights the significance of FBTCS among individuals with newly diagnosed focal epilepsy. The majority of participants who experienced FBTCS were diagnosed with epilepsy after experiencing their first FBTCS despite preceding FAS/FIAS. The more frequent FAS/FIAS in participants whose FBTCS resolved may be a characteristic of their epilepsy.

Altered protein conformation can cause incurable neurodegenerative disorders. Mutations in SERPINI1, the gene encoding neuroserpin, can alter protein conformation resulting in cytotoxic aggregation leading to neuronal death. Familial encephalopathy with neuroserpin inclusion bodies (FENIB) is a rare autosomal dominant progressive myoclonic epilepsy that progresses to dementia and premature death. We developed HEK293T and induced pluripotent stem cell (iPSC) models of FENIB, harboring a patient-specific pathogenic SERPINI1 variant or stably overexpressing mutant neuroserpin fused to GFP (MUT NS-GFP). Here, we utilized a personalized adenine base editor (ABE)-mediated approach to correct the pathogenic variant efficiently and precisely to restore neuronal dendritic morphology. ABE-treated MUT NS-GFP cells demonstrated reduced inclusion size and number. Using an inducible MUT NS-GFP neuron system, we identified early prevention of toxic protein expression allowed aggregate clearance, while late prevention halted further aggregation. To address several challenges for clinical applications of gene correction, we developed a neuron-specific engineered virus-like particle to optimize neuronal ABE delivery, resulting in higher correction efficiency. Our findings provide a targeted strategy that may treat FENIB and potentially other neurodegenerative diseases due to altered protein conformation such as Alzheimer's and Huntington's diseases.

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 convergence relevant to daily auditory discourse remain poorly understood. Here, we leveraged neurosurgical electrocorticographic (ECoG) recordings from 48 patients and dissociated two key language networks that highly overlap in time and space integral to 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 agnostic to input modalities. Functionally, we confirmed that the semantic processing network encodes word surprisal during sentence perception. Our findings characterize how humans integrate ongoing auditory semantic information over time, a critical linguistic function from passive comprehension to daily discourse.

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 an untested assumption that insights from this literature generalize to more naturalistic utterances like sentences. Here, we investigate this using high-resolution neurosurgical recordings (ECoG) and an overt production experiment where patients produce six words in isolation (picture naming) and in sentences (scene description). We trained machine learning models to identify the unique brain activity pattern for each word during picture naming, and used these patterns to decode which words patients were processing while they produced sentences. Our findings reveal that words share cortical representations across tasks. In sensorimotor cortex, words were consistently activated in the order in which they were said in the sentence. However, in inferior and middle frontal gyri (IFG and MFG), the order in which words were processed depended on the syntactic structure of the sentence. This dynamic interplay between sentence structure and word processing reveals that sentence production is not simply a sequence of single word production tasks, and highlights a regional division of labor within the language network. Finally, we argue that the dynamics of word processing in prefrontal cortex may impose a subtle pressure on language evolution, explaining why nearly all the world's languages position subjects before objects.