Faculty Bibliography

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.

Syntax, the abstract structure of language, is a hallmark of human cognition. Despite its importance, its neural underpinnings remain obscured by inherent limitations of non-invasive brain measures and a near total focus on comprehension paradigms. Here, we address these limitations with high-resolution neurosurgical recordings (electrocorticography) and a controlled sentence production experiment. We uncover three syntactic networks that are broadly distributed across traditional language regions, but with focal concentrations in middle and inferior frontal gyri. In contrast to previous findings from comprehension studies, these networks process syntax mostly to the exclusion of words and meaning, supporting a cognitive architecture with a distinct syntactic system. Most strikingly, our data reveal an unexpected property of syntax: it is encoded independent of neural activity levels. We propose that this "low-activity coding" scheme represents a novel mechanism for encoding information, reserved for higher-order cognition more broadly.

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.

Down syndrome (DS) is strongly associated with Alzheimer's disease (AD) due to APP overexpression, exhibiting Amyloid-β (Aβ) and Tau pathology similar to early-onset (EOAD) and late-onset AD (LOAD). We evaluated the Aβ plaque proteome of DS, EOAD, and LOAD using unbiased localized proteomics on post-mortem paraffin-embedded tissues from four cohorts (n = 20/group): DS (59.8 ± 4.99 y/o), EOAD (63 ± 4.07 y/o), LOAD (82.1 ± 6.37 y/o), and controls (66.4 ± 13.04). We identified differentially abundant proteins when comparing Aβ plaques and neighboring non-plaque tissue (FDR < 5%, fold-change > 1.5) in DS (n = 132), EOAD (n = 192), and LOAD (n = 128), with 43 plaque-associated proteins shared across all groups. Positive correlations were observed between plaque-associated proteins in DS and EOAD (R² = .77), DS and LOAD (R² = .73), and EOAD and LOAD (R² = .67). Top gene ontology biological processes (GOBP) included lysosomal transport (p = 1.29 × 10^-5) for DS, immune system regulation (p = 4.33 × 10^-5) for EOAD, and lysosome organization (p = 0.029) for LOAD. Protein networks revealed a plaque-associated protein signature involving APP metabolism, immune response, and lysosomal functions. In DS, EOAD, and LOAD non-plaque vs. control tissue, we identified 263, 269, and 301 differentially abundant proteins, with 65 altered proteins shared across all cohorts. Non-plaque proteins in DS showed modest correlations with EOAD (R² = .59) and LOAD (R² = .33) compared to the correlation between EOAD and LOAD (R² = .79). Top GOBP term for all groups was chromatin remodeling (p < 0.001), with additional terms for DS including extracellular matrix, and protein-DNA complexes and gene expression regulation for EOAD and LOAD. Our study reveals key functional characteristics of the amyloid plaque proteome in DS, compared to EOAD and LOAD, highlighting shared pathways in endo/lysosomal functions and immune responses. The non-plaque proteome revealed distinct alterations in ECM and chromatin structure, underscoring unique differences between DS and AD subtypes. Our findings enhance our understanding of AD pathogenesis and identify potential biomarkers and therapeutic targets.

OBJECTIVES/OBJECTIVE:Late-onset epilepsy has the highest incidence among all age groups affected by epilepsy and often occurs in the absence of known clinical risk factors such as stroke and dementia. There is increasing evidence that brain changes contributing to epileptogenesis likely start years before disease onset, and we aim to relate cognitive and imaging correlates of subclinical brain injury to incident late-onset epilepsy in a large, community-based cohort. METHODS:We studied Offspring Cohort of the Framingham Heart Study participants 45 years or older, who were free of prevalent stroke, dementia, or epilepsy, and had neuropsychological (NP) evaluation and brain magnetic resonance imaging (MRI). Cognitive measures included Visual Reproduction Delayed Recall, Logical Memory Delayed Recall, Similarities, Trail Making Test B minus A (TrTB-TrTA; attention and executive function), and a global measure of cognition derived from principal component analysis. MRI measures included total cerebral brain volume, cortical gray matter volume (CGMV), white matter hyperintensity volume (WMHV), and hippocampal volume. Incident epilepsy was identified through a review of administrative data and medical records. Cox proportional hazards regression models were used for the analyses. All analyses were adjusted for age, sex, and educational level (cognition only). RESULTS:Among participants who underwent NP testing (n = 2349, 45.81% male), 31 incident epilepsy cases were identified during follow-up. Better performance on the TrTB-TrTA was associated with a lower risk of developing epilepsy (hazard ratio [HR] .25, 95% confidence interval [CI] .08-.73; p = .011). In the subgroup of participants with MRI (n = 2056, 46.01% male), 27 developed epilepsy. Higher WMHV was associated with higher epilepsy risk (HR 1.5, 95%CI 1.01-2.20; p = .042), but higher CGMV (HR .73, 95% CI .57-.93; p = .001) was associated with lower incidence of epilepsy. SIGNIFICANCE/CONCLUSIONS:Better performance on the (TrTB-TrTA), a measure of executive function and attention, and higher cortical volumes are associated with lower risk of developing epilepsy. Conversely, higher WMHV, a measure of occult vascular injury, increases the risk. Our study shows that non-invasive tests performed in mid-life may help identify people at risk for developing epilepsy later in life.