Eli J. Cornblath

Background and ObjectivesInpatient video-EEG epilepsy monitoring aims to provide a safe environment for antiseizure medication (ASM) tapering to precipitate seizures, which is often required for di...

About half of patients who undergo epilepsy surgery for drug-resistant epilepsy have seizure recurrence, supporting the need for approaches that more accurately identify the epileptogenic zone , defined as the brain areas whose removal causes cessation of seizures. Altered network connectivity has emerged as a candidate biomarker of the epileptogenic zone, but how connectivity is altered in the epileptogenic zone remains uncertain, with prior studies reporting inconsistent results. We hypothesized that a difference in intrinsic versus extrinsic connectivity of the epileptogenic zone may explain prior discrepant findings. We studied a multicenter cohort of adult and pediatric patients who underwent intracranial EEG recording and brain stimulation as part of epilepsy surgery planning. We measured spontaneous connectivity using Pearson correlation and perturbational connectivity using stimulation evoked potentials, modeling the connectivity according to the location of contacts in relation to the seizure onset zone (SOZ) while controlling for inter-electrode distance. We analyzed 79 patients (37 adults, 42 children). For both adult and pediatric patients, resting connectivity was higher within compared to outside the SOZ, but resting connectivity between SOZ and non-SOZ contacts was reduced. Stimulation connectivity followed a similar pattern, with elevated within-SOZ connectivity but reduced connectivity between SOZ and non-SOZ. The results support the hypothesis that the epileptogenic zone is disconnected from the rest of the brain but intrinsically hyperconnected. This result helps reconcile prior inconsistencies across studies, aligns with the results of basic science studies, and suggests that future translational work should model this heterogeneous pattern to increase the yield of using connectivity to localize the epileptogenic zone.

Seizures are often induced by electrical stimulation (stim seizures) during intracranial EEG (iEEG) evaluation for epilepsy surgery, but their value for localizing seizure generating tissue remains unclear. We compared 441 low-frequency (1 Hz) stim and spontaneous seizures in a multi-center cohort of 105 patients using a novel, state-of-the-art validated automated seizure mapping algorithm. We found that stim seizures recruit a smaller, more spatially restricted network than spontaneous seizures that overlaps with their onset and propagation. Stim seizures with habitual semiology exhibited onset zones indistinguishable from spontaneous seizures. Both clinically habitual and non-habitual stim seizure onset zones were rapidly recruited during spontaneous seizures, suggesting that they arise from hyperexcitable, epileptogenic, tissue. Stim seizures preferentially originated from pathological mesial temporal structures, especially in adult-onset epilepsy. We propose that stimulation mapping has potential to supplant recording spontaneous seizures, and hypothesize that the method may identify portions of epileptic networks susceptible to seizure recurrence after focal interventions.

Objective: Resting‐state functional magnetic resonance imaging (rs‐fMRI) at ultra‐high field strengths (≥7T) is known to provide superior signal‐to‐noise to comparable acquisitions at lower field strengths. In this study, we provide a direct comparison of the seizure onset‐zone (SOZ) lateralizing ability of 7T rs‐fMRI and 3T rs‐fMRI.Methods: We investigated a cohort of 70 patients with temporal lobe epilepsy (TLE). A paired cohort of 19 patients had 3T and 7T rs‐fMRI acquisitions for direct comparison between the two field strengths. Forty‐three patients had only 3T, and eight patients had only 7T rs‐fMRI acquisitions. We quantified the functional connectivity between the hippocampus and other nodes within the default mode network (DMN) using seed‐to‐voxel connectivity, and measured how hippocampal–DMN connectivity could inform SOZ lateralization at 7T and 3T field strengths.Results: Differences in hippocampal–DMN connectivity ipsilateral and contralateral to the SOZ were significantly higher at 7T (Cohen's d = 0.51, p = 0.008) than at 3T (Cohen's d = 0.26, p = 0.68) when measured in the same subjects. We found that SOZ lateralization was superior at 7T (receiver‐operating characteristic area under the curve [ROC AUC] = 0.97, 95% confidence interval [CI]: 0.92–1.00) than 3T (ROC AUC = 0.67, 95% CI: 0.36–0.98), for the same subjects scanned at both field strengths. Our findings were reproduced in extended cohorts of subjects scanned at either 3T or 7T. Our rs‐fMRI findings at 7T, but not 3T, are consistent (Spearman ρ = 0.65, p = .01) with clinical fluorodeoxyglucose positron emission tomography (FDG‐PET) lateralizing hypometabolism.Significance: We show superior SOZ lateralization in patients with TLE when using 7T relative to 3T rs‐fMRI, supporting the adoption of high field strength functional imaging in the epilepsy presurgical evaluation.

Acute alcohol consumption leads to cognitive and behavioral disinhibition that increase health and social risks, such as traffic fatalities and violence. Although rodent studies have shown that alcohol affects inhibitory neuronal activity, its relevance to humans remains largely unexplored. Here, we used the Hurst exponent—an fMRI-based marker of neural inhibition—to examine alcohol’s effects in both rats and humans. In rats, acute alcohol administration significantly reduced the cortical Hurst exponent, suggesting a decrease in inhibitory neuronal activity. This reduction was strongly correlated with the spatial distribution of GABA _A receptor expression, highlighting the key role of these receptors in mediating alcohol’s effects. Similarly, in humans, acute alcohol consumption reduced the cortical Hurst exponent, especially in brain regions with high GABA _A receptor expression. Our findings provide cross-species in vivo evidence that acute alcohol consumption modulates neural inhibition, offering new insights into the neural mechanisms underlying alcohol-induced behavioral modulation.

Pathological tau spreads via neuronal connections in Alzheimer’s disease (AD). Given the high incidence and deleterious consequences of epileptiform activity in AD, we hypothesized that neuronal hyperactivity and seizures exacerbate tau spread. To examine the impacts of brain-wide network and population hyperactivity on tau spread, we created a novel mouse model involving the cross of targeted recombination in active populations (TRAP) and the 5 times familial AD mice (5X-TRAP) that allows for the permanent labelling of seizure-activated neurons. To explore the effects of seizures on tau spread, we injected these mice with human AD brain-derived tau to induce pathological tau spread, and induced seizures with pentylenetetrazol (PTZ) kindling. Brain mapping revealed that seizures increased tau spread in 5X-TRAP mice, which correlated extensively with memory deficits in PTZ kindled 5X-TRAP mice. Using computational models, we found data supportive of increased anterograde tau spread in 5X-TRAP mice and that regional neuronal activity levels were predictive of tau pathology. On a cellular level, we found that hyperactive neurons drive elevated tau propagation in 5X-TRAP mice. We also found corroborating evidence of increased tau spread in AD patients with a seizure history compared to those without. Our study identifies neuronal hyperactivity and seizures as key, targetable factors underlying AD progression.

It is typically assumed that large networks of neurons exhibit a large repertoire of nonlinear behaviours. Here we challenge this assumption by leveraging mathematical models derived from measurements of local field potentials via intracranial electroencephalography and of whole-brain blood-oxygen-level-dependent brain activity via functional magnetic resonance imaging. We used state-of-the-art linear and nonlinear families of models to describe spontaneous resting-state activity of 700 participants in the Human Connectome Project and 122 participants in the Restoring Active Memory project. We found that linear autoregressive models provide the best fit across both data types and three performance metrics: predictive power, computational complexity and the extent of the residual dynamics unexplained by the model. To explain this observation, we show that microscopic nonlinear dynamics can be counteracted or masked by four factors associated with macroscopic dynamics: averaging over space and over time, which are inherent to aggregated macroscopic brain activity, and observation noise and limited data samples, which stem from technological limitations. We therefore argue that easier-to-interpret linear models can faithfully describe macroscopic brain dynamics during resting-state conditions.

Schizophrenia is marked by deficits in facial affect processing associated with abnormalities in GABAergic circuitry, deficits also found in first-degree relatives. Facial affect processing involves a distributed network of brain regions including limbic regions like amygdala and visual processing areas like fusiform cortex. Pharmacological modulation of GABAergic circuitry using benzodiazepines like alprazolam can be useful for studying this facial affect processing network and associated GABAergic abnormalities in schizophrenia. Here, we use pharmacological modulation and computational modeling to study the contribution of GABAergic abnormalities toward emotion processing deficits in schizophrenia. Specifically, we apply principles from network control theory to model persistence energy – the control energy required to maintain brain activation states – during emotion identification and recall tasks, with and without administration of alprazolam, in a sample of first-degree relatives and healthy controls. Here, persistence energy quantifies the magnitude of theoretical external inputs during the task. We find that alprazolam increases persistence energy in relatives but not in controls during threatening face processing, suggesting a compensatory mechanism given the relative absence of behavioral abnormalities in this sample of unaffected relatives. Further, we demonstrate that regions in the fusiform and occipital cortices are important for facilitating state transitions during facial affect processing. Finally, we uncover spatial relationships (i) between regional variation in differential control energy (alprazolam versus placebo) and (ii) both serotonin and dopamine neurotransmitter systems, indicating that alprazolam may exert its effects by altering neuromodulatory systems. Together, these findings provide a new perspective on the distributed emotion processing network and the effect of GABAergic modulation on this network, in addition to identifying an association between schizophrenia risk and abnormal GABAergic effects on persistence energy during threat processing.

Objective: Resting-state functional magnetic resonance imaging (rs-fMRI) at ultra high-field strengths (≥7T) is known to provide superior signal-to-noise and statistical power than comparable acquisitions at lower field strengths. In this study, we aim to provide a direct comparison of the seizure onset-zone (SOZ) lateralizing ability of 7T rs-fMRI and 3T rs-fMRI. Methods: We investigated a cohort of 70 temporal lobe epilepsy (TLE) patients. A paired cohort of 19 patients had 3T and 7T rs-fMRI acquisitions for direct comparison between the two field strengths. Forty-three patients had only 3T, and 8 patients had only 7T rs-fMRI acquisitions. We quantified the functional connectivity between the hippocampus and other nodes within the default mode network (DMN) using seed-to-voxel connectivity, and measured how hippocampo-DMN connectivity could inform SOZ lateralization at 7T and 3T field strengths. Results: Differences between hippocampo-DMN connectivity ipsilateral and contralateral to the SOZ were significantly higher at 7T (p _FDR =0.008) than at 3T (p _FDR =0.80) when measured in the same subjects. We found that our ability to lateralize the SOZ, by distinguishing subjects with left TLE from subjects with right TLE, was superior at 7T (AUC = 0.97) than 3T (AUC = 0.68). Our findings were reproduced in extended cohorts of subjects scanned at either 3T or 7T. Our rs-fMRI findings at 7T, but not 3T, are consistent and highly correlated (Spearman Rho=0.65) with clinical FDG-PET lateralizing hypometabolism. Significance: We show superior SOZ lateralization in TLE patients when using 7T relative to 3T rs-fMRI, supporting the adoption of high-field strength functional imaging in the epilepsy presurgical evaluation.

Objective: Temporal lobe epilepsy (TLE) is the most common type of focal epilepsy. An increasingly identified subset of patients with TLE consists of those who show bilaterally independent temporal lobe seizures. The purpose of this study was to leverage network neuroscience to better understand the interictal whole brain network of bilateral TLE (BiTLE).Methods: In this study, using a multicenter resting state functional magnetic resonance imaging (rs‐fMRI) data set, we constructed whole‐brain functional networks of 19 patients with BiTLE, and compared them to those of 75 patients with unilateral TLE (UTLE). We quantified resting‐state, whole‐brain topological properties using metrics derived from network theory, including clustering coefficient, global efficiency, participation coefficient, and modularity. For each metric, we computed an average across all brain regions, and iterated this process across network densities. Curves of network density vs each network metric were compared between groups. Finally, we derived a combined metric, which we term the “integration‐segregation axis,” by combining whole‐brain average clustering coefficient and global efficiency curves, and applying principal component analysis (PCA)–based dimensionality reduction.Results: Compared to UTLE, BiTLE had decreased global efficiency (p = .031), and decreased whole brain average participation coefficient across a range of network densities (p = .019). Modularity maximization yielded a larger number of smaller communities in BiTLE than in UTLE (p = .020). Differences in network properties separate BiTLE and UTLE along the integration‐segregation axis, with regions within the axis having a specificity of up to 0.87 for BiTLE. Along the integration‐segregation axis, UTLE patients with poor surgical outcomes were distributed in the same regions as BiTLE, and network metrics confirmed similar patterns of increased segregation in both BiTLE and poor outcome UTLE.Significance: Increased interictal whole‐brain network segregation, as measured by rs‐fMRI, is specific to BiTLE, as well as poor surgical outcome UTLE, and may assist in non‐invasively identifying this patient population prior to intracranial electroencephalography or device implantation.