Faculty Bibliography

Computational models of Transcranial Electric Stimulation (TES) have been used extensively to predict the precise intensity and distribution of electric fields across the brain. The goal of such modeling is to guide the targeting of particular brain areas for clinical trials and research studies. While computational models have increased in sophistication and detail, to date there has been limited empirical evaluation of their precision. Previous efforts have been limited to comparing model predictions with voltage recordings on the scalp surface. To address the uncertainty of model accuracy inside the head, we recorded intra-cranial electric fields generated by TES in patients undergoing invasive monitoring for epilepsy surgery. Highresolution finite element models were constructed from patient's MRIs at 1 mm³ resolution, and voltage distribution inside the head were simulated for 1 mA currents. Preliminary analysis shows a general correspondence of model predictions and trans-cranial recordings (in over 150 cortical and subcortical electrodes for each of two patients). To determine specific conductivity values in-vivo for different tissues we are in the process of recording from depth electrodes also in rhesus macaque monkey leveraging ongoing neurophysiology experiments with TES. We have already segmented the macaque head anatomy for one subject at 1mm³ resolution and completed current flow modeling. These combined human and nonhuman primate recordings should provide strong constraints for future modeling efforts and will establish a firm empirical foundation for future clinical studies with TES that aim to target specific cortical and sub-cortical brain regions

OBJECTIVE: To evaluate the comparative safety and adjunctive efficacy of pregabalin and gabapentin in reducing seizure frequency in patients with partial-onset seizures based on prestudy modeling showing superior efficacy for pregabalin. METHODS: The design of this comparative efficacy and safety study of pregabalin and gabapentin as adjunctive treatment in adults with refractory partial-onset seizures was randomized, flexible dose, double blind, and parallel group. The study included a 6-week baseline and a 21-week treatment phase. The primary endpoint was the percentage change from baseline in 28-day seizure rate to the treatment phase. RESULTS: A total of 484 patients were randomized to pregabalin (n = 242) or gabapentin (n = 242). Of these, 359 patients (187 pregabalin, 172 gabapentin) completed the treatment phase. The observed median and mean in percentage change from baseline was -58.65 and -47.7 (SD 48.3) for pregabalin and -57.43 and -45.28 (SD 60.6) for gabapentin. For the primary endpoint, there was no significant difference between treatments. The Hodges-Lehman estimated median difference was 0.0 (95% confidence interval -6.0 to 7.0). Safety profiles were comparable and consistent with prior trials. CONCLUSIONS: The absence of the anticipated efficacy difference based on modeling of prior, nearly identical trials and the larger-than-expected response rates of the 2 antiepileptic drugs were unexpected. These findings raise questions that are potentially important to consider in future comparative efficacy trials. CLINICALTRIALSGOV IDENTIFIER: NCT00537940. CLASSIFICATION OF EVIDENCE: This study provides Class II evidence that for patients with partial seizures enrolled in this study, pregabalin is not superior to gabapentin in reducing seizure frequency. Because of the atypical response rates, the results of this study are poorly generalizable to other epilepsy populations.

In animal models, inflammation is both a cause and consequence of seizures. Less is known about the role of inflammation in human epilepsy. We performed positron emission tomography (PET) using a radiotracer sensitive to brain inflammation in a patient with frontal epilepsy ~36 h after a seizure as well as during a seizure-free period. When statistically compared to a group of 12 matched controls, both of the patient's scans identified a frontal (supplementary motor area) region of increased inflammation corresponding to his clinically defined seizure focus, but the postseizure scan showed significantly greater inflammation intensity and spatial extent. These results provide new information about transient and chronic neuroinflammation in human epilepsy and may be relevant to understanding the process of epileptogenesis and guiding therapy.

PURPOSE: To ascertain the cause of mortality and incidence of sudden unexpected death in epilepsy (SUDEP) in patients with supernumerary isodicentric chromosome 15 (idic15). METHODS: Cases were obtained from those reported to the Dup15q Alliance (www.dup15q.org) between April 2006 and June 2012; ~709 families were registered in their database. We performed a case-control study comparing reported SUDEP cases to living patients with epilepsy from the Dup15q Alliance registry who volunteered to be interviewed to examine clinical risk factors. KEY FINDINGS: There were nineteen deaths with idic15; 17 had epilepsy, and nine deaths were due to probable or definite SUDEP (4 females, median age of death was 13.5years, range: 3-26years). Possible SUDEP occurred in 2 others. The remainder died from status epilepticus (3), pneumonia (3), aspiration (1), and drowning (1). Nonambulatory status and lack of seizure control were more common among SUDEP cases than living dup15q patients. SIGNIFICANCE: Our findings suggest that SUDEP is a common cause of death among children and young adults with isodicentric chromosome 15q11.2q13 duplications and patients with the most severe neurologic dysfunction may be at highest risk. Further studies are needed to examine if this specific genetic defect plays a role in the mechanism of SUDEP in these patients.

INTRODUCTION: Perampanel is an AMPA receptor antagonist recently approved for the treatment of partial and generalized epilepsies with tonic-clonic seizures as an add-on therapy. METHODS: This single-center postmarketing study retrospectively evaluated the efficacy of perampanel in patients with partial onset and other seizure types, with a special emphasis on its efficacy, safety, and tolerability. RESULTS: Review of medical records revealed that adequate data were available on 101 patients taking perampanel. Fifty-seven patients were female. Sixteen patients were of pediatric age range. The average dose of perampanel was 6.5mg, and average treatment duration was 8.2months. After treatment, median seizure frequency reduction was 50% overall, 50% in children, and 33% in adults; 44% in primary generalized, 38% in secondarily generalized, and 33% in partial seizures. Responder rate (50% seizure frequency reduction) was 51% overall, 63% in children, and 49% in adults; 60% in partial seizures, 43% in secondarily generalized tonic-clonic seizures, 53% in primary generalized tonic-clonic seizures, and 56% in other seizure types. Seizure freedom was attained in 6% of cases. Most common adverse events were sleepiness/fatigue (35%), behavioral problems (30%), and dizziness (22%). Adverse events were correlated with dosage. Average dose was 7.3mg in patients with adverse events vs. 5.5mg in those without adverse events. Patients who developed fatigue, cognitive decline, headaches, and weight gain were more likely to discontinue perampanel than those patients who experienced coordination issues and behavioral problems. CONCLUSIONS: These findings suggest that perampanel is safe, well-tolerated, and effective in treatment of various types of adult and pediatric epilepsy syndromes. Fatigue, cognitive decline, headache and weight gain were the main causes of perampanel discontinuation.

We present a new approach to extracting low-dimensional neural trajectories that summarize the electrocorticographic (ECoG) signals recorded with high-channel-count electrode arrays implanted subdurally. In our approach, Hidden-Markov Factor Analysis (HMFA), a finite set of factor analyzers are used to model the relationship between the high-dimensional ECoG neural space and a low-dimensional latent neural space; the factor analyzers at different time points are in turn linked together with a hidden Markov model. The recorded ECoG signals were band-pass filtered such that our analysis was focused on a sub-band (76-100Hz) of high gamma. HMFA affords the quantization of the ECoG neural space and dimensionality reduction in a common probabilistic space. We applied this method to the ECoG recordings of 2 subjects who responded with button presses to audiovisual stimuli in an experimental task. Using a goodness-of-fit metric that measures how well the ECoG activity of each electrode can be predicted by all the other electrodes, we found that HMFA performed best when compared with Gaussian-Process Factor Analysis (GPFA) and other related spatiotemporal modeling techniques. In contradistinction to HMFA, GPFA and the other techniques integrate temporal smoothing with dimensionality reduction. We believe that this method will provide a powerful tool for relating high-channel-count ECoG signals to the perception and behavior of subjects.

To augment neural monitoring, a minimally intrusive multi-modal capture system was designed and implemented in the epilepsy clinic. This system provides RGB-D audio-video synchronized with patient electrocorticography (ECoG), which records neural activity across cortex. We propose an automated approach to studying the human brain in a naturalistic setting. We demonstrate coarse functional mapping of ECoG electrodes correlated to contralateral arm movements. Motor electrode mapping was generated by analyzing continuous movement data recorded over several hours from epilepsy patients in hospital rooms. From these recordings we estimate the kinematics of patient hand movement behaviors using computer vision algorithms. We compare movement behaviors to neural data collected from ECoG, specifically high-γ (70-110 Hz) spectral features. We present a functional map of electrode responses to natural arm movements, generated using a statistical test. We demonstrate that our approach has the potential to aid in the development of automated functional brain mapping using continuous video and neural recordings of patients in clinical settings.

Sudden unexpected death in epilepsy (SUDEP) is the most common cause of epilepsy-related mortality. We hypothesized that electrocardiography (ECG) features may distinguish SUDEP cases from living subjects with epilepsy. Using a matched case-control design, we compared ECG studies of 12 consecutive cases of SUDEP over 10 years and 22 epilepsy controls matched for age, sex, epilepsy type (focal, generalized, or unknown/mixed type), concomitant antiepileptic, and psychotropic drug classes. Conduction intervals and prevalence of abnormal ventricular conduction diagnosis (QRS >/=110 msec), abnormal ventricular conduction pattern (QRS <110 msec, morphology of incomplete right or left bundle branch block or intraventricular conduction delay), early repolarization, and features of inherited cardiac channelopathies were assessed. Abnormal ventricular conduction diagnosis and pattern distinguished SUDEP cases from matched controls. Abnormal ventricular conduction diagnosis was present in two cases and no controls. Abnormal ventricular conduction pattern was more common in cases than controls (58% vs. 18%, p = 0.04). Early repolarization was similarly prevalent in cases and controls, but the overall prevalence exceeded that of published community-based cohorts.