Publications by authors named "Nicholas Gregg"

The lack of reliable seizure detection remains a significant challenge for epilepsy care. A clinical deep brain stimulation (DBS) system provides constrained ambulatory brain recordings; however, limited data exist on the use of DBS recordings for seizure detection and lateralization. We present the case of an 18-year-old patient with drug-resistant focal epilepsy, who had seizure detection and lateralization by DBS recordings.

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Single pulse electrical stimulation experiments produce pulse-evoked potentials used to infer brain connectivity. The choice of recording reference for intracranial electrodes remains non-standardized and can significantly impact data interpretation. When the reference electrode is affected by stimulation or evoked brain activity, it can contaminate the pulse-evoked potentials recorded at all other electrodes and influence interpretation of findings.

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Article Synopsis
  • There are limited options for treating drug-resistant idiopathic generalized epilepsy (IGE), but centromedian thalamus deep brain stimulation (CM-DBS) shows promise based on small case studies.
  • A retrospective analysis of five patients indicated significant reductions in seizure frequency, with median convulsive seizure reduction at 66% and over 99% for absence seizures in one case.
  • The study highlights the importance of accurately targeting the middle ventral CM nucleus for optimal outcomes, as better results were linked to strong connectivity between this area and the central peri-Rolandic cortex.
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Neurostimulation is an increasingly common treatment option for medically intractable epilepsy. SANTE (Stimulation of the Anterior Nucleus of the Thalamus for Epilepsy) and Responsive Neurostimulation (RNS) System are landmark neurostimulation trials that utilized either duty cycle or a responsive stimulation paradigm. A seizure-free outcome is rarely observed with responsive and duty cycle neurostimulation devices.

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Human brain connectivity can be mapped by single pulse electrical stimulation during intracranial EEG measurements. The raw cortico-cortical evoked potentials (CCEP) are often contaminated by noise. Common average referencing (CAR) removes common noise and preserves response shapes but can introduce bias from responsive channels.

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Numerous physiological processes are cyclical, but sampling these processes densely enough to perform frequency decomposition and subsequent analyses can be challenging. Mathematical approaches for decomposition and reconstruction of sparsely and irregularly sampled signals are well established but have been under-utilized in physiological applications. We developed a basis pursuit denoising with polynomial detrending (BPWP) model that recovers oscillations and trends from sparse and irregularly sampled timeseries.

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Article Synopsis
  • Vagal neuropathy can occur after the placement of a vagal nerve stimulator (VNS), leading to vocal fold palsy, which is rare.
  • A case is highlighted where delayed nerve compression from the VNS coil caused progressive hoarseness and vocal cord paralysis.
  • To address the issue, coil removal and nerve decompression were performed, and larger coils were used for ongoing treatment to minimize the risk of similar complications in the future.
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Deep brain stimulation (DBS) is a viable treatment for a variety of neurological conditions, however, the mechanisms through which DBS modulates large-scale brain networks are unresolved. Clinical effects of DBS are observed over multiple timescales. In some conditions, such as Parkinson's disease and essential tremor, clinical improvement is observed within seconds.

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This study aims to characterize the time course of impedance, a crucial electrophysiological property of brain tissue, in the human thalamus (THL), amygdala-hippocampus, and posterior hippocampus over an extended period.Impedance was periodically sampled every 5-15 min over several months in five subjects with drug-resistant epilepsy using an investigational neuromodulation device. Initially, we employed descriptive piecewise and continuous mathematical models to characterize the impedance response for approximately three weeks post-electrode implantation.

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High frequency anterior nucleus of the thalamus deep brain stimulation (ANT DBS) is an established therapy for treatment resistant focal epilepsies. Although high frequency-ANT DBS is well tolerated, patients are rarely seizure free and the efficacy of other DBS parameters and their impact on comorbidities of epilepsy such as depression and memory dysfunction remain unclear. The purpose of this study was to assess the impact of low vs high frequency ANT DBS on verbal memory and self-reported anxiety and depression symptoms.

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Temporal lobe epilepsy is a common neurological disease characterized by recurrent seizures. These seizures often originate from limbic networks and people also experience chronic comorbidities related to memory, mood, and sleep (MMS). Deep brain stimulation targeting the anterior nucleus of the thalamus (ANT-DBS) is a proven therapy, but the optimal stimulation parameters remain unclear.

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Objective: This study aims to characterize the time course of impedance, a crucial electrophysiological property of brain tissue, in the human thalamus (THL), amygdala-hippocampus (AMG-HPC), and posterior hippocampus (post-HPC) over an extended period.

Approach: Impedance was periodically sampled every 5-15 minutes over several months in five subjects with drug-resistant epilepsy using an experimental neuromodulation device. Initially, we employed descriptive piecewise and continuous mathematical models to characterize the impedance response for approximately three weeks post-electrode implantation.

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Human brain connectivity can be measured in different ways. Intracranial EEG (iEEG) measurements during single pulse electrical stimulation provide a unique way to assess the spread of electrical information with millisecond precision. To provide a robust workflow to process these cortico-cortical evoked potential (CCEP) data and detect early evoked responses in a fully automated and reproducible fashion, we developed Early Response (ER)-detect.

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Stimulation-evoked signals are starting to be used as biomarkers to indicate the state and health of brain networks. The human limbic network, often targeted for brain stimulation therapy, is involved in emotion and memory processing. Previous anatomic, neurophysiological, and functional studies suggest distinct subsystems within the limbic network (Rolls, 2015).

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The impedance is a fundamental electrical property of brain tissue, playing a crucial role in shaping the characteristics of local field potentials, the extent of ephaptic coupling, and the volume of tissue activated by externally applied electrical brain stimulation. We tracked brain impedance, sleep-wake behavioral state, and epileptiform activity in five people with epilepsy living in their natural environment using an investigational device. The study identified impedance oscillations that span hours to weeks in the amygdala, hippocampus, and anterior nucleus thalamus.

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Long-term intracranial electroencephalography (iEEG) in freely behaving animals provides valuable electrophysiological information and when correlated with animal behavior is useful for investigating brain function.Here we develop and validate an automated iEEG-based sleep-wake classifier for canines using expert sleep labels derived from simultaneous video, accelerometry, scalp electroencephalography (EEG) and iEEG monitoring. The video, scalp EEG, and accelerometry recordings were manually scored by a board-certified sleep expert into sleep-wake state categories: awake, rapid-eye-movement (REM) sleep, and three non-REM sleep categories (NREM1, 2, 3).

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Background And Objectives: The anterior nucleus of the thalamus (ANT) is a common target for deep brain stimulation (DBS) for drug-resistant epilepsy (DRE). However, the surgical approach to the ANT remains challenging because of its unique anatomy. This study aims to summarize our experience with the posterior temporo-parietal extraventricular (TPEV) approach targeting the ANT for DBS in DRE.

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Background: Implantable pulse generators (IPGs) store energy and deliver electrical impulses for deep brain stimulation (DBS) to treat neurological and psychiatric disorders. IPGs have evolved over time to meet the demands of expanding clinical indications and more nuanced therapeutic approaches.

Objectives: The aim of this study was to examine the workflow of the first 4-lead IPG for DBS in patients with complex disease.

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Objective: Previous studies suggested that patients with epilepsy might be able to forecast their own seizures. This study aimed to assess the relationships between premonitory symptoms, perceived seizure risk, and future and recent self-reported and electroencephalographically (EEG)-confirmed seizures in ambulatory patients with epilepsy in their natural home environments.

Methods: Long-term e-surveys were collected from patients with and without concurrent EEG recordings.

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Single-pulse electrical stimulation in the nervous system, often called cortico-cortical evoked potential (CCEP) measurement, is an important technique to understand how brain regions interact with one another. Voltages are measured from implanted electrodes in one brain area while stimulating another with brief current impulses separated by several seconds. Historically, researchers have tried to understand the significance of evoked voltage polyphasic deflections by visual inspection, but no general-purpose tool has emerged to understand their shapes or describe them mathematically.

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The human ventral temporal cortex (VTC) is highly connected to integrate visual perceptual inputs with feedback from cognitive and emotional networks. In this study, we used electrical brain stimulation to understand how different inputs from multiple brain regions drive unique electrophysiological responses in the VTC. We recorded intracranial EEG data in 5 patients (3 female) implanted with intracranial electrodes for epilepsy surgery evaluation.

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Epilepsy patients often experience acute repetitive seizures, known as seizure clusters, which can progress to prolonged seizures or status epilepticus if left untreated. Predicting the onset of seizure clusters is crucial to enable patients to receive preventative treatments. Additionally, studying the patterns of seizure clusters can help predict the seizure type (isolated or cluster) after observing a just occurred seizure.

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Several studies have suggested the epileptogenic potential of temporal encephaloceles. However, there is limited literature describing the results of intracranial EEG monitoring for patients with temporal encephaloceles. We describe a 19 year-old right-handed woman with drug-resistant epilepsy who presented with seizure onset at age 16 in the setting of a left temporal encephalocele where the seizure onset zone was confirmed to be the encephalocele via stereo EEG (sEEG).

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Objective: The factors that influence seizure timing are poorly understood, and seizure unpredictability remains a major cause of disability. Work in chronobiology has shown that cyclical physiological phenomena are ubiquitous, with daily and multiday cycles evident in immune, endocrine, metabolic, neurological, and cardiovascular function. Additionally, work with chronic brain recordings has identified that seizure risk is linked to daily and multiday cycles in brain activity.

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Objective: Previous studies suggested that patients with epilepsy might be able to fore-cast their own seizures. We sought to assess the relationships of premonitory symptoms and perceived seizure risk with future and recent self-reported and EEG-confirmed seizures in the subjects living with epilepsy in their natural home environments.

Methods: We collected long-term e-surveys from ambulatory patients with and without concurrent EEG recordings.

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