Medicine and Health Sciences Commons^™

Reduced Gabaergic Signaling At The Axon Initial Segment Decreases Vigilance State Transitioning, Austin John Boren

UNLV Theses, Dissertations, Professional Papers, and Capstones

Sleep is a highly regulated homeostatic process that is disrupted in an estimated 50-70 million Americans. Regulation of sleep depends upon coordinated signaling of multiple neurotransmitter systems. In particular, inhibitory gamma-aminobutyric acid (GABA) signaling is required to suppress wake-active brain regions in order to initiate and maintain sleep states. GABA type A receptors (GABAARs) are ionotropic receptors with subunit compositions uniquely enriched on subcellular domains of target cells. α2 subunit-containing GABAARs are the primary target of GABA released onto the axon initial segment (AIS), a site critical for phasing the oscillatory activity of cortical cells. α2-containing GABAARs have previously been …

Cortical Beta Oscillations Are Associated With Motor Performance Following Visuomotor Learning, Svenja Espenhahn, Bernadette C.M. Van Wijk, Holly E. Rossiter, Archy O. De Berker, Nell D. Redman, Jane Rondina, Joern Diedrichsen, Nick S. Ward

Brain and Mind Institute Researchers' Publications

© 2019 The Authors People vary in their capacity to learn and retain new motor skills. Although the relationship between neuronal oscillations in the beta frequency range (15–30 Hz) and motor behaviour is well established, the electrophysiological mechanisms underlying individual differences in motor learning are incompletely understood. Here, we investigated the degree to which measures of resting and movement-related beta power from sensorimotor cortex account for inter-individual differences in motor learning behaviour in the young and elderly. Twenty young (18–30 years) and twenty elderly (62–77 years) healthy adults were trained on a novel wrist flexion/extension tracking task and subsequently retested …

Understanding The Neural Bases Of Implicit And Statistical Learning, Laura J. Batterink, Ken A. Paller, Paul J. Reber

Brain and Mind Institute Researchers' Publications

© 2019 Cognitive Science Society, Inc. Both implicit learning and statistical learning focus on the ability of learners to pick up on patterns in the environment. It has been suggested that these two lines of research may be combined into a single construct of “implicit statistical learning.” However, by comparing the neural processes that give rise to implicit versus statistical learning, we may determine the extent to which these two learning paradigms do indeed describe the same core mechanisms. In this review, we describe current knowledge about neural mechanisms underlying both implicit learning and statistical learning, highlighting converging findings between …

Competitive Frontoparietal Interactions Mediate Implicit Inferences, Martijn E. Wokke, Tony Ro

Publications and Research

Frequent experience with regularities in our environment allows us to use predictive information to guide our decision process. However, contingencies in our environment are not always explicitly present and sometimes need to be inferred. Heretofore, it remained unknown how predictive information guides decision-making when explicit knowledge is absent and how the brain shapes such implicit inferences. In the present experiment, 17 human participants (9 females) performed a discrimination task in which a target stimulus was preceded by a predictive cue. Critically, participants had no explicit knowledge that some of the cues signaled an upcoming target, allowing us to investigate how …

A Hidden Markov Factor Analysis Framework For Seizure Detection In Epilepsy Patients, Mahboubeh Madadi

Graduate Theses and Dissertations

Approximately 1% of the world population suffers from epilepsy. Continuous long-term electroencephalographic (EEG) monitoring is the gold-standard for recording epileptic seizures and assisting in the diagnosis and treatment of patients with epilepsy. Detection of seizure from the recorded EEG is a laborious, time consuming and expensive task. In this study, we propose an automated seizure detection framework to assist electroencephalographers and physicians with identification of seizures in recorded EEG signals. In addition, an automated seizure detection algorithm can be used for treatment through automatic intervention during the seizure activity and on time triggering of the injection of a radiotracer to …

Electroencephalogram As A Diagnostic Tool In Acquired Brain Injury, Michael Zarra

Senior Theses and Projects

The ability of electroencephalogram (EEG) to be used as a diagnostic device for acquired brain injuries (ABI) has been conceptualized previously. Averaged event-related potentials (ERP) derived from an EEG are suitable as markers of dysfunction however, distinctive properties in the frequency domain have not been established previously. In the present study, we examined pre- existing EEG signal data of healthy adults (HA), mild ABI (mABI), and severe ABI (sABI) human groups. Through Fourier analysis performed in MATLAB, we found that individuals in our sample population (n=80) were able to be categorized into their respective group based on common neuronal activity …

The Risk Of New-Onset Epilepsy And Refractory Epilepsy In Older Adult Stroke Survivors, Jorge G. Burneo, Tresah C. Antaya, Britney N. Allen, Andrea Belisle, Salimah Z. Shariff, Gustavo Saposnik

Neuroepidemiology Research Unit Project Summaries

Research Summary: Key Findings

• Stroke is a common cause of epilepsy in older adults, but little is known about stroke-related epilepsy or its outcomes in this population.
• 1.1% of older adult stroke survivors developed epilepsy in this study, of whom 12.9% developed refractory epilepsy, indicating that this population is particularly responsive to treatment.
• Over 85% of deaths in this population are not due to stroke or epilepsy.