A Report on an Internship with the New Orleans Opera Association

This paper is based on my internship at the New Orleans Opera Association, which took place from May 16th to October 31st, 2012. The primary activity of the New Orleans Opera Association is to produce three to four mainstage operas each season. The Opera Association is a vital part of the cultural and economic life of the City. The New Orleans Opera Association is governed by a Board of Directors and a General and Artistic Director heading a staff of eight. This report includes detailed information about the organization\u27s history and current programs. It also includes a description of my internship, a S.W.O.T analysis, best practices and my recommendations which are based on my practical work in the organization as well as the knowledge I learned in the Arts Administration program

A Motor Theory of Sleep-Wake Control: Arousal-Action Circuit.

Wakefulness, rapid eye movement (REM) sleep, and non-rapid eye movement (NREM) sleep are characterized by distinct electroencephalogram (EEG), electromyogram (EMG), and autonomic profiles. The circuit mechanism coordinating these changes during sleep-wake transitions remains poorly understood. The past few years have witnessed rapid progress in the identification of REM and NREM sleep neurons, which constitute highly distributed networks spanning the forebrain, midbrain, and hindbrain. Here we propose an arousal-action circuit for sleep-wake control in which wakefulness is supported by separate arousal and action neurons, while REM and NREM sleep neurons are part of the central somatic and autonomic motor circuits. This model is well supported by the currently known sleep and wake neurons. It can also account for the EEG, EMG, and autonomic profiles of wake, REM, and NREM states and several key features of their transitions. The intimate association between the sleep and autonomic/somatic motor control circuits suggests that a primary function of sleep is to suppress motor activity

Robust, automated sleep scoring by a compact neural network with distributional shift correction.

Studying the biology of sleep requires the accurate assessment of the state of experimental subjects, and manual analysis of relevant data is a major bottleneck. Recently, deep learning applied to electroencephalogram and electromyogram data has shown great promise as a sleep scoring method, approaching the limits of inter-rater reliability. As with any machine learning algorithm, the inputs to a sleep scoring classifier are typically standardized in order to remove distributional shift caused by variability in the signal collection process. However, in scientific data, experimental manipulations introduce variability that should not be removed. For example, in sleep scoring, the fraction of time spent in each arousal state can vary between control and experimental subjects. We introduce a standardization method, mixture z-scoring, that preserves this crucial form of distributional shift. Using both a simulated experiment and mouse in vivo data, we demonstrate that a common standardization method used by state-of-the-art sleep scoring algorithms introduces systematic bias, but that mixture z-scoring does not. We present a free, open-source user interface that uses a compact neural network and mixture z-scoring to allow for rapid sleep scoring with accuracy that compares well to contemporary methods. This work provides a set of computational tools for the robust automation of sleep scoring

A Motor Theory of Sleep-Wake Control: Arousal-Action Circuit.

Wakefulness, rapid eye movement (REM) sleep, and non-rapid eye movement (NREM) sleep are characterized by distinct electroencephalogram (EEG), electromyogram (EMG), and autonomic profiles. The circuit mechanism coordinating these changes during sleep-wake transitions remains poorly understood. The past few years have witnessed rapid progress in the identification of REM and NREM sleep neurons, which constitute highly distributed networks spanning the forebrain, midbrain, and hindbrain. Here we propose an arousal-action circuit for sleep-wake control in which wakefulness is supported by separate arousal and action neurons, while REM and NREM sleep neurons are part of the central somatic and autonomic motor circuits. This model is well supported by the currently known sleep and wake neurons. It can also account for the EEG, EMG, and autonomic profiles of wake, REM, and NREM states and several key features of their transitions. The intimate association between the sleep and autonomic/somatic motor control circuits suggests that a primary function of sleep is to suppress motor activity

Sleep and Motor Control by a Basal Ganglia Circuit

From invertebrates to humans, a defining feature of sleep is behavioral immobility(Campbell and Tobler, 1984; Hendricks et al., 2000; Shaw et al., 2000). In mammals, diminished electromyographic (EMG) activity is a major criterion for both rapid eye movement (REM) and non-REM (NREM) sleep. However, the relationship between sleep and motor control at the neuronal level remains poorly understood. Here we show that regions of the basal ganglia long known to be essential for motor suppression also play a key role in sleep generation. Optogenetic or chemogenetic activation of GABAergic neurons in mouse substantia nigra pars reticulata (SNr) strongly increased both REM and NREM sleep, whereas their inactivation suppressed sleep and increased wakefulness. Analysis of natural home-cage behavior showed that mice transition sequentially through several behavioral states: locomotion, non-locomotor movement, quiet wakefulness, and sleep. Activation/inactivation of SNr neurons promoted/suppressed sleep by biasing the direction of progression through the natural behavioral sequence. Virus-mediated circuit tracing showed that SNr GABAergic neurons project to multiple wake-promoting monoaminergic cell groups in addition to the thalamus and mesencephalic locomotor region, and activating each projection promoted sleep. Within the thalamus, direct optogenetic inactivation of glutamatergic neurons is sufficient to enhance sleep, but the effect is largely restricted to the regions receiving SNr projection. Furthermore, a major source of excitatory inputs to the SNr is the subthalamic nucleus (STN), and activation of neurotensin-expressing glutamatergic neurons in the STN also promoted sleep. Together, these results demonstrate a key role of the STN-SNr basal ganglia pathway in sleep generation and reveal a novel circuit mechanism linking sleep and motor control

Optical-Waveguide Based Tactile Sensing for Surgical Instruments of Minimally Invasive Surgery

In recent years, with the rapid development of minimally invasive surgery (MIS), the lack of force sensing associated with the surgical instrument used in MIS has been increasingly a desirable technology amongst clinicians. However, it is still an open technical challenge to date since most existing tactile sensing principles are not suitable to small 3-dimensional (3D) curved surfaces often seen in surgical instruments, and as a result multi-point force detection cannot be realized. In this paper, a novel optical waveguide-based sensor was proposed to deal with the above research gap. A sensor prototype for curved surfaces resembling the surface of dissection forceps was developed and experimentally evaluated. The static parameters and dynamic response characteristics of the sensor were measured. Results show that the static hysteresis error is less than 3%, the resolution is 0.026 N, and the repeatability is less than 1.5%. Under a frequency of 12.5 Hz, the sensor could quickly measure the variation of the force signal. We demonstrated that this small and high-precision sensitive sensor design is promising to be used for creating multiple-point tactile sensing for minimally invasive surgical instruments with 3D surfaces