Optomotor Swimming in Larval Zebrafish Is Driven by Global Whole-Field Visual Motion and Local Light-Dark Transitions

Stabilizing gaze and position within an environment constitutes an important task for the nervous system of many animals. The optomotor response (OMR) is a reflexive behavior, present across many species, in which animals move in the direction of perceived whole-field visual motion, therefore stabilizing themselves with respect to the visual environment. Although the OMR has been extensively used to probe visuomotor neuronal circuitry, the exact visual cues that elicit the behavior remain unidentified. In this study, we use larval zebrafish to identify spatio-temporal visual features that robustly elicit forward OMR swimming. These cues consist of a local, forward-moving, off edge together with on/off symmetric, similarly directed, global motion. Imaging experiments reveal neural units specifically activated by the forward-moving light-dark transition. We conclude that the OMR is driven not just by whole-field motion but by the interplay between global and local visual stimuli, where the latter exhibits a strong light-dark asymmetry

Neutron Spectroscopy Using LiF Thin-Film Detectors

A stacked array of segmented micro-structured semiconductor neutron detectors (MSNDs) has been fabricated to perform as a neutron spectrometer simultaneously capable of differentiating fast and thermal neutrons. The MSND devices consist of thin-film perforated diodes constructed from LiF powder back-filled into an etched silicon wafer. Geant4 simulations demonstrate than an eight-layer spectrometer consisting of alternating layers of MSND and hydrogenous moderator can successfully resolve neutron energies at a resolution dependent upon the number of layers and the thickness of the adjacent moderating materials. The simulated spectrometer response was compared to that obtained experimentally with mono-energetic neutrons from a D+D neutron generator. The commissioning tests of the spectrometer reveal that the energy of a mono-energetic neutron source can be identified to within + or -1 MeV. Following the commissioning tests, the spectrometer was used to characterize the poly-energetic neutron spectrum of a plutonium-beryllium neutron source

Automatic online spike sorting with singular value decomposition and fuzzy C-mean clustering

Background: Understanding how neurons contribute to perception, motor functions and cognition requires the reliable detection of spiking activity of individual neurons during a number of different experimental conditions. An important problem in computational neuroscience is thus to develop algorithms to automatically detect and sort the spiking activity of individual neurons from extracellular recordings. While many algorithms for spike sorting exist, the problem of accurate and fast online sorting still remains a challenging issue.Results: Here we present a novel software tool, called FSPS (Fuzzy SPike Sorting), which is designed to optimize: (i) fast and accurate detection, (ii) offline sorting and (iii) online classification of neuronal spikes with very limited or null human intervention. The method is based on a combination of Singular Value Decomposition for fast and highly accurate pre-processing of spike shapes, unsupervised Fuzzy C-mean, high-resolution alignment of extracted spike waveforms, optimal selection of the number of features to retain, automatic identification the number of clusters, and quantitative quality assessment of resulting clusters independent on their size. After being trained on a short testing data stream, the method can reliably perform supervised online classification and monitoring of single neuron activity. The generalized procedure has been implemented in our FSPS spike sorting software (available free for non-commercial academic applications at the address: http://www.spikesorting.com) using LabVIEW (National Instruments, USA). We evaluated the performance of our algorithm both on benchmark simulated datasets with different levels of background noise and on real extracellular recordings from premotor cortex of Macaque monkeys. The results of these tests showed an excellent accuracy in discriminating low-amplitude and overlapping spikes under strong background noise. The performance of our method is competitive with respect to other robust spike sorting algorithms.Conclusions: This new software provides neuroscience laboratories with a new tool for fast and robust online classification of single neuron activity. This feature could become crucial in situations when online spike detection from multiple electrodes is paramount, such as in human clinical recordings or in brain-computer interfaces.Instituto de Física La Plat

Development of a porous silicon flow-through field effect sensing system for chemical and biological detection

With an increasing need for homeland security, and breakthrough advancements in sensing applications, the demand for highly sensitive, compact, biological and chemical sensing devices is evident. Macroporous silicon (MPS) is an ideal material for meeting these demands because it exhibits a large degree of internal surface area and is fully compatible with silicon technologies. Since the surface is sensitive to charged molecules, localized field effects from analytes interfaced with MPS will cause modulation of a space charge region in the semiconductor. In this work, a porous silicon based sensing system is designed, fabricated, and characterized. The unique properties of porous silicon and its promising qualities which facilitate the means for interfacing fluidic and electrical systems are investigated. A flow-though structure is used to deliver analytes to a MPS sensing membrane region and integrated electrodes contacting the MPS can be used to take electrical measurements. Fabricated sensors are enhanced by packaging them in a fluidic system which enables the future possibility of arrayed sensing platforms. To date this sensing system has successfully performed many sensing tasks applicable to the fields of science and technology. Unique measured capacitive responses of sensor to liquid phase acetone, ethanol, isopropyl alcohol, methanol, and toluene demonstrate detection and discrimination capabilities. The sensor has proven to be useful in monitoring the quality of air by detecting solvent vapor phase concentrations of \u3c 1 ppm. Packaged devices were used to monitor the quality of a water supply and were able to detect the presence of contaminants such as isopropyl alcohol. Application to the field of biology was demonstrated by observing a repeatable trend in measured capacitance during binding events between biotin and streptavidin proteins located in the MPS sensing membrane. The work presented herein shows that this sensing platform has a high degree of potential for repeatable and day-to-day reproducible detection in the areas of chemical and biological sensing

A Hardware-in-the-Loop Platform for DC Protection

With the proliferation of power electronics, dc-based power distribution systems can be realized; however, dc electrical protection remains a significant barrier to mass implementation dc power distribution. Controller Hardware-in-the-loop (CHiL) simulation enables moving up technology readiness levels (TRL) quickly. This work presents an end-to-end solution for dc protection CHiL for early design exploration and verification for dc protection, allowing for the rapid development of dc protection schemes for both Line-to-Line (LL) and Line-to-Ground (LG) faults. The approach combines using Latency Based Linear Multistep Compound (LB-LMC), a real-time simulation method for power electronic, and National Instruments (NI) FPGA hardware to enable dc protection design with CHiL. A case study is performed for a 1.5 MW Voltage Source Rectifier (VSR) under LL and LG faults in an ungrounded system. The deficiency in real-time simulation resolution of Commercial-off-the-Shelf (COTS) for dc fault transients is shown, and addressed by using LB-LMC RT solver inside NI FPGA hardware to achieve 50 ns resolution of dc fault transients

Light Sheet Microscopy and Image Analysis of Neural Development and Programmed Cell Death in C. Elegans Embryos

The positioning of neuronal cell bodies and neurites is critical for intact functioning of the nervous system. Mapping the positions of the soma and neurites in the brains of developing embryos as important central nervous system structures are being created may yield novel insight into the role of distinct cell groups in creating these structures. New developments in microscopy have made this an excellent time to study neural development in the C. elegans embryo. In the past decade, implementations of highly light efficient methods such as single plane illumination microscopy have rendered it possible to follow development of embryonic structures in 3D with excellent temporal resolution (Huisken et al., 2004) and low phototoxicity. Recent work has resulted in quantitative characterization of the outgrowth of a single neurite in the late, rapidly moving three-fold stage of the C. elegans embryo for the first time (Christensen et al., 2015). In this thesis, I first describe the construction and programming of a single plane illumination microscope (SPIM) based on a design from Hari Shroff\u27s lab (Wu et al., 2011). The microscope is developed especially for use with C. elegans embryos and permits fast image acquisition without excessive photodamage, compared to other forms of microscopy. Second, I describe the use of the SPIM microscope to image the development of a subset of sublateral neurons, the earliest known entrants to the nerve ring (Rapti et al, in preparation), into which they grow in the 1.5-fold stage. I describe an algorithm for automatically aligning developing embryos onto one another until the beginning of the rapid embryonic movements known as twitching, which begin at the start of the twofold stage. I employ my algorithm to align a group of identically imaged embryos onto one another and deduce information about the positioning of the nerve ring in an approximately uniform coordinate system. I determine that nerve rings are precisely positioned in the embryo to within about a micrometer while the cell bodies that grow into the nerve ring are positioned over a much wider distance. My work suggests that the nerve ring grows out towards the ALA neuron as an anchor, and that twitching may begin when the developing nerve ring reaches the ALA. I additionally describe observation of new phenotypes related to the cam-1 mutation, which was previously identified as a regulator of anterior-posterior placement of the nerve ring (Kennerdell et al., 2009). Third, I describe an application of the SPIM microscope for imaging the death of the tail spike cell, a complex, multi-compartment differentiated cell which dies over a period of hours during the three-fold stage, when the animal is rapidly moving in its shell, and cannot be imaged otherwise than with a rapid, light efficient microscope such as the one described here. I determined the time course and confirmed the sequence of events of wild type tail spike cell death. Additionally, I report stronger phenotypes for some known tail spike cell death genes when imaged in the embryo, suggesting that eff-1 plays a stronger role than previously known in clearance of the distal part of the tail spike cell process, and additionally that ced-5 has a strong role in clearance of the same compartment (in addition to its known role in soma clearance). In an appendix I describe work beginning on an extension of the microscope, which will hopefully see the microscope used as a tool for selectively inducing fluorescence in individual cells and following the development of those cells in time. My results demonstrate the utility of single plane illumination microscopy for study of C. elegans embryogenesis and establish fundamental facts about the variability of the C. elegans central nervous system by making direct comparisons between animals. This work contributes to our understanding of the C. elegans nervous system by establishing fundamental bounds on the range of nerve ring positioning between individuals

Array data extractor (ADE): a LabVIEW program to extract and merge gene array data

BACKGROUND: Large data sets from gene expression array studies are publicly available offering information highly valuable for research across many disciplines ranging from fundamental to clinical research. Highly advanced bioinformatics tools have been made available to researchers, but a demand for user-friendly software allowing researchers to quickly extract expression information for multiple genes from multiple studies persists. FINDINGS: Here, we present a user-friendly LabVIEW program to automatically extract gene expression data for a list of genes from multiple normalized microarray datasets. Functionality was tested for 288 class A G protein-coupled receptors (GPCRs) and expression data from 12 studies comparing normal and diseased human hearts. Results confirmed known regulation of a beta 1 adrenergic receptor and further indicate novel research targets. CONCLUSIONS: Although existing software allows for complex data analyses, the LabVIEW based program presented here, “Array Data Extractor (ADE)”, provides users with a tool to retrieve meaningful information from multiple normalized gene expression datasets in a fast and easy way. Further, the graphical programming language used in LabVIEW allows applying changes to the program without the need of advanced programming knowledge