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Sample records for optical neural recording

  1. The first neural probe integrated with light source (blue laser diode) for optical stimulation and electrical recording.

    Science.gov (United States)

    Park, HyungDal; Shin, Hyun-Joon; Cho, Il-Joo; Yoon, Eui-sung; Suh, Jun-Kyo Francis; Im, Maesoon; Yoon, Euisik; Kim, Yong-Jun; Kim, Jinseok

    2011-01-01

    In this paper, we report a neural probe which can selectively stimulate target neurons optically through Si wet etched mirror surface and record extracellular neural signals in iridium oxide tetrodes. Consequently, the proposed approach provides to improve directional problem and achieve at least 150/m gap distance between stimulation and recording sites by wet etched mirror surface in V-groove. Also, we developed light source, blue laser diode (OSRAM Blue Laser Diode_PL 450), integration through simple jig for one-touch butt-coupling. Furthermore, optical power and impedance of iridium oxide tetrodes were measured as 200 μW on 5 mW from LD and 206.5 k Ω at 1 kHz and we demonstrated insertion test of probe in 0.5% agarose-gel successfully. We have successfully transmitted a light of 450 nm to optical fiber through the integrated LD using by butt-coupling method.

  2. A stereo-compound hybrid microscope for combined intracellular and optical recording of invertebrate neural network activity.

    Science.gov (United States)

    Frost, William N; Wang, Jean; Brandon, Christopher J

    2007-05-15

    Optical recording studies of invertebrate neural networks with voltage-sensitive dyes seldom employ conventional intracellular electrodes. This may in part be due to the traditional reliance on compound microscopes for such work. While such microscopes have high light-gathering power, they do not provide depth of field, making working with sharp electrodes difficult. Here we describe a hybrid microscope design, with switchable compound and stereo objectives, that eases the use of conventional intracellular electrodes in optical recording experiments. We use it, in combination with a voltage-sensitive dye and photodiode array, to identify neurons participating in the swim motor program of the marine mollusk Tritonia. This microscope design should be applicable to optical recording studies in many preparations.

  3. A stereo-compound hybrid microscope for combined intracellular and optical recording of invertebrate neural network activity

    OpenAIRE

    Frost, William N.; Wang, Jean; Brandon, Christopher J.

    2007-01-01

    Optical recording studies of invertebrate neural networks with voltage-sensitive dyes seldom employ conventional intracellular electrodes. This may in part be due to the traditional reliance on compound microscopes for such work. While such microscopes have high light-gathering power, they do not provide depth of field, making working with sharp electrodes difficult. Here we describe a hybrid microscope design, with switchable compound and stereo objectives, that eases the use of conventional...

  4. Optics in neural computation

    Science.gov (United States)

    Levene, Michael John

    In all attempts to emulate the considerable powers of the brain, one is struck by both its immense size, parallelism, and complexity. While the fields of neural networks, artificial intelligence, and neuromorphic engineering have all attempted oversimplifications on the considerable complexity, all three can benefit from the inherent scalability and parallelism of optics. This thesis looks at specific aspects of three modes in which optics, and particularly volume holography, can play a part in neural computation. First, holography serves as the basis of highly-parallel correlators, which are the foundation of optical neural networks. The huge input capability of optical neural networks make them most useful for image processing and image recognition and tracking. These tasks benefit from the shift invariance of optical correlators. In this thesis, I analyze the capacity of correlators, and then present several techniques for controlling the amount of shift invariance. Of particular interest is the Fresnel correlator, in which the hologram is displaced from the Fourier plane. In this case, the amount of shift invariance is limited not just by the thickness of the hologram, but by the distance of the hologram from the Fourier plane. Second, volume holography can provide the huge storage capacity and high speed, parallel read-out necessary to support large artificial intelligence systems. However, previous methods for storing data in volume holograms have relied on awkward beam-steering or on as-yet non- existent cheap, wide-bandwidth, tunable laser sources. This thesis presents a new technique, shift multiplexing, which is capable of very high densities, but which has the advantage of a very simple implementation. In shift multiplexing, the reference wave consists of a focused spot a few millimeters in front of the hologram. Multiplexing is achieved by simply translating the hologram a few tens of microns or less. This thesis describes the theory for how shift

  5. Optical recording medium

    International Nuclear Information System (INIS)

    Andriech, A.; Bivol, V.; Tridukh, G.; Tsiuleanu, D.

    2002-01-01

    The invention relates of the micro- and optoelectronics, computer engineering ,in particular, to tjhe optical information media and may be used in hilography. Summary of the invention consists in that the optical image recording medium, containing a dielectric substrates, onto one surface of which there are placed in series a transparent electricity conducting layer, a photo sensitive recording layer of chalcogenic glass and a thin film electrode of aluminium, is provided with an optically transparent protective layer, applied into the thin film electrode. The result of the invention consists in excluding the dependence of chemical processes course into the medium upon environmental conditions

  6. Optical Neural Network Classifier Architectures

    National Research Council Canada - National Science Library

    Getbehead, Mark

    1998-01-01

    We present an adaptive opto-electronic neural network hardware architecture capable of exploiting parallel optics to realize real-time processing and classification of high-dimensional data for Air...

  7. OptoZIF Drive: a 3D printed implant and assembly tool package for neural recording and optical stimulation in freely moving mice

    Science.gov (United States)

    Freedman, David S.; Schroeder, Joseph B.; Telian, Gregory I.; Zhang, Zhengyang; Sunil, Smrithi; Ritt, Jason T.

    2016-12-01

    Objective. Behavioral neuroscience studies in freely moving rodents require small, light-weight implants to facilitate neural recording and stimulation. Our goal was to develop an integrated package of 3D printed parts and assembly aids for labs to rapidly fabricate, with minimal training, an implant that combines individually positionable microelectrodes, an optical fiber, zero insertion force (ZIF-clip) headstage connection, and secondary recording electrodes, e.g. for electromyography (EMG). Approach. Starting from previous implant designs that position recording electrodes using a control screw, we developed an implant where the main drive body, protective shell, and non-metal components of the microdrives are 3D printed in parallel. We compared alternative shapes and orientations of circuit boards for electrode connection to the headstage, in terms of their size, weight, and ease of wire insertion. We iteratively refined assembly methods, and integrated additional assembly aids into the 3D printed casing. Main results. We demonstrate the effectiveness of the OptoZIF Drive by performing real time optogenetic feedback in behaving mice. A novel feature of the OptoZIF Drive is its vertical circuit board, which facilities direct ZIF-clip connection. This feature requires angled insertion of an optical fiber that still can exit the drive from the center of a ring of recording electrodes. We designed an innovative 2-part protective shell that can be installed during the implant surgery to facilitate making additional connections to the circuit board. We use this feature to show that facial EMG in mice can be used as a control signal to lock stimulation to the animal’s motion, with stable EMG signal over several months. To decrease assembly time, reduce assembly errors, and improve repeatability, we fabricate assembly aids including a drive holder, a drill guide, an implant fixture for microelectode ‘pinning’, and a gold plating fixture. Significance. The

  8. Optical resonators and neural networks

    Science.gov (United States)

    Anderson, Dana Z.

    1986-08-01

    It may be possible to implement neural network models using continuous field optical architectures. These devices offer the inherent parallelism of propagating waves and an information density in principle dictated by the wavelength of light and the quality of the bulk optical elements. Few components are needed to construct a relatively large equivalent network. Various associative memories based on optical resonators have been demonstrated in the literature, a ring resonator design is discussed in detail here. Information is stored in a holographic medium and recalled through a competitive processes in the gain medium supplying energy to the ring rsonator. The resonator memory is the first realized example of a neural network function implemented with this kind of architecture.

  9. Experimental Demonstrations of Optical Neural Computers

    OpenAIRE

    Hsu, Ken; Brady, David; Psaltis, Demetri

    1988-01-01

    We describe two experiments in optical neural computing. In the first a closed optical feedback loop is used to implement auto-associative image recall. In the second a perceptron-like learning algorithm is implemented with photorefractive holography.

  10. Recent Advances in Neural Recording Microsystems

    Directory of Open Access Journals (Sweden)

    Benoit Gosselin

    2011-04-01

    Full Text Available The accelerating pace of research in neuroscience has created a considerable demand for neural interfacing microsystems capable of monitoring the activity of large groups of neurons. These emerging tools have revealed a tremendous potential for the advancement of knowledge in brain research and for the development of useful clinical applications. They can extract the relevant control signals directly from the brain enabling individuals with severe disabilities to communicate their intentions to other devices, like computers or various prostheses. Such microsystems are self-contained devices composed of a neural probe attached with an integrated circuit for extracting neural signals from multiple channels, and transferring the data outside the body. The greatest challenge facing development of such emerging devices into viable clinical systems involves addressing their small form factor and low-power consumption constraints, while providing superior resolution. In this paper, we survey the recent progress in the design and the implementation of multi-channel neural recording Microsystems, with particular emphasis on the design of recording and telemetry electronics. An overview of the numerous neural signal modalities is given and the existing microsystem topologies are covered. We present energy-efficient sensory circuits to retrieve weak signals from neural probes and we compare them. We cover data management and smart power scheduling approaches, and we review advances in low-power telemetry. Finally, we conclude by summarizing the remaining challenges and by highlighting the emerging trends in the field.

  11. Improving Neural Recording Technology at the Nanoscale

    Science.gov (United States)

    Ferguson, John Eric

    Neural recording electrodes are widely used to study normal brain function (e.g., learning, memory, and sensation) and abnormal brain function (e.g., epilepsy, addiction, and depression) and to interface with the nervous system for neuroprosthetics. With a deep understanding of the electrode interface at the nanoscale and the use of novel nanofabrication processes, neural recording electrodes can be designed that surpass previous limits and enable new applications. In this thesis, I will discuss three projects. In the first project, we created an ultralow-impedance electrode coating by controlling the nanoscale texture of electrode surfaces. In the second project, we developed a novel nanowire electrode for long-term intracellular recordings. In the third project, we created a means of wirelessly communicating with ultra-miniature, implantable neural recording devices. The techniques developed for these projects offer significant improvements in the quality of neural recordings. They can also open the door to new types of experiments and medical devices, which can lead to a better understanding of the brain and can enable novel and improved tools for clinical applications.

  12. Conducting polymer coated neural recording electrodes

    Science.gov (United States)

    Harris, Alexander R.; Morgan, Simeon J.; Chen, Jun; Kapsa, Robert M. I.; Wallace, Gordon G.; Paolini, Antonio G.

    2013-02-01

    Objective. Neural recording electrodes suffer from poor signal to noise ratio, charge density, biostability and biocompatibility. This paper investigates the ability of conducting polymer coated electrodes to record acute neural response in a systematic manner, allowing in depth comparison of electrochemical and electrophysiological response. Approach. Polypyrrole (Ppy) and poly-3,4-ethylenedioxythiophene (PEDOT) doped with sulphate (SO4) or para-toluene sulfonate (pTS) were used to coat iridium neural recording electrodes. Detailed electrochemical and electrophysiological investigations were undertaken to compare the effect of these materials on acute in vivo recording. Main results. A range of charge density and impedance responses were seen with each respectively doped conducting polymer. All coatings produced greater charge density than uncoated electrodes, while PEDOT-pTS, PEDOT-SO4 and Ppy-SO4 possessed lower impedance values at 1 kHz than uncoated electrodes. Charge density increased with PEDOT-pTS thickness and impedance at 1 kHz was reduced with deposition times up to 45 s. Stable electrochemical response after acute implantation inferred biostability of PEDOT-pTS coated electrodes while other electrode materials had variable impedance and/or charge density after implantation indicative of a protein fouling layer forming on the electrode surface. Recording of neural response to white noise bursts after implantation of conducting polymer-coated electrodes into a rat model inferior colliculus showed a general decrease in background noise and increase in signal to noise ratio and spike count with reduced impedance at 1 kHz, regardless of the specific electrode coating, compared to uncoated electrodes. A 45 s PEDOT-pTS deposition time yielded the highest signal to noise ratio and spike count. Significance. A method for comparing recording electrode materials has been demonstrated with doped conducting polymers. PEDOT-pTS showed remarkable low fouling during

  13. Neural networks in continuous optical media

    International Nuclear Information System (INIS)

    Anderson, D.Z.

    1987-01-01

    The authors' interest is to see to what extent neural models can be implemented using continuous optical elements. Thus these optical networks represent a continuous distribution of neuronlike processors rather than a discrete collection. Most neural models have three characteristic features: interconnections; adaptivity; and nonlinearity. In their optical representation the interconnections are implemented with linear one- and two-port optical elements such as lenses and holograms. Real-time holographic media allow these interconnections to become adaptive. The nonlinearity is achieved with gain, for example, from two-beam coupling in photorefractive media or a pumped dye medium. Using these basic optical elements one can in principle construct continuous representations of a number of neural network models. The authors demonstrated two devices based on continuous optical elements: an associative memory which recalls an entire object when addressed with a partial object and a tracking novelty filter which identifies time-dependent features in an optical scene. These devices demonstrate the potential of distributed optical elements to implement more formal models of neural networks

  14. 3D silicon neural probe with integrated optical fibers for optogenetic modulation.

    Science.gov (United States)

    Kim, Eric G R; Tu, Hongen; Luo, Hao; Liu, Bin; Bao, Shaowen; Zhang, Jinsheng; Xu, Yong

    2015-07-21

    Optogenetics is a powerful modality for neural modulation that can be useful for a wide array of biomedical studies. Penetrating microelectrode arrays provide a means of recording neural signals with high spatial resolution. It is highly desirable to integrate optics with neural probes to allow for functional study of neural tissue by optogenetics. In this paper, we report the development of a novel 3D neural probe coupled simply and robustly to optical fibers using a hollow parylene tube structure. The device shanks are hollow tubes with rigid silicon tips, allowing the insertion and encasement of optical fibers within the shanks. The position of the fiber tip can be precisely controlled relative to the electrodes on the shank by inherent design features. Preliminary in vivo rat studies indicate that these devices are capable of optogenetic modulation simultaneously with 3D neural signal recording.

  15. Towards a magnetoresistive platform for neural signal recording

    Science.gov (United States)

    Sharma, P. P.; Gervasoni, G.; Albisetti, E.; D'Ercoli, F.; Monticelli, M.; Moretti, D.; Forte, N.; Rocchi, A.; Ferrari, G.; Baldelli, P.; Sampietro, M.; Benfenati, F.; Bertacco, R.; Petti, D.

    2017-05-01

    A promising strategy to get deeper insight on brain functionalities relies on the investigation of neural activities at the cellular and sub-cellular level. In this framework, methods for recording neuron electrical activity have gained interest over the years. Main technological challenges are associated to finding highly sensitive detection schemes, providing considerable spatial and temporal resolution. Moreover, the possibility to perform non-invasive assays would constitute a noteworthy benefit. In this work, we present a magnetoresistive platform for the detection of the action potential propagation in neural cells. Such platform allows, in perspective, the in vitro recording of neural signals arising from single neurons, neural networks and brain slices.

  16. An efficient optical architecture for sparsely connected neural networks

    Science.gov (United States)

    Hine, Butler P., III; Downie, John D.; Reid, Max B.

    1990-01-01

    An architecture for general-purpose optical neural network processor is presented in which the interconnections and weights are formed by directing coherent beams holographically, thereby making use of the space-bandwidth products of the recording medium for sparsely interconnected networks more efficiently that the commonly used vector-matrix multiplier, since all of the hologram area is in use. An investigation is made of the use of computer-generated holograms recorded on such updatable media as thermoplastic materials, in order to define the interconnections and weights of a neural network processor; attention is given to limits on interconnection densities, diffraction efficiencies, and weighing accuracies possible with such an updatable thin film holographic device.

  17. Stimulation and recording electrodes for neural prostheses

    CERN Document Server

    Pour Aryan, Naser; Rothermel, Albrecht

    2015-01-01

    This book provides readers with basic principles of the electrochemistry of the electrodes used in modern, implantable neural prostheses. The authors discuss the boundaries and conditions in which the electrodes continue to function properly for long time spans, which are required when designing neural stimulator devices for long-term in vivo applications. Two kinds of electrode materials, titanium nitride and iridium are discussed extensively, both qualitatively and quantitatively. The influence of the counter electrode on the safety margins and electrode lifetime in a two electrode system is explained. Electrode modeling is handled in a final chapter.

  18. The fiber-optic imaging and manipulation of neural activity during animal behavior.

    Science.gov (United States)

    Miyamoto, Daisuke; Murayama, Masanori

    2016-02-01

    Recent progress with optogenetic probes for imaging and manipulating neural activity has further increased the relevance of fiber-optic systems for neural circuitry research. Optical fibers, which bi-directionally transmit light between separate sites (even at a distance of several meters), can be used for either optical imaging or manipulating neural activity relevant to behavioral circuitry mechanisms. The method's flexibility and the specifications of the light structure are well suited for following the behavior of freely moving animals. Furthermore, thin optical fibers allow researchers to monitor neural activity from not only the cortical surface but also deep brain regions, including the hippocampus and amygdala. Such regions are difficult to target with two-photon microscopes. Optogenetic manipulation of neural activity with an optical fiber has the advantage of being selective for both cell-types and projections as compared to conventional electrophysiological brain tissue stimulation. It is difficult to extract any data regarding changes in neural activity solely from a fiber-optic manipulation device; however, the readout of data is made possible by combining manipulation with electrophysiological recording, or the simultaneous application of optical imaging and manipulation using a bundle-fiber. The present review introduces recent progress in fiber-optic imaging and manipulation methods, while also discussing fiber-optic system designs that are suitable for a given experimental protocol. Copyright © 2015 The Authors. Published by Elsevier Ireland Ltd.. All rights reserved.

  19. Surface-modified microelectrode array with flake nanostructure for neural recording and stimulation

    Energy Technology Data Exchange (ETDEWEB)

    Kim, Ju-Hyun; Choi, Yang-Kyu [Nano-Oriented Bio-Electronics Lab, Department of Electrical Engineering, College of Information Science and Technology, KAIST, Daejeon 305-701 (Korea, Republic of); Kang, Gyumin; Nam, Yoonkey, E-mail: ynam@kaist.ac.kr, E-mail: ykchoi@ee.kaist.ac.kr [Department of Bio and Brain Engineering, KAIST, KAIST Institute for Nano-Century, Daejeon 305-701 (Korea, Republic of)

    2010-02-26

    A novel microelectrode modification method is reported for neural electrode engineering with a flake nanostructure (nanoflake). The nanoflake-modified electrodes are fabricated by combining conventional lithography and electrochemical deposition to implement a microelectrode array (MEA) on a glass substrate. The unique geometrical properties of nanoflake sharp tips and valleys are studied by optical, electrochemical and electrical methods in order to verify the advantages of using nanoflakes for neural recording devices. The in vitro recording and stimulation of cultured hippocampal neurons are demonstrated on the nanoflake-modified MEA and the clear action potentials are observed due to the nanoflake impedance reduction effect.

  20. Large-scale multielectrode recording and stimulation of neural activity

    International Nuclear Information System (INIS)

    Sher, A.; Chichilnisky, E.J.; Dabrowski, W.; Grillo, A.A.; Grivich, M.; Gunning, D.; Hottowy, P.; Kachiguine, S.; Litke, A.M.; Mathieson, K.; Petrusca, D.

    2007-01-01

    Large circuits of neurons are employed by the brain to encode and process information. How this encoding and processing is carried out is one of the central questions in neuroscience. Since individual neurons communicate with each other through electrical signals (action potentials), the recording of neural activity with arrays of extracellular electrodes is uniquely suited for the investigation of this question. Such recordings provide the combination of the best spatial (individual neurons) and temporal (individual action-potentials) resolutions compared to other large-scale imaging methods. Electrical stimulation of neural activity in turn has two very important applications: it enhances our understanding of neural circuits by allowing active interactions with them, and it is a basis for a large variety of neural prosthetic devices. Until recently, the state-of-the-art in neural activity recording systems consisted of several dozen electrodes with inter-electrode spacing ranging from tens to hundreds of microns. Using silicon microstrip detector expertise acquired in the field of high-energy physics, we created a unique neural activity readout and stimulation framework that consists of high-density electrode arrays, multi-channel custom-designed integrated circuits, a data acquisition system, and data-processing software. Using this framework we developed a number of neural readout and stimulation systems: (1) a 512-electrode system for recording the simultaneous activity of as many as hundreds of neurons, (2) a 61-electrode system for electrical stimulation and readout of neural activity in retinas and brain-tissue slices, and (3) a system with telemetry capabilities for recording neural activity in the intact brain of awake, naturally behaving animals. We will report on these systems, their various applications to the field of neurobiology, and novel scientific results obtained with some of them. We will also outline future directions

  1. Optical-Correlator Neural Network Based On Neocognitron

    Science.gov (United States)

    Chao, Tien-Hsin; Stoner, William W.

    1994-01-01

    Multichannel optical correlator implements shift-invariant, high-discrimination pattern-recognizing neural network based on paradigm of neocognitron. Selected as basic building block of this neural network because invariance under shifts is inherent advantage of Fourier optics included in optical correlators in general. Neocognitron is conceptual electronic neural-network model for recognition of visual patterns. Multilayer processing achieved by iteratively feeding back output of feature correlator to input spatial light modulator and updating Fourier filters. Neural network trained by use of characteristic features extracted from target images. Multichannel implementation enables parallel processing of large number of selected features.

  2. Neural Interfaces for Intracortical Recording: Requirements, Fabrication Methods, and Characteristics.

    Science.gov (United States)

    Szostak, Katarzyna M; Grand, Laszlo; Constandinou, Timothy G

    2017-01-01

    Implantable neural interfaces for central nervous system research have been designed with wire, polymer, or micromachining technologies over the past 70 years. Research on biocompatible materials, ideal probe shapes, and insertion methods has resulted in building more and more capable neural interfaces. Although the trend is promising, the long-term reliability of such devices has not yet met the required criteria for chronic human application. The performance of neural interfaces in chronic settings often degrades due to foreign body response to the implant that is initiated by the surgical procedure, and related to the probe structure, and material properties used in fabricating the neural interface. In this review, we identify the key requirements for neural interfaces for intracortical recording, describe the three different types of probes-microwire, micromachined, and polymer-based probes; their materials, fabrication methods, and discuss their characteristics and related challenges.

  3. Neural Interfaces for Intracortical Recording: Requirements, Fabrication Methods, and Characteristics

    Directory of Open Access Journals (Sweden)

    Katarzyna M. Szostak

    2017-12-01

    Full Text Available Implantable neural interfaces for central nervous system research have been designed with wire, polymer, or micromachining technologies over the past 70 years. Research on biocompatible materials, ideal probe shapes, and insertion methods has resulted in building more and more capable neural interfaces. Although the trend is promising, the long-term reliability of such devices has not yet met the required criteria for chronic human application. The performance of neural interfaces in chronic settings often degrades due to foreign body response to the implant that is initiated by the surgical procedure, and related to the probe structure, and material properties used in fabricating the neural interface. In this review, we identify the key requirements for neural interfaces for intracortical recording, describe the three different types of probes—microwire, micromachined, and polymer-based probes; their materials, fabrication methods, and discuss their characteristics and related challenges.

  4. EEG in the classroom: Synchronised neural recordings during video presentation

    DEFF Research Database (Denmark)

    Poulsen, Andreas Trier; Kamronn, Simon Due; Dmochowski, Jacek

    2017-01-01

    We performed simultaneous recordings of electroencephalography (EEG) from multiple students in a classroom, and measured the inter-subject correlation (ISC) of activity evoked by a common video stimulus. The neural reliability, as quantified by ISC, has been linked to engagement and attentional......-evoked neural responses, known to be modulated by attention, can be tracked for groups of students with synchronized EEG acquisition. This is a step towards real-time inference of engagement in the classroom....

  5. Optical Calibration Process Developed for Neural-Network-Based Optical Nondestructive Evaluation Method

    Science.gov (United States)

    Decker, Arthur J.

    2004-01-01

    A completely optical calibration process has been developed at Glenn for calibrating a neural-network-based nondestructive evaluation (NDE) method. The NDE method itself detects very small changes in the characteristic patterns or vibration mode shapes of vibrating structures as discussed in many references. The mode shapes or characteristic patterns are recorded using television or electronic holography and change when a structure experiences, for example, cracking, debonds, or variations in fastener properties. An artificial neural network can be trained to be very sensitive to changes in the mode shapes, but quantifying or calibrating that sensitivity in a consistent, meaningful, and deliverable manner has been challenging. The standard calibration approach has been difficult to implement, where the response to damage of the trained neural network is compared with the responses of vibration-measurement sensors. In particular, the vibration-measurement sensors are intrusive, insufficiently sensitive, and not numerous enough. In response to these difficulties, a completely optical alternative to the standard calibration approach was proposed and tested successfully. Specifically, the vibration mode to be monitored for structural damage was intentionally contaminated with known amounts of another mode, and the response of the trained neural network was measured as a function of the peak-to-peak amplitude of the contaminating mode. The neural network calibration technique essentially uses the vibration mode shapes of the undamaged structure as standards against which the changed mode shapes are compared. The published response of the network can be made nearly independent of the contaminating mode, if enough vibration modes are used to train the net. The sensitivity of the neural network can be adjusted for the environment in which the test is to be conducted. The response of a neural network trained with measured vibration patterns for use on a vibration isolation

  6. EDITORIAL: Special issue on optical neural engineering: advances in optical stimulation technology Special issue on optical neural engineering: advances in optical stimulation technology

    Science.gov (United States)

    Shoham, Shy; Deisseroth, Karl

    2010-08-01

    Neural engineering, itself an 'emerging interdisciplinary research area' [1] has undergone a sea change over the past few years with the emergence of exciting new optical technologies for monitoring, stimulating, inhibiting and, more generally, modulating neural activity. To a large extent, this change is driven by the realization of the promise and complementary strengths that emerging photo-stimulation tools offer to add to the neural engineer's toolbox, which has been almost exclusively based on electrical stimulation technologies. Notably, photo-stimulation is non-contact, can in some cases be genetically targeted to specific cell populations, can achieve high spatial specificity (cellular or even sub-cellular) in two or three dimensions, and opens up the possibility of large-scale spatial-temporal patterned stimulation. It also offers a seamless solution to the problem of cross-talk generated by simultaneous electrical stimulation and recording. As in other biomedical optics phenomena [2], photo-stimulation includes multiple possible modes of interaction between light and the target neurons, including a variety of photo-physical and photo-bio-chemical effects with various intrinsic components or exogenous 'sensitizers' which can be loaded into the tissue or genetically expressed. Early isolated reports of neural excitation with light date back to the late 19th century [3] and to Arvanitaki and Chalazonitis' work five decades ago [4]; however, the mechanism by which these and other direct photo-stimulation, inhibition and modulation events [5-7] took place is yet unclear, as is their short- and long-term safety profile. Photo-chemical photolysis of covalently 'caged' neurotransmitters [8, 9] has been widely used in cellular neuroscience research for three decades, including for exciting or inhibiting neural activity, and for mapping neural circuits. Technological developments now allow neurotransmitters to be uncaged with exquisite spatial specificity (down to

  7. High-Density Stretchable Electrode Grids for Chronic Neural Recording.

    Science.gov (United States)

    Tybrandt, Klas; Khodagholy, Dion; Dielacher, Bernd; Stauffer, Flurin; Renz, Aline F; Buzsáki, György; Vörös, János

    2018-04-01

    Electrical interfacing with neural tissue is key to advancing diagnosis and therapies for neurological disorders, as well as providing detailed information about neural signals. A challenge for creating long-term stable interfaces between electronics and neural tissue is the huge mechanical mismatch between the systems. So far, materials and fabrication processes have restricted the development of soft electrode grids able to combine high performance, long-term stability, and high electrode density, aspects all essential for neural interfacing. Here, this challenge is addressed by developing a soft, high-density, stretchable electrode grid based on an inert, high-performance composite material comprising gold-coated titanium dioxide nanowires embedded in a silicone matrix. The developed grid can resolve high spatiotemporal neural signals from the surface of the cortex in freely moving rats with stable neural recording quality and preserved electrode signal coherence during 3 months of implantation. Due to its flexible and stretchable nature, it is possible to minimize the size of the craniotomy required for placement, further reducing the level of invasiveness. The material and device technology presented herein have potential for a wide range of emerging biomedical applications. © 2018 The Authors. Published by WILEY-VCH Verlag GmbH & Co. KGaA, Weinheim.

  8. Computational optical tomography using 3-D deep convolutional neural networks

    Science.gov (United States)

    Nguyen, Thanh; Bui, Vy; Nehmetallah, George

    2018-04-01

    Deep convolutional neural networks (DCNNs) offer a promising performance for many image processing areas, such as super-resolution, deconvolution, image classification, denoising, and segmentation, with outstanding results. Here, we develop for the first time, to our knowledge, a method to perform 3-D computational optical tomography using 3-D DCNN. A simulated 3-D phantom dataset was first constructed and converted to a dataset of phase objects imaged on a spatial light modulator. For each phase image in the dataset, the corresponding diffracted intensity image was experimentally recorded on a CCD. We then experimentally demonstrate the ability of the developed 3-D DCNN algorithm to solve the inverse problem by reconstructing the 3-D index of refraction distributions of test phantoms from the dataset from their corresponding diffraction patterns.

  9. Artificial earthquake record generation using cascade neural network

    Directory of Open Access Journals (Sweden)

    Bani-Hani Khaldoon A.

    2017-01-01

    Full Text Available This paper presents the results of using artificial neural networks (ANN in an inverse mapping problem for earthquake accelerograms generation. This study comprises of two parts: 1-D site response analysis; performed for Dubai Emirate at UAE, where eight earthquakes records are selected and spectral matching are performed to match Dubai response spectrum using SeismoMatch software. Site classification of Dubai soil is being considered for two classes C and D based on shear wave velocity of soil profiles. Amplifications factors are estimated to quantify Dubai soil effect. Dubai’s design response spectra are developed for site classes C & D according to International Buildings Code (IBC -2012. In the second part, ANN is employed to solve inverse mapping problem to generate time history earthquake record. Thirty earthquakes records and their design response spectrum with 5% damping are used to train two cascade forward backward neural networks (ANN1, ANN2. ANN1 is trained to map the design response spectrum to time history and ANN2 is trained to map time history records to the design response spectrum. Generalized time history earthquake records are generated using ANN1 for Dubai’s site classes C and D, and ANN2 is used to evaluate the performance of ANN1.

  10. Neural networks within multi-core optic fibers.

    Science.gov (United States)

    Cohen, Eyal; Malka, Dror; Shemer, Amir; Shahmoon, Asaf; Zalevsky, Zeev; London, Michael

    2016-07-07

    Hardware implementation of artificial neural networks facilitates real-time parallel processing of massive data sets. Optical neural networks offer low-volume 3D connectivity together with large bandwidth and minimal heat production in contrast to electronic implementation. Here, we present a conceptual design for in-fiber optical neural networks. Neurons and synapses are realized as individual silica cores in a multi-core fiber. Optical signals are transferred transversely between cores by means of optical coupling. Pump driven amplification in erbium-doped cores mimics synaptic interactions. We simulated three-layered feed-forward neural networks and explored their capabilities. Simulations suggest that networks can differentiate between given inputs depending on specific configurations of amplification; this implies classification and learning capabilities. Finally, we tested experimentally our basic neuronal elements using fibers, couplers, and amplifiers, and demonstrated that this configuration implements a neuron-like function. Therefore, devices similar to our proposed multi-core fiber could potentially serve as building blocks for future large-scale small-volume optical artificial neural networks.

  11. A digitally assisted, signal folding neural recording amplifier.

    Science.gov (United States)

    Chen, Yi; Basu, Arindam; Liu, Lei; Zou, Xiaodan; Rajkumar, Ramamoorthy; Dawe, Gavin Stewart; Je, Minkyu

    2014-08-01

    A novel signal folding and reconstruction scheme for neural recording applications that exploits the 1/f(n) characteristics of neural signals is described in this paper. The amplified output is 'folded' into a predefined range of voltages by using comparison and reset circuits along with the core amplifier. After this output signal is digitized and transmitted, a reconstruction algorithm can be applied in the digital domain to recover the amplified signal from the folded waveform. This scheme enables the use of an analog-to-digital convertor with less number of bits for the same effective dynamic range. It also reduces the transmission data rate of the recording chip. Both of these features allow power and area savings at the system level. Other advantages of the proposed topology are increased reliability due to the removal of pseudo-resistors, lower harmonic distortion and low-voltage operation. An analysis of the reconstruction error introduced by this scheme is presented along with a behavioral model to provide a quick estimate of the post reconstruction dynamic range. Measurement results from two different core amplifier designs in 65 nm and 180 nm CMOS processes are presented to prove the generality of the proposed scheme in the neural recording applications. Operating from a 1 V power supply, the amplifier in 180 nm CMOS has a gain of 54.2 dB, bandwidth of 5.7 kHz, input referred noise of 3.8 μVrms and power dissipation of 2.52 μW leading to a NEF of 3.1 in spike band. It exhibits a dynamic range of 66 dB and maximum SNDR of 43 dB in LFP band. It also reduces system level power (by reducing the number of bits in the ADC by 2) as well as data rate to 80% of a conventional design. In vivo measurements validate the ability of this amplifier to simultaneously record spike and LFP signals.

  12. Wireless Neural Recording With Single Low-Power Integrated Circuit

    Science.gov (United States)

    Harrison, Reid R.; Kier, Ryan J.; Chestek, Cynthia A.; Gilja, Vikash; Nuyujukian, Paul; Ryu, Stephen; Greger, Bradley; Solzbacher, Florian; Shenoy, Krishna V.

    2010-01-01

    We present benchtop and in vivo experimental results from an integrated circuit designed for wireless implantable neural recording applications. The chip, which was fabricated in a commercially available 0.6-μm 2P3M BiCMOS process, contains 100 amplifiers, a 10-bit analog-to-digital converter (ADC), 100 threshold-based spike detectors, and a 902–928 MHz frequency-shift-keying (FSK) transmitter. Neural signals from a selected amplifier are sampled by the ADC at 15.7 kSps and telemetered over the FSK wireless data link. Power, clock, and command signals are sent to the chip wirelessly over a 2.765-MHz inductive (coil-to-coil) link. The chip is capable of operating with only two off-chip components: a power/command receiving coil and a 100-nF capacitor. PMID:19497825

  13. Wireless neural recording with single low-power integrated circuit.

    Science.gov (United States)

    Harrison, Reid R; Kier, Ryan J; Chestek, Cynthia A; Gilja, Vikash; Nuyujukian, Paul; Ryu, Stephen; Greger, Bradley; Solzbacher, Florian; Shenoy, Krishna V

    2009-08-01

    We present benchtop and in vivo experimental results from an integrated circuit designed for wireless implantable neural recording applications. The chip, which was fabricated in a commercially available 0.6- mum 2P3M BiCMOS process, contains 100 amplifiers, a 10-bit analog-to-digital converter (ADC), 100 threshold-based spike detectors, and a 902-928 MHz frequency-shift-keying (FSK) transmitter. Neural signals from a selected amplifier are sampled by the ADC at 15.7 kSps and telemetered over the FSK wireless data link. Power, clock, and command signals are sent to the chip wirelessly over a 2.765-MHz inductive (coil-to-coil) link. The chip is capable of operating with only two off-chip components: a power/command receiving coil and a 100-nF capacitor.

  14. Neural-network-directed alignment of optical systems using the laser-beam spatial filter as an example

    Science.gov (United States)

    Decker, Arthur J.; Krasowski, Michael J.; Weiland, Kenneth E.

    1993-01-01

    This report describes an effort at NASA Lewis Research Center to use artificial neural networks to automate the alignment and control of optical measurement systems. Specifically, it addresses the use of commercially available neural network software and hardware to direct alignments of the common laser-beam-smoothing spatial filter. The report presents a general approach for designing alignment records and combining these into training sets to teach optical alignment functions to neural networks and discusses the use of these training sets to train several types of neural networks. Neural network configurations used include the adaptive resonance network, the back-propagation-trained network, and the counter-propagation network. This work shows that neural networks can be used to produce robust sequencers. These sequencers can learn by example to execute the step-by-step procedures of optical alignment and also can learn adaptively to correct for environmentally induced misalignment. The long-range objective is to use neural networks to automate the alignment and operation of optical measurement systems in remote, harsh, or dangerous aerospace environments. This work also shows that when neural networks are trained by a human operator, training sets should be recorded, training should be executed, and testing should be done in a manner that does not depend on intellectual judgments of the human operator.

  15. Incorporating an optical waveguide into a neural interface

    Energy Technology Data Exchange (ETDEWEB)

    Tolosa, Vanessa; Delima, Terri L.; Felix, Sarah H.; Pannu, Satinderpall S.; Shah, Kedar G.; Sheth, Heeral; Tooker, Angela C.

    2016-11-08

    An optical waveguide integrated into a multielectrode array (MEA) neural interface includes a device body, at least one electrode in the device body, at least one electrically conducting lead coupled to the at least one electrode, at least one optical channel in the device body, and waveguide material in the at least one optical channel. The fabrication of a neural interface device includes the steps of providing a device body, providing at least one electrode in the device body, providing at least one electrically conducting lead coupled to the at least one electrode, providing at least one optical channel in the device body, and providing a waveguide material in the at least one optical channel.

  16. Neural network post-processing of grayscale optical correlator

    Science.gov (United States)

    Lu, Thomas T; Hughlett, Casey L.; Zhoua, Hanying; Chao, Tien-Hsin; Hanan, Jay C.

    2005-01-01

    In this paper we present the use of a radial basis function neural network (RBFNN) as a post-processor to assist the optical correlator to identify the objects and to reject false alarms. Image plane features near the correlation peaks are extracted and fed to the neural network for analysis. The approach is capable of handling large number of object variations and filter sets. Preliminary experimental results are presented and the performance is analyzed.

  17. Time Multiplexed Active Neural Probe with 1356 Parallel Recording Sites

    Directory of Open Access Journals (Sweden)

    Bogdan C. Raducanu

    2017-10-01

    Full Text Available We present a high electrode density and high channel count CMOS (complementary metal-oxide-semiconductor active neural probe containing 1344 neuron sized recording pixels (20 µm × 20 µm and 12 reference pixels (20 µm × 80 µm, densely packed on a 50 µm thick, 100 µm wide, and 8 mm long shank. The active electrodes or pixels consist of dedicated in-situ circuits for signal source amplification, which are directly located under each electrode. The probe supports the simultaneous recording of all 1356 electrodes with sufficient signal to noise ratio for typical neuroscience applications. For enhanced performance, further noise reduction can be achieved while using half of the electrodes (678. Both of these numbers considerably surpass the state-of-the art active neural probes in both electrode count and number of recording channels. The measured input referred noise in the action potential band is 12.4 µVrms, while using 678 electrodes, with just 3 µW power dissipation per pixel and 45 µW per read-out channel (including data transmission.

  18. Fractal Interfaces for Stimulating and Recording Neural Implants

    Science.gov (United States)

    Watterson, William James

    From investigating movement in an insect to deciphering cognition in a human brain to treating Parkinson's disease, hearing loss, or even blindness, electronic implants are an essential tool for understanding the brain and treating neural diseases. Currently, the stimulating and recording resolution of these implants remains low. For instance, they can record all the neuron activity associated with movement in an insect, but are quite far from recording, at an individual neuron resolution, the large volumes of brain tissue associated with cognition. Likewise, there is remarkable success in the cochlear implant restoring hearing due to the relatively simple anatomy of the auditory nerves, but are failing to restore vision to the blind due to poor signal fidelity and transmission in stimulating the more complex anatomy of the visual nerves. The critically important research needed to improve the resolution of these implants is to optimize the neuron-electrode interface. This thesis explores geometrical and material modifications to both stimulating and recording electrodes which can improve the neuron-electrode interface. First, we introduce a fractal electrode geometry which radically improves the restored visual acuity achieved by retinal implants and leads to safe, long-term operation of the implant. Next, we demonstrate excellent neuron survival and neurite outgrowth on carbon nanotube electrodes, thus providing a safe biomaterial which forms a strong connection between the electrode and neurons. Additional preliminary evidence suggests carbon nanotubes patterned into a fractal geometry will provide further benefits in improving the electrode-neuron interface. Finally, we propose a novel implant based off field effect transistor technology which utilizes an interconnecting fractal network of semiconducting carbon nanotubes to record from thousands of neurons simutaneously at an individual neuron resolution. Taken together, these improvements have the potential to

  19. Microfluidic Actuation of Carbon Nanotube Fibers for Neural Recordings

    Science.gov (United States)

    Vercosa, Daniel G.

    Implantable devices to record and stimulate neural circuits have led to breakthroughs in neuroscience; however, technologies capable of electrical recording at the cellular level typically rely on rigid metals that poorly match the mechanical properties of soft brain tissue. As a result these electrodes often cause extensive acute and chronic injury, leading to short electrode lifetime. Recently, flexible electrodes such as Carbon Nanotube fibers (CNTf) have emerged as an attractive alternative to conventional electrodes and studies have shown that these flexible electrodes reduce neuro-inflammation and increase the quality and longevity of neural recordings. Insertion of these new compliant electrodes, however, remains challenge. The stiffening agents necessary to make the electrodes rigid enough to be inserted increases device footprint, which exacerbates brain damage during implantation. To overcome this challenge we have developed a novel technology to precisely implant and actuate high-performance, flexible carbon nanotube fiber (CNTf) microelectrodes without using a stiffening agents or shuttles. Instead, our technology uses drag forces within a microfluidic device to drive electrodes into tissue while minimizing the amount of fluid that is ejected into the tissue. In vitro experiments in brain phantoms, show that microfluidic actuated CNTf can be implanted at least 4.5 mm depth with 30 microm precision, while keeping the total volume of fluid ejected below 0.1 microL. As proof of concept, we inserted CNTfs in the small cnidarian Hydra littoralis and observed compound action potentials corresponding to contractions and in agreement with the literature. Additionally, brain slices extracted from transgenic mice were used to show that our device can be used to record spontaneous and light evoked activity from the cortex and deep brain regions such as the thalamic reticular nucleus (TRN). Overall our microfluidic actuation technology provides a platform for

  20. Amorphous silicon carbide ultramicroelectrode arrays for neural stimulation and recording

    Science.gov (United States)

    Deku, Felix; Cohen, Yarden; Joshi-Imre, Alexandra; Kanneganti, Aswini; Gardner, Timothy J.; Cogan, Stuart F.

    2018-02-01

    Objective. Foreign body response to indwelling cortical microelectrodes limits the reliability of neural stimulation and recording, particularly for extended chronic applications in behaving animals. The extent to which this response compromises the chronic stability of neural devices depends on many factors including the materials used in the electrode construction, the size, and geometry of the indwelling structure. Here, we report on the development of microelectrode arrays (MEAs) based on amorphous silicon carbide (a-SiC). Approach. This technology utilizes a-SiC for its chronic stability and employs semiconductor manufacturing processes to create MEAs with small shank dimensions. The a-SiC films were deposited by plasma enhanced chemical vapor deposition and patterned by thin-film photolithographic techniques. To improve stimulation and recording capabilities with small contact areas, we investigated low impedance coatings on the electrode sites. The assembled devices were characterized in phosphate buffered saline for their electrochemical properties. Main results. MEAs utilizing a-SiC as both the primary structural element and encapsulation were fabricated successfully. These a-SiC MEAs had 16 penetrating shanks. Each shank has a cross-sectional area less than 60 µm2 and electrode sites with a geometric surface area varying from 20 to 200 µm2. Electrode coatings of TiN and SIROF reduced 1 kHz electrode impedance to less than 100 kΩ from ~2.8 MΩ for 100 µm2 Au electrode sites and increased the charge injection capacities to values greater than 3 mC cm‑2. Finally, we demonstrated functionality by recording neural activity from basal ganglia nucleus of Zebra Finches and motor cortex of rat. Significance. The a-SiC MEAs provide a significant advancement in the development of microelectrodes that over the years has relied on silicon platforms for device manufacture. These flexible a-SiC MEAs have the potential for decreased tissue damage and reduced

  1. Two multichannel integrated circuits for neural recording and signal processing.

    Science.gov (United States)

    Obeid, Iyad; Morizio, James C; Moxon, Karen A; Nicolelis, Miguel A L; Wolf, Patrick D

    2003-02-01

    We have developed, manufactured, and tested two analog CMOS integrated circuit "neurochips" for recording from arrays of densely packed neural electrodes. Device A is a 16-channel buffer consisting of parallel noninverting amplifiers with a gain of 2 V/V. Device B is a 16-channel two-stage analog signal processor with differential amplification and high-pass filtering. It features selectable gains of 250 and 500 V/V as well as reference channel selection. The resulting amplifiers on Device A had a mean gain of 1.99 V/V with an equivalent input noise of 10 microV(rms). Those on Device B had mean gains of 53.4 and 47.4 dB with a high-pass filter pole at 211 Hz and an equivalent input noise of 4.4 microV(rms). Both devices were tested in vivo with electrode arrays implanted in the somatosensory cortex.

  2. Artificial Neural Network Based Optical Character Recognition

    OpenAIRE

    Vivek Shrivastava; Navdeep Sharma

    2012-01-01

    Optical Character Recognition deals in recognition and classification of characters from an image. For the recognition to be accurate, certain topological and geometrical properties are calculated, based on which a character is classified and recognized. Also, the Human psychology perceives characters by its overall shape and features such as strokes, curves, protrusions, enclosures etc. These properties, also called Features are extracted from the image by means of spatial pixel-...

  3. A review on power reducing methods of neural recording amplifiers

    Directory of Open Access Journals (Sweden)

    samira mehdipour

    2016-10-01

    Full Text Available Implantable multi-channel neural recording Microsystems comprise a large number of neural amplifiers, that can affect the overall power consumption and chip area of the analog part of the system.power, noise, size and dc offset are the main challenge faced by designers. Ideally the output of the opamp should be at zero volts when the inputs are grounded.In reality the input terminals are at slightly different dc potentials.The input offset voltage is defined as the voltage that must be applied between the two input terminals of the opamp to obtain zero volts at the output. Amplifier must have capability to reject this dc offset. First method that uses a capacitor feedback network with ac coupling of input devices to reject the offset is very popular in designs.very small low-cutoff frequency.The second method employs a closed-loop resistive feedback and electrode capacitance to form a highpass filter.Moreover,The third method adopts the symmetric floating resistor the feedback path of low noise amplifier to achieve low-frequency cutoff and rejects DC offset voltage. .In some application we can use folded cascade topology.The telescopic topology is a good candidate in terms of providing large gain and phase margin while dissipating small power. the cortical VLSI neuron model reducing power consumption of circuits.Power distribution is the best way to reduce power, noise and silicon area. The total power consumption of the amplifier array is reduced by applying the partial OTA sharing technique. The silicon area is reduced as a benefit of sharing the bulky capacitor.

  4. Optical neural network system for pose determination of spinning satellites

    Science.gov (United States)

    Lee, Andrew; Casasent, David

    1990-01-01

    An optical neural network architecture and algorithm based on a Hopfield optimization network are presented for multitarget tracking. This tracker utilizes a neuron for every possible target track, and a quadratic energy function of neural activities which is minimized using gradient descent neural evolution. The neural net tracker is demonstrated as part of a system for determining position and orientation (pose) of spinning satellites with respect to a robotic spacecraft. The input to the system is time sequence video from a single camera. Novelty detection and filtering are utilized to locate and segment novel regions from the input images. The neural net multitarget tracker determines the correspondences (or tracks) of the novel regions as a function of time, and hence the paths of object (satellite) parts. The path traced out by a given part or region is approximately elliptical in image space, and the position, shape and orientation of the ellipse are functions of the satellite geometry and its pose. Having a geometric model of the satellite, and the elliptical path of a part in image space, the three-dimensional pose of the satellite is determined. Digital simulation results using this algorithm are presented for various satellite poses and lighting conditions.

  5. Optical supervised filtering technique based on Hopfield neural network

    Science.gov (United States)

    Bal, Abdullah

    2004-11-01

    Hopfield neural network is commonly preferred for optimization problems. In image segmentation, conventional Hopfield neural networks (HNN) are formulated as a cost-function-minimization problem to perform gray level thresholding on the image histogram or the pixels' gray levels arranged in a one-dimensional array [R. Sammouda, N. Niki, H. Nishitani, Pattern Rec. 30 (1997) 921-927; K.S. Cheng, J.S. Lin, C.W. Mao, IEEE Trans. Med. Imag. 15 (1996) 560-567; C. Chang, P. Chung, Image and Vision comp. 19 (2001) 669-678]. In this paper, a new high speed supervised filtering technique is proposed for image feature extraction and enhancement problems by modifying the conventional HNN. The essential improvement in this technique is to use 2D convolution operation instead of weight-matrix multiplication. Thereby, neural network based a new filtering technique has been obtained that is required just 3 × 3 sized filter mask matrix instead of large size weight coefficient matrix. Optical implementation of the proposed filtering technique is executed easily using the joint transform correlator. The requirement of non-negative data for optical implementation is provided by bias technique to convert the bipolar data to non-negative data. Simulation results of the proposed optical supervised filtering technique are reported for various feature extraction problems such as edge detection, corner detection, horizontal and vertical line extraction, and fingerprint enhancement.

  6. Corrosion of tungsten microelectrodes used in neural recording applications.

    Science.gov (United States)

    Patrick, Erin; Orazem, Mark E; Sanchez, Justin C; Nishida, Toshikazu

    2011-06-15

    In neuroprosthetic applications, long-term electrode viability is necessary for robust recording of the activity of neural populations used for generating communication and control signals. The corrosion of tungsten microwire electrodes used for intracortical recording applications was analyzed in a controlled bench-top study and compared to the corrosion of tungsten microwires used in an in vivo study. Two electrolytes were investigated for the bench-top electrochemical analysis: 0.9% phosphate buffered saline (PBS) and 0.9% PBS containing 30 mM of hydrogen peroxide. The oxidation and reduction reactions responsible for corrosion were found by measurement of the open circuit potential and analysis of Pourbaix diagrams. Dissolution of tungsten to form the tungstic ion was found to be the corrosion mechanism. The corrosion rate was estimated from the polarization resistance, which was extrapolated from the electrochemical impedance spectroscopy data. The results show that tungsten microwires in an electrolyte of PBS have a corrosion rate of 300-700 μm/yr. The corrosion rate for tungsten microwires in an electrolyte containing PBS and 30 mM H₂O₂ is accelerated to 10,000-20,000 μm/yr. The corrosion rate was found to be controlled by the concentration of the reacting species in the cathodic reaction (e.g. O₂ and H₂O₂). The in vivo corrosion rate, averaged over the duration of implantation, was estimated to be 100 μm/yr. The reduced in vivo corrosion rate as compared to the bench-top rate is attributed to decreased rate of oxygen diffusion caused by the presence of a biological film and a reduced concentration of available oxygen in the brain. Copyright © 2011 Elsevier B.V. All rights reserved.

  7. A Low Noise Amplifier for Neural Spike Recording Interfaces

    Directory of Open Access Journals (Sweden)

    Jesus Ruiz-Amaya

    2015-09-01

    Full Text Available This paper presents a Low Noise Amplifier (LNA for neural spike recording applications. The proposed topology, based on a capacitive feedback network using a two-stage OTA, efficiently solves the triple trade-off between power, area and noise. Additionally, this work introduces a novel transistor-level synthesis methodology for LNAs tailored for the minimization of their noise efficiency factor under area and noise constraints. The proposed LNA has been implemented in a 130 nm CMOS technology and occupies 0.053 mm-sq. Experimental results show that the LNA offers a noise efficiency factor of 2.16 and an input referred noise of 3.8 μVrms for 1.2 V power supply. It provides a gain of 46 dB over a nominal bandwidth of 192 Hz–7.4 kHz and consumes 1.92 μW. The performance of the proposed LNA has been validated through in vivo experiments with animal models.

  8. Stretchable Transparent Electrode Arrays for Simultaneous Electrical and Optical Interrogation of Neural Circuits in Vivo.

    Science.gov (United States)

    Zhang, Jing; Liu, Xiaojun; Xu, Wenjing; Luo, Wenhan; Li, Ming; Chu, Fangbing; Xu, Lu; Cao, Anyuan; Guan, Jisong; Tang, Shiming; Duan, Xiaojie

    2018-04-09

    Recent developments of transparent electrode arrays provide a unique capability for simultaneous optical and electrical interrogation of neural circuits in the brain. However, none of these electrode arrays possess the stretchability highly desired for interfacing with mechanically active neural systems, such as the brain under injury, the spinal cord, and the peripheral nervous system (PNS). Here, we report a stretchable transparent electrode array from carbon nanotube (CNT) web-like thin films that retains excellent electrochemical performance and broad-band optical transparency under stretching and is highly durable under cyclic stretching deformation. We show that the CNT electrodes record well-defined neuronal response signals with negligible light-induced artifacts from cortical surfaces under optogenetic stimulation. Simultaneous two-photon calcium imaging through the transparent CNT electrodes from cortical surfaces of GCaMP-expressing mice with epilepsy shows individual activated neurons in brain regions from which the concurrent electrical recording is taken, thus providing complementary cellular information in addition to the high-temporal-resolution electrical recording. Notably, the studies on rats show that the CNT electrodes remain operational during and after brain contusion that involves the rapid deformation of both the electrode array and brain tissue. This enables real-time, continuous electrophysiological monitoring of cortical activity under traumatic brain injury. These results highlight the potential application of the stretchable transparent CNT electrode arrays in combining electrical and optical modalities to study neural circuits, especially under mechanically active conditions, which could potentially provide important new insights into the local circuit dynamics of the spinal cord and PNS as well as the mechanism underlying traumatic injuries of the nervous system.

  9. High-Density Near-Field Optical Disc Recording

    Science.gov (United States)

    Shinoda, Masataka; Saito, Kimihiro; Ishimoto, Tsutomu; Kondo, Takao; Nakaoki, Ariyoshi; Ide, Naoki; Furuki, Motohiro; Takeda, Minoru; Akiyama, Yuji; Shimouma, Takashi; Yamamoto, Masanobu

    2005-05-01

    We developed a high-density near-field optical recording disc system using a solid immersion lens. The near-field optical pick-up consists of a solid immersion lens with a numerical aperture of 1.84. The laser wavelength for recording is 405 nm. In order to realize the near-field optical recording disc, we used a phase-change recording media and a molded polycarbonate substrate. A clear eye pattern of 112 GB capacity with 160 nm track pitch and 50 nm bit length was observed. The equivalent areal density is 80.6 Gbit/in2. The bottom bit error rate of 3 tracks-write was 4.5× 10-5. The readout power margin and the recording power margin were ± 30.4% and ± 11.2%, respectively.

  10. Use of artificial neural networks on optical track width measurements

    Science.gov (United States)

    Smith, Richard J.; See, Chung W.; Somekh, Mike G.; Yacoot, Andrew

    2007-08-01

    We have demonstrated recently that, by using an ultrastable optical interferometer together with artificial neural networks (ANNs), track widths down to 60 nm can be measured with a 0.3 NA objective lens. We investigate the effective conditions for training ANNs. Experimental results will be used to show the characteristics of the training samples and the data format of the ANN inputs required to produce suitably trained ANNs. Results obtained with networks measuring double tracks, and classifying different structures, will be presented to illustrate the capability of the technique. We include a discussion on expansion of the application areas of the system, allowing it to be used as a general purpose instrument.

  11. Fast optical recording media based on semiconductor nanostructures for image recording and processing

    International Nuclear Information System (INIS)

    Kasherininov, P. G.; Tomasov, A. A.

    2008-01-01

    Fast optical recording media based on semiconductor nanostructures (CdTe, GaAs) for image recording and processing with a speed to 10 6 cycle/s (which exceeds the speed of known recording media based on metal-insulator-semiconductor-(liquid crystal) (MIS-LC) structures by two to three orders of magnitude), a photosensitivity of 10 -2 V/cm 2 , and a spatial resolution of 5-10 (line pairs)/mm are developed. Operating principles of nanostructures as fast optical recording media and methods for reading images recorded in such media are described. Fast optical processors for recording images in incoherent light based on CdTe crystal nanostructures are implemented. The possibility of their application to fabricate image correlators is shown.

  12. Polarization holographic optical recording of a new photochromic diarylethene

    Science.gov (United States)

    Pu, Shouzhi; Miao, Wenjuan; Chen, Anyin; Cui, Shiqiang

    2008-12-01

    A new symmetrical photochromic diarylethene, 1,2-bis[2-methyl-5-(3-methoxylphenyl)-3-thienyl]perfluorocyclopentene (1a), was synthesized, and its photochromic properties were investigated. The compound exhibited good photochromism both in solution and in PMMA film with alternating irradiation by UV/VIS light, and the maxima absorption of its closed-ring isomer 1b are 582 and 599 nm, respectively. Using diarylethene 1b/PMMA film as recording medium and a He-Ne laser (633 nm) for recording and readout, four types of polarization and angular multiplexing holographic optical recording were performed perfectly. For different types of polarization recording including parallel linear polarization recording, parallel circular polarization recording, orthogonal linear polarization recording and orthogonal circular polarization recording,have been accomplished successfully. The results demonstrated that the orthogonal circular polarization recording is the best method for polarization holographic optical recording when this compound was used as recording material. With angular multiplexing recording technology, two high contrast holograms were recorded in the same place on the film with the dimension of 0.78 μm2.

  13. Simultaneous surface and depth neural activity recording with graphene transistor-based dual-modality probes.

    Science.gov (United States)

    Du, Mingde; Xu, Xianchen; Yang, Long; Guo, Yichuan; Guan, Shouliang; Shi, Jidong; Wang, Jinfen; Fang, Ying

    2018-05-15

    Subdural surface and penetrating depth probes are widely applied to record neural activities from the cortical surface and intracortical locations of the brain, respectively. Simultaneous surface and depth neural activity recording is essential to understand the linkage between the two modalities. Here, we develop flexible dual-modality neural probes based on graphene transistors. The neural probes exhibit stable electrical performance even under 90° bending because of the excellent mechanical properties of graphene, and thus allow multi-site recording from the subdural surface of rat cortex. In addition, finite element analysis was carried out to investigate the mechanical interactions between probe and cortex tissue during intracortical implantation. Based on the simulation results, a sharp tip angle of π/6 was chosen to facilitate tissue penetration of the neural probes. Accordingly, the graphene transistor-based dual-modality neural probes have been successfully applied for simultaneous surface and depth recording of epileptiform activity of rat brain in vivo. Our results show that graphene transistor-based dual-modality neural probes can serve as a facile and versatile tool to study tempo-spatial patterns of neural activities. Copyright © 2018 Elsevier B.V. All rights reserved.

  14. Using Pulse Width Modulation for Wireless Transmission of Neural Signals in Multichannel Neural Recording Systems

    Science.gov (United States)

    Yin, Ming; Ghovanloo, Maysam

    2013-01-01

    We have used a well-known technique in wireless communication, pulse width modulation (PWM) of time division multiplexed (TDM) signals, within the architecture of a novel wireless integrated neural recording (WINeR) system. We have evaluated the performance of the PWM-based architecture and indicated its accuracy and potential sources of error through detailed theoretical analysis, simulations, and measurements on a setup consisting of a 15-channel WINeR prototype as the transmitter and two types of receivers; an Agilent 89600 vector signal analyzer and a custom wideband receiver, with 36 and 75 MHz of maximum bandwidth, respectively. Furthermore, we present simulation results from a realistic MATLAB-Simulink model of the entire WINeR system to observe the system behavior in response to changes in various parameters. We have concluded that the 15-ch WINeR prototype, which is fabricated in a 0.5-μm standard CMOS process and consumes 4.5 mW from ±1.5 V supplies, can acquire and wirelessly transmit up to 320 k-samples/s to a 75-MHz receiver with 8.4 bits of resolution, which is equivalent to a wireless data rate of ~ 2.26 Mb/s. PMID:19497823

  15. Quantum-dot based nanothermometry in optical plasmonic recording media

    International Nuclear Information System (INIS)

    Maestro, Laura Martinez; Zhang, Qiming; Li, Xiangping; Gu, Min; Jaque, Daniel

    2014-01-01

    We report on the direct experimental determination of the temperature increment caused by laser irradiation in a optical recording media constituted by a polymeric film in which gold nanorods have been incorporated. The incorporation of CdSe quantum dots in the recording media allowed for single beam thermal reading of the on-focus temperature from a simple analysis of the two-photon excited fluorescence of quantum dots. Experimental results have been compared with numerical simulations revealing an excellent agreement and opening a promising avenue for further understanding and optimization of optical writing processes and media

  16. Techniques for extracting single-trial activity patterns from large-scale neural recordings

    Science.gov (United States)

    Churchland, Mark M; Yu, Byron M; Sahani, Maneesh; Shenoy, Krishna V

    2008-01-01

    Summary Large, chronically-implanted arrays of microelectrodes are an increasingly common tool for recording from primate cortex, and can provide extracellular recordings from many (order of 100) neurons. While the desire for cortically-based motor prostheses has helped drive their development, such arrays also offer great potential to advance basic neuroscience research. Here we discuss the utility of array recording for the study of neural dynamics. Neural activity often has dynamics beyond that driven directly by the stimulus. While governed by those dynamics, neural responses may nevertheless unfold differently for nominally identical trials, rendering many traditional analysis methods ineffective. We review recent studies – some employing simultaneous recording, some not – indicating that such variability is indeed present both during movement generation, and during the preceding premotor computations. In such cases, large-scale simultaneous recordings have the potential to provide an unprecedented view of neural dynamics at the level of single trials. However, this enterprise will depend not only on techniques for simultaneous recording, but also on the use and further development of analysis techniques that can appropriately reduce the dimensionality of the data, and allow visualization of single-trial neural behavior. PMID:18093826

  17. Optical imaging of neuronal activity and visualization of fine neural structures in non-desheathed nervous systems.

    Directory of Open Access Journals (Sweden)

    Christopher John Goldsmith

    Full Text Available Locating circuit neurons and recording from them with single-cell resolution is a prerequisite for studying neural circuits. Determining neuron location can be challenging even in small nervous systems because neurons are densely packed, found in different layers, and are often covered by ganglion and nerve sheaths that impede access for recording electrodes and neuronal markers. We revisited the voltage-sensitive dye RH795 for its ability to stain and record neurons through the ganglion sheath. Bath-application of RH795 stained neuronal membranes in cricket, earthworm and crab ganglia without removing the ganglion sheath, revealing neuron cell body locations in different ganglion layers. Using the pyloric and gastric mill central pattern generating neurons in the stomatogastric ganglion (STG of the crab, Cancer borealis, we found that RH795 permeated the ganglion without major residue in the sheath and brightly stained somatic, axonal and dendritic membranes. Visibility improved significantly in comparison to unstained ganglia, allowing the identification of somata location and number of most STG neurons. RH795 also stained axons and varicosities in non-desheathed nerves, and it revealed the location of sensory cell bodies in peripheral nerves. Importantly, the spike activity of the sensory neuron AGR, which influences the STG motor patterns, remained unaffected by RH795, while desheathing caused significant changes in AGR activity. With respect to recording neural activity, RH795 allowed us to optically record membrane potential changes of sub-sheath neuronal membranes without impairing sensory activity. The signal-to-noise ratio was comparable with that previously observed in desheathed preparations and sufficiently high to identify neurons in single-sweep recordings and synaptic events after spike-triggered averaging. In conclusion, RH795 enabled staining and optical recording of neurons through the ganglion sheath and is therefore both a

  18. System and carrier for optical images and holographic information recording

    International Nuclear Information System (INIS)

    Andries, A.; Bivol, V.; Iovu, M

    2002-01-01

    The invention relates to the semiconducting silverless photography, in particular to the technique for optical information recording and may be used in microphotography for manifacture of microfiches, microfilms, storage disks, i the multiplication and copying technique, in holography, in micro- and optoelectronics, cinematography etc. The system for optical images and holographic information recording includes an optical exposure system, an information carrier , containing a dielectric substrate with the first electrode, a photosensitive element and the second electrode, arranged in consecutive order, a constant and impulse voltage source, a means for climbing and movement of the information carrier, a control unit for connection of the voltage source to the electroconducting strate, a personal computer, connected to the control unit of the recording modes ,to the exposure system and the information carrier, an electrooptical transparency, connected to the computer by means of the matching unit. The carrier for optical images and holographic information recording contains a dielectric substrate, a photosensitive element formed of a layer of the vitreous chalcogenic semiconductor and a layer of the crystalline or amorphous semiconductor, forming a heterojunction, the photosensitive element is arranged between two electrodes , one of which is made transparent , in such case rge layer of the vitreous chalcogenic semiconductor comes into contact with the superior transparent electrode, subjected to exposure

  19. System-Level Design of a 64-Channel Low Power Neural Spike Recording Sensor.

    Science.gov (United States)

    Delgado-Restituto, Manuel; Rodriguez-Perez, Alberto; Darie, Angela; Soto-Sanchez, Cristina; Fernandez-Jover, Eduardo; Rodriguez-Vazquez, Angel

    2017-04-01

    This paper reports an integrated 64-channel neural spike recording sensor, together with all the circuitry to process and configure the channels, process the neural data, transmit via a wireless link the information and receive the required instructions. Neural signals are acquired, filtered, digitized and compressed in the channels. Additionally, each channel implements an auto-calibration algorithm which individually configures the transfer characteristics of the recording site. The system has two transmission modes; in one case the information captured by the channels is sent as uncompressed raw data; in the other, feature vectors extracted from the detected neural spikes are released. Data streams coming from the channels are serialized by the embedded digital processor. Experimental results, including in vivo measurements, show that the power consumption of the complete system is lower than 330 μW.

  20. Modified-hybrid optical neural network filter for multiple object recognition within cluttered scenes

    Science.gov (United States)

    Kypraios, Ioannis; Young, Rupert C. D.; Chatwin, Chris R.

    2009-08-01

    Motivated by the non-linear interpolation and generalization abilities of the hybrid optical neural network filter between the reference and non-reference images of the true-class object we designed the modifiedhybrid optical neural network filter. We applied an optical mask to the hybrid optical neural network's filter input. The mask was built with the constant weight connections of a randomly chosen image included in the training set. The resulted design of the modified-hybrid optical neural network filter is optimized for performing best in cluttered scenes of the true-class object. Due to the shift invariance properties inherited by its correlator unit the filter can accommodate multiple objects of the same class to be detected within an input cluttered image. Additionally, the architecture of the neural network unit of the general hybrid optical neural network filter allows the recognition of multiple objects of different classes within the input cluttered image by modifying the output layer of the unit. We test the modified-hybrid optical neural network filter for multiple objects of the same and of different classes' recognition within cluttered input images and video sequences of cluttered scenes. The filter is shown to exhibit with a single pass over the input data simultaneously out-of-plane rotation, shift invariance and good clutter tolerance. It is able to successfully detect and classify correctly the true-class objects within background clutter for which there has been no previous training.

  1. Hopfield neural network and optical fiber sensor as intelligent heart rate monitor

    Science.gov (United States)

    Mutter, Kussay Nugamesh

    2018-01-01

    This paper presents a design and fabrication of an intelligent fiber-optic sensor used for examining and monitoring heart rate activity. It is found in the literature that the use of fiber sensors as heart rate sensor is widely studied. However, the use of smart sensors based on Hopfield neural networks is very low. In this work, the sensor is a three fibers without cladding of about 1 cm, fed by laser light of 1550 nm of wavelength. The sensing portions are mounted with a micro sensitive diaphragm to transfer the pulse pressure on the left radial wrist. The influenced light intensity will be detected by a three photodetectors as inputs into the Hopfield neural network algorithm. The latter is a singlelayer auto-associative memory structure with a same input and output layers. The prior training weights are stored in the net memory for the standard recorded normal heart rate signals. The sensors' heads work on the reflection intensity basis. The novelty here is that the sensor uses a pulse pressure and Hopfield neural network in an integrity approach. The results showed a significant output measurements of heart rate and counting with a plausible error rate.

  2. Analysis of deep brain stimulation electrode characteristics for neural recording

    Science.gov (United States)

    Kent, Alexander R.; Grill, Warren M.

    2014-08-01

    Objective. Closed-loop deep brain stimulation (DBS) systems have the potential to optimize treatment of movement disorders by enabling automatic adjustment of stimulation parameters based on a feedback signal. Evoked compound action potentials (ECAPs) and local field potentials (LFPs) recorded from the DBS electrode may serve as suitable closed-loop control signals. The objective of this study was to understand better the factors that influence ECAP and LFP recording, including the physical presence of the electrode, the geometrical dimensions of the electrode, and changes in the composition of the peri-electrode space across recording conditions. Approach. Coupled volume conductor-neuron models were used to calculate single-unit activity as well as ECAP responses and LFP activity from a population of model thalamic neurons. Main results. Comparing ECAPs and LFPs measured with and without the presence of the highly conductive recording contacts, we found that the presence of these contacts had a negligible effect on the magnitude of single-unit recordings, ECAPs (7% RMS difference between waveforms), and LFPs (5% change in signal magnitude). Spatial averaging across the contact surface decreased the ECAP magnitude in a phase-dependent manner (74% RMS difference), resulting from a differential effect of the contact on the contribution from nearby or distant elements, and decreased the LFP magnitude (25% change). Reductions in the electrode diameter or recording contact length increased signal energy and increased spatial sensitivity of single neuron recordings. Moreover, smaller diameter electrodes (500 µm) were more selective for recording from local cells over passing axons, with the opposite true for larger diameters (1500 µm). Changes in electrode dimensions had phase-dependent effects on ECAP characteristics, and generally had small effects on the LFP magnitude. ECAP signal energy and LFP magnitude decreased with tighter contact spacing (100 µm), compared to

  3. Optical path of infrared neural stimulation in the guinea pig and cat cochlea

    Science.gov (United States)

    Rajguru, Suhrud M.; Hwang, Margaret; Moreno, Laura E.; Matic, Agnella I.; Stock, Stuart R.; Richter, Claus-Peter

    2011-03-01

    It has been demonstrated previously that infrared neural stimulation (INS) can be used to stimulate spiral ganglion cells in the cochlea. With INS, neural stimulation can be achieved without direct contact of the radiation source and the tissue and is spatially well resolved. The presence of fluids or bone between the target structure and the radiation source may lead to absorption or scattering of the radiation and limit the efficacy of INS. To develop INS based cochlear implants, it is critical to determine the beam path of the radiation in the cochlea. In the present study, we utilized noninvasive X-ray microtomography (microCT) to visualize the orientation and location of the optical fiber within the guinea pig and cat cochlea. Overall, the results indicated that the optical fiber was directed towards the spiral ganglion cells in the cochlea and not the nerve fibers in the center of the modiolus. The fiber was approximately 300 μm away from the target structures. In future studies, results from the microCT will be correlated with physiology obtained from recordings in the midbrain.

  4. Logarithmic r-θ mapping for hybrid optical neural network filter for multiple objects recognition within cluttered scenes

    Science.gov (United States)

    Kypraios, Ioannis; Young, Rupert C. D.; Chatwin, Chris R.; Birch, Phil M.

    2009-04-01

    θThe window unit in the design of the complex logarithmic r-θ mapping for hybrid optical neural network filter can allow multiple objects of the same class to be detected within the input image. Additionally, the architecture of the neural network unit of the complex logarithmic r-θ mapping for hybrid optical neural network filter becomes attractive for accommodating the recognition of multiple objects of different classes within the input image by modifying the output layer of the unit. We test the overall filter for multiple objects of the same and of different classes' recognition within cluttered input images and video sequences of cluttered scenes. Logarithmic r-θ mapping for hybrid optical neural network filter is shown to exhibit with a single pass over the input data simultaneously in-plane rotation, out-of-plane rotation, scale, log r-θ map translation and shift invariance, and good clutter tolerance by recognizing correctly the different objects within the cluttered scenes. We record in our results additional extracted information from the cluttered scenes about the objects' relative position, scale and in-plane rotation.

  5. Neural signal processing and closed-loop control algorithm design for an implanted neural recording and stimulation system.

    Science.gov (United States)

    Hamilton, Lei; McConley, Marc; Angermueller, Kai; Goldberg, David; Corba, Massimiliano; Kim, Louis; Moran, James; Parks, Philip D; Sang Chin; Widge, Alik S; Dougherty, Darin D; Eskandar, Emad N

    2015-08-01

    A fully autonomous intracranial device is built to continually record neural activities in different parts of the brain, process these sampled signals, decode features that correlate to behaviors and neuropsychiatric states, and use these features to deliver brain stimulation in a closed-loop fashion. In this paper, we describe the sampling and stimulation aspects of such a device. We first describe the signal processing algorithms of two unsupervised spike sorting methods. Next, we describe the LFP time-frequency analysis and feature derivation from the two spike sorting methods. Spike sorting includes a novel approach to constructing a dictionary learning algorithm in a Compressed Sensing (CS) framework. We present a joint prediction scheme to determine the class of neural spikes in the dictionary learning framework; and, the second approach is a modified OSort algorithm which is implemented in a distributed system optimized for power efficiency. Furthermore, sorted spikes and time-frequency analysis of LFP signals can be used to generate derived features (including cross-frequency coupling, spike-field coupling). We then show how these derived features can be used in the design and development of novel decode and closed-loop control algorithms that are optimized to apply deep brain stimulation based on a patient's neuropsychiatric state. For the control algorithm, we define the state vector as representative of a patient's impulsivity, avoidance, inhibition, etc. Controller parameters are optimized to apply stimulation based on the state vector's current state as well as its historical values. The overall algorithm and software design for our implantable neural recording and stimulation system uses an innovative, adaptable, and reprogrammable architecture that enables advancement of the state-of-the-art in closed-loop neural control while also meeting the challenges of system power constraints and concurrent development with ongoing scientific research designed

  6. Artificial neural network techniques to improve the ability of optical coherence tomography to detect optic neuritis.

    Science.gov (United States)

    Garcia-Martin, Elena; Herrero, Raquel; Bambo, Maria P; Ara, Jose R; Martin, Jesus; Polo, Vicente; Larrosa, Jose M; Garcia-Feijoo, Julian; Pablo, Luis E

    2015-01-01

    To analyze the ability of Spectralis optical coherence tomography (OCT) to detect multiple sclerosis (MS) and to distinguish MS eyes with antecedent optic neuritis (ON). To analyze the capability of artificial neural network (ANN) techniques to improve the diagnostic precision. MS patients and controls were enrolled (n = 217). OCT was used to determine the 768 retinal nerve fiber layer thicknesses. Sensitivity and specificity were evaluated to test the ability of OCT to discriminate between MS and healthy eyes, and between MS with and without antecedent ON using ANN. Using ANN technique multilayer perceptrons, OCT could detect MS with a sensitivity of 89.3%, a specificity of 87.6%, and a diagnostic precision of 88.5%. Compared with the OCT-provided parameters, the ANN had a better sensitivity-specificity balance. ANN technique improves the capability of Spectralis OCT to detect MS disease and to distinguish MS eyes with or without antecedent ON.

  7. Circuit Models and Experimental Noise Measurements of Micropipette Amplifiers for Extracellular Neural Recordings from Live Animals

    Directory of Open Access Journals (Sweden)

    Chang Hao Chen

    2014-01-01

    Full Text Available Glass micropipettes are widely used to record neural activity from single neurons or clusters of neurons extracellularly in live animals. However, to date, there has been no comprehensive study of noise in extracellular recordings with glass micropipettes. The purpose of this work was to assess various noise sources that affect extracellular recordings and to create model systems in which novel micropipette neural amplifier designs can be tested. An equivalent circuit of the glass micropipette and the noise model of this circuit, which accurately describe the various noise sources involved in extracellular recordings, have been developed. Measurement schemes using dead brain tissue as well as extracellular recordings from neurons in the inferior colliculus, an auditory brain nucleus of an anesthetized gerbil, were used to characterize noise performance and amplification efficacy of the proposed micropipette neural amplifier. According to our model, the major noise sources which influence the signal to noise ratio are the intrinsic noise of the neural amplifier and the thermal noise from distributed pipette resistance. These two types of noise were calculated and measured and were shown to be the dominating sources of background noise for in vivo experiments.

  8. A Wireless Fully Passive Neural Recording Device for Unobtrusive Neuropotential Monitoring.

    Science.gov (United States)

    Kiourti, Asimina; Lee, Cedric W L; Chae, Junseok; Volakis, John L

    2016-01-01

    We propose a novel wireless fully passive neural recording device for unobtrusive neuropotential monitoring. Previous work demonstrated the feasibility of monitoring emulated brain signals in a wireless fully passive manner. In this paper, we propose a novel realistic recorder that is significantly smaller and much more sensitive. The proposed recorder utilizes a highly efficient microwave backscattering method and operates without any formal power supply or regulating elements. Also, no intracranial wires or cables are required. In-vitro testing is performed inside a four-layer head phantom (skin, bone, gray matter, and white matter). Compared to our former implementation, the neural recorder proposed in this study has the following improved features: 1) 59% smaller footprint, 2) up to 20-dB improvement in neuropotential detection sensitivity, and 3) encapsulation in biocompatible polymer. For the first time, temporal emulated neuropotentials as low as 63 μVpp can be detected in a wireless fully passive manner. Remarkably, the high-sensitivity achieved in this study implies reading of most neural signals generated by the human brain. The proposed recorder brings forward transformational possibilities in wireless fully passive neural detection for a very wide range of applications (e.g., epilepsy, Alzheimer's, mental disorders, etc.).

  9. The application of neural network techniques to magnetic and optical inverse problems

    International Nuclear Information System (INIS)

    Jones, H.V.

    2000-12-01

    The processing power of the computer has increased at unimaginable rates over the last few decades. However, even today's fastest computer can take several hours to find solutions to some mathematical problems; and there are instances where a high powered supercomputer may be impractical, with the need for near instant solutions just as important (such as in an on-line testing system). This led us to believe that such complex problems could be solved using a novel approach, whereby the system would have prior knowledge about the expected solutions through a process of learning. One method of approaching this kind of problem is through the use of machine learning. Just as a human can be trained and is able to learn from past experiences, a machine is can do just the same. This is the concept of neural networks. The research which was conducted involves the investigation of various neural network techniques, and their applicability to solve some known complex inverse problems in the field of magnetic and optical recording. In some cases a comparison is also made to more conventional methods of solving the problems, from which it was possible to outline some key advantages of using a neural network approach. We initially investigated the application of neural networks to transverse susceptibility data in order to determine anisotropy distributions. This area of research is proving to be very important, as it gives us information about the switching field distribution, which then determines the minimum transition width achievable in a medium, and affects the overwrite characteristics of the media. Secondly, we investigated a similar situation, but applied to an optical problem. This involved the determination of important compact disc parameters from the diffraction pattern of a laser from a disc. This technique was then intended for use in an on-line testing system. Finally we investigated another area of neural networks with the analysis of magnetisation maps and

  10. Plasma control using neural network and optical emission spectroscopy

    International Nuclear Information System (INIS)

    Kim, Byungwhan; Bae, Jung Ki; Hong, Wan-Shick

    2005-01-01

    Due to high sensitivity to process parameters, plasma processes should be tightly controlled. For plasma control, a predictive model was constructed using a neural network and optical emission spectroscopy (OES). Principal component analysis (PCA) was used to reduce OES dimensionality. This approach was applied to an oxide plasma etching conducted in a CHF 3 /CF 4 magnetically enhanced reactive ion plasma. The etch process was systematically characterized by means of a statistical experimental design. Three etch outputs (etch rate, profile angle, and etch rate nonuniformity) were modeled using three different approaches, including conventional, OES, and PCA-OES models. For all etch outputs, OES models demonstrated improved predictions over the conventional or PCA-OES models. Compared to conventional models, OES models yielded an improvement of more than 25% in modeling profile angle and etch rate nonuniformtiy. More than 40% improvement over PCA-OES model was achieved in modeling etch rate and profile angle. These results demonstrate that nonreduced in situ data are more beneficial than reduced one in constructing plasma control model

  11. Accelerated optical holographic recording using bis-DNO

    DEFF Research Database (Denmark)

    Rasmussen, Palle H.; Ramanujam, P.S.; Hvilsted, Søren

    1999-01-01

    The design, synthesis and optical holographic recording properties of bis-DNO are reported. Bis-DNO is composed of two identical azobenzene oligoornithine segments (DNO) connected via a dipeptide linker. The two segments were assembled in a parallel fashion at the two amino groups of the dipeptid...... linker by Merrifield synthesis. Surprisingly, the response time of films of bis-DNOs was found to be much faster than that of their linear counterparts. (C) 1999 Elsevier Science Ltd. All rights reserved....

  12. Mapping face categorization in the human ventral occipitotemporal cortex with direct neural intracranial recordings.

    Science.gov (United States)

    Rossion, Bruno; Jacques, Corentin; Jonas, Jacques

    2018-02-26

    The neural basis of face categorization has been widely investigated with functional magnetic resonance imaging (fMRI), identifying a set of face-selective local regions in the ventral occipitotemporal cortex (VOTC). However, indirect recording of neural activity with fMRI is associated with large fluctuations of signal across regions, often underestimating face-selective responses in the anterior VOTC. While direct recording of neural activity with subdural grids of electrodes (electrocorticography, ECoG) or depth electrodes (stereotactic electroencephalography, SEEG) offers a unique opportunity to fill this gap in knowledge, these studies rather reveal widely distributed face-selective responses. Moreover, intracranial recordings are complicated by interindividual variability in neuroanatomy, ambiguity in definition, and quantification of responses of interest, as well as limited access to sulci with ECoG. Here, we propose to combine SEEG in large samples of individuals with fast periodic visual stimulation to objectively define, quantify, and characterize face categorization across the whole VOTC. This approach reconciles the wide distribution of neural face categorization responses with their (right) hemispheric and regional specialization, and reveals several face-selective regions in anterior VOTC sulci. We outline the challenges of this research program to understand the neural basis of face categorization and high-level visual recognition in general. © 2018 New York Academy of Sciences.

  13. High Speed PAM -8 Optical Interconnects with Digital Equalization based on Neural Network

    DEFF Research Database (Denmark)

    Gaiarin, Simone; Pang, Xiaodan; Ozolins, Oskars

    2016-01-01

    We experimentally evaluate a high-speed optical interconnection link with neural network equalization. Enhanced equalization performances are shown comparing to standard linear FFE for an EML-based 32 GBd PAM-8 signal after 4-km SMF transmission.......We experimentally evaluate a high-speed optical interconnection link with neural network equalization. Enhanced equalization performances are shown comparing to standard linear FFE for an EML-based 32 GBd PAM-8 signal after 4-km SMF transmission....

  14. Optical computing and neural networks; Proceedings of the Meeting, National Chiao Tung Univ., Hsinchu, Taiwan, Dec. 16, 17, 1992

    Science.gov (United States)

    Hsu, Ken-Yuh (Editor); Liu, Hua-Kuang (Editor)

    1992-01-01

    The present conference discusses optical neural networks, photorefractive nonlinear optics, optical pattern recognition, digital and analog processors, and holography and its applications. Attention is given to bifurcating optical information processing, neural structures in digital halftoning, an exemplar-based optical neural net classifier for color pattern recognition, volume storage in photorefractive disks, and microlaser-based compact optical neuroprocessors. Also treated are the optical implementation of a feature-enhanced optical interpattern-associative neural network model and its optical implementation, an optical pattern binary dual-rail logic gate module, a theoretical analysis for holographic associative memories, joint transform correlators, image addition and subtraction via the Talbot effect, and optical wavelet-matched filters. (No individual items are abstracted in this volume)

  15. Optical computing and neural networks; Proceedings of the Meeting, National Chiao Tung Univ., Hsinchu, Taiwan, Dec. 16, 17, 1992

    Science.gov (United States)

    Hsu, Ken-Yuh; Liu, Hua-Kuang

    The present conference discusses optical neural networks, photorefractive nonlinear optics, optical pattern recognition, digital and analog processors, and holography and its applications. Attention is given to bifurcating optical information processing, neural structures in digital halftoning, an exemplar-based optical neural net classifier for color pattern recognition, volume storage in photorefractive disks, and microlaser-based compact optical neuroprocessors. Also treated are the optical implementation of a feature-enhanced optical interpattern-associative neural network model and its optical implementation, an optical pattern binary dual-rail logic gate module, a theoretical analysis for holographic associative memories, joint transform correlators, image addition and subtraction via the Talbot effect, and optical wavelet-matched filters. (No individual items are abstracted in this volume)

  16. Optical implementation of a feature-based neural network with application to automatic target recognition

    Science.gov (United States)

    Chao, Tien-Hsin; Stoner, William W.

    1993-01-01

    An optical neural network based on the neocognitron paradigm is introduced. A novel aspect of the architecture design is shift-invariant multichannel Fourier optical correlation within each processing layer. Multilayer processing is achieved by feeding back the ouput of the feature correlator interatively to the input spatial light modulator and by updating the Fourier filters. By training the neural net with characteristic features extracted from the target images, successful pattern recognition with intraclass fault tolerance and interclass discrimination is achieved. A detailed system description is provided. Experimental demonstrations of a two-layer neural network for space-object discrimination is also presented.

  17. Automatic target recognition using a feature-based optical neural network

    Science.gov (United States)

    Chao, Tien-Hsin

    1992-01-01

    An optical neural network based upon the Neocognitron paradigm (K. Fukushima et al. 1983) is introduced. A novel aspect of the architectural design is shift-invariant multichannel Fourier optical correlation within each processing layer. Multilayer processing is achieved by iteratively feeding back the output of the feature correlator to the input spatial light modulator and updating the Fourier filters. By training the neural net with characteristic features extracted from the target images, successful pattern recognition with intra-class fault tolerance and inter-class discrimination is achieved. A detailed system description is provided. Experimental demonstration of a two-layer neural network for space objects discrimination is also presented.

  18. Multifocal fluorescence microscope for fast optical recordings of neuronal action potentials.

    Science.gov (United States)

    Shtrahman, Matthew; Aharoni, Daniel B; Hardy, Nicholas F; Buonomano, Dean V; Arisaka, Katsushi; Otis, Thomas S

    2015-02-03

    In recent years, optical sensors for tracking neural activity have been developed and offer great utility. However, developing microscopy techniques that have several kHz bandwidth necessary to reliably capture optically reported action potentials (APs) at multiple locations in parallel remains a significant challenge. To our knowledge, we describe a novel microscope optimized to measure spatially distributed optical signals with submillisecond and near diffraction-limit resolution. Our design uses a spatial light modulator to generate patterned illumination to simultaneously excite multiple user-defined targets. A galvanometer driven mirror in the emission path streaks the fluorescence emanating from each excitation point during the camera exposure, using unused camera pixels to capture time varying fluorescence at rates that are ∼1000 times faster than the camera's native frame rate. We demonstrate that this approach is capable of recording Ca(2+) transients resulting from APs in neurons labeled with the Ca(2+) sensor Oregon Green Bapta-1 (OGB-1), and can localize the timing of these events with millisecond resolution. Furthermore, optically reported APs can be detected with the voltage sensitive dye DiO-DPA in multiple locations within a neuron with a signal/noise ratio up to ∼40, resolving delays in arrival time along dendrites. Thus, the microscope provides a powerful tool for photometric measurements of dynamics requiring submillisecond sampling at multiple locations. Copyright © 2015 Biophysical Society. Published by Elsevier Inc. All rights reserved.

  19. Polymer SU-8 Based Microprobes for Neural Recording and Drug Delivery

    Science.gov (United States)

    Altuna, Ane; Fernandez, Luis; Berganzo, Javier

    2015-06-01

    This manuscript makes a reflection about SU-8 based microprobes for neural activity recording and drug delivery. By taking advantage of improvements in microfabrication technologies and using polymer SU-8 as the only structural material, we developed several microprobe prototypes aimed to: a) minimize injury in neural tissue, b) obtain high-quality electrical signals and c) deliver drugs at a micrometer precision scale. Dedicated packaging tools have been developed in parallel to fulfill requirements concerning electric and fluidic connections, size and handling. After these advances have been experimentally proven in brain using in vivo preparation, the technological concepts developed during consecutive prototypes are discussed in depth now.

  20. POLYMER SU-8 BASED MICROPROBES FOR NEURAL RECORDING AND DRUG DELIVERY

    Directory of Open Access Journals (Sweden)

    Ane eAltuna

    2015-06-01

    Full Text Available This manuscript makes a reflection about SU-8 based microprobes for neural activity recording and drug delivery. By taking advantage of improvements in microfabrication technologies and using polymer SU-8 as the only structural material, we developed several microprobe prototypes aimed to: a minimize injury in neural tissue, b obtain high-quality electrical signals and c deliver drugs at a micrometer precision scale. Dedicated packaging tools have been developed in parallel to fulfill requirements concerning electric and fluidic connections, size and handling. After these advances have been experimentally proven in brain using in vivo preparation, the technological concepts developed during consecutive prototypes are discussed in depth now.

  1. Reactively sputtered TeOx optical recording media

    International Nuclear Information System (INIS)

    Di Giulio, M.; Manno, D.; Micocci, G.; Rella, R.; Rizzo, A.; Tepore, A.

    1987-01-01

    Telluriom suboxide (TeO x ) thin films have been obtained by R.F. reactive sputtering deposition by using a Te target and an Ar-O 2 gas mixture. This technique of preparation has been shown to be a valid method because it is possible to easily obtain films with desired characteristics by an appropriate selection of the deposition conditions. Different samples were prepared by changing both the R.F. power (80-300 Watt) and the oxygen concentration in the sputtering gas. The films were analyzed in order to study their optical characteristics and the morphology before and after heat treatment. In particular, transmissivity and reflectivity have been found to change markedly by thermal treatment and critical temperatures in the range 120-150 grades centigrade. This property makes these films suitable for optical recording with a low output power laser diode

  2. Construction of implantable optical fibers for long-term optogenetic manipulation of neural circuits.

    Science.gov (United States)

    Sparta, Dennis R; Stamatakis, Alice M; Phillips, Jana L; Hovelsø, Nanna; van Zessen, Ruud; Stuber, Garret D

    2011-12-08

    In vivo optogenetic strategies have redefined our ability to assay how neural circuits govern behavior. Although acutely implanted optical fibers have previously been used in such studies, long-term control over neuronal activity has been largely unachievable. Here we describe a method to construct implantable optical fibers to readily manipulate neural circuit elements with minimal tissue damage or change in light output over time (weeks to months). Implanted optical fibers readily interface with in vivo electrophysiological arrays or electrochemical detection electrodes. The procedure described here, from implant construction to the start of behavioral experimentation, can be completed in approximately 2-6 weeks. Successful use of implantable optical fibers will allow for long-term control of mammalian neural circuits in vivo, which is integral to the study of the neurobiology of behavior.

  3. An Implantable Wireless Neural Interface System for Simultaneous Recording and Stimulation of Peripheral Nerve with a Single Cuff Electrode.

    Science.gov (United States)

    Shon, Ahnsei; Chu, Jun-Uk; Jung, Jiuk; Kim, Hyungmin; Youn, Inchan

    2017-12-21

    Recently, implantable devices have become widely used in neural prostheses because they eliminate endemic drawbacks of conventional percutaneous neural interface systems. However, there are still several issues to be considered: low-efficiency wireless power transmission; wireless data communication over restricted operating distance with high power consumption; and limited functionality, working either as a neural signal recorder or as a stimulator. To overcome these issues, we suggest a novel implantable wireless neural interface system for simultaneous neural signal recording and stimulation using a single cuff electrode. By using widely available commercial off-the-shelf (COTS) components, an easily reconfigurable implantable wireless neural interface system was implemented into one compact module. The implantable device includes a wireless power consortium (WPC)-compliant power transmission circuit, a medical implant communication service (MICS)-band-based radio link and a cuff-electrode path controller for simultaneous neural signal recording and stimulation. During in vivo experiments with rabbit models, the implantable device successfully recorded and stimulated the tibial and peroneal nerves while communicating with the external device. The proposed system can be modified for various implantable medical devices, especially such as closed-loop control based implantable neural prostheses requiring neural signal recording and stimulation at the same time.

  4. An Implantable Wireless Neural Interface System for Simultaneous Recording and Stimulation of Peripheral Nerve with a Single Cuff Electrode

    Directory of Open Access Journals (Sweden)

    Ahnsei Shon

    2017-12-01

    Full Text Available Recently, implantable devices have become widely used in neural prostheses because they eliminate endemic drawbacks of conventional percutaneous neural interface systems. However, there are still several issues to be considered: low-efficiency wireless power transmission; wireless data communication over restricted operating distance with high power consumption; and limited functionality, working either as a neural signal recorder or as a stimulator. To overcome these issues, we suggest a novel implantable wireless neural interface system for simultaneous neural signal recording and stimulation using a single cuff electrode. By using widely available commercial off-the-shelf (COTS components, an easily reconfigurable implantable wireless neural interface system was implemented into one compact module. The implantable device includes a wireless power consortium (WPC-compliant power transmission circuit, a medical implant communication service (MICS-band-based radio link and a cuff-electrode path controller for simultaneous neural signal recording and stimulation. During in vivo experiments with rabbit models, the implantable device successfully recorded and stimulated the tibial and peroneal nerves while communicating with the external device. The proposed system can be modified for various implantable medical devices, especially such as closed-loop control based implantable neural prostheses requiring neural signal recording and stimulation at the same time.

  5. The 128-channel fully differential digital integrated neural recording and stimulation interface.

    Science.gov (United States)

    Shahrokhi, Farzaneh; Abdelhalim, Karim; Serletis, Demitre; Carlen, Peter L; Genov, Roman

    2010-06-01

    We present a fully differential 128-channel integrated neural interface. It consists of an array of 8 X 16 low-power low-noise signal-recording and generation circuits for electrical neural activity monitoring and stimulation, respectively. The recording channel has two stages of signal amplification and conditioning with and a fully differential 8-b column-parallel successive approximation (SAR) analog-to-digital converter (ADC). The total measured power consumption of each recording channel, including the SAR ADC, is 15.5 ¿W. The measured input-referred noise is 6.08 ¿ Vrms over a 5-kHz bandwidth, resulting in a noise efficiency factor of 5.6. The stimulation channel performs monophasic or biphasic voltage-mode stimulation, with a maximum stimulation current of 5 mA and a quiescent power dissipation of 51.5 ¿W. The design is implemented in 0.35-¿m complementary metal-oxide semiconductor technology with the channel pitch of 200 ¿m for a total die size of 3.4 mm × 2.5 mm and a total power consumption of 9.33 mW. The neural interface was validated in in vitro recording of a low-Mg(2+)/high-K(+) epileptic seizure model in an intact hippocampus of a mouse.

  6. Clinical Assistant Diagnosis for Electronic Medical Record Based on Convolutional Neural Network.

    Science.gov (United States)

    Yang, Zhongliang; Huang, Yongfeng; Jiang, Yiran; Sun, Yuxi; Zhang, Yu-Jin; Luo, Pengcheng

    2018-04-20

    Automatically extracting useful information from electronic medical records along with conducting disease diagnoses is a promising task for both clinical decision support(CDS) and neural language processing(NLP). Most of the existing systems are based on artificially constructed knowledge bases, and then auxiliary diagnosis is done by rule matching. In this study, we present a clinical intelligent decision approach based on Convolutional Neural Networks(CNN), which can automatically extract high-level semantic information of electronic medical records and then perform automatic diagnosis without artificial construction of rules or knowledge bases. We use collected 18,590 copies of the real-world clinical electronic medical records to train and test the proposed model. Experimental results show that the proposed model can achieve 98.67% accuracy and 96.02% recall, which strongly supports that using convolutional neural network to automatically learn high-level semantic features of electronic medical records and then conduct assist diagnosis is feasible and effective.

  7. Simultaneous in vivo recording of local brain temperature and electrophysiological signals with a novel neural probe

    Science.gov (United States)

    Fekete, Z.; Csernai, M.; Kocsis, K.; Horváth, Á. C.; Pongrácz, A.; Barthó, P.

    2017-06-01

    Objective. Temperature is an important factor for neural function both in normal and pathological states, nevertheless, simultaneous monitoring of local brain temperature and neuronal activity has not yet been undertaken. Approach. In our work, we propose an implantable, calibrated multimodal biosensor that facilitates the complex investigation of thermal changes in both cortical and deep brain regions, which records multiunit activity of neuronal populations in mice. The fabricated neural probe contains four electrical recording sites and a platinum temperature sensor filament integrated on the same probe shaft within a distance of 30 µm from the closest recording site. The feasibility of the simultaneous functionality is presented in in vivo studies. The probe was tested in the thalamus of anesthetized mice while manipulating the core temperature of the animals. Main results. We obtained multiunit and local field recordings along with measurement of local brain temperature with accuracy of 0.14 °C. Brain temperature generally followed core body temperature, but also showed superimposed fluctuations corresponding to epochs of increased local neural activity. With the application of higher currents, we increased the local temperature by several degrees without observable tissue damage between 34-39 °C. Significance. The proposed multifunctional tool is envisioned to broaden our knowledge on the role of the thermal modulation of neuronal activity in both cortical and deeper brain regions.

  8. The development of a PZT-based microdrive for neural signal recording

    International Nuclear Information System (INIS)

    Park, Sangkyu; Yoon, Euisung; Park, Sukho; Lee, Sukchan; Shin, Hee-sup; Park, Hyunjun; Kim, Byungkyu; Kim, Daesoo; Park, Jongoh

    2008-01-01

    A hand-controlled microdrive has been used to obtain neural signals from rodents such as rats and mice. However, it places severe physical stress on the rodents during its manipulation, and this stress leads to alertness in the mice and low efficiency in obtaining neural signals from the mice. To overcome this issue, we developed a novel microdrive, which allows one to adjust the electrodes by a piezoelectric device (PZT) with high precision. Its mass is light enough to install on the mouse's head. The proposed microdrive has three H-type PZT actuators and their guiding structure. The operation principle of the microdrive is based on the well known inchworm mechanism. When the three PZT actuators are synchronized, linear motion of the electrode is produced along the guiding structure. The electrodes used for the recording of the neural signals from neuron cells were fixed at one of the PZT actuators. Our proposed microdrive has an accuracy of about 400 nm and a long stroke of about 5 mm. In response to formalin-induced pain, single unit activities are robustly measured at the thalamus with electrodes whose vertical depth is adjusted by the microdrive under urethane anesthesia. In addition, the microdrive was efficient in detecting neural signals from mice that were moving freely. Thus, the present study suggests that the PZT-based microdrive could be an alternative for the efficient detection of neural signals from mice during behavioral states without any stress to the mice. (technical note)

  9. Dynamics of Stability of Orientation Maps Recorded with Optical Imaging.

    Science.gov (United States)

    Shumikhina, S I; Bondar, I V; Svinov, M M

    2018-03-15

    Orientation selectivity is an important feature of visual cortical neurons. Optical imaging of the visual cortex allows for the generation of maps of orientation selectivity that reflect the activity of large populations of neurons. To estimate the statistical significance of effects of experimental manipulations, evaluation of the stability of cortical maps over time is required. Here, we performed optical imaging recordings of the visual cortex of anesthetized adult cats. Monocular stimulation with moving clockwise square-wave gratings that continuously changed orientation and direction was used as the mapping stimulus. Recordings were repeated at various time intervals, from 15 min to 16 h. Quantification of map stability was performed on a pixel-by-pixel basis using several techniques. Map reproducibility showed clear dynamics over time. The highest degree of stability was seen in maps recorded 15-45 min apart. Averaging across all time intervals and all stimulus orientations revealed a mean shift of 2.2 ± 0.1°. There was a significant tendency for larger shifts to occur at longer time intervals. Shifts between 2.8° (mean ± 2SD) and 5° were observed more frequently at oblique orientations, while shifts greater than 5° appeared more frequently at cardinal orientations. Shifts greater than 5° occurred rarely overall (5.4% of cases) and never exceeded 11°. Shifts of 10-10.6° (0.7%) were seen occasionally at time intervals of more than 4 h. Our findings should be considered when evaluating the potential effect of experimental manipulations on orientation selectivity mapping studies. Copyright © 2018 IBRO. Published by Elsevier Ltd. All rights reserved.

  10. Simultaneous neural and movement recording in large-scale immersive virtual environments.

    Science.gov (United States)

    Snider, Joseph; Plank, Markus; Lee, Dongpyo; Poizner, Howard

    2013-10-01

    Virtual reality (VR) allows precise control and manipulation of rich, dynamic stimuli that, when coupled with on-line motion capture and neural monitoring, can provide a powerful means both of understanding brain behavioral relations in the high dimensional world and of assessing and treating a variety of neural disorders. Here we present a system that combines state-of-the-art, fully immersive, 3D, multi-modal VR with temporally aligned electroencephalographic (EEG) recordings. The VR system is dynamic and interactive across visual, auditory, and haptic interactions, providing sight, sound, touch, and force. Crucially, it does so with simultaneous EEG recordings while subjects actively move about a 20 × 20 ft² space. The overall end-to-end latency between real movement and its simulated movement in the VR is approximately 40 ms. Spatial precision of the various devices is on the order of millimeters. The temporal alignment with the neural recordings is accurate to within approximately 1 ms. This powerful combination of systems opens up a new window into brain-behavioral relations and a new means of assessment and rehabilitation of individuals with motor and other disorders.

  11. Segmentation of Drosophila Heart in Optical Coherence Microscopy Images Using Convolutional Neural Networks

    OpenAIRE

    Duan, Lian; Qin, Xi; He, Yuanhao; Sang, Xialin; Pan, Jinda; Xu, Tao; Men, Jing; Tanzi, Rudolph E.; Li, Airong; Ma, Yutao; Zhou, Chao

    2018-01-01

    Convolutional neural networks are powerful tools for image segmentation and classification. Here, we use this method to identify and mark the heart region of Drosophila at different developmental stages in the cross-sectional images acquired by a custom optical coherence microscopy (OCM) system. With our well-trained convolutional neural network model, the heart regions through multiple heartbeat cycles can be marked with an intersection over union (IOU) of ~86%. Various morphological and dyn...

  12. Holographic Optical Elements Recorded in Silver Halide Sensitized Gelatin Emulsions. Part I. Transmission Holographic Optical Elements

    Science.gov (United States)

    Kim, Jong Man; Choi, Byung So; Kim, Sun Il; Kim, Jong Min; Bjelkhagen, Hans I.; Phillips, Nicholas J.

    2001-02-01

    Silver halide sensitized gelatin (SHSG) holograms are similar to holograms recorded in dichromated gelatin (DCG), the main recording material for holographic optical elements (HOE s). The drawback of DCG is its low sensitivity and limited spectral response. Silver halide materials can be processed in such a way that the final hologram will have properties like a DCG hologram. Recently this technique has become more interesting since the introduction of new ultra-high-resolution silver halide emulsions. An optimized processing technique for transmission HOE s recorded in these materials is introduced. Diffraction efficiencies over 90% can be obtained for transmissive diffraction gratings. Understanding the importance of the selective hardening process has made it possible to obtain results similar to conventional DCG processing. The main advantage of the SHSG process is that high-sensitivity recording can be performed with laser wavelengths anywhere within the visible spectrum. This simplifies the manufacturing of high-quality, large-format HOE s.

  13. Poly(3,4-ethylenedioxythiophene) (PEDOT) polymer coatings facilitate smaller neural recording electrodes

    Science.gov (United States)

    Ludwig, Kip A.; Langhals, Nicholas B.; Joseph, Mike D.; Richardson-Burns, Sarah M.; Hendricks, Jeffrey L.; Kipke, Daryl R.

    2011-02-01

    We investigated using poly(3,4-ethylenedioxythiophene) (PEDOT) to lower the impedance of small, gold recording electrodes with initial impedances outside of the effective recording range. Smaller electrode sites enable more densely packed arrays, increasing the number of input and output channels to and from the brain. Moreover, smaller electrode sizes promote smaller probe designs; decreasing the dimensions of the implanted probe has been demonstrated to decrease the inherent immune response, a known contributor to the failure of long-term implants. As expected, chronically implanted control electrodes were unable to record well-isolated unit activity, primarily as a result of a dramatically increased noise floor. Conversely, electrodes coated with PEDOT consistently recorded high-quality neural activity, and exhibited a much lower noise floor than controls. These results demonstrate that PEDOT coatings enable electrode designs 15 µm in diameter.

  14. Physiological Parameter Monitoring from Optical Recordings with a Mobile Phone

    Science.gov (United States)

    Scully, Christopher G.; Lee, Jinseok; Meyer, Joseph; Gorbach, Alexander M.; Granquist-Fraser, Domhnull; Mendelson, Yitzhak

    2012-01-01

    We show that a mobile phone can serve as an accurate monitor for several physiological variables, based on its ability to record and analyze the varying color signals of a fingertip placed in contact with its optical sensor. We confirm the accuracy of measurements of breathing rate, cardiac R-R intervals, and blood oxygen saturation, by comparisons to standard methods for making such measurements (respiration belts, ECGs, and pulse-oximeters, respectively). Measurement of respiratory rate uses a previously reported algorithm developed for use with a pulse-oximeter, based on amplitude and frequency modulation sequences within the light signal. We note that this technology can also be used with recently developed algorithms for detection of atrial fibrillation or blood loss. PMID:21803676

  15. Optical waveguides with memory effect using photochromic material for neural network

    Science.gov (United States)

    Tanimoto, Keisuke; Amemiya, Yoshiteru; Yokoyama, Shin

    2018-04-01

    An optical neural network using a waveguide with a memory effect, a photodiode, CMOS circuits and LEDs was proposed. To realize the neural network, optical waveguides with a memory effect were fabricated using a cladding layer containing the photochromic material “diarylethene”. The transmittance of green light was decreased by UV light irradiation and recovered by the passage of green light through the waveguide. It was confirmed that the transmittance versus total energy of the green light that passed through the waveguide well fit the universal exponential curve.

  16. Reorganization of neural systems mediating peripheral visual selective attention in the deaf: An optical imaging study.

    Science.gov (United States)

    Seymour, Jenessa L; Low, Kathy A; Maclin, Edward L; Chiarelli, Antonio M; Mathewson, Kyle E; Fabiani, Monica; Gratton, Gabriele; Dye, Matthew W G

    2017-01-01

    Theories of brain plasticity propose that, in the absence of input from the preferred sensory modality, some specialized brain areas may be recruited when processing information from other modalities, which may result in improved performance. The Useful Field of View task has previously been used to demonstrate that early deafness positively impacts peripheral visual attention. The current study sought to determine the neural changes associated with those deafness-related enhancements in visual performance. Based on previous findings, we hypothesized that recruitment of posterior portions of Brodmann area 22, a brain region most commonly associated with auditory processing, would be correlated with peripheral selective attention as measured using the Useful Field of View task. We report data from severe to profoundly deaf adults and normal-hearing controls who performed the Useful Field of View task while cortical activity was recorded using the event-related optical signal. Behavioral performance, obtained in a separate session, showed that deaf subjects had lower thresholds (i.e., better performance) on the Useful Field of View task. The event-related optical data indicated greater activity for the deaf adults than for the normal-hearing controls during the task in the posterior portion of Brodmann area 22 in the right hemisphere. Furthermore, the behavioral thresholds correlated significantly with this neural activity. This work provides further support for the hypothesis that cross-modal plasticity in deaf individuals appears in higher-order auditory cortices, whereas no similar evidence was obtained for primary auditory areas. It is also the only neuroimaging study to date that has linked deaf-related changes in the right temporal lobe to visual task performance outside of the imaging environment. The event-related optical signal is a valuable technique for studying cross-modal plasticity in deaf humans. The non-invasive and relatively quiet characteristics of

  17. An implantable wireless neural interface for recording cortical circuit dynamics in moving primates

    Science.gov (United States)

    Borton, David A.; Yin, Ming; Aceros, Juan; Nurmikko, Arto

    2013-04-01

    Objective. Neural interface technology suitable for clinical translation has the potential to significantly impact the lives of amputees, spinal cord injury victims and those living with severe neuromotor disease. Such systems must be chronically safe, durable and effective. Approach. We have designed and implemented a neural interface microsystem, housed in a compact, subcutaneous and hermetically sealed titanium enclosure. The implanted device interfaces the brain with a 510k-approved, 100-element silicon-based microelectrode array via a custom hermetic feedthrough design. Full spectrum neural signals were amplified (0.1 Hz to 7.8 kHz, 200× gain) and multiplexed by a custom application specific integrated circuit, digitized and then packaged for transmission. The neural data (24 Mbps) were transmitted by a wireless data link carried on a frequency-shift-key-modulated signal at 3.2 and 3.8 GHz to a receiver 1 m away by design as a point-to-point communication link for human clinical use. The system was powered by an embedded medical grade rechargeable Li-ion battery for 7 h continuous operation between recharge via an inductive transcutaneous wireless power link at 2 MHz. Main results. Device verification and early validation were performed in both swine and non-human primate freely-moving animal models and showed that the wireless implant was electrically stable, effective in capturing and delivering broadband neural data, and safe for over one year of testing. In addition, we have used the multichannel data from these mobile animal models to demonstrate the ability to decode neural population dynamics associated with motor activity. Significance. We have developed an implanted wireless broadband neural recording device evaluated in non-human primate and swine. The use of this new implantable neural interface technology can provide insight into how to advance human neuroprostheses beyond the present early clinical trials. Further, such tools enable mobile

  18. Automated target recognition and tracking using an optical pattern recognition neural network

    Science.gov (United States)

    Chao, Tien-Hsin

    1991-01-01

    The on-going development of an automatic target recognition and tracking system at the Jet Propulsion Laboratory is presented. This system is an optical pattern recognition neural network (OPRNN) that is an integration of an innovative optical parallel processor and a feature extraction based neural net training algorithm. The parallel optical processor provides high speed and vast parallelism as well as full shift invariance. The neural network algorithm enables simultaneous discrimination of multiple noisy targets in spite of their scales, rotations, perspectives, and various deformations. This fully developed OPRNN system can be effectively utilized for the automated spacecraft recognition and tracking that will lead to success in the Automated Rendezvous and Capture (AR&C) of the unmanned Cargo Transfer Vehicle (CTV). One of the most powerful optical parallel processors for automatic target recognition is the multichannel correlator. With the inherent advantages of parallel processing capability and shift invariance, multiple objects can be simultaneously recognized and tracked using this multichannel correlator. This target tracking capability can be greatly enhanced by utilizing a powerful feature extraction based neural network training algorithm such as the neocognitron. The OPRNN, currently under investigation at JPL, is constructed with an optical multichannel correlator where holographic filters have been prepared using the neocognitron training algorithm. The computation speed of the neocognitron-type OPRNN is up to 10(exp 14) analog connections/sec that enabling the OPRNN to outperform its state-of-the-art electronics counterpart by at least two orders of magnitude.

  19. Toward a distributed free-floating wireless implantable neural recording system.

    Science.gov (United States)

    Pyungwoo Yeon; Xingyuan Tong; Byunghun Lee; Mirbozorgi, Abdollah; Ash, Bruce; Eckhardt, Helmut; Ghovanloo, Maysam

    2016-08-01

    To understand the complex correlations between neural networks across different regions in the brain and their functions at high spatiotemporal resolution, a tool is needed for obtaining long-term single unit activity (SUA) across the entire brain area. The concept and preliminary design of a distributed free-floating wireless implantable neural recording (FF-WINeR) system are presented, which can enabling SUA acquisition by dispersedly implanting tens to hundreds of untethered 1 mm3 neural recording probes, floating with the brain and operating wirelessly across the cortical surface. For powering FF-WINeR probes, a 3-coil link with an intermediate high-Q resonator provides a minimum S21 of -22.22 dB (in the body medium) and -21.23 dB (in air) at 2.8 cm coil separation, which translates to 0.76%/759 μW and 0.6%/604 μW of power transfer efficiency (PTE) / power delivered to a 9 kΩ load (PDL), in body and air, respectively. A mock-up FF-WINeR is implemented to explore microassembly method of the 1×1 mm2 micromachined silicon die with a bonding wire-wound coil and a tungsten micro-wire electrode. Circuit design methods to fit the active circuitry in only 0.96 mm2 of die area in a 130 nm standard CMOS process, and satisfy the strict power and performance requirements (in simulations) are discussed.

  20. Optical implementation of neural learning algorithms based on cross-gain modulation in a semiconductor optical amplifier

    Science.gov (United States)

    Li, Qiang; Wang, Zhi; Le, Yansi; Sun, Chonghui; Song, Xiaojia; Wu, Chongqing

    2016-10-01

    Neuromorphic engineering has a wide range of applications in the fields of machine learning, pattern recognition, adaptive control, etc. Photonics, characterized by its high speed, wide bandwidth, low power consumption and massive parallelism, is an ideal way to realize ultrafast spiking neural networks (SNNs). Synaptic plasticity is believed to be critical for learning, memory and development in neural circuits. Experimental results have shown that changes of synapse are highly dependent on the relative timing of pre- and postsynaptic spikes. Synaptic plasticity in which presynaptic spikes preceding postsynaptic spikes results in strengthening, while the opposite timing results in weakening is called antisymmetric spike-timing-dependent plasticity (STDP) learning rule. And synaptic plasticity has the opposite effect under the same conditions is called antisymmetric anti-STDP learning rule. We proposed and experimentally demonstrated an optical implementation of neural learning algorithms, which can achieve both of antisymmetric STDP and anti-STDP learning rule, based on the cross-gain modulation (XGM) within a single semiconductor optical amplifier (SOA). The weight and height of the potentitation and depression window can be controlled by adjusting the injection current of the SOA, to mimic the biological antisymmetric STDP and anti-STDP learning rule more realistically. As the injection current increases, the width of depression and potentitation window decreases and height increases, due to the decreasing of recovery time and increasing of gain under a stronger injection current. Based on the demonstrated optical STDP circuit, ultrafast learning in optical SNNs can be realized.

  1. Differential Covariance: A New Class of Methods to Estimate Sparse Connectivity from Neural Recordings.

    Science.gov (United States)

    Lin, Tiger W; Das, Anup; Krishnan, Giri P; Bazhenov, Maxim; Sejnowski, Terrence J

    2017-10-01

    With our ability to record more neurons simultaneously, making sense of these data is a challenge. Functional connectivity is one popular way to study the relationship of multiple neural signals. Correlation-based methods are a set of currently well-used techniques for functional connectivity estimation. However, due to explaining away and unobserved common inputs (Stevenson, Rebesco, Miller, & Körding, 2008 ), they produce spurious connections. The general linear model (GLM), which models spike trains as Poisson processes (Okatan, Wilson, & Brown, 2005 ; Truccolo, Eden, Fellows, Donoghue, & Brown, 2005 ; Pillow et al., 2008 ), avoids these confounds. We develop here a new class of methods by using differential signals based on simulated intracellular voltage recordings. It is equivalent to a regularized AR(2) model. We also expand the method to simulated local field potential recordings and calcium imaging. In all of our simulated data, the differential covariance-based methods achieved performance better than or similar to the GLM method and required fewer data samples. This new class of methods provides alternative ways to analyze neural signals.

  2. Differential Covariance: A New Class of Methods to Estimate Sparse Connectivity from Neural Recordings

    Science.gov (United States)

    Lin, Tiger W.; Das, Anup; Krishnan, Giri P.; Bazhenov, Maxim; Sejnowski, Terrence J.

    2017-01-01

    With our ability to record more neurons simultaneously, making sense of these data is a challenge. Functional connectivity is one popular way to study the relationship of multiple neural signals. Correlation-based methods are a set of currently well-used techniques for functional connectivity estimation. However, due to explaining away and unobserved common inputs (Stevenson, Rebesco, Miller, & Körding, 2008), they produce spurious connections. The general linear model (GLM), which models spike trains as Poisson processes (Okatan, Wilson, & Brown, 2005; Truccolo, Eden, Fellows, Donoghue, & Brown, 2005; Pillow et al., 2008), avoids these confounds. We develop here a new class of methods by using differential signals based on simulated intracellular voltage recordings. It is equivalent to a regularized AR(2) model. We also expand the method to simulated local field potential recordings and calcium imaging. In all of our simulated data, the differential covariance-based methods achieved performance better than or similar to the GLM method and required fewer data samples. This new class of methods provides alternative ways to analyze neural signals. PMID:28777719

  3. Compact holographic optical neural network system for real-time pattern recognition

    Science.gov (United States)

    Lu, Taiwei; Mintzer, David T.; Kostrzewski, Andrew A.; Lin, Freddie S.

    1996-08-01

    One of the important characteristics of artificial neural networks is their capability for massive interconnection and parallel processing. Recently, specialized electronic neural network processors and VLSI neural chips have been introduced in the commercial market. The number of parallel channels they can handle is limited because of the limited parallel interconnections that can be implemented with 1D electronic wires. High-resolution pattern recognition problems can require a large number of neurons for parallel processing of an image. This paper describes a holographic optical neural network (HONN) that is based on high- resolution volume holographic materials and is capable of performing massive 3D parallel interconnection of tens of thousands of neurons. A HONN with more than 16,000 neurons packaged in an attache case has been developed. Rotation- shift-scale-invariant pattern recognition operations have been demonstrated with this system. System parameters such as the signal-to-noise ratio, dynamic range, and processing speed are discussed.

  4. Neural Network for Image-to-Image Control of Optical Tweezers

    Science.gov (United States)

    Decker, Arthur J.; Anderson, Robert C.; Weiland, Kenneth E.; Wrbanek, Susan Y.

    2004-01-01

    A method is discussed for using neural networks to control optical tweezers. Neural-net outputs are combined with scaling and tiling to generate 480 by 480-pixel control patterns for a spatial light modulator (SLM). The SLM can be combined in various ways with a microscope to create movable tweezers traps with controllable profiles. The neural nets are intended to respond to scattered light from carbon and silicon carbide nanotube sensors. The nanotube sensors are to be held by the traps for manipulation and calibration. Scaling and tiling allow the 100 by 100-pixel maximum resolution of the neural-net software to be applied in stages to exploit the full 480 by 480-pixel resolution of the SLM. One of these stages is intended to create sensitive null detectors for detecting variations in the scattered light from the nanotube sensors.

  5. Connectivity inference from neural recording data: Challenges, mathematical bases and research directions.

    Science.gov (United States)

    Magrans de Abril, Ildefons; Yoshimoto, Junichiro; Doya, Kenji

    2018-06-01

    This article presents a review of computational methods for connectivity inference from neural activity data derived from multi-electrode recordings or fluorescence imaging. We first identify biophysical and technical challenges in connectivity inference along the data processing pipeline. We then review connectivity inference methods based on two major mathematical foundations, namely, descriptive model-free approaches and generative model-based approaches. We investigate representative studies in both categories and clarify which challenges have been addressed by which method. We further identify critical open issues and possible research directions. Copyright © 2018 The Author(s). Published by Elsevier Ltd.. All rights reserved.

  6. An Integrated Circuit for Simultaneous Extracellular Electrophysiology Recording and Optogenetic Neural Manipulation.

    Science.gov (United States)

    Chen, Chang Hao; McCullagh, Elizabeth A; Pun, Sio Hang; Mak, Peng Un; Vai, Mang I; Mak, Pui In; Klug, Achim; Lei, Tim C

    2017-03-01

    The ability to record and to control action potential firing in neuronal circuits is critical to understand how the brain functions. The objective of this study is to develop a monolithic integrated circuit (IC) to record action potentials and simultaneously control action potential firing using optogenetics. A low-noise and high input impedance (or low input capacitance) neural recording amplifier is combined with a high current laser/light-emitting diode (LED) driver in a single IC. The low input capacitance of the amplifier (9.7 pF) was achieved by adding a dedicated unity gain stage optimized for high impedance metal electrodes. The input referred noise of the amplifier is [Formula: see text], which is lower than the estimated thermal noise of the metal electrode. Thus, the action potentials originating from a single neuron can be recorded with a signal-to-noise ratio of at least 6.6. The LED/laser current driver delivers a maximum current of 330 mA, which is adequate for optogenetic control. The functionality of the IC was tested with an anesthetized Mongolian gerbil and auditory stimulated action potentials were recorded from the inferior colliculus. Spontaneous firings of fifth (trigeminal) nerve fibers were also inhibited using the optogenetic protein Halorhodopsin. Moreover, a noise model of the system was derived to guide the design. A single IC to measure and control action potentials using optogenetic proteins is realized so that more complicated behavioral neuroscience research and the translational neural disorder treatments become possible in the future.

  7. A neural network based approach for determination of optical scattering and absorption coefficients of biological tissue

    International Nuclear Information System (INIS)

    Warncke, D; Lewis, E; Leahy, M; Lochmann, S

    2009-01-01

    The propagation of light in biological tissue depends on the absorption and reduced scattering coefficient. The aim of this project is the determination of these two optical properties using spatially resolved reflectance measurements. The sensor system consists of five laser sources at different wavelengths, an optical fibre probe and five photodiodes. For these kinds of measurements it has been shown that an often used solution of the diffusion equation can not be applied. Therefore a neural network is being developed to extract the needed optical properties out of the reflectance data. Data sets for the training, validation and testing process are provided by Monte Carlo Simulations.

  8. Use of neural network based auto-associative memory as a data compressor for pre-processing optical emission spectra in gas thermometry with the help of neural network

    International Nuclear Information System (INIS)

    Dolenko, S.A.; Filippov, A.V.; Pal, A.F.; Persiantsev, I.G.; Serov, A.O.

    2003-01-01

    Determination of temperature from optical emission spectra is an inverse problem that is often very difficult to solve, especially when substantial noise is present. One of the means that can be used to solve such a problem is a neural network trained on the results of modeling of spectra at different temperatures (Dolenko, et al., in: I.C. Parmee (Ed.), Adaptive Computing in Design and Manufacture, Springer, London, 1998, p. 345). Reducing the dimensionality of the input data prior to application of neural network can increase the accuracy and stability of temperature determination. In this study, such pre-processing is performed with another neural network working as an auto-associative memory with a narrow bottleneck in the hidden layer. The improvement in the accuracy and stability of temperature determination in presence of noise is demonstrated on model spectra similar to those recorded in a DC-discharge CVD reactor

  9. The DSFPN, a new neural network for optical character recognition.

    Science.gov (United States)

    Morns, L P; Dlay, S S

    1999-01-01

    A new type of neural network for recognition tasks is presented in this paper. The network, called the dynamic supervised forward-propagation network (DSFPN), is based on the forward only version of the counterpropagation network (CPN). The DSFPN, trains using a supervised algorithm and can grow dynamically during training, allowing subclasses in the training data to be learnt in an unsupervised manner. It is shown to train in times comparable to the CPN while giving better classification accuracies than the popular backpropagation network. Both Fourier descriptors and wavelet descriptors are used for image preprocessing and the wavelets are proven to give a far better performance.

  10. Comparative Study of Neural Network Frameworks for the Next Generation of Adaptive Optics Systems.

    Science.gov (United States)

    González-Gutiérrez, Carlos; Santos, Jesús Daniel; Martínez-Zarzuela, Mario; Basden, Alistair G; Osborn, James; Díaz-Pernas, Francisco Javier; De Cos Juez, Francisco Javier

    2017-06-02

    Many of the next generation of adaptive optics systems on large and extremely large telescopes require tomographic techniques in order to correct for atmospheric turbulence over a large field of view. Multi-object adaptive optics is one such technique. In this paper, different implementations of a tomographic reconstructor based on a machine learning architecture named "CARMEN" are presented. Basic concepts of adaptive optics are introduced first, with a short explanation of three different control systems used on real telescopes and the sensors utilised. The operation of the reconstructor, along with the three neural network frameworks used, and the developed CUDA code are detailed. Changes to the size of the reconstructor influence the training and execution time of the neural network. The native CUDA code turns out to be the best choice for all the systems, although some of the other frameworks offer good performance under certain circumstances.

  11. A wireless recording system that utilizes Bluetooth technology to transmit neural activity in freely moving animals

    Science.gov (United States)

    Hampson, Robert E.; Collins, Vernell; Deadwyler, Sam A.

    2009-01-01

    A new wireless transceiver is described for recording individual neuron firing from behaving rats utilizing Bluetooth transmission technology and a processor onboard for discrimination of neuronal waveforms and associated time stamps. This universal brain activity transmitter (UBAT) is attached to rodents via a backpack and amplifier headstage and can transmit 16 channels of captured neuronal firing data via a Bluetooth transceiver chip over very large and unconstrained distances. The onboard microprocessor of the UBAT allows flexible online control over waveform isolation criteria via transceiver instruction and the two-way communication capacity allows for closed-loop applications between neural events and behavioral or physiological processes which can be modified by transceiver instructions. A detailed description of the multiplexer processing of channel data as well as examples of neuronal recordings in different behavioral testing contexts is provided to demonstrate the capacity for robust transmission within almost any laboratory environment. A major advantage of the UBAT is the long transmission range and lack of object-based line of sight interference afforded by Bluetooth technology, allowing flexible recording capabilities within multiple experimental paradigms without interruption. Continuous recordings over very large distance separations from the monitor station are demonstrated providing experimenters with recording advantages not previously available with other telemetry devices. PMID:19524612

  12. A wireless recording system that utilizes Bluetooth technology to transmit neural activity in freely moving animals.

    Science.gov (United States)

    Hampson, Robert E; Collins, Vernell; Deadwyler, Sam A

    2009-09-15

    A new wireless transceiver is described for recording individual neuron firing from behaving rats utilizing Bluetooth transmission technology and a processor onboard for discrimination of neuronal waveforms and associated time stamps. This universal brain activity transmitter (UBAT) is attached to rodents via a backpack and amplifier headstage and can transmit 16 channels of captured neuronal firing data via a Bluetooth transceiver chip over very large and unconstrained distances. The onboard microprocessor of the UBAT allows flexible online control over waveform isolation criteria via transceiver instruction and the two-way communication capacity allows for closed-loop applications between neural events and behavioral or physiological processes which can be modified by transceiver instructions. A detailed description of the multiplexer processing of channel data as well as examples of neuronal recordings in different behavioral testing contexts is provided to demonstrate the capacity for robust transmission within almost any laboratory environment. A major advantage of the UBAT is the long transmission range and lack of object-based line of sight interference afforded by Bluetooth technology, allowing flexible recording capabilities within multiple experimental paradigms without interruption. Continuous recordings over very large distance separations from the monitor station are demonstrated providing experimenters with recording advantages not previously available with other telemetry devices.

  13. Application of artificial neural networks for versatile preprocessing of electrocardiogram recordings.

    Science.gov (United States)

    Mateo, J; Rieta, J J

    2012-02-01

    The electrocardiogram (ECG) is the most widely used method for diagnosis of heart diseases, where a good quality of recordings allows the proper interpretation and identification of physiological and pathological phenomena. However, ECG recordings often have interference from noises including thermal, muscle, baseline and powerline noises. These signals severely limit ECG recording utility and, hence, have to be removed. To deal with this problem, the present paper proposes an artificial neural network (ANN) as a filter to remove all kinds of noise in just one step. The method is based on a growing ANN which optimizes both the number of nodes in the hidden layer and the coefficient matrices, which are optimized by means of the Widrow-Hoff delta algorithm. The ANN has been trained with a database comprising all kinds of noise, both from synthesized and real ECG recordings, in order to handle any noise signal present in the ECG. The proposed system improves results yielded by conventional techniques of ECG filtering, such as FIR-based systems, adaptive filtering and wavelet filtering. Therefore, the algorithm could serve as an effective framework to substantially reduce noise in ECG recordings. In addition, the resulting ECG signal distortion is notably more reduced in comparison with conventional methodologies. In summary, the current contribution introduces a new method which is able to suppress all ECG interference signals in only one step with low ECG distortion and a high noise reduction.

  14. Holographic Optical Elements Recorded in Silver Halide Sensitized Gelatin Emulsions. Part 2. Reflection Holographic Optical Elements

    Science.gov (United States)

    Kim, Jong Man; Choi, Byung So; Choi, Yoon Sun; Kim, Jong Min; Bjelkhagen, Hans I.; Phillips, Nicholas J.

    2002-03-01

    Silver halide sensitized gelatin (SHSG) holograms are similar to holograms recorded in dichromated gelatin (DCG), the main recording material for holographic optical elements (HOEs). The drawback of DCG is its low energetic sensitivity and limited spectral response. Silver halide materials can be processed in such a way that the final hologram will have properties like a DCG hologram. Recently this technique has become more interesting since the introduction of new ultra-fine-grain silver halide (AgHal) emulsions. In particular, high spatial-frequency fringes associated with HOEs of the reflection type are difficult to construct when SHSG processing methods are employed. Therefore an optimized processing technique for reflection HOEs recorded in the new AgHal materials is introduced. Diffraction efficiencies over 90% can be obtained repeatably for reflection diffraction gratings. Understanding the importance of a selective hardening process has made it possible to obtain results similar to conventional DCG processing. The main advantage of the SHSG process is that high-sensitivity recording can be performed with laser wavelengths anywhere within the visible spectrum. This simplifies the manufacturing of high-quality, large-format HOEs, also including high-quality display holograms of the reflection type in both monochrome and full color.

  15. Tracking Single Units in Chronic, Large Scale, Neural Recordings for Brain Machine Interface Applications

    Directory of Open Access Journals (Sweden)

    Ahmed eEleryan

    2014-07-01

    Full Text Available In the study of population coding in neurobiological systems, tracking unit identity may be critical to assess possible changes in the coding properties of neuronal constituents over prolonged periods of time. Ensuring unit stability is even more critical for reliable neural decoding of motor variables in intra-cortically controlled brain-machine interfaces (BMIs. Variability in intrinsic spike patterns, tuning characteristics, and single-unit identity over chronic use is a major challenge to maintaining this stability, requiring frequent daily calibration of neural decoders in BMI sessions by an experienced human operator. Here, we report on a unit-stability tracking algorithm that efficiently and autonomously identifies putative single-units that are stable across many sessions using a relatively short duration recording interval at the start of each session. The algorithm first builds a database of features extracted from units' average spike waveforms and firing patterns across many days of recording. It then uses these features to decide whether spike occurrences on the same channel on one day belong to the same unit recorded on another day or not. We assessed the overall performance of the algorithm for different choices of features and classifiers trained using human expert judgment, and quantified it as a function of accuracy and execution time. Overall, we found a trade-off between accuracy and execution time with increasing data volumes from chronically implanted rhesus macaques, with an average of 12 seconds processing time per channel at ~90% classification accuracy. Furthermore, 77% of the resulting putative single-units matched those tracked by human experts. These results demonstrate that over the span of a few months of recordings, automated unit tracking can be performed with high accuracy and used to streamline the calibration phase during BMI sessions.

  16. Assessing artificial neural networks and statistical methods for infilling missing soil moisture records

    Science.gov (United States)

    Dumedah, Gift; Walker, Jeffrey P.; Chik, Li

    2014-07-01

    Soil moisture information is critically important for water management operations including flood forecasting, drought monitoring, and groundwater recharge estimation. While an accurate and continuous record of soil moisture is required for these applications, the available soil moisture data, in practice, is typically fraught with missing values. There are a wide range of methods available to infilling hydrologic variables, but a thorough inter-comparison between statistical methods and artificial neural networks has not been made. This study examines 5 statistical methods including monthly averages, weighted Pearson correlation coefficient, a method based on temporal stability of soil moisture, and a weighted merging of the three methods, together with a method based on the concept of rough sets. Additionally, 9 artificial neural networks are examined, broadly categorized into feedforward, dynamic, and radial basis networks. These 14 infilling methods were used to estimate missing soil moisture records and subsequently validated against known values for 13 soil moisture monitoring stations for three different soil layer depths in the Yanco region in southeast Australia. The evaluation results show that the top three highest performing methods are the nonlinear autoregressive neural network, rough sets method, and monthly replacement. A high estimation accuracy (root mean square error (RMSE) of about 0.03 m/m) was found in the nonlinear autoregressive network, due to its regression based dynamic network which allows feedback connections through discrete-time estimation. An equally high accuracy (0.05 m/m RMSE) in the rough sets procedure illustrates the important role of temporal persistence of soil moisture, with the capability to account for different soil moisture conditions.

  17. Long-term neural recordings using MEMS based moveable microelectrodes in the brain

    Directory of Open Access Journals (Sweden)

    Nathan Jackson

    2010-06-01

    Full Text Available One of the critical requirements of the emerging class of neural prosthetic devices is to maintain good quality neural recordings over long time periods. We report here a novel (Micro-ElectroMechanical Systems based technology that can move microelectrodes in the event of deterioration in neural signal to sample a new set of neurons. Microscale electro-thermal actuators are used to controllably move microelectrodes post-implantation in steps of approximately 9 µm. In this study, a total of 12 moveable microelectrode chips were individually implanted in adult rats. Two of the 12 moveable microelectrode chips were not moved over a period of 3 weeks and were treated as control experiments. During the first three weeks of implantation, moving the microelectrodes led to an improvement in the average SNR from 14.61 ± 5.21 dB before movement to 18.13 ± 4.99 dB after movement across all microelectrodes and all days. However, the average RMS values of noise amplitudes were similar at 2.98 ± 1.22 µV and 3.01 ± 1.16 µV before and after microelectrode movement. Beyond three weeks, the primary observed failure mode was biological rejection of the PMMA (dental cement based skull mount resulting in the device loosening and eventually falling from the skull. Additionally, the average SNR for functioning devices beyond three weeks was 11.88 ± 2.02 dB before microelectrode movement and was significantly different (p<0.01 from the average SNR of 13.34 ± 0.919 dB after movement. The results of this study demonstrate that MEMS based technologies can move microelectrodes in rodent brains in long-term experiments resulting in improvements in signal quality. Further improvements in packaging and surgical techniques will potentially enable movable microelectrodes to record cortical neuronal activity in chronic experiments.

  18. Bayesian neural network modeling of tree-ring temperature variability record from the Western Himalayas

    Directory of Open Access Journals (Sweden)

    R. K. Tiwari

    2011-08-01

    Full Text Available A novel technique based on the Bayesian neural network (BNN theory is developed and employed to model the temperature variation record from the Western Himalayas. In order to estimate an a posteriori probability function, the BNN is trained with the Hybrid Monte Carlo (HMC/Markov Chain Monte Carlo (MCMC simulations algorithm. The efficacy of the new algorithm is tested on the well known chaotic, first order autoregressive (AR and random models and then applied to model the temperature variation record decoded from the tree-ring widths of the Western Himalayas for the period spanning over 1226–2000 AD. For modeling the actual tree-ring temperature data, optimum network parameters are chosen appropriately and then cross-validation test is performed to ensure the generalization skill of the network on the new data set. Finally, prediction result based on the BNN model is compared with the conventional artificial neural network (ANN and the AR linear models results. The comparative results show that the BNN based analysis makes better prediction than the ANN and the AR models. The new BNN modeling approach provides a viable tool for climate studies and could also be exploited for modeling other kinds of environmental data.

  19. Classification of remotely sensed data using OCR-inspired neural network techniques. [Optical Character Recognition

    Science.gov (United States)

    Kiang, Richard K.

    1992-01-01

    Neural networks have been applied to classifications of remotely sensed data with some success. To improve the performance of this approach, an examination was made of how neural networks are applied to the optical character recognition (OCR) of handwritten digits and letters. A three-layer, feedforward network, along with techniques adopted from OCR, was used to classify Landsat-4 Thematic Mapper data. Good results were obtained. To overcome the difficulties that are characteristic of remote sensing applications and to attain significant improvements in classification accuracy, a special network architecture may be required.

  20. End-to-End Neural Optical Music Recognition of Monophonic Scores

    Directory of Open Access Journals (Sweden)

    Jorge Calvo-Zaragoza

    2018-04-01

    Full Text Available Optical Music Recognition is a field of research that investigates how to computationally decode music notation from images. Despite the efforts made so far, there are hardly any complete solutions to the problem. In this work, we study the use of neural networks that work in an end-to-end manner. This is achieved by using a neural model that combines the capabilities of convolutional neural networks, which work on the input image, and recurrent neural networks, which deal with the sequential nature of the problem. Thanks to the use of the the so-called Connectionist Temporal Classification loss function, these models can be directly trained from input images accompanied by their corresponding transcripts into music symbol sequences. We also present the Printed Music Scores dataset, containing more than 80,000 monodic single-staff real scores in common western notation, that is used to train and evaluate the neural approach. In our experiments, it is demonstrated that this formulation can be carried out successfully. Additionally, we study several considerations about the codification of the output musical sequences, the convergence and scalability of the neural models, as well as the ability of this approach to locate symbols in the input score.

  1. Integrated optical isolators using magnetic surface plasmon (Presentation Recording)

    Science.gov (United States)

    Shimizu, Hiromasa; Kaihara, Terunori; Umetsu, Saori; Hosoda, Masashi

    2015-09-01

    Optical isolators are one of the essential components to protect semiconductor laser diodes (LDs) from backward reflected light in integrated optics. In order to realize optical isolators, nonreciprocal propagation of light is necessary, which can be realized by magnetic materials. Semiconductor optical isolators have been strongly desired on Si and III/V waveguides. We have developed semiconductor optical isolators based on nonreciprocal loss owing to transverse magneto-optic Kerr effect, where the ferromagnetic metals are deposited on semiconductor optical waveguides1). Use of surface plasmon polariton at the interface of ferromagnetic metal and insulator leads to stronger optical confinement and magneto-optic effect. It is possible to modulate the optical confinement by changing the magnetic field direction, thus optical isolator operation is proposed2, 3). We have investigated surface plasmons at the interfaces between ferrimagnetic garnet/gold film, and applications to waveguide optical isolators. We assumed waveguides composed of Au/Si(38.63nm)/Ce:YIG(1700nm)/Si(220nm)/Si , and calculated the coupling lengths between Au/Si(38.63nm)/Ce:YIG plasmonic waveguide and Ce:YIG/Si(220nm)/Si waveguide for transversely magnetized Ce:YIG with forward and backward directions. The coupling length was calculated to 232.1um for backward propagating light. On the other hand, the coupling was not complete, and the length was calculated to 175.5um. The optical isolation by using the nonreciprocal coupling and propagation loss was calculated to be 43.7dB when the length of plasmonic waveguide is 700um. 1) H. Shimizu et al., J. Lightwave Technol. 24, 38 (2006). 2) V. Zayets et al., Materials, 5, 857-871 (2012). 3) J. Montoya, et al, J. Appl. Phys. 106, 023108, (2009).

  2. Underwater Inherent Optical Properties Estimation Using a Depth Aided Deep Neural Network

    Directory of Open Access Journals (Sweden)

    Zhibin Yu

    2017-01-01

    Full Text Available Underwater inherent optical properties (IOPs are the fundamental clues to many research fields such as marine optics, marine biology, and underwater vision. Currently, beam transmissometers and optical sensors are considered as the ideal IOPs measuring methods. But these methods are inflexible and expensive to be deployed. To overcome this problem, we aim to develop a novel measuring method using only a single underwater image with the help of deep artificial neural network. The power of artificial neural network has been proved in image processing and computer vision fields with deep learning technology. However, image-based IOPs estimation is a quite different and challenging task. Unlike the traditional applications such as image classification or localization, IOP estimation looks at the transparency of the water between the camera and the target objects to estimate multiple optical properties simultaneously. In this paper, we propose a novel Depth Aided (DA deep neural network structure for IOPs estimation based on a single RGB image that is even noisy. The imaging depth information is considered as an aided input to help our model make better decision.

  3. Underwater Inherent Optical Properties Estimation Using a Depth Aided Deep Neural Network.

    Science.gov (United States)

    Yu, Zhibin; Wang, Yubo; Zheng, Bing; Zheng, Haiyong; Wang, Nan; Gu, Zhaorui

    2017-01-01

    Underwater inherent optical properties (IOPs) are the fundamental clues to many research fields such as marine optics, marine biology, and underwater vision. Currently, beam transmissometers and optical sensors are considered as the ideal IOPs measuring methods. But these methods are inflexible and expensive to be deployed. To overcome this problem, we aim to develop a novel measuring method using only a single underwater image with the help of deep artificial neural network. The power of artificial neural network has been proved in image processing and computer vision fields with deep learning technology. However, image-based IOPs estimation is a quite different and challenging task. Unlike the traditional applications such as image classification or localization, IOP estimation looks at the transparency of the water between the camera and the target objects to estimate multiple optical properties simultaneously. In this paper, we propose a novel Depth Aided (DA) deep neural network structure for IOPs estimation based on a single RGB image that is even noisy. The imaging depth information is considered as an aided input to help our model make better decision.

  4. A comparison of neural tube defects identified by two independent routine recording systems for congenital malformations in Northern Ireland.

    Science.gov (United States)

    Nevin, N C; McDonald, J R; Walby, A L

    1978-12-01

    The efficiency of two systems for recording congenital malformations has been compared; one system, the Registrar General's Congenital Malformation Notification, is based on registering all malformed infants, and the other, the Child Health System, records all births. In Northern Ireland for three years [1974--1976], using multiple sources of ascertainment, a total of 686 infants with neural tube defects was identified among 79 783 live and stillbirths. The incidence for all neural tube defects in 8 60 per 1 000 births. The Registrar General's Congenital Malformation Notification System identified 83.6% whereas the Child Health System identified only 63.3% of all neural tube defects. Both systems together identified 86.2% of all neural tube defects. The two systems are suitable for monitoring of malformations and the addition of information from the Genetic Counselling Clinics would enhance the data for epidemiological studies.

  5. Minimally-Invasive Neural Interface for Distributed Wireless Electrocorticogram Recording Systems

    Directory of Open Access Journals (Sweden)

    Sun-Il Chang

    2018-01-01

    Full Text Available This paper presents a minimally-invasive neural interface for distributed wireless electrocorticogram (ECoG recording systems. The proposed interface equips all necessary components for ECoG recording, such as the high performance front-end integrated circuits, a fabricated flexible microelectrode array, and wireless communication inside a miniaturized custom-made platform. The multiple units of the interface systems can be deployed to cover a broad range of the target brain region and transmit signals via a built-in intra-skin communication (ISCOM module. The core integrated circuit (IC consists of 16-channel, low-power push-pull double-gated preamplifiers, in-channel successive approximation register analog-to-digital converters (SAR ADC with a single-clocked bootstrapping switch and a time-delayed control unit, an ISCOM module for wireless data transfer through the skin instead of a power-hungry RF wireless transmitter, and a monolithic voltage/current reference generator to support the aforementioned analog and mixed-signal circuit blocks. The IC was fabricated using 250 nm CMOS processes in an area of 3.2 × 0.9 mm2 and achieved the low-power operation of 2.5 µW per channel. Input-referred noise was measured as 5.62 µVrms for 10 Hz to 10 kHz and ENOB of 7.21 at 31.25 kS/s. The implemented system successfully recorded multi-channel neural activities in vivo from a primate and demonstrated modular expandability using the ISCOM with power consumption of 160 µW.

  6. Minimally-Invasive Neural Interface for Distributed Wireless Electrocorticogram Recording Systems.

    Science.gov (United States)

    Chang, Sun-Il; Park, Sung-Yun; Yoon, Euisik

    2018-01-17

    This paper presents a minimally-invasive neural interface for distributed wireless electrocorticogram (ECoG) recording systems. The proposed interface equips all necessary components for ECoG recording, such as the high performance front-end integrated circuits, a fabricated flexible microelectrode array, and wireless communication inside a miniaturized custom-made platform. The multiple units of the interface systems can be deployed to cover a broad range of the target brain region and transmit signals via a built-in intra-skin communication (ISCOM) module. The core integrated circuit (IC) consists of 16-channel, low-power push-pull double-gated preamplifiers, in-channel successive approximation register analog-to-digital converters (SAR ADC) with a single-clocked bootstrapping switch and a time-delayed control unit, an ISCOM module for wireless data transfer through the skin instead of a power-hungry RF wireless transmitter, and a monolithic voltage/current reference generator to support the aforementioned analog and mixed-signal circuit blocks. The IC was fabricated using 250 nm CMOS processes in an area of 3.2 × 0.9 mm² and achieved the low-power operation of 2.5 µW per channel. Input-referred noise was measured as 5.62 µV rms for 10 Hz to 10 kHz and ENOB of 7.21 at 31.25 kS/s. The implemented system successfully recorded multi-channel neural activities in vivo from a primate and demonstrated modular expandability using the ISCOM with power consumption of 160 µW.

  7. An Inductively-Powered Wireless Neural Recording System with a Charge Sampling Analog Front-End.

    Science.gov (United States)

    Lee, Seung Bae; Lee, Byunghun; Kiani, Mehdi; Mahmoudi, Babak; Gross, Robert; Ghovanloo, Maysam

    2016-01-15

    An inductively-powered wireless integrated neural recording system (WINeR-7) is presented for wireless and battery less neural recording from freely-behaving animal subjects inside a wirelessly-powered standard homecage. The WINeR-7 system employs a novel wide-swing dual slope charge sampling (DSCS) analog front-end (AFE) architecture, which performs amplification, filtering, sampling, and analog-to-time conversion (ATC) with minimal interference and small amount of power. The output of the DSCS-AFE produces a pseudo-digital pulse width modulated (PWM) signal. A circular shift register (CSR) time division multiplexes (TDM) the PWM pulses to create a TDM-PWM signal, which is fed into an on-chip 915 MHz transmitter (Tx). The AFE and Tx are supplied at 1.8 V and 4.2 V, respectively, by a power management block, which includes a high efficiency active rectifier and automatic resonance tuning (ART), operating at 13.56 MHz. The 8-ch system-on-a-chip (SoC) was fabricated in a 0.35-μm CMOS process, occupying 5.0 × 2.5 mm 2 and consumed 51.4 mW. For each channel, the sampling rate is 21.48 kHz and the power consumption is 19.3 μW. In vivo experiments were conducted on freely behaving rats in an energized homecage by continuously delivering 51.4 mW to the WINeR-7 system in a closed-loop fashion and recording local field potentials (LFP).

  8. Integrated low noise low power interface for neural bio-potentials recording and conditioning

    Science.gov (United States)

    Bottino, Emanuele; Martinoia, Sergio; Valle, Maurizio

    2005-06-01

    The recent progress in both neurobiology and microelectronics suggests the creation of new, powerful tools to investigate the basic mechanisms of brain functionality. In particular, a lot of efforts are spent by scientific community to define new frameworks devoted to the analysis of in-vitro cultured neurons. One possible approach is recording their spiking activity to monitor the coordinated cellular behaviour and get insights about neural plasticity. Due to the nature of neurons action-potentials, when considering the design of an integrated microelectronic-based recording system, a number of problems arise. First, one would desire to have a high number of recording sites (i.e. several hundreds): this poses constraints on silicon area and power consumption. In this regard, our aim is to integrate-through on-chip post-processing techniques-hundreds of bio-compatible microsensors together with CMOS standard-process low-power (i.e. some tenths of uW per channel) conditioning electronics. Each recording channel is provided with sampling electronics to insure synchronous recording so that, for example, cross-correlation between signals coming from different sites can be performed. Extra-cellular potentials are in the range of [50-150] uV, so a comparison in terms of noise-efficiency was carried out among different architectures and very low-noise pre-amplification electronics (i.e. less than 5 uVrms) was designed. As spikes measurements are made with respect to the voltage of a reference electrode, we opted for an AC-coupled differential-input preamplifier provided with band-pass filtering capability. To achieve this, we implemented large time-constant (up to seconds) integrated components in the preamp feedback path. Thus, we got rid also of random slow-drifting DC-offsets and common mode signals. The paper will present our achievements in the design and implementation of a fully integrated bio-abio interface to record neural spiking activity. In particular

  9. A fast, robust algorithm for power line interference cancellation in neural recording

    Science.gov (United States)

    Keshtkaran, Mohammad Reza; Yang, Zhi

    2014-04-01

    Objective. Power line interference may severely corrupt neural recordings at 50/60 Hz and harmonic frequencies. The interference is usually non-stationary and can vary in frequency, amplitude and phase. To retrieve the gamma-band oscillations at the contaminated frequencies, it is desired to remove the interference without compromising the actual neural signals at the interference frequency bands. In this paper, we present a robust and computationally efficient algorithm for removing power line interference from neural recordings. Approach. The algorithm includes four steps. First, an adaptive notch filter is used to estimate the fundamental frequency of the interference. Subsequently, based on the estimated frequency, harmonics are generated by using discrete-time oscillators, and then the amplitude and phase of each harmonic are estimated by using a modified recursive least squares algorithm. Finally, the estimated interference is subtracted from the recorded data. Main results. The algorithm does not require any reference signal, and can track the frequency, phase and amplitude of each harmonic. When benchmarked with other popular approaches, our algorithm performs better in terms of noise immunity, convergence speed and output signal-to-noise ratio (SNR). While minimally affecting the signal bands of interest, the algorithm consistently yields fast convergence (30 dB) in different conditions of interference strengths (input SNR from -30 to 30 dB), power line frequencies (45-65 Hz) and phase and amplitude drifts. In addition, the algorithm features a straightforward parameter adjustment since the parameters are independent of the input SNR, input signal power and the sampling rate. A hardware prototype was fabricated in a 65 nm CMOS process and tested. Software implementation of the algorithm has been made available for open access at https://github.com/mrezak/removePLI. Significance. The proposed algorithm features a highly robust operation, fast adaptation to

  10. On the robustness of EC-PC spike detection method for online neural recording.

    Science.gov (United States)

    Zhou, Yin; Wu, Tong; Rastegarnia, Amir; Guan, Cuntai; Keefer, Edward; Yang, Zhi

    2014-09-30

    Online spike detection is an important step to compress neural data and perform real-time neural information decoding. An unsupervised, automatic, yet robust signal processing is strongly desired, thus it can support a wide range of applications. We have developed a novel spike detection algorithm called "exponential component-polynomial component" (EC-PC) spike detection. We firstly evaluate the robustness of the EC-PC spike detector under different firing rates and SNRs. Secondly, we show that the detection Precision can be quantitatively derived without requiring additional user input parameters. We have realized the algorithm (including training) into a 0.13 μm CMOS chip, where an unsupervised, nonparametric operation has been demonstrated. Both simulated data and real data are used to evaluate the method under different firing rates (FRs), SNRs. The results show that the EC-PC spike detector is the most robust in comparison with some popular detectors. Moreover, the EC-PC detector can track changes in the background noise due to the ability to re-estimate the neural data distribution. Both real and synthesized data have been used for testing the proposed algorithm in comparison with other methods, including the absolute thresholding detector (AT), median absolute deviation detector (MAD), nonlinear energy operator detector (NEO), and continuous wavelet detector (CWD). Comparative testing results reveals that the EP-PC detection algorithm performs better than the other algorithms regardless of recording conditions. The EC-PC spike detector can be considered as an unsupervised and robust online spike detection. It is also suitable for hardware implementation. Copyright © 2014 Elsevier B.V. All rights reserved.

  11. Immature visual neural system in children reflected by contrast sensitivity with adaptive optics correction

    Science.gov (United States)

    Liu, Rong; Zhou, Jiawei; Zhao, Haoxin; Dai, Yun; Zhang, Yudong; Tang, Yong; Zhou, Yifeng

    2014-01-01

    This study aimed to explore the neural development status of the visual system of children (around 8 years old) using contrast sensitivity. We achieved this by eliminating the influence of higher order aberrations (HOAs) with adaptive optics correction. We measured HOAs, modulation transfer functions (MTFs) and contrast sensitivity functions (CSFs) of six children and five adults with both corrected and uncorrected HOAs. We found that when HOAs were corrected, children and adults both showed improvements in MTF and CSF. However, the CSF of children was still lower than the adult level, indicating the difference in contrast sensitivity between groups cannot be explained by differences in optical factors. Further study showed that the difference between the groups also could not be explained by differences in non-visual factors. With these results we concluded that the neural systems underlying vision in children of around 8 years old are still immature in contrast sensitivity. PMID:24732728

  12. Wide-field optical mapping of neural activity and brain haemodynamics: considerations and novel approaches

    Science.gov (United States)

    Ma, Ying; Shaik, Mohammed A.; Kozberg, Mariel G.; Thibodeaux, David N.; Zhao, Hanzhi T.; Yu, Hang

    2016-01-01

    Although modern techniques such as two-photon microscopy can now provide cellular-level three-dimensional imaging of the intact living brain, the speed and fields of view of these techniques remain limited. Conversely, two-dimensional wide-field optical mapping (WFOM), a simpler technique that uses a camera to observe large areas of the exposed cortex under visible light, can detect changes in both neural activity and haemodynamics at very high speeds. Although WFOM may not provide single-neuron or capillary-level resolution, it is an attractive and accessible approach to imaging large areas of the brain in awake, behaving mammals at speeds fast enough to observe widespread neural firing events, as well as their dynamic coupling to haemodynamics. Although such wide-field optical imaging techniques have a long history, the advent of genetically encoded fluorophores that can report neural activity with high sensitivity, as well as modern technologies such as light emitting diodes and sensitive and high-speed digital cameras have driven renewed interest in WFOM. To facilitate the wider adoption and standardization of WFOM approaches for neuroscience and neurovascular coupling research, we provide here an overview of the basic principles of WFOM, considerations for implementation of wide-field fluorescence imaging of neural activity, spectroscopic analysis and interpretation of results. This article is part of the themed issue ‘Interpreting BOLD: a dialogue between cognitive and cellular neuroscience’. PMID:27574312

  13. Wide-field optical mapping of neural activity and brain haemodynamics: considerations and novel approaches.

    Science.gov (United States)

    Ma, Ying; Shaik, Mohammed A; Kim, Sharon H; Kozberg, Mariel G; Thibodeaux, David N; Zhao, Hanzhi T; Yu, Hang; Hillman, Elizabeth M C

    2016-10-05

    Although modern techniques such as two-photon microscopy can now provide cellular-level three-dimensional imaging of the intact living brain, the speed and fields of view of these techniques remain limited. Conversely, two-dimensional wide-field optical mapping (WFOM), a simpler technique that uses a camera to observe large areas of the exposed cortex under visible light, can detect changes in both neural activity and haemodynamics at very high speeds. Although WFOM may not provide single-neuron or capillary-level resolution, it is an attractive and accessible approach to imaging large areas of the brain in awake, behaving mammals at speeds fast enough to observe widespread neural firing events, as well as their dynamic coupling to haemodynamics. Although such wide-field optical imaging techniques have a long history, the advent of genetically encoded fluorophores that can report neural activity with high sensitivity, as well as modern technologies such as light emitting diodes and sensitive and high-speed digital cameras have driven renewed interest in WFOM. To facilitate the wider adoption and standardization of WFOM approaches for neuroscience and neurovascular coupling research, we provide here an overview of the basic principles of WFOM, considerations for implementation of wide-field fluorescence imaging of neural activity, spectroscopic analysis and interpretation of results.This article is part of the themed issue 'Interpreting BOLD: a dialogue between cognitive and cellular neuroscience'. © 2016 The Authors.

  14. Optical track width measurements below 100 nm using artificial neural networks

    Science.gov (United States)

    Smith, R. J.; See, C. W.; Somekh, M. G.; Yacoot, A.; Choi, E.

    2005-12-01

    This paper discusses the feasibility of using artificial neural networks (ANNs), together with a high precision scanning optical profiler, to measure very fine track widths that are considerably below the conventional diffraction limit of a conventional optical microscope. The ANN is trained using optical profiles obtained from tracks of known widths, the network is then assessed by applying it to test profiles. The optical profiler is an ultra-stable common path scanning interferometer, which provides extremely precise surface measurements. Preliminary results, obtained with a 0.3 NA objective lens and a laser wavelength of 633 nm, show that the system is capable of measuring a 50 nm track width, with a standard deviation less than 4 nm.

  15. Neural network-based feature point descriptors for registration of optical and SAR images

    Science.gov (United States)

    Abulkhanov, Dmitry; Konovalenko, Ivan; Nikolaev, Dmitry; Savchik, Alexey; Shvets, Evgeny; Sidorchuk, Dmitry

    2018-04-01

    Registration of images of different nature is an important technique used in image fusion, change detection, efficient information representation and other problems of computer vision. Solving this task using feature-based approaches is usually more complex than registration of several optical images because traditional feature descriptors (SIFT, SURF, etc.) perform poorly when images have different nature. In this paper we consider the problem of registration of SAR and optical images. We train neural network to build feature point descriptors and use RANSAC algorithm to align found matches. Experimental results are presented that confirm the method's effectiveness.

  16. An analog VLSI real time optical character recognition system based on a neural architecture

    International Nuclear Information System (INIS)

    Bo, G.; Caviglia, D.; Valle, M.

    1999-01-01

    In this paper a real time Optical Character Recognition system is presented: it is based on a feature extraction module and a neural network classifier which have been designed and fabricated in analog VLSI technology. Experimental results validate the circuit functionality. The results obtained from a validation based on a mixed approach (i.e., an approach based on both experimental and simulation results) confirm the soundness and reliability of the system

  17. An analog VLSI real time optical character recognition system based on a neural architecture

    Energy Technology Data Exchange (ETDEWEB)

    Bo, G.; Caviglia, D.; Valle, M. [Genoa Univ. (Italy). Dip. of Biophysical and Electronic Engineering

    1999-03-01

    In this paper a real time Optical Character Recognition system is presented: it is based on a feature extraction module and a neural network classifier which have been designed and fabricated in analog VLSI technology. Experimental results validate the circuit functionality. The results obtained from a validation based on a mixed approach (i.e., an approach based on both experimental and simulation results) confirm the soundness and reliability of the system.

  18. Eigenanalysis of a neural network for optic flow processing

    International Nuclear Information System (INIS)

    Weber, F; Eichner, H; Borst, A; Cuntz, H

    2008-01-01

    Flies gain information about self-motion during free flight by processing images of the environment moving across their retina. The visual course control center in the brain of the blowfly contains, among others, a population of ten neurons, the so-called vertical system (VS) cells that are mainly sensitive to downward motion. VS cells are assumed to encode information about rotational optic flow induced by self-motion (Krapp and Hengstenberg 1996 Nature 384 463-6). Recent evidence supports a connectivity scheme between the VS cells where neurons with neighboring receptive fields are connected to each other by electrical synapses at the axonal terminals, whereas the boundary neurons in the network are reciprocally coupled via inhibitory synapses (Haag and Borst 2004 Nat. Neurosci. 7 628-34; Farrow et al 2005 J. Neurosci. 25 3985-93; Cuntz et al 2007 Proc. Natl Acad. Sci. USA). Here, we investigate the functional properties of the VS network and its connectivity scheme by reducing a biophysically realistic network to a simplified model, where each cell is represented by a dendritic and axonal compartment only. Eigenanalysis of this model reveals that the whole population of VS cells projects the synaptic input provided from local motion detectors on to its behaviorally relevant components. The two major eigenvectors consist of a horizontal and a slanted line representing the distribution of vertical motion components across the fly's azimuth. They are, thus, ideally suited for reliably encoding translational and rotational whole-field optic flow induced by respective flight maneuvers. The dimensionality reduction compensates for the contrast and texture dependence of the local motion detectors of the correlation-type, which becomes particularly pronounced when confronted with natural images and their highly inhomogeneous contrast distribution

  19. Artificial neural networks based estimation of optical parameters by diffuse reflectance imaging under in vitro conditions

    Directory of Open Access Journals (Sweden)

    Mahmut Ozan Gökkan

    2017-01-01

    Full Text Available Optical parameters (properties of tissue-mimicking phantoms are determined through noninvasive optical imaging. Objective of this study is to decompose obtained diffuse reflectance into these optical properties such as absorption and scattering coefficients. To do so, transmission spectroscopy is firstly used to measure the coefficients via an experimental setup. Next, the optical properties of each characterized phantom are input for Monte Carlo (MC simulations to get diffuse reflectance. Also, a surface image for each single phantom with its known optical properties is obliquely captured due to reflectance-based geometrical setup using CMOS camera that is positioned at 5∘ angle to the phantoms. For the illumination of light, a laser light source at 633nm wavelength is preferred, because optical properties of different components in a biological tissue on that wavelength are nonoverlapped. During in vitro measurements, we prepared 30 different mixture samples adding clinoleic intravenous lipid emulsion (CILE and evans blue (EB dye into a distilled water. Finally, all obtained diffuse reflectance values are used to estimate the optical coefficients by artificial neural networks (ANNs in inverse modeling. For a biological tissue it is found that the simulated and measured values in our results are in good agreement.

  20. In-plane silicon probes for simultaneous neural recording and drug delivery

    International Nuclear Information System (INIS)

    Seidl, K; Herwik, S; Paul, O; Ruther, P; Spieth, S; Zengerle, R; Steigert, J

    2010-01-01

    This paper reports on the design, fabrication and characterization of silicon-based microprobes for simultaneous neural recording and drug delivery. The fabrication technology is based on two-stage deep reactive ion etching combined with silicon wafer bonding and grinding to realize channel structures integrated in needle-like probe shafts. Liquids can be supplied to microfluidic devices via in-plane and out-of-plane ports. The liquid is dispensed at circular out-of-plane ports with a diameter of 25 µm and rectangular in-plane ports with dimensions of 50 × 50 µm 2 . Two-shaft probes with a pitch between shafts of 1.0 and 1.5 mm were realized. The probe shafts have a length of 8 mm and rectangular cross-sections of w × h (w = 250 µm and h = 200 or 250 µm). Each shaft contains one or two fluidic channels with a cross-section of 50 × 50 µm 2 . In addition, each probe shaft comprises four recording sites with diameters of 20 µm close to the outlet ports. Mechanical and fluidic characterization demonstrated the functionality of the probes. Typical infusion rates of 1.5 µL min −1 are achieved at a differential pressure of 1 kPa. The Pt-gray electrodes have an average electrode impedance of 260 ± 59 kΩ at 1 kHz

  1. Controlling selective stimulations below a spinal cord hemisection using brain recordings with a neural interface system approach

    Science.gov (United States)

    Panetsos, Fivos; Sanchez-Jimenez, Abel; Torets, Carlos; Largo, Carla; Micera, Silvestro

    2011-08-01

    In this work we address the use of realtime cortical recordings for the generation of coherent, reliable and robust motor activity in spinal-lesioned animals through selective intraspinal microstimulation (ISMS). The spinal cord of adult rats was hemisectioned and groups of multielectrodes were implanted in both the central nervous system (CNS) and the spinal cord below the lesion level to establish a neural system interface (NSI). To test the reliability of this new NSI connection, highly repeatable neural responses recorded from the CNS were used as a pattern generator of an open-loop control strategy for selective ISMS of the spinal motoneurons. Our experimental procedure avoided the spontaneous non-controlled and non-repeatable neural activity that could have generated spurious ISMS and the consequent undesired muscle contractions. Combinations of complex CNS patterns generated precisely coordinated, reliable and robust motor actions.

  2. Online Recorded Data-Based Composite Neural Control of Strict-Feedback Systems With Application to Hypersonic Flight Dynamics.

    Science.gov (United States)

    Xu, Bin; Yang, Daipeng; Shi, Zhongke; Pan, Yongping; Chen, Badong; Sun, Fuchun

    2017-09-25

    This paper investigates the online recorded data-based composite neural control of uncertain strict-feedback systems using the backstepping framework. In each step of the virtual control design, neural network (NN) is employed for uncertainty approximation. In previous works, most designs are directly toward system stability ignoring the fact how the NN is working as an approximator. In this paper, to enhance the learning ability, a novel prediction error signal is constructed to provide additional correction information for NN weight update using online recorded data. In this way, the neural approximation precision is highly improved, and the convergence speed can be faster. Furthermore, the sliding mode differentiator is employed to approximate the derivative of the virtual control signal, and thus, the complex analysis of the backstepping design can be avoided. The closed-loop stability is rigorously established, and the boundedness of the tracking error can be guaranteed. Through simulation of hypersonic flight dynamics, the proposed approach exhibits better tracking performance.

  3. Automatic modulation format recognition for the next generation optical communication networks using artificial neural networks

    Science.gov (United States)

    Guesmi, Latifa; Hraghi, Abir; Menif, Mourad

    2015-03-01

    A new technique for Automatic Modulation Format Recognition (AMFR) in next generation optical communication networks is presented. This technique uses the Artificial Neural Network (ANN) in conjunction with the features of Linear Optical Sampling (LOS) of the detected signal at high bit rates using direct detection or coherent detection. The use of LOS method for this purpose mainly driven by the increase of bit rates which enables the measurement of eye diagrams. The efficiency of this technique is demonstrated under different transmission impairments such as chromatic dispersion (CD) in the range of -500 to 500 ps/nm, differential group delay (DGD) in the range of 0-15 ps and the optical signal tonoise ratio (OSNR) in the range of 10-30 dB. The results of numerical simulation for various modulation formats demonstrate successful recognition from a known bit rates with a higher estimation accuracy, which exceeds 99.8%.

  4. A Neural Network Approach to Infer Optical Depth of Thick Ice Clouds at Night

    Science.gov (United States)

    Minnis, P.; Hong, G.; Sun-Mack, S.; Chen, Yan; Smith, W. L., Jr.

    2016-01-01

    One of the roadblocks to continuously monitoring cloud properties is the tendency of clouds to become optically black at cloud optical depths (COD) of 6 or less. This constraint dramatically reduces the quantitative information content at night. A recent study found that because of their diffuse nature, ice clouds remain optically gray, to some extent, up to COD of 100 at certain wavelengths. Taking advantage of this weak dependency and the availability of COD retrievals from CloudSat, an artificial neural network algorithm was developed to estimate COD values up to 70 from common satellite imager infrared channels. The method was trained using matched 2007 CloudSat and Aqua MODIS data and is tested using similar data from 2008. The results show a significant improvement over the use of default values at night with high correlation. This paper summarizes the results and suggests paths for future improvement.

  5. Optical fibre Bragg grating recorded in TOPAS cyclic olefin copolymer

    DEFF Research Database (Denmark)

    Johnson, I.P.; Yuan, Scott Wu; Stefani, Alessio

    2011-01-01

    A report is presented on the inscription of a fibre Bragg grating into a microstructured polymer optical fibre fabricated from TOPAS cyclic olefin copolymer. This material offers two important advantages over poly (methyl methacrylate), which up to now has formed the basis for polymer fibre Bragg...

  6. Dichromated gelatin and its importance for optical hologram recording

    Czech Academy of Sciences Publication Activity Database

    Šmíd, Petr; Hiklová, H.; Keprt, Jiří

    2004-01-01

    Roč. 54, č. 12 (2004), s. 1461-1472 ISSN 0011-4626 R&D Projects: GA MŠk(CZ) LN00A015 Keywords : dichromated gelatin * holography * volume program Subject RIV: BH - Optics, Masers, Lasers Impact factor: 0.292, year: 2004

  7. Cu-Si bilayers as storage medium in optical recording

    International Nuclear Information System (INIS)

    Kuiper, A.E. T.; Vullers, R.J.M.; Pasquariello, D.; Naburgh, E.P.

    2005-01-01

    Instead of a phase change or a dye layer, a Cu/Si bilayer can be applied as the recording medium in a write-once Blu-ray Disc. The write process basically comprises the formation of a CuSi alloy containing 25-30 at. % Si, while any excess of Si is left behind as unreacted film. Auger analyses of the laser-written layers indicate that recording consists primarily of the diffusion of Si into Cu. The data allow for discrimination between the various models presented in literature for Cu/Si-based recording and to optimize the stack. Very low jitter levels of typically 4% proved to be achievable with equally thick films of Cu and Si as recording medium

  8. Chronic multisite brain recordings from a totally implantable bidirectional neural interface: experience in 5 patients with Parkinson's disease.

    Science.gov (United States)

    Swann, Nicole C; de Hemptinne, Coralie; Miocinovic, Svjetlana; Qasim, Salman; Ostrem, Jill L; Galifianakis, Nicholas B; Luciano, Marta San; Wang, Sarah S; Ziman, Nathan; Taylor, Robin; Starr, Philip A

    2018-02-01

    OBJECTIVE Dysfunction of distributed neural networks underlies many brain disorders. The development of neuromodulation therapies depends on a better understanding of these networks. Invasive human brain recordings have a favorable temporal and spatial resolution for the analysis of network phenomena but have generally been limited to acute intraoperative recording or short-term recording through temporarily externalized leads. Here, the authors describe their initial experience with an investigational, first-generation, totally implantable, bidirectional neural interface that allows both continuous therapeutic stimulation and recording of field potentials at multiple sites in a neural network. METHODS Under a physician-sponsored US Food and Drug Administration investigational device exemption, 5 patients with Parkinson's disease were implanted with the Activa PC+S system (Medtronic Inc.). The device was attached to a quadripolar lead placed in the subdural space over motor cortex, for electrocorticography potential recordings, and to a quadripolar lead in the subthalamic nucleus (STN), for both therapeutic stimulation and recording of local field potentials. Recordings from the brain of each patient were performed at multiple time points over a 1-year period. RESULTS There were no serious surgical complications or interruptions in deep brain stimulation therapy. Signals in both the cortex and the STN were relatively stable over time, despite a gradual increase in electrode impedance. Canonical movement-related changes in specific frequency bands in the motor cortex were identified in most but not all recordings. CONCLUSIONS The acquisition of chronic multisite field potentials in humans is feasible. The device performance characteristics described here may inform the design of the next generation of totally implantable neural interfaces. This research tool provides a platform for translating discoveries in brain network dynamics to improved neurostimulation

  9. Optical Reading and Playing of Sound Signals from Vinyl Records

    OpenAIRE

    Hensman, Arnold; Casey, Kevin

    2007-01-01

    While advanced digital music systems such as compact disk players and MP3 have become the standard in sound reproduction technology, critics claim that conversion to digital often results in a loss of sound quality and richness. For this reason, vinyl records remain the medium of choice for many audiophiles involved in specialist areas. The waveform cut into a vinyl record is an exact replica of the analogue version from the original source. However, while some perceive this media as reproduc...

  10. High-density near-field optical disc recording using phase change media and polycarbonate substrate

    Science.gov (United States)

    Shinoda, Masataka; Saito, Kimihiro; Ishimoto, Tsutomu; Kondo, Takao; Nakaoki, Ariyoshi; Furuki, Motohiro; Takeda, Minoru; Akiyama, Yuji; Shimouma, Takashi; Yamamoto, Masanobu

    2004-09-01

    We developed a high density near field optical recording disc system with a solid immersion lens and two laser sources. In order to realize the near field optical recording, we used a phase change recording media and a molded polycarbonate substrate. The near field optical pick-up consists of a solid immersion lens with numerical aperture of 1.84. The clear eye pattern of 90.2 GB capacity (160nm track pitch and 62 nm per bit) was observed. The jitter using a limit equalizer was 10.0 % without cross-talk. The bit error rate using an adaptive PRML with 8 taps was 3.7e-6 without cross-talk. We confirmed that the near field optical disc system is a promising technology for a next generation high density optical disc system.

  11. In vivo monitoring of glial scar proliferation on chronically implanted neural electrodes by fiber optical coherence tomography

    Science.gov (United States)

    Xie, Yijing; Martini, Nadja; Hassler, Christina; Kirch, Robert D.; Stieglitz, Thomas; Seifert, Andreas; Hofmann, Ulrich G.

    2014-01-01

    In neural prosthetics and stereotactic neurosurgery, intracortical electrodes are often utilized for delivering therapeutic electrical pulses, and recording neural electrophysiological signals. Unfortunately, neuroinflammation impairs the neuron-electrode-interface by developing a compact glial encapsulation around the implants in long term. At present, analyzing this immune reaction is only feasible with post-mortem histology; currently no means for specific in vivo monitoring exist and most applicable imaging modalities can not provide information in deep brain regions. Optical coherence tomography (OCT) is a well established imaging modality for in vivo studies, providing cellular resolution and up to 1.2 mm imaging depth in brain tissue. A fiber based spectral domain OCT was shown to be capable of minimally invasive brain imaging. In the present study, we propose to use a fiber based spectral domain OCT to monitor the progression of the tissue's immune response through scar encapsulation progress in a rat animal model. A fine fiber catheter was implanted in rat brain together with a flexible polyimide microelectrode in sight both of which acts as a foreign body and induces the brain tissue immune reaction. OCT signals were collected from animals up to 12 weeks after implantation and thus gliotic scarring in vivo monitored for that time. Preliminary data showed a significant enhancement of the OCT backscattering signal during the first 3 weeks after implantation, and increased attenuation factor of the sampled tissue due to the glial scar formation. PMID:25191264

  12. Estimation of monthly wind power outputs of WECS with limited record period using artificial neural networks

    International Nuclear Information System (INIS)

    Tu, Yi-Long; Chang, Tsang-Jung; Chen, Cheng-Lung; Chang, Yu-Jung

    2012-01-01

    Highlights: ► ANN with short record training data is used to estimate power outputs in an existing station. ► The suitable numbers/parameters of input neurons for ANN are presented. ► Current wind speeds and previous power outputs are the most important input neurons. ► Choosing suitable input parameters is more important than choosing multiple parameters. - Abstract: For the brand new wind power industry, online recordings of wind power data are always in a relatively limited period. The aim of the study is to investigate the suitable numbers/parameters of input neurons for artificial neural networks under a short record of measured data. Measured wind speeds, wind directions (yaw angles) and power outputs with 10-min resolution at an existing wind power station, located at Jhongtun, Taiwan, are integrated to form three types of input neuron numbers and sixteen cases of input neurons. The first-10 days of each month in 2006 are used for data training to simulate the following 20-day power generation of the same month. The performance of various input neuron cases is evaluated. The simulated results show that using the first 10-day training data with adequate input neurons can estimate energy outputs well except the weak wind regime (May, June, and July). Among the input neuron parameters used, current wind speeds V(t) and previous power outputs P(t − 1) are the most important. Individually using one of them into input neurons can only provide satisfactory estimation. However, simultaneously using these two parameters into input neurons can give the best estimation. Thus, choosing suitable input parameters is more important than choosing multiple parameters.

  13. A Fully Integrated Wireless Compressed Sensing Neural Signal Acquisition System for Chronic Recording and Brain Machine Interface.

    Science.gov (United States)

    Liu, Xilin; Zhang, Milin; Xiong, Tao; Richardson, Andrew G; Lucas, Timothy H; Chin, Peter S; Etienne-Cummings, Ralph; Tran, Trac D; Van der Spiegel, Jan

    2016-07-18

    Reliable, multi-channel neural recording is critical to the neuroscience research and clinical treatment. However, most hardware development of fully integrated, multi-channel wireless neural recorders to-date, is still in the proof-of-concept stage. To be ready for practical use, the trade-offs between performance, power consumption, device size, robustness, and compatibility need to be carefully taken into account. This paper presents an optimized wireless compressed sensing neural signal recording system. The system takes advantages of both custom integrated circuits and universal compatible wireless solutions. The proposed system includes an implantable wireless system-on-chip (SoC) and an external wireless relay. The SoC integrates 16-channel low-noise neural amplifiers, programmable filters and gain stages, a SAR ADC, a real-time compressed sensing module, and a near field wireless power and data transmission link. The external relay integrates a 32 bit low-power microcontroller with Bluetooth 4.0 wireless module, a programming interface, and an inductive charging unit. The SoC achieves high signal recording quality with minimized power consumption, while reducing the risk of infection from through-skin connectors. The external relay maximizes the compatibility and programmability. The proposed compressed sensing module is highly configurable, featuring a SNDR of 9.78 dB with a compression ratio of 8×. The SoC has been fabricated in a 180 nm standard CMOS technology, occupying 2.1 mm × 0.6 mm silicon area. A pre-implantable system has been assembled to demonstrate the proposed paradigm. The developed system has been successfully used for long-term wireless neural recording in freely behaving rhesus monkey.

  14. LAI inversion from optical reflectance using a neural network trained with a multiple scattering model

    Science.gov (United States)

    Smith, James A.

    1992-01-01

    The inversion of the leaf area index (LAI) canopy parameter from optical spectral reflectance measurements is obtained using a backpropagation artificial neural network trained using input-output pairs generated by a multiple scattering reflectance model. The problem of LAI estimation over sparse canopies (LAI 1000 percent for low LAI. Minimization methods applied to merit functions constructed from differences between measured reflectances and predicted reflectances using multiple-scattering models are unacceptably sensitive to a good initial guess for the desired parameter. In contrast, the neural network reported generally yields absolute percentage errors of <30 percent when weighting coefficients trained on one soil type were applied to predicted canopy reflectance at a different soil background.

  15. ELHnet: a convolutional neural network for classifying cochlear endolymphatic hydrops imaged with optical coherence tomography.

    Science.gov (United States)

    Liu, George S; Zhu, Michael H; Kim, Jinkyung; Raphael, Patrick; Applegate, Brian E; Oghalai, John S

    2017-10-01

    Detection of endolymphatic hydrops is important for diagnosing Meniere's disease, and can be performed non-invasively using optical coherence tomography (OCT) in animal models as well as potentially in the clinic. Here, we developed ELHnet, a convolutional neural network to classify endolymphatic hydrops in a mouse model using learned features from OCT images of mice cochleae. We trained ELHnet on 2159 training and validation images from 17 mice, using only the image pixels and observer-determined labels of endolymphatic hydrops as the inputs. We tested ELHnet on 37 images from 37 mice that were previously not used, and found that the neural network correctly classified 34 of the 37 mice. This demonstrates an improvement in performance from previous work on computer-aided classification of endolymphatic hydrops. To the best of our knowledge, this is the first deep CNN designed for endolymphatic hydrops classification.

  16. Engrafted human induced pluripotent stem cell-derived anterior specified neural progenitors protect the rat crushed optic nerve.

    Directory of Open Access Journals (Sweden)

    Leila Satarian

    Full Text Available BACKGROUND: Degeneration of retinal ganglion cells (RGCs is a common occurrence in several eye diseases. This study examined the functional improvement and protection of host RGCs in addition to the survival, integration and neuronal differentiation capabilities of anterior specified neural progenitors (NPs following intravitreal transplantation. METHODOLOGY/PRINCIPAL FINDINGS: NPs were produced under defined conditions from human induced pluripotent stem cells (hiPSCs and transplanted into rats whose optic nerves have been crushed (ONC. hiPSCs were induced to differentiate into anterior specified NPs by the use of Noggin and retinoic acid. The hiPSC-NPs were labeled by green fluorescent protein or a fluorescent tracer 1,1' -dioctadecyl-3,3,3',3'-tetramethylindocarbocyanine perchlorate (DiI and injected two days after induction of ONC in hooded rats. Functional analysis according to visual evoked potential recordings showed significant amplitude recovery in animals transplanted with hiPSC-NPs. Retrograde labeling by an intra-collicular DiI injection showed significantly higher numbers of RGCs and spared axons in ONC rats treated with hiPSC-NPs or their conditioned medium (CM. The analysis of CM of hiPSC-NPs showed the secretion of ciliary neurotrophic factor, basic fibroblast growth factor, and insulin-like growth factor. Optic nerve of cell transplanted groups also had increased GAP43 immunoreactivity and myelin staining by FluoroMyelin™ which imply for protection of axons and myelin. At 60 days post-transplantation hiPSC-NPs were integrated into the ganglion cell layer of the retina and expressed neuronal markers. CONCLUSIONS/SIGNIFICANCE: The transplantation of anterior specified NPs may improve optic nerve injury through neuroprotection and differentiation into neuronal lineages. These NPs possibly provide a promising new therapeutic approach for traumatic optic nerve injuries and loss of RGCs caused by other diseases.

  17. Ultrafast chirped optical waveform recorder using a time microscope

    Science.gov (United States)

    Bennett, Corey Vincent

    2015-04-21

    A new technique for capturing both the amplitude and phase of an optical waveform is presented. This technique can capture signals with many THz of bandwidths in a single shot (e.g., temporal resolution of about 44 fs), or be operated repetitively at a high rate. That is, each temporal window (or frame) is captured single shot, in real time, but the process may be run repeatedly or single-shot. By also including a variety of possible demultiplexing techniques, this process is scalable to recoding continuous signals.

  18. Identification of input variables for feature based artificial neural networks-saccade detection in EOG recordings.

    Science.gov (United States)

    Tigges, P; Kathmann, N; Engel, R R

    1997-07-01

    Though artificial neural networks (ANN) are excellent tools for pattern recognition problems when signal to noise ratio is low, the identification of decision relevant features for ANN input data is still a crucial issue. The experience of the ANN designer and the existing knowledge and understanding of the problem seem to be the only links for a specific construction. In the present study a backpropagation ANN based on modified raw data inputs showed encouraging results. Investigating the specific influences of prototypical input patterns on a specially designed ANN led to a new sparse and efficient input data presentation. This data coding obtained by a semiautomatic procedure combining existing expert knowledge and the internal representation structures of the raw data based ANN yielded a list of feature vectors, each representing the relevant information for saccade identification. The feature based ANN produced a reduction of the error rate of nearly 40% compared with the raw data ANN. An overall correct classification of 92% of so far unknown data was realized. The proposed method of extracting internal ANN knowledge for the production of a better input data representation is not restricted to EOG recordings, and could be used in various fields of signal analysis.

  19. Design and measurements of low power multichannel chip for recording and stimulation of neural activity.

    Science.gov (United States)

    Zoladz, M; Kmon, P; Grybos, P; Szczygiel, R; Kleczek, R; Otfinowski, P; Rauza, J

    2012-01-01

    A 64-channel Neuro-Stimulation-Recording chip named NRS64 for neural activity measurements has been designed and tested. The NRS64 occupies 5×5 mm² of silicon area and consumes only 25 µW/channel. A low cut-off frequency can be tuned in the 60 mHz-100 Hz range while a high cut-off frequency can be set to 4.7 kHz or 12 kHz. A voltage gain can be set to 139 V/V or 1100 V/V. A measured input referenced noise is 3.7 µV rms in 100 Hz-12 kHz band and 7.6 µV rms in 3 Hz-12 kHz band. A digital correction is used in each channel to tune the low cut-off frequency and offset voltage. Each channel is equipped additionally with a stimulation circuit with an artifact cancellation circuit. The stimulation circuit can be set with 8-bit resolution in six different ranges from 500 nA-512 µA range.

  20. Estimation of the non records logs from existing logs using artificial neural networks

    Directory of Open Access Journals (Sweden)

    Mehdi Mohammad Salehi

    2017-12-01

    Full Text Available Finding the information of the hydrocarbon reservoirs from well logs is one of the main objectives of the engineers. But, missing the log records (due to many reasons such as broken instruments, unsuitable borehole and etc. is a major challenge to achieve it. Prediction of the density and resistivity logs (Rt, DT and LLS from the conventional wire-line logs in one of the Iranian southwest oil fields is the main purpose of this study. Multilayer neural network was applied to develop an intelligent predictive model for prediction of the logs. A total of 3000 data sets from 3 wells (A, B and C of the studied field were used. Among them, the data of A, B and C wells were used to constructing and testing the model, respectively. To evaluate the performance of the model, the mean square error (MSE and correlation coefficient (R2 in the test data were calculated. A comparison between the MSE of the proposed model and recently intelligent models shows that the proposed model is more accurate than others. Acceptable accuracy and using conventional well logging data are the highlight advantages of the proposed intelligent model.

  1. New Optical Card for Sneaker’s Network in Place of Electronic Clinical Record

    Science.gov (United States)

    Goto, Kenya; Satsukawa, Takatoshi; Chiba, Seisho; Ohmori, Takaaki

    2006-02-01

    In order to solve problems in electronic medical records, a new optical card of the digital versatile disk (DVD) type with higher capacity and lower cost than conventional compact disc recording (CD-R)-type cards has been developed, which is thinner, stronger and wearable like a credit card.

  2. Methylene blue doped polymers: efficient media for optical recording

    Science.gov (United States)

    Ushamani, M.; Sreekumar, K.; Sudha Kartha, C.; Joseph, R.

    2004-05-01

    Polymer materials find application in optical storage technology, namely in the development of high information density and fast access type memories. A new polymer blend of methylene blue sensitized polyvinyl alcohol (PVA) and polyacrylic acid (PAA) in methanol is prepared and characterized and its comparison with methylene blue sensitized PVA in methanol and complexed methylene blue sensitized polyvinyl chloride (CMBPVC) is presented. The optical absorption spectra of the thin films of these polymers showed a strong and broad absorption region at 670-650 nm, matching the wavelength of the laser used. A very slow recovery of the dye on irradiation was observed when a 7:3 blend of polyvinyl alcohol/polyacrylic acid at a pH of 3.8 and a sensitizer concentration of 4.67 · 10-5 g/ml were used. A diffraction efficiency of up to 20% was observed for the MBPVA/alcohol system and an energetic sensitivity of 2000 mJ/cm2 was obtained in the photosensitive films with a spatial frequency of 588 lines/mm.

  3. Line width measurement below 60 nm using an optical interferometer and artificial neural network

    Science.gov (United States)

    See, Chung W.; Smith, Richard J.; Somekh, Michael G.; Yacoot, Andrew

    2007-03-01

    We have recently described a technique for optical line-width measurements. The system currently is capable of measuring line-width down to 60 nm with a precision of 2 nm, and potentially should be able to measure down to 10nm. The system consists of an ultra-stable interferometer and artificial neural networks (ANNs). The former is used to generate optical profiles which are input to the ANNs. The outputs of the ANNs are the desired sample parameters. Different types of samples have been tested with equally impressive results. In this paper we will discuss the factors that are essential to extend the application of the technique. Two of the factors are signal conditioning and sample classification. Methods, including principal component analysis, that are capable of performing these tasks will be considered.

  4. An externally head-mounted wireless neural recording device for laboratory animal research and possible human clinical use.

    Science.gov (United States)

    Yin, Ming; Li, Hao; Bull, Christopher; Borton, David A; Aceros, Juan; Larson, Lawrence; Nurmikko, Arto V

    2013-01-01

    In this paper we present a new type of head-mounted wireless neural recording device in a highly compact package, dedicated for untethered laboratory animal research and designed for future mobile human clinical use. The device, which takes its input from an array of intracortical microelectrode arrays (MEA) has ninety-seven broadband parallel neural recording channels and was integrated on to two custom designed printed circuit boards. These house several low power, custom integrated circuits, including a preamplifier ASIC, a controller ASIC, plus two SAR ADCs, a 3-axis accelerometer, a 48MHz clock source, and a Manchester encoder. Another ultralow power RF chip supports an OOK transmitter with the center frequency tunable from 3GHz to 4GHz, mounted on a separate low loss dielectric board together with a 3V LDO, with output fed to a UWB chip antenna. The IC boards were interconnected and packaged in a polyether ether ketone (PEEK) enclosure which is compatible with both animal and human use (e.g. sterilizable). The entire system consumes 17mA from a 1.2Ahr 3.6V Li-SOCl2 1/2AA battery, which operates the device for more than 2 days. The overall system includes a custom RF receiver electronics which are designed to directly interface with any number of commercial (or custom) neural signal processors for multi-channel broadband neural recording. Bench-top measurements and in vivo testing of the device in rhesus macaques are presented to demonstrate the performance of the wireless neural interface.

  5. Multi-GPU Development of a Neural Networks Based Reconstructor for Adaptive Optics

    Directory of Open Access Journals (Sweden)

    Carlos González-Gutiérrez

    2018-01-01

    Full Text Available Aberrations introduced by the atmospheric turbulence in large telescopes are compensated using adaptive optics systems, where the use of deformable mirrors and multiple sensors relies on complex control systems. Recently, the development of larger scales of telescopes as the E-ELT or TMT has created a computational challenge due to the increasing complexity of the new adaptive optics systems. The Complex Atmospheric Reconstructor based on Machine Learning (CARMEN is an algorithm based on artificial neural networks, designed to compensate the atmospheric turbulence. During recent years, the use of GPUs has been proved to be a great solution to speed up the learning process of neural networks, and different frameworks have been created to ease their development. The implementation of CARMEN in different Multi-GPU frameworks is presented in this paper, along with its development in a language originally developed for GPU, like CUDA. This implementation offers the best response for all the presented cases, although its advantage of using more than one GPU occurs only in large networks.

  6. All-optical bidirectional neural interfacing using hybrid multiphoton holographic optogenetic stimulation.

    Science.gov (United States)

    Paluch-Siegler, Shir; Mayblum, Tom; Dana, Hod; Brosh, Inbar; Gefen, Inna; Shoham, Shy

    2015-07-01

    Our understanding of neural information processing could potentially be advanced by combining flexible three-dimensional (3-D) neuroimaging and stimulation. Recent developments in optogenetics suggest that neurophotonic approaches are in principle highly suited for noncontact stimulation of network activity patterns. In particular, two-photon holographic optical neural stimulation (2P-HONS) has emerged as a leading approach for multisite 3-D excitation, and combining it with temporal focusing (TF) further enables axially confined yet spatially extended light patterns. Here, we study key steps toward bidirectional cell-targeted 3-D interfacing by introducing and testing a hybrid new 2P-TF-HONS stimulation path for accurate parallel optogenetic excitation into a recently developed hybrid multiphoton 3-D imaging system. The system is shown to allow targeted all-optical probing of in vitro cortical networks expressing channelrhodopsin-2 using a regeneratively amplified femtosecond laser source tuned to 905 nm. These developments further advance a prospective new tool for studying and achieving distributed control over 3-D neuronal circuits both in vitro and in vivo.

  7. Near-field optical recording based on solid immersion lens system

    Science.gov (United States)

    Hong, Tao; Wang, Jia; Wu, Yan; Li, Dacheng

    2002-09-01

    Near-field optical recording based on solid immersion lens (SIL) system has attracted great attention in the field of high-density data storage in recent years. The diffraction limited spot size in optical recording and lithography can be decreased by utilizing the SIL. The SIL near-field optical storage has advantages of high density, mass storage capacity and compatibility with many technologies well developed. We have set up a SIL near-field static recording system. The recording medium is placed on a 3-D scanning stage with the scanning range of 70×70×70μm and positioning accuracy of sub-nanometer, which will ensure the rigorous separation control in SIL system and the precision motion of the recording medium. The SIL is mounted on an inverted microscope. The focusing between long working distance objective and SIL can be monitored and observed by the CCD camera and eyes. Readout signal can be collected by a detector. Some experiments have been performed based on the SIL near-field recording system. The attempt of the near-field recording on photochromic medium has been made and the resolution improvement of the SIL has been presented. The influence factors in SIL near-field recording system are also discussed in the paper.

  8. A CMOS frontend chip for implantable neural recording with wide voltage supply range

    International Nuclear Information System (INIS)

    Liu Jialin; Zhang Xu; Hu Xiaohui; Li Peng; Liu Ming; Chen Hongda; Guo Yatao; Li Bin

    2015-01-01

    A design for a CMOS frontend integrated circuit (chip) for neural signal acquisition working at wide voltage supply range is presented in this paper. The chip consists of a preamplifier, a serial instrumental amplifier (IA) and a cyclic analog-to-digital converter (CADC). The capacitive-coupled and capacitive-feedback topology combined with MOS-bipolar pseudo-resistor element is adopted in the preamplifier to create a −3 dB upper cut-off frequency less than 1 Hz without using a ponderous discrete device. A dual-amplifier instrumental amplifier is used to provide a low output impedance interface for ADC as well as to boost the gain. The preamplifier and the serial instrumental amplifier together provide a midband gain of 45.8 dB and have an input-referred noise of 6.7 μV rms integrated from 1 Hz to 5 kHz. The ADC digitizes the amplified signal at 12-bits precision with a highest sampling rate of 130 kS/s. The measured effective number of bits (ENOB) of the ADC is 8.7 bits. The entire circuit draws 165 to 216 μA current from the supply voltage varied from 1.34 to 3.3 V. The prototype chip is fabricated in the 0.18-μm CMOS process and occupies an area of 1.23 mm 2 (including pads). In-vitro recording was successfully carried out by the proposed frontend chip. (paper)

  9. A CMOS frontend chip for implantable neural recording with wide voltage supply range

    Science.gov (United States)

    Jialin, Liu; Xu, Zhang; Xiaohui, Hu; Yatao, Guo; Peng, Li; Ming, Liu; Bin, Li; Hongda, Chen

    2015-10-01

    A design for a CMOS frontend integrated circuit (chip) for neural signal acquisition working at wide voltage supply range is presented in this paper. The chip consists of a preamplifier, a serial instrumental amplifier (IA) and a cyclic analog-to-digital converter (CADC). The capacitive-coupled and capacitive-feedback topology combined with MOS-bipolar pseudo-resistor element is adopted in the preamplifier to create a -3 dB upper cut-off frequency less than 1 Hz without using a ponderous discrete device. A dual-amplifier instrumental amplifier is used to provide a low output impedance interface for ADC as well as to boost the gain. The preamplifier and the serial instrumental amplifier together provide a midband gain of 45.8 dB and have an input-referred noise of 6.7 μVrms integrated from 1 Hz to 5 kHz. The ADC digitizes the amplified signal at 12-bits precision with a highest sampling rate of 130 kS/s. The measured effective number of bits (ENOB) of the ADC is 8.7 bits. The entire circuit draws 165 to 216 μA current from the supply voltage varied from 1.34 to 3.3 V. The prototype chip is fabricated in the 0.18-μm CMOS process and occupies an area of 1.23 mm2 (including pads). In-vitro recording was successfully carried out by the proposed frontend chip. Project supported by the National Natural Science Foundation of China (Nos. 61474107, 61372060, 61335010, 61275200, 61178051) and the Key Program of the Chinese Academy of Sciences (No. KJZD-EW-L11-01).

  10. Optical recording of neuronal activity with a genetically-encoded calcium indicator in anesthetized and freely moving mice

    Directory of Open Access Journals (Sweden)

    Henry Lütcke

    2010-04-01

    Full Text Available Fluorescent calcium (Ca2+ indicator proteins (FCIPs are promising tools for functional imaging of cellular activity in living animals. However, they have still not reached their full potential for in vivo imaging of neuronal activity due to limitations in expression levels, dynamic range, and sensitivity for reporting action potentials. Here, we report that viral expression of the ratiometric Ca2+ sensor yellow cameleon 3.60 (YC3.60 in pyramidal neurons of mouse barrel cortex enables in vivo measurement of neuronal activity with high dynamic range and sensitivity across multiple spatial scales. By combining juxtacellular recordings and two-photon imaging in vitro and in vivo, we demonstrate that YC3.60 can resolve single action potential (AP-evoked Ca2+ transients and reliably reports bursts of APs with negligible saturation. Spontaneous and whisker-evoked Ca2+ transients were detected in individual apical dendrites and somata as well as in local neuronal populations. Moreover, bulk measurements using wide-field imaging or fiber-optics revealed sensory-evoked YC3.60 signals in large areas of the barrel field. Fiber-optic recordings in particular enabled measurements in awake, freely moving mice and revealed complex Ca2+ dynamics, possibly reflecting different behavior-related brain states. Viral expression of YC3.60 - in combination with various optical techniques - thus opens a multitude of opportunities for functional studies of the neural basis of animal behavior, from dendrites to the levels of local and large-scale neuronal populations.

  11. Toward a multipoint optical fibre sensor system for use in process water systems based on artificial neural network pattern recognition

    International Nuclear Information System (INIS)

    King, D; Lyons, W B; Flanagan, C; Lewis, E

    2005-01-01

    An optical fibre sensor capable of detecting various concentrations of ethanol in water supplies is reported. The sensor is based on a U-bend sensor configuration and is incorporated into a 170-metre length of silica cladding silica core optical fibre. The sensor is interrogated using Optical Time Domain Reflectometry (OTDR) and it is proposed to apply artificial neural network (ANN) pattern recognition techniques to the resulting OTDR signals to accurately classify the sensor test conditions. It is also proposed that additional U-bend configuration sensors will be added to the fibre measurement length, in order to implement a multipoint optical fibre sensor system

  12. Dispersion compensation of fiber optic communication system with direct detection using artificial neural networks (ANNs)

    Science.gov (United States)

    Maghrabi, Mahmoud M. T.; Kumar, Shiva; Bakr, Mohamed H.

    2018-02-01

    This work introduces a powerful digital nonlinear feed-forward equalizer (NFFE), exploiting multilayer artificial neural network (ANN). It mitigates impairments of optical communication systems arising due to the nonlinearity introduced by direct photo-detection. In a direct detection system, the detection process is nonlinear due to the fact that the photo-current is proportional to the absolute square of the electric field intensity. The proposed equalizer provides the most efficient computational cost with high equalization performance. Its performance is comparable to the benchmark compensation performance achieved by maximum-likelihood sequence estimator. The equalizer trains an ANN to act as a nonlinear filter whose impulse response removes the intersymbol interference (ISI) distortions of the optical channel. Owing to the proposed extensive training of the equalizer, it achieves the ultimate performance limit of any feed-forward equalizer (FFE). The performance and efficiency of the equalizer is investigated by applying it to various practical short-reach fiber optic communication system scenarios. These scenarios are extracted from practical metro/media access networks and data center applications. The obtained results show that the ANN-NFFE compensates for the received BER degradation and significantly increases the tolerance to the chromatic dispersion distortion.

  13. A light and faster regional convolutional neural network for object detection in optical remote sensing images

    Science.gov (United States)

    Ding, Peng; Zhang, Ye; Deng, Wei-Jian; Jia, Ping; Kuijper, Arjan

    2018-07-01

    Detection of objects from satellite optical remote sensing images is very important for many commercial and governmental applications. With the development of deep convolutional neural networks (deep CNNs), the field of object detection has seen tremendous advances. Currently, objects in satellite remote sensing images can be detected using deep CNNs. In general, optical remote sensing images contain many dense and small objects, and the use of the original Faster Regional CNN framework does not yield a suitably high precision. Therefore, after careful analysis we adopt dense convoluted networks, a multi-scale representation and various combinations of improvement schemes to enhance the structure of the base VGG16-Net for improving the precision. We propose an approach to reduce the test-time (detection time) and memory requirements. To validate the effectiveness of our approach, we perform experiments using satellite remote sensing image datasets of aircraft and automobiles. The results show that the improved network structure can detect objects in satellite optical remote sensing images more accurately and efficiently.

  14. Regulation of spindle orientation and neural stem cell fate in the Drosophila optic lobe

    Directory of Open Access Journals (Sweden)

    Brand Andrea H

    2007-01-01

    Full Text Available Abstract Background The choice of a stem cell to divide symmetrically or asymmetrically has profound consequences for development and disease. Unregulated symmetric division promotes tumor formation, whereas inappropriate asymmetric division affects organ morphogenesis. Despite its importance, little is known about how spindle positioning is regulated. In some tissues cell fate appears to dictate the type of cell division, whereas in other tissues it is thought that stochastic variation in spindle position dictates subsequent sibling cell fate. Results Here we investigate the relationship between neural progenitor identity and spindle positioning in the Drosophila optic lobe. We use molecular markers and live imaging to show that there are two populations of progenitors in the optic lobe: symmetrically dividing neuroepithelial cells and asymmetrically dividing neuroblasts. We use genetically marked single cell clones to show that neuroepithelial cells give rise to neuroblasts. To determine if a change in spindle orientation can trigger a neuroepithelial to neuroblast transition, we force neuroepithelial cells to divide along their apical/basal axis by misexpressing Inscuteable. We find that this does not induce neuroblasts, nor does it promote premature neuronal differentiation. Conclusion We show that symmetrically dividing neuroepithelial cells give rise to asymmetrically dividing neuroblasts in the optic lobe, and that regulation of spindle orientation and division symmetry is a consequence of cell type specification, rather than a mechanism for generating cell type diversity.

  15. Determination of Electron Optical Properties for Aperture Zoom Lenses Using an Artificial Neural Network Method.

    Science.gov (United States)

    Isik, Nimet

    2016-04-01

    Multi-element electrostatic aperture lens systems are widely used to control electron or charged particle beams in many scientific instruments. By means of applied voltages, these lens systems can be operated for different purposes. In this context, numerous methods have been performed to calculate focal properties of these lenses. In this study, an artificial neural network (ANN) classification method is utilized to determine the focused/unfocused charged particle beam in the image point as a function of lens voltages for multi-element electrostatic aperture lenses. A data set for training and testing of ANN is taken from the SIMION 8.1 simulation program, which is a well known and proven accuracy program in charged particle optics. Mean squared error results of this study indicate that the ANN classification method provides notable performance characteristics for electrostatic aperture zoom lenses.

  16. Ship detection in optical remote sensing images based on deep convolutional neural networks

    Science.gov (United States)

    Yao, Yuan; Jiang, Zhiguo; Zhang, Haopeng; Zhao, Danpei; Cai, Bowen

    2017-10-01

    Automatic ship detection in optical remote sensing images has attracted wide attention for its broad applications. Major challenges for this task include the interference of cloud, wave, wake, and the high computational expenses. We propose a fast and robust ship detection algorithm to solve these issues. The framework for ship detection is designed based on deep convolutional neural networks (CNNs), which provide the accurate locations of ship targets in an efficient way. First, the deep CNN is designed to extract features. Then, a region proposal network (RPN) is applied to discriminate ship targets and regress the detection bounding boxes, in which the anchors are designed by intrinsic shape of ship targets. Experimental results on numerous panchromatic images demonstrate that, in comparison with other state-of-the-art ship detection methods, our method is more efficient and achieves higher detection accuracy and more precise bounding boxes in different complex backgrounds.

  17. A CMOS IC–based multisite measuring system for stimulation and recording in neural preparations in vitro

    Directory of Open Access Journals (Sweden)

    Takashi eTateno

    2014-10-01

    Full Text Available In this report, we describe the system integration of a complementary metal oxide semiconductor (CMOS integrated circuit (IC chip, capable of both stimulation and recording of neurons or neural tissues, to investigate electrical signal propagation within cellular networks in vitro. The overall system consisted of three major subunits: a 5.0 mm × 5.0 mm CMOS IC chip, a reconfigurable logic device (field-programmable gate array, FPGA, and a PC. To test the system, microelectrode arrays (MEAs were used to extracellularly measure the activity of cultured rat cortical neurons and mouse cortical slices. The MEA had 64 bidirectional (stimulation and recording electrodes. In addition, the CMOS IC chip was equipped with dedicated analog filters, amplification stages, and a stimulation buffer. Signals from the electrodes were sampled at 15.6 kHz with 16-bit resolution. The measured input-referred circuitry noise was 10.1 μV root mean square (10 Hz to 100 kHz, which allowed reliable detection of neural signals ranging from several millivolts down to approximately 33 μVpp. Experiments were performed involving the stimulation of neurons with several spatiotemporal patterns and the recording of the triggered activity. An advantage over current MEAs, as demonstrated by our experiments, includes the ability to stimulate (voltage stimulation, 5-bit resolution spatiotemporal patterns in arbitrary subsets of electrodes. Furthermore, the fast stimulation reset mechanism allowed us to record neuronal signals from a stimulating electrode around 3 ms after stimulation. We demonstrate that the system can be directly applied to, for example, auditory neural prostheses in conjunction with an acoustic sensor and a sound processing system.

  18. Neural organisation in the first optic ganglion of the nocturnal bee Megalopta genalis.

    Science.gov (United States)

    Greiner, Birgit; Ribi, Willi A; Wcislo, William T; Warrant, Eric J

    2004-11-01

    Each neural unit (cartridge) in the first optic ganglion (lamina) of the nocturnal bee Megalopta genalis contains nine receptor cell axons (6 short and 3 long visual fibres), and four different types of first-order interneurons, also known as L-fibres (L1 to L4) or lamina monopolar cells. The short visual fibres terminate within the lamina as three different types (svf 1, 2, 3). The three long visual fibres pass through the lamina without forming characteristic branching patterns and terminate in the second optic ganglion, the medulla. The lateral branching pattern of svf 2 into adjacent cartridges is unique for hymenopterans. In addition, all four types of L-fibres show dorso-ventrally arranged, wide, lateral branching in this nocturnal bee. This is in contrast to the diurnal bees Apis mellifera and Lasioglossum leucozonium, where only two out of four L-fibre types (L2 and L4) reach neighbouring cartridges. In M. genalis, L1 forms two sub-types, viz. L1-a and L1-b; L1-b in particular has the potential to contact several neighbouring cartridges. L2 and L4 in the nocturnal bee are similar to L2 and L4 in the diurnal bees but have dorso-ventral arborisations that are twice as wide. A new type of laterally spreading L3 has been discovered in the nocturnal bee. The extensive neural branching pattern of L-fibres in M. genalis indicates a potential role for these neurons in the spatial summation of photons from large groups of ommatidia. This specific adaptation in the nocturnal bee could significantly improve reliability of vision in dim light.

  19. Microstructures and Recording Mechanism of Mo/Si Bilayer Applied for Write-Once Blue Laser Optical Recording

    Directory of Open Access Journals (Sweden)

    Sin-Liang Ou

    2014-01-01

    Full Text Available Mo/Si bilayer thin films were grown by magnetron sputtering and applied to write-once blu-ray disc (BD-R. The microstructures and optical storage properties of Mo/Si bilayer were investigated. From the temperature dependence of reflectivity measurement, it was revealed that a phase change occurred in the range of 255–425°C. Transmission electron microscopy analysis showed that the as-deposited film possessed Mo polycrystalline phase. The hexagonal MoSi2 and cubic Mo3Si phases appeared after annealing at 300 and 450°C, respectively. By measuring the optical reflectivity at a wavelength of 405 nm, the optical contrast of Mo/Si bilayer between as-deposited and 450°C-annealed states was evaluated to 25.8%. The optimum jitter value of 6.8% was obtained at 10.65 mW for 4× recording speed. The dynamic tests show that the Mo/Si bilayer has high potential in BD-R applications.

  20. Optical biopsy of head and neck cancer using hyperspectral imaging and convolutional neural networks

    Science.gov (United States)

    Halicek, Martin; Little, James V.; Wang, Xu; Patel, Mihir; Griffith, Christopher C.; El-Deiry, Mark W.; Chen, Amy Y.; Fei, Baowei

    2018-02-01

    Successful outcomes of surgical cancer resection necessitate negative, cancer-free surgical margins. Currently, tissue samples are sent to pathology for diagnostic confirmation. Hyperspectral imaging (HSI) is an emerging, non-contact optical imaging technique. A reliable optical method could serve to diagnose and biopsy specimens in real-time. Using convolutional neural networks (CNNs) as a tissue classifier, we developed a method to use HSI to perform an optical biopsy of ex-vivo surgical specimens, collected from 21 patients undergoing surgical cancer resection. Training and testing on samples from different patients, the CNN can distinguish squamous cell carcinoma (SCCa) from normal aerodigestive tract tissues with an area under the curve (AUC) of 0.82, 81% accuracy, 81% sensitivity, and 80% specificity. Additionally, normal oral tissues can be sub-classified into epithelium, muscle, and glandular mucosa using a decision tree method, with an average AUC of 0.94, 90% accuracy, 93% sensitivity, and 89% specificity. After separately training on thyroid tissue, the CNN differentiates between thyroid carcinoma and normal thyroid with an AUC of 0.95, 92% accuracy, 92% sensitivity, and 92% specificity. Moreover, the CNN can discriminate medullary thyroid carcinoma from benign multi-nodular goiter (MNG) with an AUC of 0.93, 87% accuracy, 88% sensitivity, and 85% specificity. Classical-type papillary thyroid carcinoma is differentiated from benign MNG with an AUC of 0.91, 86% accuracy, 86% sensitivity, and 86% specificity. Our preliminary results demonstrate that an HSI-based optical biopsy method using CNNs can provide multi-category diagnostic information for normal head-and-neck tissue, SCCa, and thyroid carcinomas. More patient data are needed in order to fully investigate the proposed technique to establish reliability and generalizability of the work.

  1. Polymer Optical Fiber Sensor and the Prediction of Sensor Response Utilizing Artificial Neural Networks

    Science.gov (United States)

    Haroglu, Derya

    characteristics: reproducibility, accuracy, selectivity, aging, and resolution. Artificial neural network (ANN), a mathematical model formed by mimicking the human nervous system, was used to predict the sensor response. Qwiknet (version 2.23) software was used to develop ANNs and according to the results of Qwiknet the prediction performances for training and testing data sets were 75%, and 83.33% respectively. In this dissertation, Chapter 1 describes the worldwide plastic optical fiber (POF) and fiber optic sensor markets, and the existing textile structures used in fiber optic sensing design particularly for the applications of biomedical and structural health monitoring (SHM). Chapter 2 provides a literature review in detail on polymer optical fibers, fiber optic sensors, and occupancy sensing in the passenger seats of automobiles. Chapter 3 includes the research objectives. Chapter 4 presents the response of POF to tensile loading, bending, and cyclic tensile loading with discussion parts. Chapter 5 includes an e-mail based survey to prioritize customer needs in a Quality Function Deployment (QFD) format utilizing Analytic Hierarchy Process (AHP) and survey results. Chapter 6 describes the POF sensor design and the behavior of it under pressure. Chapter 7 provides a data analysis based on the experimental results of Chapter 6. Chapter 8 presents the summary of this study and recommendations for future work.

  2. The influence of oxygen and nitrogen doping on GeSbTe phase-change optical recording media properties

    Energy Technology Data Exchange (ETDEWEB)

    Dimitrov, D.; Shieh, H.-P.D

    2004-03-15

    Nitrogen and oxygen doped and co-doped GeSbTe (GST) films for phase-change optical recording are investigated. It is found that the crystallization temperature increased as well as the crystalline microstructure refined by doping. The carrier-to-noise ratio (CNR) and erasability of phase-change optical disks are improved being up to 52 and 35 dB, respectively, by using an appropriate nitrogen doping or co-doping concentration in the recording layer. Optical disks with co-doped recording layer are found to be superior in the recording characteristics then the single doped recording layer disks.

  3. Optical processing of holographic lateral shear interferograms recorded by displacing an object

    International Nuclear Information System (INIS)

    Lyalikov, A M

    2008-01-01

    A new approach is considered which is used in holographic lateral shear interferometry and allows the combination of the displacement of a phase object under study during the recording of holographic interferograms with the optical processing of displaced and optically conjugate holographic interferograms. Depending on the method of optical processing of such a pair of holographic interferograms, several aberration-free interference patterns are observed, which reflect with different sensitivities variations in the light wave phase caused by the phase object. Due to the lateral shear, which is equal to or exceeds the linear size of the object, the interference patterns of the object are identical to interference patterns obtained in a two-beam, reference-wave interferometer. The possibility of using this method to control optical inhomogeneities in active crystals in solid-state lasers is studied experimentally. (interferometry)

  4. Optical efficiency for fission fragment track counting in Muscovite solid state track recorders

    International Nuclear Information System (INIS)

    Roberts, J.H.; Ruddy, F.H.; Gold, R.

    1984-01-01

    In order to determine absolute fission rates from thin actinide deposits placed in direct contact with Muscovite Solid State Track Recorders, it is necessary to know the efficiency with which fission fragment tracks are recorded. In this paper, a redetermination of the 'optical efficiency', i.e. the fraction of fission events recorded and observed in the Muscovite is reported. The value obtained from a well-calibrated thin deposit of 252 Cf and Muscovite etched about 90 min. in 49% HF at room temperature, is 0.9875 +- 0.0085. Manual counting was used. Preliminary results from a deposit of 242 Pu are also reported, along with preliminary comparisons of track counting with an automated system. Reasons for the discrepancy of the optical efficiency reported here with an earlier measurement are also reported. (author)

  5. Optical efficiency for fission-fragment track counting in Muscovite Solid-State Track Recorders

    International Nuclear Information System (INIS)

    Roberts, J.H.; Ruddy, F.H.; Gold, R.

    1983-07-01

    In order to determine absolute fission rates from thin actinide deposits placed in direct contact with Muscovite Solid-State Track Recorders, it is necessary to know the efficiency with which fission-fragment tracks are recorded. In this paper, a redetermination of the optical efficiency, i.e., the fraction of fission events recorded and observed in the Muscovite, is reported. The value obtained from a well-calibrated thin deposit of 252 Cf and Muscovite etched about 90 min. in 49% HF at room temperature, is 0.9875 +- 0.0085. Manual counting was used. Preliminary results from a deposit of 242 Pu are also reported, along with preliminary comparisons of track counting with an automated system. Reasons for the discrepancy of the optical efficiency reported here with an earlier measurement are also reported. 5 references, 1 figure, 3 tables

  6. Network analysis of mesoscale optical recordings to assess regional, functional connectivity.

    Science.gov (United States)

    Lim, Diana H; LeDue, Jeffrey M; Murphy, Timothy H

    2015-10-01

    With modern optical imaging methods, it is possible to map structural and functional connectivity. Optical imaging studies that aim to describe large-scale neural connectivity often need to handle large and complex datasets. In order to interpret these datasets, new methods for analyzing structural and functional connectivity are being developed. Recently, network analysis, based on graph theory, has been used to describe and quantify brain connectivity in both experimental and clinical studies. We outline how to apply regional, functional network analysis to mesoscale optical imaging using voltage-sensitive-dye imaging and channelrhodopsin-2 stimulation in a mouse model. We include links to sample datasets and an analysis script. The analyses we employ can be applied to other types of fluorescence wide-field imaging, including genetically encoded calcium indicators, to assess network properties. We discuss the benefits and limitations of using network analysis for interpreting optical imaging data and define network properties that may be used to compare across preparations or other manipulations such as animal models of disease.

  7. High-speed all-optical DNA local sequence alignment based on a three-dimensional artificial neural network.

    Science.gov (United States)

    Maleki, Ehsan; Babashah, Hossein; Koohi, Somayyeh; Kavehvash, Zahra

    2017-07-01

    This paper presents an optical processing approach for exploring a large number of genome sequences. Specifically, we propose an optical correlator for global alignment and an extended moiré matching technique for local analysis of spatially coded DNA, whose output is fed to a novel three-dimensional artificial neural network for local DNA alignment. All-optical implementation of the proposed 3D artificial neural network is developed and its accuracy is verified in Zemax. Thanks to its parallel processing capability, the proposed structure performs local alignment of 4 million sequences of 150 base pairs in a few seconds, which is much faster than its electrical counterparts, such as the basic local alignment search tool.

  8. The role of records management professionals in optical disk-based document imaging systems in the petroleum industry

    International Nuclear Information System (INIS)

    Cisco, S.L.

    1992-01-01

    Analyses of the data indicated that nearly one third of the 83 companies in this study had implemented one or more document imaging systems. Companies with imaging systems mostly were large (more than 1,001 employees), and mostly were international in scope. Although records management professionals traditionally were delegated responsibility for acquiring, designing, implementing, and maintaining paper-based information systems and the records therein, when records were converted to optical disks, responsibility for acquiring, designing, implementing, and maintaining optical disk-based information systems and the records therein, was delegated more frequently to end user departments and IS/MIS/DP professionals than to records professionals. Records management professionals assert that the need of an organization for a comprehensive records management program is not served best when individuals who are not professional records managers are responsible for the records stored in optical disk-based information systems

  9. In Vivo Recording of Neural and Behavioral Correlates of Anesthesia Induction, Reversal, and Euthanasia in Cephalopod Molluscs

    Directory of Open Access Journals (Sweden)

    Hanna M. Butler-Struben

    2018-02-01

    Full Text Available Cephalopod molluscs are among the most behaviorally and neurologically complex invertebrates. As they are now included in research animal welfare regulations in many countries, humane and effective anesthesia is required during invasive procedures. However, currently there is no evidence that agents believed to act as anesthetics produce effects beyond immobility. In this study we demonstrate, for the first time, that two of the most commonly used agents in cephalopod general anesthesia, magnesium chloride and ethanol, are capable of producing strong and reversible blockade of afferent and efferent neural signal; thus they are genuine anesthetics, rather than simply sedating agents that render animals immobile but not insensible. Additionally, we demonstrate that injected magnesium chloride and lidocaine are effective local anesthetic agents. This represents a considerable advance for cephalopod welfare. Using a reversible, minimally invasive recording procedure, we measured activity in the pallial nerve of cuttlefish (Sepia bandensis and octopus (Abdopus aculeatus, Octopus bocki, during induction and reversal for five putative general anesthetic and two local anesthetic agents. We describe the temporal relationship between loss of behavioral responses (immobility, loss of efferent neural signal (loss of “consciousness” and loss of afferent neural signal (anesthesia for general anesthesia, and loss of afferent signal for local anesthesia. Both ethanol and magnesium chloride were effective as bath-applied general anesthetics, causing immobility, complete loss of behavioral responsiveness and complete loss of afferent and efferent neural signal. Cold seawater, diethyl ether, and MS-222 (tricaine were ineffective. Subcutaneous injection of either lidocaine or magnesium chloride blocked behavioral and neural responses to pinch in the injected area, and we conclude that both are effective local anesthetic agents for cephalopods. Lastly, we

  10. In Vivo Recording of Neural and Behavioral Correlates of Anesthesia Induction, Reversal, and Euthanasia in Cephalopod Molluscs.

    Science.gov (United States)

    Butler-Struben, Hanna M; Brophy, Samantha M; Johnson, Nasira A; Crook, Robyn J

    2018-01-01

    Cephalopod molluscs are among the most behaviorally and neurologically complex invertebrates. As they are now included in research animal welfare regulations in many countries, humane and effective anesthesia is required during invasive procedures. However, currently there is no evidence that agents believed to act as anesthetics produce effects beyond immobility. In this study we demonstrate, for the first time, that two of the most commonly used agents in cephalopod general anesthesia, magnesium chloride and ethanol, are capable of producing strong and reversible blockade of afferent and efferent neural signal; thus they are genuine anesthetics, rather than simply sedating agents that render animals immobile but not insensible. Additionally, we demonstrate that injected magnesium chloride and lidocaine are effective local anesthetic agents. This represents a considerable advance for cephalopod welfare. Using a reversible, minimally invasive recording procedure, we measured activity in the pallial nerve of cuttlefish ( Sepia bandensis ) and octopus ( Abdopus aculeatus, Octopus bocki ), during induction and reversal for five putative general anesthetic and two local anesthetic agents. We describe the temporal relationship between loss of behavioral responses (immobility), loss of efferent neural signal (loss of "consciousness") and loss of afferent neural signal (anesthesia) for general anesthesia, and loss of afferent signal for local anesthesia. Both ethanol and magnesium chloride were effective as bath-applied general anesthetics, causing immobility, complete loss of behavioral responsiveness and complete loss of afferent and efferent neural signal. Cold seawater, diethyl ether, and MS-222 (tricaine) were ineffective. Subcutaneous injection of either lidocaine or magnesium chloride blocked behavioral and neural responses to pinch in the injected area, and we conclude that both are effective local anesthetic agents for cephalopods. Lastly, we demonstrate that a

  11. Cell death in neural precursor cells and neurons before neurite formation prevents the emergence of abnormal neural structures in the Drosophila optic lobe.

    Science.gov (United States)

    Hara, Yusuke; Sudo, Tatsuya; Togane, Yu; Akagawa, Hiromi; Tsujimura, Hidenobu

    2018-04-01

    Programmed cell death is a conserved strategy for neural development both in vertebrates and invertebrates and is recognized at various developmental stages in the brain from neurogenesis to adulthood. To understand the development of the central nervous system, it is essential to reveal not only molecular mechanisms but also the role of neural cell death (Pinto-Teixeira et al., 2016). To understand the role of cell death in neural development, we investigated the effect of inhibition of cell death on optic lobe development. Our data demonstrate that, in the optic lobe of Drosophila, cell death occurs in neural precursor cells and neurons before neurite formation and functions to prevent various developmental abnormalities. When neuronal cell death was inhibited by an effector caspase inhibitor, p35, multiple abnormal neuropil structures arose during optic lobe development-e.g., enlarged or fused neuropils, misrouted neurons and abnormal neurite lumps. Inhibition of cell death also induced morphogenetic defects in the lamina and medulla development-e.g., failures in the separation of the lamina and medulla cortices and the medulla rotation. These defects were reproduced in the mutant of an initiator caspase, dronc. If cell death was a mechanism for removing the abnormal neuropil structures, we would also expect to observe them in mutants defective for corpse clearance. However, they were not observed in these mutants. When dead cell-membranes were visualized with Apoliner, they were observed only in cortices and not in neuropils. These results suggest that the cell death occurs before mature neurite formation. Moreover, we found that inhibition of cell death induced ectopic neuroepithelial cells, neuroblasts and ganglion mother cells in late pupal stages, at sites where the outer and inner proliferation centers were located at earlier developmental stages. Caspase-3 activation was observed in the neuroepithelial cells and neuroblasts in the proliferation centers

  12. Adaptive quantization of local field potentials for wireless implants in freely moving animals: an open-source neural recording device

    Science.gov (United States)

    Martinez, Dominique; Clément, Maxime; Messaoudi, Belkacem; Gervasoni, Damien; Litaudon, Philippe; Buonviso, Nathalie

    2018-04-01

    Objective. Modern neuroscience research requires electrophysiological recording of local field potentials (LFPs) in moving animals. Wireless transmission has the advantage of removing the wires between the animal and the recording equipment but is hampered by the large number of data to be sent at a relatively high rate. Approach. To reduce transmission bandwidth, we propose an encoder/decoder scheme based on adaptive non-uniform quantization. Our algorithm uses the current transmitted codeword to adapt the quantization intervals to changing statistics in LFP signals. It is thus backward adaptive and does not require the sending of side information. The computational complexity is low and similar at the encoder and decoder sides. These features allow for real-time signal recovery and facilitate hardware implementation with low-cost commercial microcontrollers. Main results. As proof-of-concept, we developed an open-source neural recording device called NeRD. The NeRD prototype digitally transmits eight channels encoded at 10 kHz with 2 bits per sample. It occupies a volume of 2  ×  2  ×  2 cm3 and weighs 8 g with a small battery allowing for 2 h 40 min of autonomy. The power dissipation is 59.4 mW for a communication range of 8 m and transmission losses below 0.1%. The small weight and low power consumption offer the possibility of mounting the entire device on the head of a rodent without resorting to a separate head-stage and battery backpack. The NeRD prototype is validated in recording LFPs in freely moving rats at 2 bits per sample while maintaining an acceptable signal-to-noise ratio (>30 dB) over a range of noisy channels. Significance. Adaptive quantization in neural implants allows for lower transmission bandwidths while retaining high signal fidelity and preserving fundamental frequencies in LFPs.

  13. The design and optimization of disk structures for MAMMOS/MSR magneto-optic recording

    International Nuclear Information System (INIS)

    Hendren, W R; Atkinson, R; Pollard, R J; Salter, I W; Wright, C D; Clegg, W W; Jenkins, D F L

    2005-01-01

    Existing quadrilayer and trilayer techniques for optimizing the magneto-optical effects from magnetic materials have been applied to new generation recording media to investigate the possibility of maximizing the signal-to-noise readout performance. Various methods are reviewed and the designs they produce are compared with each other and with the working media found in the literature. In order to address a number of inadequacies, a new numerical approach to the optimization of a quadrilayer structure is used to find further solutions that are considered more suitable for the practical recording media. The effects on design and performance of medium of incidence, type of storage layer and wavelength are all considered

  14. Enhancement of the measurement sensitivity at large aberrations of an optical system of hologram recording

    International Nuclear Information System (INIS)

    Lyalikov, A.M.

    1994-01-01

    The method of the measurement sensitivity enhancement with compensation of aberrations based on rewriting object and master holograms recorded on one common carrier using the double-exposure method is considered. Experimental studies indicated the proposed technique of the enhancement of the measurement sensitivity to be promising in the case of large aberrations of an optical system for initial hologram recording. The reconstructed interferograms are presented with enhanced sensitivity of measurements by a factor of 16 characterizing the quality of exit windows of a glass cuvette. 16 refs., 3 figs

  15. Acoustical holographic recording with coherent optical read-out and image processing

    Science.gov (United States)

    Liu, H. K.

    1980-10-01

    New acoustic holographic wave memory devices have been designed for real-time in-situ recording applications. The basic operating principles of these devices and experimental results through the use of some of the prototypes of the devices are presented. Recording media used in the device include thermoplastic resin, Crisco vegetable oil, and Wilson corn oil. In addition, nonlinear coherent optical image processing techniques including equidensitometry, A-D conversion, and pseudo-color, all based on the new contact screen technique, are discussed with regard to the enhancement of the normally poor-resolved acoustical holographic images.

  16. The design and optimization of disk structures for MAMMOS/MSR magneto-optic recording

    Energy Technology Data Exchange (ETDEWEB)

    Hendren, W R [School of Mathematics and Physics, Queen' s University Belfast, Belfast BT7 1NN (United Kingdom); Atkinson, R [School of Mathematics and Physics, Queen' s University Belfast, Belfast BT7 1NN (United Kingdom); Pollard, R J [School of Mathematics and Physics, Queen' s University Belfast, Belfast BT7 1NN (United Kingdom); Salter, I W [School of Mathematics and Physics, Queen' s University Belfast, Belfast BT7 1NN (United Kingdom); Wright, C D [School of Engineering and Computer Science, University of Exeter, Exeter EX4 4QF (United Kingdom); Clegg, W W [Centre for Research in Information Storage Technology, University of Plymouth, Plymouth PL4 8AA (United Kingdom); Jenkins, D F L [Centre for Research in Information Storage Technology, University of Plymouth, Plymouth PL4 8AA (United Kingdom)

    2005-07-21

    Existing quadrilayer and trilayer techniques for optimizing the magneto-optical effects from magnetic materials have been applied to new generation recording media to investigate the possibility of maximizing the signal-to-noise readout performance. Various methods are reviewed and the designs they produce are compared with each other and with the working media found in the literature. In order to address a number of inadequacies, a new numerical approach to the optimization of a quadrilayer structure is used to find further solutions that are considered more suitable for the practical recording media. The effects on design and performance of medium of incidence, type of storage layer and wavelength are all considered.

  17. Developing a Mixed Neural Network Approach to Forecast the Residential Electricity Consumption Based on Sensor Recorded Data.

    Science.gov (United States)

    Oprea, Simona-Vasilica; Pîrjan, Alexandru; Căruțașu, George; Petroșanu, Dana-Mihaela; Bâra, Adela; Stănică, Justina-Lavinia; Coculescu, Cristina

    2018-05-05

    In this paper, we report a study having as a main goal the obtaining of a method that can provide an accurate forecast of the residential electricity consumption, refining it up to the appliance level, using sensor recorded data, for residential smart homes complexes that use renewable energy sources as a part of their consumed electricity, overcoming the limitations of not having available historical meteorological data and the unwillingness of the contractor to acquire such data periodically in the future accurate short-term forecasts from a specialized institute due to the implied costs. In this purpose, we have developed a mixed artificial neural network (ANN) approach using both non-linear autoregressive with exogenous input (NARX) ANNs and function fitting neural networks (FITNETs). We have used a large dataset containing detailed electricity consumption data recorded by sensors, monitoring a series of individual appliances, while in the NARX case we have also used timestamps datasets as exogenous variables. After having developed and validated the forecasting method, we have compiled it in view of incorporating it into a cloud solution, being delivered to the contractor that can provide it as a service for a monthly fee to both the operators and residential consumers.

  18. Chemically deposited Sb2S3 thin films for optical recording

    International Nuclear Information System (INIS)

    Shaji, S; Arato, A; Castillo, G Alan; Palma, M I Mendivil; Roy, T K Das; Krishnan, B; O'Brien, J J; Liu, J

    2010-01-01

    Laser induced changes in the properties of Sb 2 S 3 thin films prepared by chemical bath deposition are described in this paper. Sb 2 S 3 thin films of thickness 550 nm were deposited from a solution containing SbCl 3 and Na 2 S 2 O 3 at 27 0 C for 5 h. These thin films were irradiated by a 532 nm continuous wave laser beam under different conditions at ambient atmosphere. X-ray diffraction analysis showed amorphous to polycrystalline transformation due to laser exposure of these thin films. Morphology and composition of these films were described. Optical properties of these films before and after laser irradiation were analysed. The optical band gap of the material was decreased due to laser induced crystallization. The results obtained confirm that there is further scope for developing this material as an optical recording media.

  19. Chemically deposited Sb{sub 2}S{sub 3} thin films for optical recording

    Energy Technology Data Exchange (ETDEWEB)

    Shaji, S; Arato, A; Castillo, G Alan; Palma, M I Mendivil; Roy, T K Das; Krishnan, B [Facultad de IngenierIa Mecanica y Electrica, Universidad Autonoma de Nuevo Leon, San Nicolas de los Garza, Nuevo Leon, C.P- 66450 (Mexico); O' Brien, J J; Liu, J, E-mail: bkrishnan@fime.uanl.m [Center for Nanoscience and Department of Chemistry and Biochemistry, University of Missouri-St. Louis, One Univ. Blvd., St. Louis, MO - 63121 (United States)

    2010-02-24

    Laser induced changes in the properties of Sb{sub 2}S{sub 3} thin films prepared by chemical bath deposition are described in this paper. Sb{sub 2}S{sub 3} thin films of thickness 550 nm were deposited from a solution containing SbCl{sub 3} and Na{sub 2}S{sub 2}O{sub 3} at 27 {sup 0}C for 5 h. These thin films were irradiated by a 532 nm continuous wave laser beam under different conditions at ambient atmosphere. X-ray diffraction analysis showed amorphous to polycrystalline transformation due to laser exposure of these thin films. Morphology and composition of these films were described. Optical properties of these films before and after laser irradiation were analysed. The optical band gap of the material was decreased due to laser induced crystallization. The results obtained confirm that there is further scope for developing this material as an optical recording media.

  20. Solvent-free optical recording of structural colours on pre-imprinted photocrosslinkable nanostructures

    Science.gov (United States)

    Jiang, Hao; Rezaei, Mohamad; Abdolahi, Mahssa; Kaminska, Bozena

    2017-09-01

    Optical digital information storage media, despite their ever-increasing storage capacity and data transfer rate, are vulnerable to the potential risk of turning inaccessible. For this reason, long-term eye-readable full-colour optical archival storage is in high demand for preserving valuable information from cultural, intellectual, and scholarly resources. However, the concurrent requirements in recording colours inexpensively and precisely, and preserving colours for the very long term (for at least 100 years), have not yet been met by existing storage techniques. Structural colours hold the promise to overcome such challenges. However, there is still the lack of an inexpensive, rapid, reliable, and solvent-free optical patterning technique for recording structural colours. In this paper, we introduce an enabling technique based on optical and thermal patterning of nanoimprinted SU-8 nanocone arrays. Using photocrosslinking and thermoplastic flow of SU-8, diffractive structural colours of nanocone arrays are recorded using ultra-violet (UV) exposure followed by the thermal development and reshaping of nanocones. Different thermal treatment procedures in reshaping nanocones are investigated and compared, and two-step progressive baking is found to allow the controllable reshaping of nanocones. The height of the nanocones and brightness of diffractive colours are modulated by varying the UV exposure dose to enable grey-scale patterning. An example of recorded full-colour image through half-tone patterning is also demonstrated. The presented technique requires only low-power continuous-wave UV light and is very promising to be adopted for professional and consumer archival storage applications.

  1. Single-intensity-recording optical encryption technique based on phase retrieval algorithm and QR code

    Science.gov (United States)

    Wang, Zhi-peng; Zhang, Shuai; Liu, Hong-zhao; Qin, Yi

    2014-12-01

    Based on phase retrieval algorithm and QR code, a new optical encryption technology that only needs to record one intensity distribution is proposed. In this encryption process, firstly, the QR code is generated from the information to be encrypted; and then the generated QR code is placed in the input plane of 4-f system to have a double random phase encryption. For only one intensity distribution in the output plane is recorded as the ciphertext, the encryption process is greatly simplified. In the decryption process, the corresponding QR code is retrieved using phase retrieval algorithm. A priori information about QR code is used as support constraint in the input plane, which helps solve the stagnation problem. The original information can be recovered without distortion by scanning the QR code. The encryption process can be implemented either optically or digitally, and the decryption process uses digital method. In addition, the security of the proposed optical encryption technology is analyzed. Theoretical analysis and computer simulations show that this optical encryption system is invulnerable to various attacks, and suitable for harsh transmission conditions.

  2. Classification of Antarctic algae by applying Kohonen neural network with 14 elements determined by inductively coupled plasma optical emission spectrometry

    Energy Technology Data Exchange (ETDEWEB)

    Balbinot, L. [Departamento de Quimica Analitica-Instituto de Quimica-Unicamp, PO Box 6154, CEP: 13083-971, Campinas, SP (Brazil); Smichowski, P. [Comision Nacional de Energia Atomica, Unidad de Actividad Quimica, Centro Atomico Constituyentes, Av. Gral Paz 1499, B1650KNA, San Martin, Provincia de Buenos Aires (Argentina); Farias, S. [Comision Nacional de Energia Atomica, Unidad de Actividad Quimica, Centro Atomico Constituyentes, Av. Gral Paz 1499, B1650KNA, San Martin, Provincia de Buenos Aires (Argentina); Arruda, M.A.Z. [Departamento de Quimica Analitica-Instituto de Quimica-Unicamp, PO Box 6154, CEP: 13083-971, Campinas, SP (Brazil); Vodopivez, C. [Instituto Antartico Argentino, Cerrito 1010, C1248AAZ, Buenos Aires (Argentina); Poppi, R.J. [Departamento de Quimica Analitica-Instituto de Quimica-Unicamp, PO Box 6154, CEP: 13083-971, Campinas, SP (Brazil)]. E-mail: ronei@iqm.unicamp.br

    2005-06-30

    Optical emission spectrometers can generate results, which sometimes are not easy to interpret, mainly when the analyses involve classifications. To make simultaneous data interpretation possible, the Kohonen neural network is used to classify different Antarctic algae according to their taxonomic groups from the determination of 14 analytes. The Kohonen neural network architecture used was 5x5 neurons, thus reducing 14-dimension input data to two-dimensional space. The input data were 14 analytes (As, Co, Cu, Fe, Mn, Sr, Zn, Cd, Cr, Mo, Ni, Pb, Se, V) with their concentrations, determined by inductively coupled plasma optical emission spectrometry in 11 different species of algae. Three taxonomic groups (Rhodophyta, Phaeophyta and Cholorophyta) can be differentiated and classified through only their Cu content.

  3. Modal demultiplexing properties of tapered and nanostructured optical fibers for in vivo optogenetic control of neural activity.

    Science.gov (United States)

    Pisanello, Marco; Della Patria, Andrea; Sileo, Leonardo; Sabatini, Bernardo L; De Vittorio, Massimo; Pisanello, Ferruccio

    2015-10-01

    Optogenetic approaches to manipulate neural activity have revolutionized the ability of neuroscientists to uncover the functional connectivity underlying brain function. At the same time, the increasing complexity of in vivo optogenetic experiments has increased the demand for new techniques to precisely deliver light into the brain, in particular to illuminate selected portions of the neural tissue. Tapered and nanopatterned gold-coated optical fibers were recently proposed as minimally invasive multipoint light delivery devices, allowing for site-selective optogenetic stimulation in the mammalian brain [Pisanello , Neuron82, 1245 (2014)]. Here we demonstrate that the working principle behind these devices is based on the mode-selective photonic properties of the fiber taper. Using analytical and ray tracing models we model the finite conductance of the metal coating, and show that single or multiple optical windows located at specific taper sections can outcouple only specific subsets of guided modes injected into the fiber.

  4. Classification of Antarctic algae by applying Kohonen neural network with 14 elements determined by inductively coupled plasma optical emission spectrometry

    International Nuclear Information System (INIS)

    Balbinot, L.; Smichowski, P.; Farias, S.; Arruda, M.A.Z.; Vodopivez, C.; Poppi, R.J.

    2005-01-01

    Optical emission spectrometers can generate results, which sometimes are not easy to interpret, mainly when the analyses involve classifications. To make simultaneous data interpretation possible, the Kohonen neural network is used to classify different Antarctic algae according to their taxonomic groups from the determination of 14 analytes. The Kohonen neural network architecture used was 5x5 neurons, thus reducing 14-dimension input data to two-dimensional space. The input data were 14 analytes (As, Co, Cu, Fe, Mn, Sr, Zn, Cd, Cr, Mo, Ni, Pb, Se, V) with their concentrations, determined by inductively coupled plasma optical emission spectrometry in 11 different species of algae. Three taxonomic groups (Rhodophyta, Phaeophyta and Cholorophyta) can be differentiated and classified through only their Cu content

  5. An implantable two axis micromanipulator made with a 3D printer for recording neural activity in free-swimming fish.

    Science.gov (United States)

    Rogers, Loranzie S; Van Wert, Jacey C; Mensinger, Allen F

    2017-08-15

    Chronically implanted electrodes allow monitoring neural activity from free moving animals. While a wide variety of implanted headstages, microdrives and electrodes exist for terrestrial animals, few have been developed for use with aquatic animals. A two axis micromanipulator was fabricated with a Formlabs 3D printer for implanting electrodes into free-swimming oyster toadfish (Opsanus tau). The five piece manipulator consisted of a base, body, electrode holder, manual screw drive and locking nut. The manipulator measured approximately 25×20×30mm (l×w×h) and weighed 5.28g after hand assembly. Microwire electrodes were inserted successfully with the manipulator to record high fidelity signals from the anterior lateral line nerve of the toadfish. The micromanipulator allowed the chronically implanted electrodes to be repositioned numerous times to record from multiple sites and extended successful recording time in the toadfish by several days. Three dimensional printing allowed an inexpensive (<$US 5 material), two axis micromanipulator to be printed relatively rapidly (<2h) to successfully record from multiple sites in the anterior lateral line nerve of free-swimming toadfish. Copyright © 2017 Elsevier B.V. All rights reserved.

  6. Illusions in the spatial sense of the eye: geometrical-optical illusions and the neural representation of space.

    Science.gov (United States)

    Westheimer, Gerald

    2008-09-01

    Differences between the geometrical properties of simple configurations and their visual percept are called geometrical-optical illusions. They can be differentiated from illusions in the brightness or color domains, from ambiguous figures and impossible objects, from trompe l'oeil and perspective drawing with perfectly valid views, and from illusory contours. They were discovered independently by several scientists in a short time span in the 1850's. The clear distinction between object and visual space that they imply allows the question to be raised whether the transformation between the two spaces can be productively investigated in terms of differential geometry and metrical properties. Perceptual insight and psychophysical research prepares the ground for investigation of the neural representation of space but, because visual attributes are processed separately in parallel, one looks in vain for a neural map that is isomorphic with object space or even with individual forms it contains. Geometrical-optical illusions help reveal parsing rules for sensory signals by showing how conflicts are resolved when there is mismatch in the output of the processing modules for various primitives as a perceptual pattern's unitary structure is assembled. They point to a hierarchical ordering of spatial primitives: cardinal directions and explicit contours predominate over oblique orientation and implicit contours (Poggendorff illusion); rectilinearity yields to continuity (Hering illusion), point position and line length to contour orientation (Ponzo). Hence the geometrical-optical illusions show promise as analytical tools in unraveling neural processing in vision.

  7. Development of an optical character recognition pipeline for handwritten form fields from an electronic health record.

    Science.gov (United States)

    Rasmussen, Luke V; Peissig, Peggy L; McCarty, Catherine A; Starren, Justin

    2012-06-01

    Although the penetration of electronic health records is increasing rapidly, much of the historical medical record is only available in handwritten notes and forms, which require labor-intensive, human chart abstraction for some clinical research. The few previous studies on automated extraction of data from these handwritten notes have focused on monolithic, custom-developed recognition systems or third-party systems that require proprietary forms. We present an optical character recognition processing pipeline, which leverages the capabilities of existing third-party optical character recognition engines, and provides the flexibility offered by a modular custom-developed system. The system was configured and run on a selected set of form fields extracted from a corpus of handwritten ophthalmology forms. The processing pipeline allowed multiple configurations to be run, with the optimal configuration consisting of the Nuance and LEADTOOLS engines running in parallel with a positive predictive value of 94.6% and a sensitivity of 13.5%. While limitations exist, preliminary experience from this project yielded insights on the generalizability and applicability of integrating multiple, inexpensive general-purpose third-party optical character recognition engines in a modular pipeline.

  8. Beyond the neuropsychology of dreaming: Insights into the neural basis of dreaming with new techniques of sleep recording and analysis.

    Science.gov (United States)

    Cipolli, Carlo; Ferrara, Michele; De Gennaro, Luigi; Plazzi, Giuseppe

    2017-10-01

    Recent advances in electrophysiological [e.g., surface high-density electroencephalographic (hd-EEG) and intracranial recordings], video-polysomnography (video-PSG), transcranial stimulation and neuroimaging techniques allow more in-depth and more accurate investigation of the neural correlates of dreaming in healthy individuals and in patients with brain-damage, neurodegenerative diseases, sleep disorders or parasomnias. Convergent evidence provided by studies using these techniques in healthy subjects has led to a reformulation of several unresolved issues of dream generation and recall [such as the inter- and intra-individual differences in dream recall and the predictivity of specific EEG rhythms, such as theta in rapid eye movement (REM) sleep, for dream recall] within more comprehensive models of human consciousness and its variations across sleep/wake states than the traditional models, which were largely based on the neurophysiology of REM sleep in animals. These studies are casting new light on the neural bases (in particular, the activity of dorsal medial prefrontal cortex regions and hippocampus and amygdala areas) of the inter- and intra-individual differences in dream recall, the temporal location of specific contents or properties (e.g., lucidity) of dream experience and the processing of memories accessed during sleep and incorporated into dream content. Hd-EEG techniques, used on their own or in combination with neuroimaging, appear able to provide further important insights into how the brain generates not only dreaming during sleep but also some dreamlike experiences in waking. Copyright © 2016 Elsevier Ltd. All rights reserved.

  9. Selectivity of recording of neural signals with micromachined intraneural micro electrodes

    NARCIS (Netherlands)

    Rutten, Wim; Rozijn, T.H.; Rozijn, Tom H.; Meier, J.H.; Meier, Jan H.

    1993-01-01

    The number uf afferent fibers in a peripheral nerve fascicle and the electrical volume conduction in neuraI tissue determine the interelectrode spacing, needed for selective recording with mufticontact devices. These factors taking into account, and also assuming uniform distribution of fibers

  10. A CMOS power-efficient low-noise current-mode front-end amplifier for neural signal recording.

    Science.gov (United States)

    Wu, Chung-Yu; Chen, Wei-Ming; Kuo, Liang-Ting

    2013-04-01

    In this paper, a new current-mode front-end amplifier (CMFEA) for neural signal recording systems is proposed. In the proposed CMFEA, a current-mode preamplifier with an active feedback loop operated at very low frequency is designed as the first gain stage to bypass any dc offset current generated by the electrode-tissue interface and to achieve a low high-pass cutoff frequency below 0.5 Hz. No reset signal or ultra-large pseudo resistor is required. The current-mode preamplifier has low dc operation current to enhance low-noise performance and decrease power consumption. A programmable current gain stage is adopted to provide adjustable gain for adaptive signal scaling. A following current-mode filter is designed to adjust the low-pass cutoff frequency for different neural signals. The proposed CMFEA is designed and fabricated in 0.18-μm CMOS technology and the area of the core circuit is 0.076 mm(2). The measured high-pass cutoff frequency is as low as 0.3 Hz and the low-pass cutoff frequency is adjustable from 1 kHz to 10 kHz. The measured maximum current gain is 55.9 dB. The measured input-referred current noise density is 153 fA /√Hz , and the power consumption is 13 μW at 1-V power supply. The fabricated CMFEA has been successfully applied to the animal test for recording the seizure ECoG of Long-Evan rats.

  11. A dual slope charge sampling analog front-end for a wireless neural recording system.

    Science.gov (United States)

    Lee, Seung Bae; Lee, Byunghun; Gosselin, Benoit; Ghovanloo, Maysam

    2014-01-01

    This paper presents a novel dual slope charge sampling (DSCS) analog front-end (AFE) architecture, which amplifies neural signals by taking advantage of the charge sampling concept for analog signal conditioning, such as amplification and filtering. The presented DSCS-AFE achieves amplification, filtering, and sampling in a simultaneous fashion, while consuming very small amount of power. The output of the DSCS-AFE produces a pulse width modulated (PWM) signal that is proportional to the input voltage amplitude. A circular shift register (CSR) utilizes time division multiplexing (TDM) of the PWM pulses to create a pseudo-digital TDM-PWM signal that can feed a wireless transmitter. The 8-channel system-on-a-chip was fabricated in a 0.35-μm CMOS process, occupying 2.4 × 2.1 mm(2) and consuming 255 μW from a 1.8V supply. Measured input-referred noise for the entire system, including the FPGA in order to recover PWM signal is 6.50 μV(rms) in the 288 Hz~10 kHz range. For each channel, sampling rate is 31.25 kHz, and power consumption is 31.8 μW.

  12. NOAA JPSS Visible Infrared Imaging Radiometer Suite (VIIRS) Nighttime Cloud Optical Microphysical Properties (NCOMP) Environmental Data Record (EDR) from NDE

    Data.gov (United States)

    National Oceanic and Atmospheric Administration, Department of Commerce — This data set contains a high quality Environmental Data Record (EDR) of nighttime cloud optical and microphysical properties (NCOMP) from the Visible Infrared...

  13. NOAA JPSS Visible Infrared Imaging Radiometer Suite (VIIRS) Cloud Optical Thickness (COT) Environmental Data Record (EDR) from IDPS

    Data.gov (United States)

    National Oceanic and Atmospheric Administration, Department of Commerce — This dataset contains a high quality operational Environmental Data Record (EDR) of Cloud Optical Thickness (COT) from the Visible Infrared Imaging Radiometer Suite...

  14. Linear-regression convolutional neural network for fully automated coronary lumen segmentation in intravascular optical coherence tomography.

    Science.gov (United States)

    Yong, Yan Ling; Tan, Li Kuo; McLaughlin, Robert A; Chee, Kok Han; Liew, Yih Miin

    2017-12-01

    Intravascular optical coherence tomography (OCT) is an optical imaging modality commonly used in the assessment of coronary artery diseases during percutaneous coronary intervention. Manual segmentation to assess luminal stenosis from OCT pullback scans is challenging and time consuming. We propose a linear-regression convolutional neural network to automatically perform vessel lumen segmentation, parameterized in terms of radial distances from the catheter centroid in polar space. Benchmarked against gold-standard manual segmentation, our proposed algorithm achieves average locational accuracy of the vessel wall of 22 microns, and 0.985 and 0.970 in Dice coefficient and Jaccard similarity index, respectively. The average absolute error of luminal area estimation is 1.38%. The processing rate is 40.6 ms per image, suggesting the potential to be incorporated into a clinical workflow and to provide quantitative assessment of vessel lumen in an intraoperative time frame. (2017) COPYRIGHT Society of Photo-Optical Instrumentation Engineers (SPIE).

  15. Feature extraction for magnetic domain images of magneto-optical recording films using gradient feature segmentation

    International Nuclear Information System (INIS)

    Quanqing, Zhu.; Xinsai, Wang; Xuecheng, Zou; Haihua, Li; Xiaofei, Yang

    2002-01-01

    In this paper, we present a method to realize feature extraction on low contrast magnetic domain images of magneto-optical recording films. The method is based on the following three steps: first, Lee-filtering method is adopted to realize pre-filtering and noise reduction; this is followed by gradient feature segmentation, which separates the object area from the background area; finally the common linking method is adopted and the characteristic parameters of magnetic domain are calculated. We describe these steps with particular emphasis on the gradient feature segmentation. The results show that this method has advantages over other traditional ones for feature extraction of low contrast images

  16. Reactively sputtered TeO/sub x/ thin films for optical recording systems

    International Nuclear Information System (INIS)

    Di Giulio, M.; Micocci, G.; Rella, R.; Tepore, A.

    1988-01-01

    Tellurium suboxide (TeO/sub x/ ) thin films have been obtained by rf reactive sputtering deposition by using a Te target and an Ar--O 2 gas mixture. Different samples were prepared by changing both the rf power (80--200 W) and the oxygen concentration in the sputtering gas. The transmissivity and the reflectivity of these films change markedly by thermal treatment at critical temperatures in the range 120--150 0 C. This property makes these films suitable for optical disk recording with a low-output power laser diode

  17. Modulated error diffusion CGHs for neural nets

    Science.gov (United States)

    Vermeulen, Pieter J. E.; Casasent, David P.

    1990-05-01

    New modulated error diffusion CGHs (computer generated holograms) for optical computing are considered. Specific attention is given to their use in optical matrix-vector, associative processor, neural net and optical interconnection architectures. We consider lensless CGH systems (many CGHs use an external Fourier transform (FT) lens), the Fresnel sampling requirements, the effects of finite CGH apertures (sample and hold inputs), dot size correction (for laser recorders), and new applications for this novel encoding method (that devotes attention to quantization noise effects).

  18. An integrated multichannel neural recording analog front-end ASIC with area-efficient driven right leg circuit.

    Science.gov (United States)

    Tao Tang; Wang Ling Goh; Lei Yao; Jia Hao Cheong; Yuan Gao

    2017-07-01

    This paper describes an integrated multichannel neural recording analog front end (AFE) with a novel area-efficient driven right leg (DRL) circuit to improve the system common mode rejection ratio (CMRR). The proposed AFE consists of an AC-coupled low-noise programmable-gain amplifier, an area-efficient DRL block and a 10-bit SAR ADC. Compared to conventional DRL circuit, the proposed capacitor-less DRL design achieves 90% chip area reduction with enhanced CMRR performance, making it ideal for multichannel biomedical recording applications. The AFE circuit has been designed in a standard 0.18-μm CMOS process. Post-layout simulation results show that the AFE provides two gain settings of 54dB/60dB while consuming 1 μA per channel under a supply voltage of 1 V. The input-referred noise of the AFE integrated from 1 Hz to 10k Hz is only 4 μVrms and the CMRR is 110 dB.

  19. Extension and statistical analysis of the GACP aerosol optical thickness record

    Science.gov (United States)

    Geogdzhayev, Igor V.; Mishchenko, Michael I.; Li, Jing; Rossow, William B.; Liu, Li; Cairns, Brian

    2015-10-01

    The primary product of the Global Aerosol Climatology Project (GACP) is a continuous record of the aerosol optical thickness (AOT) over the oceans. It is based on channel-1 and -2 radiance data from the Advanced Very High Resolution Radiometer (AVHRR) instruments flown on successive National Oceanic and Atmospheric Administration (NOAA) platforms. We extend the previous GACP dataset by four years through the end of 2009 using NOAA-17 and -18 AVHRR radiances recalibrated against MODerate resolution Imaging Spectroradiometer (MODIS) radiance data, thereby making the GACP record almost three decades long. The temporal overlap of over three years of the new NOAA-17 and the previous NOAA-16 record reveals an excellent agreement of the corresponding global monthly mean AOT values, thereby confirming the robustness of the vicarious radiance calibration used in the original GACP product. The temporal overlap of the NOAA-17 and -18 instruments is used to introduce a small additive adjustment to the channel-2 calibration of the latter resulting in a consistent record with increased data density. The Principal Component Analysis (PCA) of the newly extended GACP record shows that most of the volcanic AOT variability can be isolated into one mode responsible for ~ 12% of the total variance. This conclusion is confirmed by a combined PCA analysis of the GACP, MODIS, and Multi-angle Imaging SpectroRadiometer (MISR) AOTs during the volcano-free period from February 2000 to December 2009. We show that the modes responsible for the tropospheric AOT variability in the three datasets agree well in terms of correlation and spatial patterns. A previously identified negative AOT trend which started in the late 1980s and continued into the early 2000s is confirmed. Its magnitude and duration indicate that it was caused by changes in tropospheric aerosols. The latest multi-satellite segment of the GACP record shows that this trend tapered off, with no noticeable AOT change after 2002. This

  20. Fatigue Property of Oxidized Photochromic Dithienylethene Derivative for Permanent Optical Recording

    International Nuclear Information System (INIS)

    Jeong, Yong Chul; Ahn, Kwang Hyun; Yang, Sung Ik; Kim, Eun Kyoung

    2005-01-01

    We have synthesized and characterized the photophysical and fatigue properties of DMTFO4. The results have shown that the photo-stability of DMTFO4 was significantly decreased compared with the unoxidized DMTF6. The possible application of DMTFO4 would be the development of permanent recording material based on a non-reversible photochromic conversion. Photochromic diarylethenes, such as 1,2-bis(2-methyl-1-benzothiophene-3-yl)perfluorocyclopentene (BTF6) and 1,2-bis(2,5-dimethylthien-3-yl)perfluorocyclopentene (DMTF6), have been extensively investigated in recent years in order to develop materials for molecular photonic devices such as optical memory and switch. In the design of photochromic materials, thermal stability and fatigue resistant are important features to be considered. The thiophene analogues undergo photochromic ring closure efficiently but the fatigue property is generally low, resulting irreversible photochromism. If the photochromism is in an irreversible manner it could be applied in the permanent optical recording such as write once read many (WORM) memory. This motivates us to examine the effect of oxidation in the photophysical properties of diarylethenes with thiophene unit. As the thiophene analogues, we chose DMTF6 and its oxidized analogue, 1,2-bis(2,5-dimethylthien-1,1-dioxide-3-yl)perfluorocyclopentene (DMTFO4). Herein we report the synthesis and characterization of the photochromic properties including the fatigue property of DMTFO4

  1. All-optical recording and stimulation of retinal neurons in vivo in retinal degeneration mice

    Science.gov (United States)

    Strazzeri, Jennifer M.; Williams, David R.; Merigan, William H.

    2018-01-01

    Here we demonstrate the application of a method that could accelerate the development of novel therapies by allowing direct and repeatable visualization of cellular function in the living eye, to study loss of vision in animal models of retinal disease, as well as evaluate the time course of retinal function following therapeutic intervention. We use high-resolution adaptive optics scanning light ophthalmoscopy to image fluorescence from the calcium sensor GCaMP6s. In mice with photoreceptor degeneration (rd10), we measured restored visual responses in ganglion cell layer neurons expressing the red-shifted channelrhodopsin ChrimsonR over a six-week period following significant loss of visual responses. Combining a fluorescent calcium sensor, a channelrhodopsin, and adaptive optics enables all-optical stimulation and recording of retinal neurons in the living eye. Because the retina is an accessible portal to the central nervous system, our method also provides a novel non-invasive method of dissecting neuronal processing in the brain. PMID:29596518

  2. Comparison of optical spectra recorded during DPF-1000U plasma experiments with gas-puffing

    Directory of Open Access Journals (Sweden)

    Zaloga Dobromil R.

    2015-06-01

    Full Text Available The results are presented of the optical spectra measurements for free plasma streams generated with the use of the modified DPF-1000U machine. This facility was recently equipped with a gas injection system (the so-called gas-puff placed on the symmetry axis behind the central opening in the inner electrode. The DPF-1000U experimental chamber was filled up with pure deuterium at the initial pressure of 1.6 or 2.4 mbar. Additionally, when the use was made of the gas-puff system about 1 cm3 of pure deuterium was injected at the pressure of 2 bars. The gas injection was initiated 1.5 or 2 ms before the triggering of the main discharge. The investigated plasma discharges were powered from a condenser bank charged initially to 23 kV (corresponding to the energy of 352 kJ, and the maximum discharge current amounted to about 1.8 MA. In order to investigate properties of a dense plasma column formed during DPF-1000U discharges the use was made of the optical emission spectroscopy. The optical spectra were recorded along the line of sight perpendicular to the vacuum chamber, using a Mechelle®900 spectrometer. The recent analysis of all the recorded spectra made it possible to compare the temporal changes in the electron density of a freely propagating plasma stream for discharges without and with the gas-puffing. Using this data an appropriate mode of operation of the DPF-1000U facility could be determined.

  3. Linear-regression convolutional neural network for fully automated coronary lumen segmentation in intravascular optical coherence tomography

    Science.gov (United States)

    Yong, Yan Ling; Tan, Li Kuo; McLaughlin, Robert A.; Chee, Kok Han; Liew, Yih Miin

    2017-12-01

    Intravascular optical coherence tomography (OCT) is an optical imaging modality commonly used in the assessment of coronary artery diseases during percutaneous coronary intervention. Manual segmentation to assess luminal stenosis from OCT pullback scans is challenging and time consuming. We propose a linear-regression convolutional neural network to automatically perform vessel lumen segmentation, parameterized in terms of radial distances from the catheter centroid in polar space. Benchmarked against gold-standard manual segmentation, our proposed algorithm achieves average locational accuracy of the vessel wall of 22 microns, and 0.985 and 0.970 in Dice coefficient and Jaccard similarity index, respectively. The average absolute error of luminal area estimation is 1.38%. The processing rate is 40.6 ms per image, suggesting the potential to be incorporated into a clinical workflow and to provide quantitative assessment of vessel lumen in an intraoperative time frame.

  4. System of laser pump and synchrotron radiation probe microdiffraction to investigate optical recording process

    International Nuclear Information System (INIS)

    Yasuda, Nobuhiro; Fukuyama, Yoshimitsu; Osawa, Hitoshi; Kimura, Shigeru; Ito, Kiminori; Tanaka, Yoshihito; Matsunaga, Toshiyuki; Kojima, Rie; Hisada, Kazuya; Tsuchino, Akio; Birukawa, Masahiro; Yamada, Noboru; Sekiguchi, Koji; Fujiie, Kazuhiko; Kawakubo, Osamu; Takata, Masaki

    2013-01-01

    We have developed a system of laser-pump and synchrotron radiation probe microdiffraction to investigate the phase-change process on a nanosecond time scale of Ge 2 Sb 2 Te 5 film embedded in multi-layer structures, which corresponds to real optical recording media. The measurements were achieved by combining (i) the pump-laser system with a pulse width of 300 ps, (ii) a highly brilliant focused microbeam with wide peak-energy width (ΔE/E ∼ 2%) made by focusing helical undulator radiation without monochromatization, and (iii) a precise sample rotation stage to make repetitive measurements. We successfully detected a very weak time-resolved diffraction signal by using this system from 100-nm-thick Ge 2 Sb 2 Te 5 phase-change layers. This enabled us to find the dependence of the crystal-amorphous phase change process of the Ge 2 Sb 2 Te 5 layers on laser power.

  5. Optical and magneto-optical characterization of TbFeCo and GdFeCo thin films for high-density recording

    International Nuclear Information System (INIS)

    Hendren, W R; Atkinson, R; Pollard, R J; Salter, I W; Wright, C D; Clegg, W W; Jenkins, D F L

    2003-01-01

    Thin, optically semi-infinite films of amorphous TbFeCo and GdFeCo, suitable for magneto-optical recording, have been deposited by DC magnetron sputtering onto glass. Ellipsometric techniques have been used to determine the complex refractive index and complex magneto-optical parameter of the films in the wavelength range 400-900 nm, thus characterizing the materials. A review of the literature is presented and shows that the results for the TbFeCo films compare favourably with published results obtained from measurements conducted in situ, with the films protected with ZnS barrier layers. It is found that GdFeCo and TbFeCo are optically very similar, but magneto-optically the materials are quite different

  6. Optical and magneto-optical characterization of TbFeCo and GdFeCo thin films for high-density recording

    Energy Technology Data Exchange (ETDEWEB)

    Hendren, W R [Department of Pure and Applied Physics, Queen' s University Belfast, Belfast BT7 1NN (United Kingdom); Atkinson, R [Department of Pure and Applied Physics, Queen' s University Belfast, Belfast BT7 1NN (United Kingdom); Pollard, R J [Department of Pure and Applied Physics, Queen' s University Belfast, Belfast BT7 1NN (United Kingdom); Salter, I W [Department of Pure and Applied Physics, Queen' s University Belfast, Belfast BT7 1NN (United Kingdom); Wright, C D [School of Engineering and Computer Science, University of Exeter, Exeter EX4 4QF (United Kingdom); Clegg, W W [CRIST, University of Plymouth, Plymouth PL4 8AA (United Kingdom); Jenkins, D F L [CRIST, University of Plymouth, Plymouth PL4 8AA (United Kingdom)

    2003-03-12

    Thin, optically semi-infinite films of amorphous TbFeCo and GdFeCo, suitable for magneto-optical recording, have been deposited by DC magnetron sputtering onto glass. Ellipsometric techniques have been used to determine the complex refractive index and complex magneto-optical parameter of the films in the wavelength range 400-900 nm, thus characterizing the materials. A review of the literature is presented and shows that the results for the TbFeCo films compare favourably with published results obtained from measurements conducted in situ, with the films protected with ZnS barrier layers. It is found that GdFeCo and TbFeCo are optically very similar, but magneto-optically the materials are quite different.

  7. Refractometry of melanocyte cell nuclei using optical scatter images recorded by digital Fourier microscopy.

    Science.gov (United States)

    Seet, Katrina Y T; Nieminen, Timo A; Zvyagin, Andrei V

    2009-01-01

    The cell nucleus is the dominant optical scatterer in the cell. Neoplastic cells are characterized by cell nucleus polymorphism and polychromism-i.e., the nuclei exhibits an increase in the distribution of both size and refractive index. The relative size parameter, and its distribution, is proportional to the product of the nucleus size and its relative refractive index and is a useful discriminant between normal and abnormal (cancerous) cells. We demonstrate a recently introduced holographic technique, digital Fourier microscopy (DFM), to provide a sensitive measure of this relative size parameter. Fourier holograms were recorded and optical scatter of individual scatterers were extracted and modeled with Mie theory to determine the relative size parameter. The relative size parameter of individual melanocyte cell nuclei were found to be 16.5+/-0.2, which gives a cell nucleus refractive index of 1.38+/-0.01 and is in good agreement with previously reported data. The relative size parameters of individual malignant melanocyte cell nuclei are expected to be greater than 16.5.

  8. Optical transmission testing based on asynchronous sampling techniques: images analysis containing chromatic dispersion using convolutional neural network

    Science.gov (United States)

    Mrozek, T.; Perlicki, K.; Tajmajer, T.; Wasilewski, P.

    2017-08-01

    The article presents an image analysis method, obtained from an asynchronous delay tap sampling (ADTS) technique, which is used for simultaneous monitoring of various impairments occurring in the physical layer of the optical network. The ADTS method enables the visualization of the optical signal in the form of characteristics (so called phase portraits) that change their shape under the influence of impairments such as chromatic dispersion, polarization mode dispersion and ASE noise. Using this method, a simulation model was built with OptSim 4.0. After the simulation study, data were obtained in the form of images that were further analyzed using the convolutional neural network algorithm. The main goal of the study was to train a convolutional neural network to recognize the selected impairment (distortion); then to test its accuracy and estimate the impairment for the selected set of test images. The input data consisted of processed binary images in the form of two-dimensional matrices, with the position of the pixel. This article focuses only on the analysis of images containing chromatic dispersion.

  9. Near-Field Phase-Change Optical Recording of 1.36 Numerical Aperture

    Science.gov (United States)

    Ichimura, Isao; Kishima, Koichiro; Osato, Kiyoshi; Yamamoto, Kenji; Kuroda, Yuji; Saito, Kimihiro

    2000-02-01

    A bit density of 125 nm was demonstrated through near-field phase-change (PC) optical recording at the wavelength of 657 nm by using a supersphere solid immersion lens (SIL). The lens unit consists of a standard objective and a φ2.5 mm SIL@. Since this lens size still prevents the unit from being mounted on an air-bearing slider, we developed a one-axis positioning actuator and an active capacitance servo for precise gap control to thoroughly investigate near-field recording. An electrode was fabricated on the bottom of the SIL, and a capacitor was formed facing a disk material. This setup realized a stable air gap below 50 nm, and a new method of simulating modulation transfer function (MTF) optimized the PC disk structure at this gap height. Obtained jitter of 8.8% and a clear eye-pattern prove that our system successfully attained the designed numerical-aperture (\\mathit{NA}) of 1.36.

  10. Free-surface velocity measurements using an optically recording velocity interferometer

    International Nuclear Information System (INIS)

    Lu Jianxin; Wang Zhao; Liang Jing; Shan Yusheng; Zhou Chuangzhi; Xiang Yihuai; Lu Ze; Tang Xiuzhang

    2006-01-01

    An optically recording velocity interferometer system (ORVIS) was developed for the free-surface velocity measurements in the equation of state experiments. The time history of free-surface velocity could be recorded by the electronic streak camera. In the experiments, ORVIS got a 179 ps time resolution, and a higher time resolution could be got by minimizing the delay time. The equation of state experiments were carried out on the high power excimer laser system called 'Heaven I' with laser wavelength of 248.4 nm, pulse duration of 25 ns and maximum energy 158 J. Free-surface velocity of 20 μm thick iron got 3.86 km/s with laser intensity of 6.24 x 10 11 W·cm -2 , and free-surface velocity of 100 μm thick aluminum with 100 μm CH foil at the front got 2.87 km/s with laser intensity 7.28 x 10 11 W·cm -2 . (authors)

  11. A novel neural prosthesis providing long-term electrocorticography recording and cortical stimulation for epilepsy and brain-computer interface.

    Science.gov (United States)

    Romanelli, Pantaleo; Piangerelli, Marco; Ratel, David; Gaude, Christophe; Costecalde, Thomas; Puttilli, Cosimo; Picciafuoco, Mauro; Benabid, Alim; Torres, Napoleon

    2018-05-11

    OBJECTIVE Wireless technology is a novel tool for the transmission of cortical signals. Wireless electrocorticography (ECoG) aims to improve the safety and diagnostic gain of procedures requiring invasive localization of seizure foci and also to provide long-term recording of brain activity for brain-computer interfaces (BCIs). However, no wireless devices aimed at these clinical applications are currently available. The authors present the application of a fully implantable and externally rechargeable neural prosthesis providing wireless ECoG recording and direct cortical stimulation (DCS). Prolonged wireless ECoG monitoring was tested in nonhuman primates by using a custom-made device (the ECoG implantable wireless 16-electrode [ECOGIW-16E] device) containing a 16-contact subdural grid. This is a preliminary step toward large-scale, long-term wireless ECoG recording in humans. METHODS The authors implanted the ECOGIW-16E device over the left sensorimotor cortex of a nonhuman primate ( Macaca fascicularis), recording ECoG signals over a time span of 6 months. Daily electrode impedances were measured, aiming to maintain the impedance values below a threshold of 100 KΩ. Brain mapping was obtained through wireless cortical stimulation at fixed intervals (1, 3, and 6 months). After 6 months, the device was removed. The authors analyzed cortical tissues by using conventional histological and immunohistological investigation to assess whether there was evidence of damage after the long-term implantation of the grid. RESULTS The implant was well tolerated; no neurological or behavioral consequences were reported in the monkey, which resumed his normal activities within a few hours of the procedure. The signal quality of wireless ECoG remained excellent over the 6-month observation period. Impedance values remained well below the threshold value; the average impedance per contact remains approximately 40 KΩ. Wireless cortical stimulation induced movements of the upper

  12. Fast optical detecting media based on semiconductor nanostructures for recording images obtained using charges of free photocarriers

    International Nuclear Information System (INIS)

    Kasherininov, P. G.; Tomasov, A. A.; Beregulin, E. V.

    2011-01-01

    Available published data on the properties of optical recording media based on semiconductor structures are reviewed. The principles of operation, structure, parameters, and the range of application for optical recording media based on MIS structures formed of photorefractive crystals with a thick layer of insulator and MIS structures with a liquid crystal as the insulator (the MIS LC modulators), as well as the effect of optical bistability in semiconductor structures (semiconductor MIS structures with nanodimensionally thin insulator (TI) layer, M(TI)S nanostructures). Special attention is paid to recording media based on the M(TI)S nanostructures promising for fast processing of highly informative images and to fabrication of optoelectronic correlators of images for noncoherent light.

  13. A Wireless and Batteryless Microsystem with Implantable Grid Electrode/3-Dimensional Probe Array for ECoG and Extracellular Neural Recording in Rats

    Directory of Open Access Journals (Sweden)

    Chih-Wei Chang

    2013-04-01

    Full Text Available This paper presents the design and implementation of an integrated wireless microsystem platform that provides the possibility to support versatile implantable neural sensing devices in free laboratory rats. Inductive coupled coils with low dropout regulator design allows true long-term recording without limitation of battery capacity. A 16-channel analog front end chip located on the headstage is designed for high channel account neural signal conditioning with low current consumption and noise. Two types of implantable electrodes including grid electrode and 3D probe array are also presented for brain surface recording and 3D biopotential acquisition in the implanted target volume of tissue. The overall system consumes less than 20 mA with small form factor, 3.9 × 3.9 cm2 mainboard and 1.8 × 3.4 cm2 headstage, is packaged into a backpack for rats. Practical in vivo recordings including auditory response, brain resection tissue and PZT-induced seizures recording demonstrate the correct function of the proposed microsystem. Presented achievements addressed the aforementioned properties by combining MEMS neural sensors, low-power circuit designs and commercial chips into system-level integration.

  14. Analog design of a new neural network for optical character recognition.

    Science.gov (United States)

    Morns, I P; Dlay, S S

    1999-01-01

    An electronic circuit is presented for a new type of neural network, which gives a recognition rate of over 100 kHz. The network is used to classify handwritten numerals, presented as Fourier and wavelet descriptors, and has been shown to train far quicker than the popular backpropagation network while maintaining classification accuracy.

  15. Decoding of digital magnetic recording with longitudinal magnetization of a tape from a magneto-optical image of stray fields

    Science.gov (United States)

    Lisovskii, F. V.; Mansvetova, E. G.

    2017-05-01

    For digital magnetic recording of encoded information with longitudinal magnetization of the tape, the connection between the domain structure of a storage medium and magneto-optical image of its stray fields obtained using a magnetic film with a perpendicular anisotropy and a large Faraday rotation has been studied. For two-frequency binary code without returning to zero, an algorithm is developed, that allows uniquely decoding of the information recorded on the tape based on analysis of an image of stray fields.

  16. Estimating nocturnal opaque ice cloud optical depth from MODIS multispectral infrared radiances using a neural network method

    Science.gov (United States)

    Minnis, Patrick; Hong, Gang; Sun-Mack, Szedung; Smith, William L.; Chen, Yan; Miller, Steven D.

    2016-05-01

    Retrieval of ice cloud properties using IR measurements has a distinct advantage over the visible and near-IR techniques by providing consistent monitoring regardless of solar illumination conditions. Historically, the IR bands at 3.7, 6.7, 11.0, and 12.0 µm have been used to infer ice cloud parameters by various methods, but the reliable retrieval of ice cloud optical depth τ is limited to nonopaque cirrus with τ < 8. The Ice Cloud Optical Depth from Infrared using a Neural network (ICODIN) method is developed in this paper by training Moderate Resolution Imaging Spectroradiometer (MODIS) radiances at 3.7, 6.7, 11.0, and 12.0 µm against CloudSat-estimated τ during the nighttime using 2 months of matched global data from 2007. An independent data set comprising observations from the same 2 months of 2008 was used to validate the ICODIN. One 4-channel and three 3-channel versions of the ICODIN were tested. The training and validation results show that IR channels can be used to estimate ice cloud τ up to 150 with correlations above 78% and 69% for all clouds and only opaque ice clouds, respectively. However, τ for the deepest clouds is still underestimated in many instances. The corresponding RMS differences relative to CloudSat are ~100 and ~72%. If the opaque clouds are properly identified with the IR methods, the RMS differences in the retrieved optical depths are ~62%. The 3.7 µm channel appears to be most sensitive to optical depth changes but is constrained by poor precision at low temperatures. A method for estimating total optical depth is explored for estimation of cloud water path in the future. Factors affecting the uncertainties and potential improvements are discussed. With improved techniques for discriminating between opaque and semitransparent ice clouds, the method can ultimately improve cloud property monitoring over the entire diurnal cycle.

  17. A multi-channel low-power system-on-chip for single-unit recording and narrowband wireless transmission of neural signal.

    Science.gov (United States)

    Bonfanti, A; Ceravolo, M; Zambra, G; Gusmeroli, R; Spinelli, A S; Lacaita, A L; Angotzi, G N; Baranauskas, G; Fadiga, L

    2010-01-01

    This paper reports a multi-channel neural recording system-on-chip (SoC) with digital data compression and wireless telemetry. The circuit consists of a 16 amplifiers, an analog time division multiplexer, an 8-bit SAR AD converter, a digital signal processor (DSP) and a wireless narrowband 400-MHz binary FSK transmitter. Even though only 16 amplifiers are present in our current die version, the whole system is designed to work with 64 channels demonstrating the feasibility of a digital processing and narrowband wireless transmission of 64 neural recording channels. A digital data compression, based on the detection of action potentials and storage of correspondent waveforms, allows the use of a 1.25-Mbit/s binary FSK wireless transmission. This moderate bit-rate and a low frequency deviation, Manchester-coded modulation are crucial for exploiting a narrowband wireless link and an efficient embeddable antenna. The chip is realized in a 0.35- εm CMOS process with a power consumption of 105 εW per channel (269 εW per channel with an extended transmission range of 4 m) and an area of 3.1 × 2.7 mm(2). The transmitted signal is captured by a digital TV tuner and demodulated by a wideband phase-locked loop (PLL), and then sent to a PC via an FPGA module. The system has been tested for electrical specifications and its functionality verified in in-vivo neural recording experiments.

  18. Exemplar-based optical neural net classifier for color pattern recognition

    Science.gov (United States)

    Yu, Francis T. S.; Uang, Chii-Maw; Yang, Xiangyang

    1992-10-01

    We present a color exemplar-based neural network that can be used as an optimum image classifier or an associative memory. Color decomposition and composition technique is used for constructing the polychromatic interconnection weight matrix (IWM). The Hamming net algorithm is modified to relax the dynamic range requirement of the spatial light modulator and to reduce the number of iteration cycles in the winner-take-all layer. Computer simulation results demonstrated the feasibility of this approach

  19. Magneto-optical labeling of fetal neural stem cells for in vivo MRI tracking.

    Science.gov (United States)

    Flexman, J A; Minoshima, S; Kim, Y; Cross, D J

    2006-01-01

    Neural stem cell therapy for neurological pathologies, such as Alzheimer's and Parkinson's disease, may delay the onset of symptoms, replace damaged neurons and/or support the survival of endogenous cells. Magnetic resonance imaging (MRI) can be used to track magnetically labeled cells in vivo to observe migration. Prior to transplantation, labeled cells must be characterized to show that they retain their intrinsic properties, such as cell proliferation into neurospheres in a supplemented environment. In vivo images must also be correlated to sensitive, histological markers. In this study, we show that fetus-derived neural stem cells can be co-labeled with superparamagnetic iron oxide and PKH26, a fluorescent dye. Labeled cells retain the ability to proliferate into neurospheres in culture, but labeling prevents neurospheres from merging in a non-adherent culture environment. After labeled NSCs were transplantation into the rat brain, their location and subsequent migration along the corpus callosum was detected using MRI. This study demonstrates an imaging paradigm with which to develop an in vivo assay for quantitatively evaluating fetal neural stem cell migration.

  20. Reconstruction of mechanically recorded sound from an edison cylinder using three dimensional non-contact optical surface metrology

    Energy Technology Data Exchange (ETDEWEB)

    Fadeyev, V.; Haber, C.; Maul, C.; McBride, J.W.; Golden, M.

    2004-04-20

    Audio information stored in the undulations of grooves in a medium such as a phonograph disc record or cylinder may be reconstructed, without contact, by measuring the groove shape using precision optical metrology methods and digital image processing. The viability of this approach was recently demonstrated on a 78 rpm shellac disc using two dimensional image acquisition and analysis methods. The present work reports the first three dimensional reconstruction of mechanically recorded sound. The source material, a celluloid cylinder, was scanned using color coded confocal microscopy techniques and resulted in a faithful playback of the recorded information.

  1. System of laser pump and synchrotron radiation probe microdiffraction to investigate optical recording process

    Energy Technology Data Exchange (ETDEWEB)

    Yasuda, Nobuhiro; Fukuyama, Yoshimitsu; Osawa, Hitoshi [Research and Utilization Division, Japan Synchrotron Radiation Research Institute, 1-1-1 Kouto, Sayo-cho, Sayo-gun, Hyogo 679-5198 (Japan); Kimura, Shigeru [Research and Utilization Division, Japan Synchrotron Radiation Research Institute, 1-1-1 Kouto, Sayo-cho, Sayo-gun, Hyogo 679-5198 (Japan); Japan Science and Technology Agency, CREST, 5 Sanbancho, Chiyoda-ku, Tokyo 102-0075 (Japan); Ito, Kiminori; Tanaka, Yoshihito [RIKEN SPring-8 Center, RIKEN, 1-1-1 Kouto, Sayo-cho, Sayo-gun, Hyogo 679-5148 (Japan); Matsunaga, Toshiyuki; Kojima, Rie; Hisada, Kazuya; Tsuchino, Akio; Birukawa, Masahiro [R and D Division, Panasonic Corporation, 3-4 Hikaridai, Seika-cho, Soraku-gun, Kyoto 619-0237 (Japan); Yamada, Noboru [Department of Materials Science and Engineering, Kyoto University, Yoshida-honmachi, Sakyo-ku, Kyoto, Kyoto 606-8501 (Japan); Sekiguchi, Koji; Fujiie, Kazuhiko; Kawakubo, Osamu [Advanced Optical Storage Development Department, Advanced Device Technology Platform, Sony Corporation, 4-14-1 Asahi-cho, Atsugi, Kanagawa 243-0014 (Japan); Takata, Masaki [Research and Utilization Division, Japan Synchrotron Radiation Research Institute, 1-1-1 Kouto, Sayo-cho, Sayo-gun, Hyogo 679-5198 (Japan); RIKEN SPring-8 Center, RIKEN, 1-1-1 Kouto, Sayo-cho, Sayo-gun, Hyogo 679-5148 (Japan); Department of Advanced Materials Science, School of Frontier Sciences, The University of Tokyo, 5-1-5 Kashiwanoha, Kashiwa, Chiba 277-8561 (Japan)

    2013-06-15

    We have developed a system of laser-pump and synchrotron radiation probe microdiffraction to investigate the phase-change process on a nanosecond time scale of Ge{sub 2}Sb{sub 2}Te{sub 5} film embedded in multi-layer structures, which corresponds to real optical recording media. The measurements were achieved by combining (i) the pump-laser system with a pulse width of 300 ps, (ii) a highly brilliant focused microbeam with wide peak-energy width ({Delta}E/E {approx} 2%) made by focusing helical undulator radiation without monochromatization, and (iii) a precise sample rotation stage to make repetitive measurements. We successfully detected a very weak time-resolved diffraction signal by using this system from 100-nm-thick Ge{sub 2}Sb{sub 2}Te{sub 5} phase-change layers. This enabled us to find the dependence of the crystal-amorphous phase change process of the Ge{sub 2}Sb{sub 2}Te{sub 5} layers on laser power.

  2. Optical study of interactions among propagation waves of neural excitation in the rat somatosensory cortex evoked by forelimb and hindlimb stimuli.

    Science.gov (United States)

    Hama, Noriyuki; Kawai, Minako; Ito, Shin-Ichi; Hirota, Akihiko

    2018-02-14

    Multisite optical recording has revealed that the neural excitation wave induced by a sensory stimulation begins at a focus and propagates on the cortex. This wave is considered to be important for computation in the sensory cortex, particularly the integration of sensory information; however, the nature of this wave remains largely unknown. In the present study, we examined the interaction between two waves in the rat sensory cortex induced by hindlimb and forelimb stimuli with different inter-stimulus intervals. We classified the resultant patterns as follows: 1) the collision of two waves; 2) the hindlimb response being evoked while the forelimb-induced wave is passing the hindlimb focus; and 3) the hindlimb response being evoked after the forelimb-induced wave has passed the hindlimb focus. In pattern 1, the two waves fused into a single wave, but the propagation pattern differed from that predicted by the superimposition of two solely induced propagation courses. In pattern 2, the state of the interaction between the two waves varied depending on the phase of optical signals constituting the forelimb-induced wave around the hindlimb focus. Although no hindlimb-induced wave was observed in the rising phase, the propagating velocity of the forelimb-induced wave increased. At the peak, neither the hindlimb-induced response nor a modulatory effect on the forelimb-induced wave was detected. In pattern 3, the hindlimb-induced wave showed a reduced amplitude and spatial extent. These results indicate that the state of the interaction between waves was strongly influenced by the relative timing of sensory inputs.

  3. Broccoli/weed/soil discrimination by optical reflectance using neural networks

    Science.gov (United States)

    Hahn, Federico

    1995-04-01

    Broccoli is grown extensively in Scotland, and has become one of the main vegetables cropped, due to its high yields and profits. Broccoli, weed and soil samples from 6 different farms were collected and their spectra obtained and analyzed using discriminant analysis. High crop/weed/soil discrimination success rates were encountered in each farm, but the selected wavelengths varied in each farm due to differences in broccoli variety, weed species incidence and soil type. In order to use only three wavelengths, neural networks were introduced and high crop/weed/soil discrimination accuracies for each farm were achieved.

  4. Combined use of high-definition and volumetric optical coherence tomography for the segmentation of neural canal opening in cases of optic nerve edema

    Science.gov (United States)

    Wang, Jui-Kai; Kardon, Randy H.; Garvin, Mona K.

    2015-03-01

    In cases of optic-nerve-head edema, the presence of the swelling reduces the visibility of the underlying neural canal opening (NCO) within spectral-domain optical coherence tomography (SD-OCT) volumes. Consequently, traditional SD-OCT-based NCO segmentation methods often overestimate the size of the NCO. The visibility of the NCO can be improved using high-definition 2D raster scans, but such scans do not provide 3D contextual image information. In this work, we present a semi-automated approach for the segmentation of the NCO in cases of optic disc edema by combining image information from volumetric and high-definition raster SD-OCT image sequences. In particular, for each subject, five high-definition OCT B-scans and the OCT volume are first separately segmented, and then the five high-definition B-scans are automatically registered to the OCT volume. Next, six NCO points are placed (manually, in this work) in the central three high-definition OCT B-scans (two points for each central B-scans) and are automatically transferred into the OCT volume. Utilizing a combination of these mapped points and the 3D image information from the volumetric scans, a graph-based approach is used to identify the complete NCO on the OCT en-face image. The segmented NCO points using the new approach were significantly closer to expert-marked points than the segmented NCO points using a traditional approach (root mean square differences in pixels: 5.34 vs. 21.71, p < 0.001).

  5. Data-driven model comparing the effects of glial scarring and interface interactions on chronic neural recordings in non-human primates

    Science.gov (United States)

    Malaga, Karlo A.; Schroeder, Karen E.; Patel, Paras R.; Irwin, Zachary T.; Thompson, David E.; Bentley, J. Nicole; Lempka, Scott F.; Chestek, Cynthia A.; Patil, Parag G.

    2016-02-01

    Objective. We characterized electrode stability over twelve weeks of impedance and neural recording data from four chronically-implanted Utah arrays in two rhesus macaques, and investigated the effects of glial scarring and interface interactions at the electrode recording site on signal quality using a computational model. Approach. A finite-element model of a Utah array microelectrode in neural tissue was coupled with a multi-compartmental model of a neuron to quantify the effects of encapsulation thickness, encapsulation resistivity, and interface resistivity on electrode impedance and waveform amplitude. The coupled model was then reconciled with the in vivo data. Histology was obtained seventeen weeks post-implantation to measure gliosis. Main results. From week 1-3, mean impedance and amplitude increased at rates of 115.8 kΩ/week and 23.1 μV/week, respectively. This initial ramp up in impedance and amplitude was observed across all arrays, and is consistent with biofouling (increasing interface resistivity) and edema clearing (increasing tissue resistivity), respectively, in the model. Beyond week 3, the trends leveled out. Histology showed that thin scars formed around the electrodes. In the model, scarring could not match the in vivo data. However, a thin interface layer at the electrode tip could. Despite having a large effect on impedance, interface resistivity did not have a noticeable effect on amplitude. Significance. This study suggests that scarring does not cause an electrical problem with regard to signal quality since it does not appear to be the main contributor to increasing impedance or significantly affect amplitude unless it displaces neurons. This, in turn, suggests that neural signals can be obtained reliably despite scarring as long as the recording site has sufficiently low impedance after accumulating a thin layer of biofouling. Therefore, advancements in microelectrode technology may be expedited by focusing on improvements to the

  6. Optical characterization and blu-ray recording properties of metal(II) azo barbituric acid complex films

    Energy Technology Data Exchange (ETDEWEB)

    Li, X.Y. [Shanghai Institute of Optics and Fine Mechanics, Chinese Academy of Sciences, Shanghai 201800 (China)], E-mail: xyli@siom.ac.cn; Wu, Y.Q. [Shanghai Institute of Optics and Fine Mechanics, Chinese Academy of Sciences, Shanghai 201800 (China); Key Lab of Functional Inorganic Material Chemistry (Heilongjiang University), Ministry of Education, Haerbin 150080 (China)], E-mail: yqwu@siom.ac.cn; Gu, D.D.; Gan, F.X. [Shanghai Institute of Optics and Fine Mechanics, Chinese Academy of Sciences, Shanghai 201800 (China)

    2009-02-25

    Smooth thin films of nickel(II), cobalt(II) and zinc(II) complexes with azo barbituric acid were prepared by the spin-coating method. Absorption spectra of the thin films on K9 glass substrates in 300-700 nm wavelength region were measured. Optical constants (complex refractive index N = n + ik) of the thin films prepared on single-crystal silicon substrates in 275-695 nm wavelength region were investigated on rotating analyzer-polarizer type of scanning ellipsometer, and dielectric constant {epsilon} ({epsilon} = {epsilon}{sub 1} + i{epsilon}{sub 2}) as well as absorption coefficient {alpha} of thin films were calculated at 405 nm. In addition, static optical recording properties of the cobalt(II) complex thin film with an Ag reflective layer was carried out using a 406.7 nm blue-violet laser and a high numerical aperture (NA) of 0.90. Clear recording marks with high reflectivity contrast (>60%) at proper laser power and pulse width were obtained, and the size of recording mark was as small as 250 nm. The results indicate that these metal(II) complexes are promising organic recording medium for the blu-ray optical storage system.

  7. The visual development of hand-centered receptive fields in a neural network model of the primate visual system trained with experimentally recorded human gaze changes.

    Science.gov (United States)

    Galeazzi, Juan M; Navajas, Joaquín; Mender, Bedeho M W; Quian Quiroga, Rodrigo; Minini, Loredana; Stringer, Simon M

    2016-01-01

    Neurons have been found in the primate brain that respond to objects in specific locations in hand-centered coordinates. A key theoretical challenge is to explain how such hand-centered neuronal responses may develop through visual experience. In this paper we show how hand-centered visual receptive fields can develop using an artificial neural network model, VisNet, of the primate visual system when driven by gaze changes recorded from human test subjects as they completed a jigsaw. A camera mounted on the head captured images of the hand and jigsaw, while eye movements were recorded using an eye-tracking device. This combination of data allowed us to reconstruct the retinal images seen as humans undertook the jigsaw task. These retinal images were then fed into the neural network model during self-organization of its synaptic connectivity using a biologically plausible trace learning rule. A trace learning mechanism encourages neurons in the model to learn to respond to input images that tend to occur in close temporal proximity. In the data recorded from human subjects, we found that the participant's gaze often shifted through a sequence of locations around a fixed spatial configuration of the hand and one of the jigsaw pieces. In this case, trace learning should bind these retinal images together onto the same subset of output neurons. The simulation results consequently confirmed that some cells learned to respond selectively to the hand and a jigsaw piece in a fixed spatial configuration across different retinal views.

  8. Marinesco-Sjogren Syndrome With Sensori Neural Deafness And Primary Optic Atrophy

    Directory of Open Access Journals (Sweden)

    Aleem M A

    1999-01-01

    Full Text Available Marinesco-Sjogren syndrome (MSS is a rare genetically determined disorder characterised by bilateral cataract, cerebellar ataxia and mental deficiency. The pattern of inheritance is autosomal recessive but it may be variable. In MSS association of hyperlactacidaemia and hypopyruvicaemia, a defective oxidative phosphorylation in mitochondria, is supposed. We are reporting three patients of MSS along with sensorineural deafness and optic atrophy from a single Indian family.

  9. Effect of neonatal capsaicin treatment on neural activity in the medullary dorsal horn of neonatal rats evoked by electrical stimulation to the trigeminal afferents: an optical, electrophysiological, and quantitative study.

    Science.gov (United States)

    Takuma, S

    2001-07-06

    To elucidate which glutamate receptors, NMDA or non-NMDA, have the main role in synaptic transmission via unmyelinated afferents in the trigeminal subnucleus caudalis (the medullary dorsal horn), and to examine the early functional effects of neonatal capsaicin treatment to the subnucleus caudalis, optical recording, field potential recording, and quantitative study using electron micrographs were employed. A medulla oblongata isolated from a rat 5--7 days old was sectioned horizontally 400-microm thick or parasagittally and stained with a voltage-sensitive dye, RH482 or RH795. Single-pulse stimulation with high intensity to the trigeminal afferents evoked optical responses mainly in the subnucleus caudalis. The optical signals were composed of two phases, a fast component followed by a long-lasting component. The spatiotemporal properties of the optical signals were well correlated to those of the field potentials recorded simultaneously. The fast component was eliminated by 6-cyano-7-nitro-quinoxaline-2,3-dione (CNQX; 10 microM), while the long-lasting component was not. The latter increased in amplitude under a condition of low Mg(2+) but was significantly reduced by DL-2-amino-5-phosphonovaleric acid (AP5; 30 microM). Neonatal capsaicin treatment also reduced the long-lasting component markedly. In addition, the decreases in the ratio of unmyelinated axons to myelinated axons and in the ratio of unmyelinated axons to Schwann cell subunits of trigeminal nerve roots both showed significant differences (P<0.05, Student's t-test) between the control group and the neonatal capsaicin treatment group. This line of evidence indirectly suggests that synaptic transmission via unmyelinated afferents in the subnucleus caudalis is mediated substantially by NMDA glutamate receptors and documented that neonatal capsaicin treatment induced a functional alteration of the neural transmission in the subnucleus caudalis as well as a morphological alteration of primary afferents

  10. Temporal formation of optical anisotropy and surface relief during polarization holographic recording in polymethylmethacrylate with azobenzene side groups

    Science.gov (United States)

    Sasaki, Tomoyuki; Izawa, Masahiro; Noda, Kohei; Nishioka, Emi; Kawatsuki, Nobuhiro; Ono, Hiroshi

    2014-03-01

    The formation of polarization holographic gratings with both optical anisotropy and surface relief (SR) deformation was studied for polymethylmethacrylate with azobenzene side groups. Temporal contributions of isotropic and anisotropic phase gratings were simultaneously determined by observing transitional intensity and polarization states of the diffraction beams and characterizing by means of Jones calculus. To clarify the mechanism of SR deformation, cross sections of SR were characterized based on the optical gradient force model; experimental observations were in good agreement with the theoretical expectation. We clarified that the anisotropic phase change originating in the reorientation of the azobenzene side groups was induced immediately at the beginning of the holographic recording, while the response time of the isotropic phase change originating in the molecular migration due to the optical gradient force was relatively slow.

  11. Neural mechanisms underlying spatial realignment during adaptation to optical wedge prisms.

    Science.gov (United States)

    Chapman, Heidi L; Eramudugolla, Ranmalee; Gavrilescu, Maria; Strudwick, Mark W; Loftus, Andrea; Cunnington, Ross; Mattingley, Jason B

    2010-07-01

    Visuomotor adaptation to a shift in visual input produced by prismatic lenses is an example of dynamic sensory-motor plasticity within the brain. Prism adaptation is readily induced in healthy individuals, and is thought to reflect the brain's ability to compensate for drifts in spatial calibration between different sensory systems. The neural correlate of this form of functional plasticity is largely unknown, although current models predict the involvement of parieto-cerebellar circuits. Recent studies that have employed event-related functional magnetic resonance imaging (fMRI) to identify brain regions associated with prism adaptation have discovered patterns of parietal and cerebellar modulation as participants corrected their visuomotor errors during the early part of adaptation. However, the role of these regions in the later stage of adaptation, when 'spatial realignment' or true adaptation is predicted to occur, remains unclear. Here, we used fMRI to quantify the distinctive patterns of parieto-cerebellar activity as visuomotor adaptation develops. We directly contrasted activation patterns during the initial error correction phase of visuomotor adaptation with that during the later spatial realignment phase, and found significant recruitment of the parieto-cerebellar network--with activations in the right inferior parietal lobe and the right posterior cerebellum. These findings provide the first evidence of both cerebellar and parietal involvement during the spatial realignment phase of prism adaptation. Copyright (c) 2010 Elsevier Ltd. All rights reserved.

  12. Integration of silicon-based neural probes and micro-drive arrays for chronic recording of large populations of neurons in behaving animals.

    Science.gov (United States)

    Michon, Frédéric; Aarts, Arno; Holzhammer, Tobias; Ruther, Patrick; Borghs, Gustaaf; McNaughton, Bruce; Kloosterman, Fabian

    2016-08-01

    Understanding how neuronal assemblies underlie cognitive function is a fundamental question in system neuroscience. It poses the technical challenge to monitor the activity of populations of neurons, potentially widely separated, in relation to behaviour. In this paper, we present a new system which aims at simultaneously recording from a large population of neurons from multiple separated brain regions in freely behaving animals. The concept of the new device is to combine the benefits of two existing electrophysiological techniques, i.e. the flexibility and modularity of micro-drive arrays and the high sampling ability of electrode-dense silicon probes. Newly engineered long bendable silicon probes were integrated into a micro-drive array. The resulting device can carry up to 16 independently movable silicon probes, each carrying 16 recording sites. Populations of neurons were recorded simultaneously in multiple cortical and/or hippocampal sites in two freely behaving implanted rats. Current approaches to monitor neuronal activity either allow to flexibly record from multiple widely separated brain regions (micro-drive arrays) but with a limited sampling density or to provide denser sampling at the expense of a flexible placement in multiple brain regions (neural probes). By combining these two approaches and their benefits, we present an alternative solution for flexible and simultaneous recordings from widely distributed populations of neurons in freely behaving rats.

  13. Laboratory-based recording of holographic fine structure in X-ray absorption anisotropy using polycapillary optics

    Energy Technology Data Exchange (ETDEWEB)

    Dabrowski, K.M. [Institute of Physics, Jagiellonian University, Reymonta 4, 30-059 Krakow (Poland); Korecki, P., E-mail: pawel.korecki@uj.edu.pl [Institute of Physics, Jagiellonian University, Reymonta 4, 30-059 Krakow (Poland)

    2012-08-15

    Highlights: Black-Right-Pointing-Pointer Holographic fine structures in X-ray absorption recorded using a tabletop setup. Black-Right-Pointing-Pointer Setup based on polycapillary collimating optics and an HOPG crystal. Black-Right-Pointing-Pointer Demonstration of element sensitivity by detection of X-ray fluorescence. Black-Right-Pointing-Pointer Potential of laboratory-based experiments for heavily doped crystals and thin films. - Abstract: A tabletop setup composed of a collimating polycapillary optics and a highly oriented pyrolytic graphite monochromator (HOPG) was characterized and used for recording two-dimensional maps of X-ray absorption anisotropy (XAA). XAA originates from interference of X-rays directly inside the sample. Depending on experimental conditions, fine structures in XAA can be interpreted in terms of X-ray holograms or X-ray standing waves and can be used for an element selective atomic-resolved structural analysis. The implementation of polycapillary optics resulted in a two-order of magnitude gain in the radiant intensity (photons/s/solid angle) as compared to a system without optics and enabled efficient recording of XAA with a resolution of 0.15 Degree-Sign for Mo K{alpha} radiation. Element sensitivity was demonstrated by acquisition of distinct XAA signals for Ga and As atoms in a GaAs (1 1 1) wafer by using X-ray fluorescence as a secondary signal. These results indicate the possibility of performing laboratory-based XAA experiments for heavily doped single crystals or thin films. So far, because of the weak holographic modulation of XAA, such experiments could be only performed using synchrotron radiation.

  14. Neural Correlates of Auditory Perceptual Awareness and Release from Informational Masking Recorded Directly from Human Cortex: A Case Study

    Directory of Open Access Journals (Sweden)

    Andrew R Dykstra

    2016-10-01

    Full Text Available In complex acoustic environments, even salient supra-threshold sounds sometimes go unperceived, a phenomenon known as informational masking. The neural basis of informational masking (and its release has not been well characterized, particularly outside auditory cortex. We combined electrocorticography in a neurosurgical patient undergoing invasive epilepsy monitoring with trial-by-trial perceptual reports of isochronous target-tone streams embedded in random multi-tone maskers. Awareness of such masker-embedded target streams was associated with a focal negativity between 100 and 200 ms and high-gamma activity between 50 and 250 ms (both in auditory cortex on the posterolateral superior temporal gyrus as well as a broad P3b-like potential (between ~300 and 600 ms with generators in ventrolateral frontal and lateral temporal cortex. Unperceived target tones elicited drastically reduced versions of such responses, if at all. While it remains unclear whether these responses reflect conscious perception, itself, as opposed to pre- or post-perceptual processing, the results suggest that conscious perception of target sounds in complex listening environments may engage diverse neural mechanisms in distributed brain areas.

  15. Optical recording in functional polymer nanocomposites by multi-beam interference holography

    Science.gov (United States)

    Zhuk, Dmitrij; Burunkova, Julia; Kalabin, Viacheslav; Csarnovics, Istvan; Kokenyesi, Sandor

    2017-05-01

    Our investigations relate to the development of new polymer nanocomposite materials and technologies for fabrication of photonic elements like gratings, integrated elements, photonic crystals. The goal of the present work was the development and application of the multi-beam interference method for one step, direct formation of 1-, 2- or even 3D photonic structures in functional acrylate nanocomposites, which contain SiO2 and Au nanoparticles and which are sensitized to blue and green laser illumination. The presence of gold nanoparticles and possibility to excite plasmonic effects can essentially influence the polymerization processes and the spatial redistribution of nanoparticles in the nanocomposite during the recording. This way surface and volume phase reliefs can be recorded. It is essential, that no additional treatments of the material after the recording are necessary and the elements possess high transparency, are stable after some relaxation time. New functionalities can be provided to the recorded structures if luminescent materials are added to such materials.

  16. NOAA JPSS Visible Infrared Imaging Radiometer Suite (VIIRS) Aerosol Optical Thickness (AOT) and Aerosol Particle Size Parameter (APSP) Environmental Data Record (EDR) from IDPS

    Data.gov (United States)

    National Oceanic and Atmospheric Administration, Department of Commerce — This dataset contains a high quality operational Environmental Data Record (EDR) of Aerosol Optical Thickness (AOT) from the Visible Infrared Imaging Radiometer...

  17. NOAA JPSS Visible Infrared Imaging Radiometer Suite (VIIRS) Aerosol Optical Depth and Aerosol Particle Size Distribution Environmental Data Record (EDR) from NDE

    Data.gov (United States)

    National Oceanic and Atmospheric Administration, Department of Commerce — This dataset contains a high quality operational Environmental Data Record (EDR) of aerosol optical depth (AOD) and particle size from the Visible Infrared Imaging...

  18. Postsynaptic potentials recorded in neurons of the cat's lateral geniculate nucleus following electrical stimulation of the optic chiasm.

    Science.gov (United States)

    Bloomfield, S A; Sherman, S M

    1988-12-01

    1. We recorded intracellularly from X and Y cells of the cat's lateral geniculate nucleus and measured the postsynaptic potentials (PSPs) evoked from electrical stimulation of the optic chiasm. We used an in vivo preparation and computer averaged the PSPs to enhance their signal-to-noise ratio. 2. The vast majority (46 of 50) of our sample of X and Y cells responded to stimulation of the optic chiasm with an excitatory postsynaptic potential (EPSP) followed by an inhibitory postsynaptic potential (IPSP); these were tentatively identified as relay cells. We quantified several parameters of these PSPs, including amplitude, latency, time to peak (i.e., rise time), and duration. 3. Among the relay cells, the latencies of both the EPSP and action potential evoked by optic chiasm stimulation were shorter in Y cells than in X cells. Furthermore, the difference between the latencies of the EPSP and action potential was shorter for Y cells than for X cells. This means that the EPSPs generated in Y cells reached threshold for generation of action potentials faster than did those in X cells. The EPSPs of Y cells also displayed larger amplitudes and faster rise times than did those in X cells, but neither of these distinctions was sufficient to explain the shorter latency difference between the EPSP and action potential for Y cells. 4. The EPSPs recorded in relay Y cells had longer durations than did those in relay X cells. Our data suggest that the subsequent IPSP actively terminates the EPSP, which, in turn, suggests that the time interval between EPSP and IPSP onsets is longer in Y cells than in X cells. Furthermore, we found that, for individual Y cells, the latency and duration of the evoked EPSP were inversely related. These observations lead to the conclusion that the latency of IPSPs activated from the optic chiasm is relatively constant among Y cells and thus independent of the EPSP latencies. Thus the excitation and inhibition produced in individual geniculate Y

  19. A low-power current-reuse dual-band analog front-end for multi-channel neural signal recording.

    Science.gov (United States)

    Sepehrian, H; Gosselin, B

    2014-01-01

    Thoroughly studying the brain activity of freely moving subjects requires miniature data acquisition systems to measure and wirelessly transmit neural signals in real time. In this application, it is mandatory to simultaneously record the bioelectrical activity of a large number of neurons to gain a better knowledge of brain functions. However, due to limitations in transferring the entire raw data to a remote base station, employing dedicated data reduction techniques to extract the relevant part of neural signals is critical to decrease the amount of data to transfer. In this work, we present a new dual-band neural amplifier to separate the neuronal spike signals (SPK) and the local field potential (LFP) simultaneously in the analog domain, immediately after the pre-amplification stage. By separating these two bands right after the pre-amplification stage, it is possible to process LFP and SPK separately. As a result, the required dynamic range of the entire channel, which is determined by the signal-to-noise ratio of the SPK signal of larger bandwidth, can be relaxed. In this design, a new current-reuse low-power low-noise amplifier and a new dual-band filter that separates SPK and LFP while saving capacitors and pseudo resistors. A four-channel dual-band (SPK, LFP) analog front-end capable of simultaneously separating SPK and LFP is implemented in a TSMC 0.18 μm technology. Simulation results present a total power consumption per channel of 3.1 μw for an input referred noise of 3.28 μV and a NEF for 2.07. The cutoff frequency of the LFP band is fc=280 Hz, and fL=725 Hz and fL=11.2 KHz for SPK, with 36 dB gain for LFP band 46 dB gain for SPK band.

  20. Restocking the optical designers' toolbox for next-generation wearable displays (Presentation Recording)

    Science.gov (United States)

    Kress, Bernard C.

    2015-09-01

    Three years ago, industry and consumers learned that there was more to Head Mounted Displays (HMDs) than the long-lasting but steady market for defense or the market for gadget video player headsets: the first versions of Smart Glasses were introduced to the public. Since then, most major consumer electronics companies unveiled their own versions of Connected Glasses, Smart Glasses or Smart Eyewear, AR (Augmented Reality) and VR (Virtual Reality) headsets. This rush resulted in the build-up of a formidable zoo of optical technologies, each claiming to be best suited for the task on hand. Today, the question is not so much anymore "will the Smart Glass market happen?" but rather "which optical technologies will be best fitted for the various declinations of the existing wearable display market," one of the main declination being the Smart Glasses market.

  1. Estimation of corn yield using multi-temporal optical and radar satellite data and artificial neural networks

    Science.gov (United States)

    Fieuzal, R.; Marais Sicre, C.; Baup, F.

    2017-05-01

    The yield forecasting of corn constitutes a key issue in agricultural management, particularly in the context of demographic pressure and climate change. This study presents two methods to estimate yields using artificial neural networks: a diagnostic approach based on all the satellite data acquired throughout the agricultural season, and a real-time approach, where estimates are updated after each image was acquired in the microwave and optical domains (Formosat-2, Spot-4/5, TerraSAR-X, and Radarsat-2) throughout the crop cycle. The results are based on the Multispectral Crop Monitoring experimental campaign conducted by the CESBIO (Centre d'Études de la BIOsphère) laboratory in 2010 over an agricultural region in southwestern France. Among the tested sensor configurations (multi-frequency, multi-polarization or multi-source data), the best yield estimation performance (using the diagnostic approach) is obtained with reflectance acquired in the red wavelength region, with a coefficient of determination of 0.77 and an RMSE of 6.6 q ha-1. In the real-time approach the combination of red reflectance and CHH backscattering coefficients provides the best compromise between the accuracy and earliness of the yield estimate (more than 3 months before the harvest), with an R2 of 0.69 and an RMSE of 7.0 q ha-1 during the development of the central stem. The two best yield estimates are similar in most cases (for more than 80% of the monitored fields), and the differences are related to discrepancies in the crop growth cycle and/or the consequences of pests.

  2. Studies of the underlying mechanisms for optical nonlinearities of blue phase liquid crystals (Presentation Recording)

    Science.gov (United States)

    Chen, Chun-Wei; Khoo, Iam Choon; Zhao, Shuo; Lin, Tsung-Hsien; Ho, Tsung-Jui

    2015-10-01

    We have investigated the mechanisms responsible for nonlinear optical processes occurring in azobenzene-doped blue phase liquid crystals (BPLC), which exhibit two thermodynamically stable BPs: BPI and BPII. In coherent two wave-mixing experiments, a slow (minutes) and a fast (few milliseconds) side diffractions are observed. The underlying mechanisms were disclosed by monitoring the dynamics of grating formation and relaxation as well as by some supplementary experiments. We found the photothermal indexing and dye/LC intermolecular torque leading to lattice distortion to be the dominant mechanisms for the observed nonlinear response in BPLC. Moreover, the response time of the nonlinear optical process varied with operating phase. The rise time of the thermal indexing process was in good agreement with our findings on the temperature dependence of BP refractive index: τ(ISO) > τ(BPI) > τ(BPII). The relaxation time of the torque-induced lattice distortion was analogue to its electrostriction counterpart: τ'(BPI) > τ'(BPII). In a separate experiment, lattice swelling with selective reflection of direction changed from green to red was also observed. This was attributable to the isomerization-induced change in cholesteric pitch, which directly affects the lattice spacing. The phenomenon was confirmed by measuring the optical rotatory power of the BPLC.

  3. Closed-Loop Real-Time Imaging Enables Fully Automated Cell-Targeted Patch-Clamp Neural Recording In Vivo.

    Science.gov (United States)

    Suk, Ho-Jun; van Welie, Ingrid; Kodandaramaiah, Suhasa B; Allen, Brian; Forest, Craig R; Boyden, Edward S

    2017-08-30

    Targeted patch-clamp recording is a powerful method for characterizing visually identified cells in intact neural circuits, but it requires skill to perform. We previously developed an algorithm that automates "blind" patching in vivo, but full automation of visually guided, targeted in vivo patching has not been demonstrated, with currently available approaches requiring human intervention to compensate for cell movement as a patch pipette approaches a targeted neuron. Here we present a closed-loop real-time imaging strategy that automatically compensates for cell movement by tracking cell position and adjusting pipette motion while approaching a target. We demonstrate our system's ability to adaptively patch, under continuous two-photon imaging and real-time analysis, fluorophore-expressing neurons of multiple types in the living mouse cortex, without human intervention, with yields comparable to skilled human experimenters. Our "imagepatching" robot is easy to implement and will help enable scalable characterization of identified cell types in intact neural circuits. Copyright © 2017 Elsevier Inc. All rights reserved.

  4. Recording of radiation-induced optical density changes in doped agarose gels with a CCD camera

    International Nuclear Information System (INIS)

    Tarte, B.J.; Jardine, P.A.; Van Doorn, T.

    1996-01-01

    Full text: Spatially resolved dose measurement with iron-doped agarose gels is continuing to be investigated for applications in radiotherapy dosimetry. It has previously been proposed to use optical methods, rather than MRI, for dose measurement with such gels and this has been investigated using a spectrophotometer (Appleby A and Leghrouz A, Med Phys, 18:309-312, 1991). We have previously studied the use of a pencil beam laser for such optical density measurement of gels and are currently investigating charge-coupled devices (CCD) camera imaging for the same purpose but with the advantages of higher data acquisition rates and potentially greater spatial resolution. The gels used in these studies were poured, irradiated and optically analysed in Perspex casts providing gel sections 1 cm thick and up to 20 cm x 30 cm in dimension. The gels were also infused with a metal indicator dye (xylenol orange) to render the radiation induced oxidation of the iron in the gel sensitive to optical radiation, specifically in the green spectral region. Data acquisition with the CCD camera involved illumination of the irradiated gel section with a diffuse white light source, with the light from the plane of the gel section focussed to the CCD array with a manual zoom lens. The light was also filtered with a green colour glass filter to maximise the contrast between unirradiated and irradiated gels. The CCD camera (EG and G Reticon MC4013) featured a 1024 x 1024 pixel array and was interfaced to a PC via a frame grabber acquisition board with 8 bit resolution. The performance of the gel dosimeter was appraised in mapping of physical and dynamic wedged 6 MV X-ray fields. The results from the CCD camera detection system were compared with both ionisation chamber data and laser based optical density measurements of the gels. Cross beam profiles were extracted from each measurement system at a particular depth (eg. 2.3 cm for the physical wedge field) for direct comparison. A

  5. Assessing sensory versus optogenetic network activation by combining (o)fMRI with optical Ca2+ recordings

    Science.gov (United States)

    Schmid, Florian; Wachsmuth, Lydia; Schwalm, Miriam; Prouvot, Pierre-Hugues; Jubal, Eduardo Rosales; Fois, Consuelo; Pramanik, Gautam; Zimmer, Claus; Stroh, Albrecht

    2015-01-01

    Encoding of sensory inputs in the cortex is characterized by sparse neuronal network activation. Optogenetic stimulation has previously been combined with fMRI (ofMRI) to probe functional networks. However, for a quantitative optogenetic probing of sensory-driven sparse network activation, the level of similarity between sensory and optogenetic network activation needs to be explored. Here, we complement ofMRI with optic fiber-based population Ca2+ recordings for a region-specific readout of neuronal spiking activity in rat brain. Comparing Ca2+ responses to the blood oxygenation level-dependent signal upon sensory stimulation with increasing frequencies showed adaptation of Ca2+ transients contrasted by an increase of blood oxygenation level-dependent responses, indicating that the optical recordings convey complementary information on neuronal network activity to the corresponding hemodynamic response. To study the similarity of optogenetic and sensory activation, we quantified the density of cells expressing channelrhodopsin-2 and modeled light propagation in the tissue. We estimated the effectively illuminated volume and numbers of optogenetically stimulated neurons, being indicative of sparse activation. At the functional level, upon either sensory or optogenetic stimulation we detected single-peak short-latency primary Ca2+ responses with similar amplitudes and found that blood oxygenation level-dependent responses showed similar time courses. These data suggest that ofMRI can serve as a representative model for functional brain mapping. PMID:26661247

  6. Assessing sensory versus optogenetic network activation by combining (o)fMRI with optical Ca2+ recordings.

    Science.gov (United States)

    Schmid, Florian; Wachsmuth, Lydia; Schwalm, Miriam; Prouvot, Pierre-Hugues; Jubal, Eduardo Rosales; Fois, Consuelo; Pramanik, Gautam; Zimmer, Claus; Faber, Cornelius; Stroh, Albrecht

    2016-11-01

    Encoding of sensory inputs in the cortex is characterized by sparse neuronal network activation. Optogenetic stimulation has previously been combined with fMRI (ofMRI) to probe functional networks. However, for a quantitative optogenetic probing of sensory-driven sparse network activation, the level of similarity between sensory and optogenetic network activation needs to be explored. Here, we complement ofMRI with optic fiber-based population Ca 2+ recordings for a region-specific readout of neuronal spiking activity in rat brain. Comparing Ca 2+ responses to the blood oxygenation level-dependent signal upon sensory stimulation with increasing frequencies showed adaptation of Ca 2+ transients contrasted by an increase of blood oxygenation level-dependent responses, indicating that the optical recordings convey complementary information on neuronal network activity to the corresponding hemodynamic response. To study the similarity of optogenetic and sensory activation, we quantified the density of cells expressing channelrhodopsin-2 and modeled light propagation in the tissue. We estimated the effectively illuminated volume and numbers of optogenetically stimulated neurons, being indicative of sparse activation. At the functional level, upon either sensory or optogenetic stimulation we detected single-peak short-latency primary Ca 2+ responses with similar amplitudes and found that blood oxygenation level-dependent responses showed similar time courses. These data suggest that ofMRI can serve as a representative model for functional brain mapping. © The Author(s) 2015.

  7. Open Ephys electroencephalography (Open Ephys  +  EEG): a modular, low-cost, open-source solution to human neural recording.

    Science.gov (United States)

    Black, Christopher; Voigts, Jakob; Agrawal, Uday; Ladow, Max; Santoyo, Juan; Moore, Christopher; Jones, Stephanie

    2017-06-01

    Electroencephalography (EEG) offers a unique opportunity to study human neural activity non-invasively with millisecond resolution using minimal equipment in or outside of a lab setting. EEG can be combined with a number of techniques for closed-loop experiments, where external devices are driven by specific neural signals. However, reliable, commercially available EEG systems are expensive, often making them impractical for individual use and research development. Moreover, by design, a majority of these systems cannot be easily altered to the specification needed by the end user. We focused on mitigating these issues by implementing open-source tools to develop a new EEG platform to drive down research costs and promote collaboration and innovation. Here, we present methods to expand the open-source electrophysiology system, Open Ephys (www.openephys.org), to include human EEG recordings. We describe the equipment and protocol necessary to interface various EEG caps with the Open Ephys acquisition board, and detail methods for processing data. We present applications of Open Ephys  +  EEG as a research tool and discuss how this innovative EEG technology lays a framework for improved closed-loop paradigms and novel brain-computer interface experiments. The Open Ephys  +  EEG system can record reliable human EEG data, as well as human EMG data. A side-by-side comparison of eyes closed 8-14 Hz activity between the Open Ephys  +  EEG system and the Brainvision ActiCHamp EEG system showed similar average power and signal to noise. Open Ephys  +  EEG enables users to acquire high-quality human EEG data comparable to that of commercially available systems, while maintaining the price point and extensibility inherent to open-source systems.

  8. Open Ephys electroencephalography (Open Ephys  +  EEG): a modular, low-cost, open-source solution to human neural recording

    Science.gov (United States)

    Black, Christopher; Voigts, Jakob; Agrawal, Uday; Ladow, Max; Santoyo, Juan; Moore, Christopher; Jones, Stephanie

    2017-06-01

    Objective. Electroencephalography (EEG) offers a unique opportunity to study human neural activity non-invasively with millisecond resolution using minimal equipment in or outside of a lab setting. EEG can be combined with a number of techniques for closed-loop experiments, where external devices are driven by specific neural signals. However, reliable, commercially available EEG systems are expensive, often making them impractical for individual use and research development. Moreover, by design, a majority of these systems cannot be easily altered to the specification needed by the end user. We focused on mitigating these issues by implementing open-source tools to develop a new EEG platform to drive down research costs and promote collaboration and innovation. Approach. Here, we present methods to expand the open-source electrophysiology system, Open Ephys (www.openephys.org), to include human EEG recordings. We describe the equipment and protocol necessary to interface various EEG caps with the Open Ephys acquisition board, and detail methods for processing data. We present applications of Open Ephys  +  EEG as a research tool and discuss how this innovative EEG technology lays a framework for improved closed-loop paradigms and novel brain-computer interface experiments. Main results. The Open Ephys  +  EEG system can record reliable human EEG data, as well as human EMG data. A side-by-side comparison of eyes closed 8-14 Hz activity between the Open Ephys  +  EEG system and the Brainvision ActiCHamp EEG system showed similar average power and signal to noise. Significance. Open Ephys  +  EEG enables users to acquire high-quality human EEG data comparable to that of commercially available systems, while maintaining the price point and extensibility inherent to open-source systems.

  9. Deformation Recording Process In Polymer-Metal Bilayers And Its Use For Optical Storage

    Science.gov (United States)

    Cornet, Jean A.

    1983-11-01

    A non-antireflective polymer-metal bilayer structure, encapsulated inside a closed cons-truction/is used for digital data storage in the Thomson-CSF Gigadisc. In this paper, a simple model is presented for microdeformation recording in the medium. This model enables a good understanding of the readout signal as a function of the recording power and leads to some practical consequences. Useful polymers and metallic layers are identified and the disc performance is reported. It is shown that recording using laser diodes can be performed at bit rate up to 14 Mbits.s-1 with a laser power of 7 mW at the disc entry face, in case of a 1200 rpm disc speed. Moreover a working range of 4 mW, as defined by a 3 dB attenuation, is demonstrated. Discs from pilot production exhibit raw bit error rates at the level of 2.10-5. For usual environmental conditions, the disc behaviour is compatible with shelf-and archival life at scale of 10 years. Finally, the processes for both layers deposition and disc construction are easy and cost effective. It is concluded that Giaadisc can successfully enter today the market place.

  10. Phenotype analysis of early risk factors from electronic medical records improves image-derived diagnostic classifiers for optic nerve pathology

    Science.gov (United States)

    Chaganti, Shikha; Nabar, Kunal P.; Nelson, Katrina M.; Mawn, Louise A.; Landman, Bennett A.

    2017-03-01

    We examine imaging and electronic medical records (EMR) of 588 subjects over five major disease groups that affect optic nerve function. An objective evaluation of the role of imaging and EMR data in diagnosis of these conditions would improve understanding of these diseases and help in early intervention. We developed an automated image processing pipeline that identifies the orbital structures within the human eyes from computed tomography (CT) scans, calculates structural size, and performs volume measurements. We customized the EMR-based phenome-wide association study (PheWAS) to derive diagnostic EMR phenotypes that occur at least two years prior to the onset of the conditions of interest from a separate cohort of 28,411 ophthalmology patients. We used random forest classifiers to evaluate the predictive power of image-derived markers, EMR phenotypes, and clinical visual assessments in identifying disease cohorts from a control group of 763 patients without optic nerve disease. Image-derived markers showed more predictive power than clinical visual assessments or EMR phenotypes. However, the addition of EMR phenotypes to the imaging markers improves the classification accuracy against controls: the AUC improved from 0.67 to 0.88 for glaucoma, 0.73 to 0.78 for intrinsic optic nerve disease, 0.72 to 0.76 for optic nerve edema, 0.72 to 0.77 for orbital inflammation, and 0.81 to 0.85 for thyroid eye disease. This study illustrates the importance of diagnostic context for interpretation of image-derived markers and the proposed PheWAS technique provides a flexible approach for learning salient features of patient history and incorporating these data into traditional machine learning analyses.

  11. Ultrafast chirped optical waveform recorder using referenced heterodyning and a time microscope

    Science.gov (United States)

    Bennett, Corey Vincent [Livermore, CA

    2011-11-22

    A new technique for capturing both the amplitude and phase of an optical waveform is presented. This technique can capture signals with many THz of bandwidths in a single shot (e.g., temporal resolution of about 44 fs), or be operated repetitively at a high rate. That is, each temporal window (or frame) is captured single shot, in real time, but the process may be run repeatedly or single-shot. This invention expands upon previous work in temporal imaging by adding heterodyning, which can be self-referenced for improved precision and stability, to convert frequency chirp (the second derivative of phase with respect to time) into a time varying intensity modulation. By also including a variety of possible demultiplexing techniques, this process is scalable to recoding continuous signals.

  12. Ultrafast chirped optical waveform recording using referenced heterodyning and a time microscope

    Science.gov (United States)

    Bennett, Corey Vincent

    2010-06-15

    A new technique for capturing both the amplitude and phase of an optical waveform is presented. This technique can capture signals with many THz of bandwidths in a single shot (e.g., temporal resolution of about 44 fs), or be operated repetitively at a high rate. That is, each temporal window (or frame) is captured single shot, in real time, but the process may be run repeatedly or single-shot. This invention expands upon previous work in temporal imaging by adding heterodyning, which can be self-referenced for improved precision and stability, to convert frequency chirp (the second derivative of phase with respect to time) into a time varying intensity modulation. By also including a variety of possible demultiplexing techniques, this process is scalable to recoding continuous signals.

  13. An optical age chronology of late Quaternary extreme fluvial events recorded in Ugandan dambo soils

    Science.gov (United States)

    Mahan, S.A.; Brown, D.J.

    2007-01-01

    There is little geochonological data on sedimentation in dambos (seasonally saturated, channel-less valley floors) found throughout Central and Southern Africa. Radiocarbon dating is problematic for dambos due to (i) oxidation of organic materials during dry seasons; and (ii) the potential for contemporary biological contamination of near-surface sediments. However, for luminescence dating the equatorial site and semi-arid climate facilitate grain bleaching, while the gentle terrain ensures shallow water columns, low turbidity, and relatively long surface exposures for transported grains prior to deposition and burial. For this study, we focused on dating sandy strata (indicative of high-energy fluvial events) at various positions and depths within a second-order dambo in central Uganda. Blue-light quartz optically stimulated luminescences (OSL) ages were compared with infrared stimulated luminescence (IRSL) and thermoluminescence (TL) ages from finer grains in the same sample. A total of 8 samples were dated, with 6 intervals obtained at ???35, 33, 16, 10.4, 8.4, and 5.9 ka. In general, luminescence ages were stratigraphically, geomorphically and ordinally consistent and most blue-light OSL ages could be correlated with well-dated climatic events registered either in Greenland ice cores or Lake Victoria sediments. Based upon OSL age correlations, we theorize that extreme fluvial dambo events occur primarily during relatively wet periods, often preceding humid-to-arid transitions. The optical ages reported in this study provide the first detailed chronology of dambo sedimentation, and we anticipate that further dambo work could provide a wealth of information on the paleohydrology of Central and Southern Africa. ?? 2006 Elsevier Ltd. All rights reserved.

  14. The use of optical fibers in the Trans Iron Galactic Element Recorder (TIGER)

    International Nuclear Information System (INIS)

    Sposato, S. H.; Binns, W. R.; Dowkontt, P. F.; Epstein, J. W.; Hink, P. L.; Israel, M. H.; Klarmann, J.; Lawrence, D. J.; Barbier, L. M.; Christian, E. R.; Mitchell, J. W.; Streitmatter, R. E.; Nolfo, G. A. de; Mewaldt, R. A.; Shindler, S. M.; Waddington, C. J.

    1998-01-01

    TIGER, the Trans-Iron Galactic Element Recorder, is a cosmic-ray balloon borne experiment that utilizes a scintillating Fiber Hodoscope/Time of Flight (TOF) counter. It was flown aboard a high altitude balloon on September 24, 1997. The objective of this experiment is to measure the elemental abundances of all nuclei within the charge range: 26≤Z≤40. This initial balloon flight will test the detector concept, which will be used in future balloon and space experiments. The instrument and the fiber detector are described

  15. Recording and Modelling of MONUMENTS' Interior Space Using Range and Optical Sensors

    Science.gov (United States)

    Georgiadis, Charalampos; Patias, Petros; Tsioukas, Vasilios

    2016-06-01

    Three dimensional modelling of artefacts and building interiors is a highly active research field in our days. Several techniques are being utilized to perform such a task, spanning from traditional surveying techniques and photogrammetry to structured light scanners, laser scanners and so on. New technological advancements in both hardware and software create new recording techniques, tools and approaches. In this paper we present a new recording and modelling approach based on the SwissRanger SR4000 range camera coupled with a Canon 400D dSLR camera. The hardware component of our approach consists of a fixed base, which encloses the range and SLR cameras. The two sensors are fully calibrated and registered to each other thus we were able to produce colorized point clouds acquired from the range camera. In this paper we present the initial design and calibration of the system along with experimental data regarding the accuracy of the proposed approach. We are also providing results regarding the modelling of interior spaces and artefacts accompanied with accuracy tests from other modelling approaches based on photogrammetry and laser scanning.

  16. Searching for learning-dependent changes in the antennal lobe: simultaneous recording of neural activity and aversive olfactory learning in honeybees

    Directory of Open Access Journals (Sweden)

    Edith Roussel

    2010-09-01

    Full Text Available Plasticity in the honeybee brain has been studied using the appetitive olfactory conditioning of the proboscis extension reflex, in which a bee learns the association between an odor and a sucrose reward. In this framework, coupling behavioral measurements of proboscis extension and invasive recordings of neural activity has been difficult because proboscis movements usually introduce brain movements that affect physiological preparations. Here we took advantage of a new conditioning protocol, the aversive olfactory conditioning of the sting extension reflex, which does not generate this problem. We achieved the first simultaneous recordings of conditioned sting extension responses and calcium imaging of antennal lobe activity, thus revealing on-line processing of olfactory information during conditioning trials. Based on behavioral output we distinguished learners and non-learners and analyzed possible learning-dependent changes in antennal lobe activity. We did not find differences between glomerular responses to the CS+ and the CS- in learners. Unexpectedly, we found that during conditioning trials non-learners exhibited a progressive decrease in physiological responses to odors, irrespective of their valence. This effect could neither be attributed to a fitness problem nor to abnormal dye bleaching. We discuss the absence of learning-induced changes in the antennal lobe of learners and the decrease in calcium responses found in non-learners. Further studies will have to extend the search for functional plasticity related to aversive learning to other brain areas and to look on a broader range of temporal scales

  17. Brain machine interfaces combining microelectrode arrays with nanostructured optical biochemical sensors

    Science.gov (United States)

    Hajj-Hassan, Mohamad; Gonzalez, Timothy; Ghafer-Zadeh, Ebrahim; Chodavarapu, Vamsy; Musallam, Sam; Andrews, Mark

    2009-02-01

    Neural microelectrodes are an important component of neural prosthetic systems which assist paralyzed patients by allowing them to operate computers or robots using their neural activity. These microelectrodes are also used in clinical settings to localize the locus of seizure initiation in epilepsy or to stimulate sub-cortical structures in patients with Parkinson's disease. In neural prosthetic systems, implanted microelectrodes record the electrical potential generated by specific thoughts and relay the signals to algorithms trained to interpret these thoughts. In this paper, we describe novel elongated multi-site neural electrodes that can record electrical signals and specific neural biomarkers and that can reach depths greater than 8mm in the sulcus of non-human primates (monkeys). We hypothesize that additional signals recorded by the multimodal probes will increase the information yield when compared to standard probes that record just electropotentials. We describe integration of optical biochemical sensors with neural microelectrodes. The sensors are made using sol-gel derived xerogel thin films that encapsulate specific biomarker responsive luminophores in their nanostructured pores. The desired neural biomarkers are O2, pH, K+, and Na+ ions. As a prototype, we demonstrate direct-write patterning to create oxygen-responsive xerogel waveguide structures on the neural microelectrodes. The recording of neural biomarkers along with electrical activity could help the development of intelligent and more userfriendly neural prosthesis/brain machine interfaces as well as aid in providing answers to complex brain diseases and disorders.

  18. Optics

    CERN Document Server

    Mathieu, Jean Paul

    1975-01-01

    Optics, Parts 1 and 2 covers electromagnetic optics and quantum optics. The first part of the book examines the various of the important properties common to all electromagnetic radiation. This part also studies electromagnetic waves; electromagnetic optics of transparent isotropic and anisotropic media; diffraction; and two-wave and multi-wave interference. The polarization states of light, the velocity of light, and the special theory of relativity are also examined in this part. The second part is devoted to quantum optics, specifically discussing the classical molecular theory of optical p

  19. Statistical identification of stimulus-activated network nodes in multi-neuron voltage-sensitive dye optical recordings.

    Science.gov (United States)

    Fathiazar, Elham; Anemuller, Jorn; Kretzberg, Jutta

    2016-08-01

    Voltage-Sensitive Dye (VSD) imaging is an optical imaging method that allows measuring the graded voltage changes of multiple neurons simultaneously. In neuroscience, this method is used to reveal networks of neurons involved in certain tasks. However, the recorded relative dye fluorescence changes are usually low and signals are superimposed by noise and artifacts. Therefore, establishing a reliable method to identify which cells are activated by specific stimulus conditions is the first step to identify functional networks. In this paper, we present a statistical method to identify stimulus-activated network nodes as cells, whose activities during sensory network stimulation differ significantly from the un-stimulated control condition. This method is demonstrated based on voltage-sensitive dye recordings from up to 100 neurons in a ganglion of the medicinal leech responding to tactile skin stimulation. Without relying on any prior physiological knowledge, the network nodes identified by our statistical analysis were found to match well with published cell types involved in tactile stimulus processing and to be consistent across stimulus conditions and preparations.

  20. Short communication: Use of genomic and metabolic information as well as milk performance records for prediction of subclinical ketosis risk via artificial neural networks.

    Science.gov (United States)

    Ehret, A; Hochstuhl, D; Krattenmacher, N; Tetens, J; Klein, M S; Gronwald, W; Thaller, G

    2015-01-01

    Subclinical ketosis is one of the most prevalent metabolic disorders in high-producing dairy cows during early lactation. This renders its early detection and prevention important for both economical and animal-welfare reasons. Construction of reliable predictive models is challenging, because traits like ketosis are commonly affected by multiple factors. In this context, machine learning methods offer great advantages because of their universal learning ability and flexibility in integrating various sorts of data. Here, an artificial-neural-network approach was applied to investigate the utility of metabolic, genetic, and milk performance data for the prediction of milk levels of β-hydroxybutyrate within and across consecutive weeks postpartum. Data were collected from 218 dairy cows during their first 5wk in milk. All animals were genotyped with a 50,000 SNP panel, and weekly information on the concentrations of the milk metabolites glycerophosphocholine and phosphocholine as well as milk composition data (milk yield, fat and protein percentage) was available. The concentration of β-hydroxybutyric acid in milk was used as target variable in all prediction models. Average correlations between observed and predicted target values up to 0.643 could be obtained, if milk metabolite and routine milk recording data were combined for prediction at the same day within weeks. Predictive performance of metabolic as well as milk performance-based models was higher than that of models based on genetic information. Copyright © 2015 American Dairy Science Association. Published by Elsevier Inc. All rights reserved.

  1. A Sub-µW Tuneable Switched-Capacitor Amplifier-Filter for Neural Recording Using a Class-C Inverter

    Directory of Open Access Journals (Sweden)

    A Ghorbani-Nejad

    2013-12-01

    Full Text Available A two stage sub-µW Inverter-based switched-capacitor amplifier-filter is presented which is capable of amplifying both spikes and local field potentials (LFP signals. Here we employ a switched capacitor technique for frequency tuning and reducing of 1/f noise of two stages. The reduction of power consumption is very necessary for neural recording devices however, in switched capacitor (SC circuits OTA is a major building block that consumes most of the power. Therefore an OTA-less technique utilizing a class-C inverter is employed that significantly reduces the power consumption. A detailed analysis of noise performance for the inverter-based SC circuits is presented. A mathematical model useful for analysis of such SC integrators is derived and a good comparison is obtained between simulation and analytical technique. With a supply voltage of 0.7V and using 0.18 µm CMOS technology, this design can achieves a power consumption of about 538 nW. The designed amplifier-filter has the gains 18.6 dB and 28.2 dB for low pass only and cascaded filter, respectively. By applying different sampling frequencies, the filter attains a reconfigurable bandwidth.

  2. Optics

    CERN Document Server

    Fincham, W H A

    2013-01-01

    Optics: Ninth Edition Optics: Ninth Edition covers the work necessary for the specialization in such subjects as ophthalmic optics, optical instruments and lens design. The text includes topics such as the propagation and behavior of light; reflection and refraction - their laws and how different media affect them; lenses - thick and thin, cylindrical and subcylindrical; photometry; dispersion and color; interference; and polarization. Also included are topics such as diffraction and holography; the limitation of beams in optical systems and its effects; and lens systems. The book is recommen

  3. Optics

    CERN Document Server

    Fincham, W H A

    2013-01-01

    Optics: Eighth Edition covers the work necessary for the specialization in such subjects as ophthalmic optics, optical instruments and lens design. The text includes topics such as the propagation and behavior of light; reflection and refraction - their laws and how different media affect them; lenses - thick and thin, cylindrical and subcylindrical; photometry; dispersion and color; interference; and polarization. Also included are topics such as diffraction and holography; the limitation of beams in optical systems and its effects; and lens systems. The book is recommended for engineering st

  4. High-density optical data storage based on grey level recording in photobleaching polymers using two-photon excitation under ultrashort pulse and continuous wave illumination

    International Nuclear Information System (INIS)

    Ganic, D.; Day, D.; Gu, M.

    1999-01-01

    Full text: Two-photon excitation has been employed in three-dimensional optical data storage by many researchers in an attempt to increase the storage density of a given material. The probability of two-photon excitation is proportional to the squared intensity of the incident light; this effect produces excitation only within a small region of the focus spot. Another advantage of two-photon excitation is the use of infrared illumination, which results in the reduction of scattering and enables the recording of layers at a deep depth in a thick material. The storage density thus obtained using multi-layered bit optical recording can be as high as Tbit/cm 3 . To increase this storage density even further, grey level recording can be employed. This method utilises variable exposure times of a laser beam focused into a photobleaching sample. As a result, the bleached area possesses a certain pixel value which depends upon the exposure time; this can increase the storage density many times depending upon the number of grey levels used. Our experiment shows that it is possible to attain grey level recording using both ultrashort pulsed and continuous-wave illumination. Although continuous wave illumination requires an average power of approximately 2 orders of magnitude higher than that for ultrashort pulsed illumination, it is a preferred method of recording due to its relatively low system cost and compactness. Copyright (1999) Australian Optical Society

  5. Performance of the Wavelet Transform-Neural Network Based Receiver for DPIM in Diffuse Indoor Optical Wireless Links in Presence of Artificial Light Interference

    Directory of Open Access Journals (Sweden)

    Sujan Rajbhandari

    2009-06-01

    Full Text Available Artificial neural network (ANN has application in communication engineering in diverse areas such as channel equalization, channel modeling, error control code because of its capability of nonlinear processing, adaptability, and parallel processing. On the other hand, wavelet transform (WT with both the time and the frequency resolution provides the exact representation of signal in both domains. Applying these signal processing tools for channel compensation and noise reduction can provide an enhanced performance compared to the traditional tools. In this paper, the slot error rate (SER performance of digital pulse interval modulation (DPIM in diffuse indoor optical wireless (OW links subjected to the artificial light interference (ALI is reported with new receiver structure based on the discrete WT (DWT and ANN. Simulation results show that the DWT-ANN based receiver is very effective in reducing the effect of multipath induced inter-symbol interference (ISI and ALI.

  6. Monitoring food quality using an optical fibre based sensor system—a comparison of Kohonen and back-propagation neural network classification techniques

    Science.gov (United States)

    Sheridan, C.; O'Farrell, M.; Lewis, E.; Lyons, W. B.; Flanagan, C.; Jackman, N.

    2006-02-01

    This paper reports on two methods of classifying the spectral data from an optical fibre based sensor system as used in the food industry. The first method uses a feed-forward back-propagation artificial neural network while the second method involves using Kohonen self-organizing maps. The sensor monitors the food colour online as the food cooks by examining the reflected light from both the surface and the core of the product. The combination of using principal component analysis and back-propagation neural networks has been successfully investigated previously. In this paper, results obtained using this method are compared with results obtained using a self-organizing map trained on the principal components. The principal components used to train both classifiers are ordered in a 'colourscale'—a scale developed to allow several products of similar colour to be tested using a single network that had been trained using the colourscale. The results presented show that both classifiers perform well, and that any differences that arise occur at the boundaries of the classes.

  7. The potential of computer vision, optical backscattering parameters and artificial neural network modelling in monitoring the shrinkage of sweet potato (Ipomoea batatas L.) during drying.

    Science.gov (United States)

    Onwude, Daniel I; Hashim, Norhashila; Abdan, Khalina; Janius, Rimfiel; Chen, Guangnan

    2018-03-01

    Drying is a method used to preserve agricultural crops. During the drying of products with high moisture content, structural changes in shape, volume, area, density and porosity occur. These changes could affect the final quality of dried product and also the effective design of drying equipment. Therefore, this study investigated a novel approach in monitoring and predicting the shrinkage of sweet potato during drying. Drying experiments were conducted at temperatures of 50-70 °C and samples thicknesses of 2-6 mm. The volume and surface area obtained from camera vision, and the perimeter and illuminated area from backscattered optical images were analysed and used to evaluate the shrinkage of sweet potato during drying. The relationship between dimensionless moisture content and shrinkage of sweet potato in terms of volume, surface area, perimeter and illuminated area was found to be linearly correlated. The results also demonstrated that the shrinkage of sweet potato based on computer vision and backscattered optical parameters is affected by the product thickness, drying temperature and drying time. A multilayer perceptron (MLP) artificial neural network with input layer containing three cells, two hidden layers (18 neurons), and five cells for output layer, was used to develop a model that can monitor, control and predict the shrinkage parameters and moisture content of sweet potato slices under different drying conditions. The developed ANN model satisfactorily predicted the shrinkage and dimensionless moisture content of sweet potato with correlation coefficient greater than 0.95. Combined computer vision, laser light backscattering imaging and artificial neural network can be used as a non-destructive, rapid and easily adaptable technique for in-line monitoring, predicting and controlling the shrinkage and moisture changes of food and agricultural crops during drying. © 2017 Society of Chemical Industry. © 2017 Society of Chemical Industry.

  8. Smart time-pulse coding photoconverters as basic components 2D-array logic devices for advanced neural networks and optical computers

    Science.gov (United States)

    Krasilenko, Vladimir G.; Nikolsky, Alexander I.; Lazarev, Alexander A.; Michalnichenko, Nikolay N.

    2004-04-01

    The article deals with a conception of building arithmetic-logic devices (ALD) with a 2D-structure and optical 2D-array inputs-outputs as advanced high-productivity parallel basic operational training modules for realization of basic operation of continuous, neuro-fuzzy, multilevel, threshold and others logics and vector-matrix, vector-tensor procedures in neural networks, that consists in use of time-pulse coding (TPC) architecture and 2D-array smart optoelectronic pulse-width (or pulse-phase) modulators (PWM or PPM) for transformation of input pictures. The input grayscale image is transformed into a group of corresponding short optical pulses or time positions of optical two-level signal swing. We consider optoelectronic implementations of universal (quasi-universal) picture element of two-valued ALD, multi-valued ALD, analog-to-digital converters, multilevel threshold discriminators and we show that 2D-array time-pulse photoconverters are the base elements for these devices. We show simulation results of the time-pulse photoconverters as base components. Considered devices have technical parameters: input optical signals power is 200nW_200μW (if photodiode responsivity is 0.5A/W), conversion time is from tens of microseconds to a millisecond, supply voltage is 1.5_15V, consumption power is from tens of microwatts to a milliwatt, conversion nonlinearity is less than 1%. One cell consists of 2-3 photodiodes and about ten CMOS transistors. This simplicity of the cells allows to carry out their integration in arrays of 32x32, 64x64 elements and more.

  9. Reaching record-low β* at the CERN Large Hadron Collider using a novel scheme of collimator settings and optics

    Science.gov (United States)

    Bruce, R.; Bracco, C.; De Maria, R.; Giovannozzi, M.; Mereghetti, A.; Mirarchi, D.; Redaelli, S.; Quaranta, E.; Salvachua, B.

    2017-03-01

    The Large Hadron Collider (LHC) at CERN is built to collide intense proton beams with an unprecedented energy of 7 TeV. The design stored energy per beam of 362 MJ makes the LHC beams highly destructive, so that any beam losses risk to cause quenches of superconducting magnets or damage to accelerator components. Collimators are installed to protect the machine and they define a minimum normalized aperture, below which no other element is allowed. This imposes a limit on the achievable luminosity, since when squeezing β* (the β-function at the collision point) to smaller values for increased luminosity, the β-function in the final focusing system increases. This leads to a smaller normalized aperture that risks to go below the allowed collimation aperture. In the first run of the LHC, this was the main limitation on β*, which was constrained to values above the design specification. In this article, we show through theoretical and experimental studies how tighter collimator openings and a new optics with specific phase-advance constraints allows a β* as small as 40 cm, a factor 2 smaller than β*=80 cm used in 2015 and significantly below the design value β*=55 cm, in spite of a lower beam energy. The proposed configuration with β*=40 cm has been successfully put into operation and has been used throughout 2016 as the LHC baseline. The decrease in β* compared to 2015 has been an essential contribution to reaching and surpassing, in 2016, the LHC design luminosity for the first time, and to accumulating a record-high integrated luminosity of around 40 fb-1 in one year, in spite of using less bunches than in the design.

  10. A novel method to produce nonlinear empirical physical formulas for experimental nonlinear electro-optical responses of doped nematic liquid crystals: Feedforward neural network approach

    Energy Technology Data Exchange (ETDEWEB)

    Yildiz, Nihat, E-mail: nyildiz@cumhuriyet.edu.t [Cumhuriyet University, Faculty of Science and Literature, Department of Physics, 58140 Sivas (Turkey); San, Sait Eren; Okutan, Mustafa [Department of Physics, Gebze Institute of Technology, P.O. Box 141, Gebze 41400, Kocaeli (Turkey); Kaya, Hueseyin [Cumhuriyet University, Faculty of Science and Literature, Department of Physics, 58140 Sivas (Turkey)

    2010-04-15

    Among other significant obstacles, inherent nonlinearity in experimental physical response data poses severe difficulty in empirical physical formula (EPF) construction. In this paper, we applied a novel method (namely layered feedforward neural network (LFNN) approach) to produce explicit nonlinear EPFs for experimental nonlinear electro-optical responses of doped nematic liquid crystals (NLCs). Our motivation was that, as we showed in a previous theoretical work, an appropriate LFNN, due to its exceptional nonlinear function approximation capabilities, is highly relevant to EPF construction. Therefore, in this paper, we obtained excellently produced LFNN approximation functions as our desired EPFs for above-mentioned highly nonlinear response data of NLCs. In other words, by using suitable LFNNs, we successfully fitted the experimentally measured response and predicted the new (yet-to-be measured) response data. The experimental data (response versus input) were diffraction and dielectric properties versus bias voltage; and they were all taken from our previous experimental work. We conclude that in general, LFNN can be applied to construct various types of EPFs for the corresponding various nonlinear physical perturbation (thermal, electronic, molecular, electric, optical, etc.) data of doped NLCs.

  11. A novel method to produce nonlinear empirical physical formulas for experimental nonlinear electro-optical responses of doped nematic liquid crystals: Feedforward neural network approach

    International Nuclear Information System (INIS)

    Yildiz, Nihat; San, Sait Eren; Okutan, Mustafa; Kaya, Hueseyin

    2010-01-01

    Among other significant obstacles, inherent nonlinearity in experimental physical response data poses severe difficulty in empirical physical formula (EPF) construction. In this paper, we applied a novel method (namely layered feedforward neural network (LFNN) approach) to produce explicit nonlinear EPFs for experimental nonlinear electro-optical responses of doped nematic liquid crystals (NLCs). Our motivation was that, as we showed in a previous theoretical work, an appropriate LFNN, due to its exceptional nonlinear function approximation capabilities, is highly relevant to EPF construction. Therefore, in this paper, we obtained excellently produced LFNN approximation functions as our desired EPFs for above-mentioned highly nonlinear response data of NLCs. In other words, by using suitable LFNNs, we successfully fitted the experimentally measured response and predicted the new (yet-to-be measured) response data. The experimental data (response versus input) were diffraction and dielectric properties versus bias voltage; and they were all taken from our previous experimental work. We conclude that in general, LFNN can be applied to construct various types of EPFs for the corresponding various nonlinear physical perturbation (thermal, electronic, molecular, electric, optical, etc.) data of doped NLCs.

  12. Novel aluminum near field transducer and highly integrated micro-nano-optics design for heat-assisted ultra-high-density magnetic recording

    International Nuclear Information System (INIS)

    Miao, Lingyun; Hsiang, Thomas Y; Stoddart, Paul R

    2014-01-01

    Heat-assisted magnetic recording (HAMR) has attracted increasing attention as one of the most promising future techniques for ultra-high-density magnetic recording beyond the current limit of 1 Tb in −2 . Localized surface plasmon resonance plays an important role in HAMR by providing a highly focused optical spot for heating the recording medium within a small volume. In this work, we report an aluminum near-field transducer (NFT) based on a novel bow-tie design. At an operating wavelength of 450 nm, the proposed transducer can generate a 35 nm spot size inside the magnetic recording medium, corresponding to a recording density of up to 2 Tb in −2 . A highly integrated micro-nano-optics design is also proposed to ensure process compatibility and corrosion-resistance of the aluminum NFT. Our work has demonstrated the feasibility of using aluminum as a plasmonic material for HAMR, with advantages of reduced cost and improved efficiency compared to traditional noble metals. (paper)

  13. Quantifying the Evolution of Melt Ponds in the Marginal Ice Zone Using High Resolution Optical Imagery and Neural Networks

    Science.gov (United States)

    Ortiz, M.; Pinales, J. C.; Graber, H. C.; Wilkinson, J.; Lund, B.

    2016-02-01

    Melt ponds on sea ice play a significant and complex role on the thermodynamics in the Marginal Ice Zone (MIZ). Ponding reduces the sea ice's ability to reflect sunlight, and in consequence, exacerbates the albedo positive feedback cycle. In order to understand how melt ponds work and their effect on the heat uptake of sea ice, we must quantify ponds through their seasonal evolution first. A semi-supervised neural network three-class learning scheme using a gradient descent with momentum and adaptive learning rate backpropagation function is applied to classify melt ponds/melt areas in the Beaufort Sea region. The network uses high resolution panchromatic satellite images from the MEDEA program, which are collocated with autonomous platform arrays from the Marginal Ice Zone Program, including ice mass-balance buoys, arctic weather stations and wave buoys. The goal of the study is to capture the spatial variation of melt onset and freeze-up of the ponds within the MIZ, and gather ponding statistics such as size and concentration. The innovation of this work comes from training the neural network as the melt ponds evolve over time; making the machine learning algorithm time-dependent, which has not been previously done. We will achieve this by analyzing the image histograms through quantification of the minima and maxima intensity changes as well as linking textural variation information of the imagery. We will compare the evolution of the melt ponds against several different array sites on the sea ice to explore if there are spatial differences among the separated platforms in the MIZ.

  14. Neural organization of first optic neuropils in the littoral crab Hemigrapsus oregonensis and the semiterrestrial species Chasmagnathus granulatus.

    Science.gov (United States)

    Sztarker, Julieta; Strausfeld, Nicholas; Andrew, David; Tomsic, Daniel

    2009-03-10

    Crustaceans are among the most extensively distributed arthropods, occupying many ecologies and manifesting a great variety of compound eye optics; but in comparison with insects, relatively little is known about the organization and neuronal morphologies of their underlying optic neuropils. Most studies, which have been limited to descriptions of the first neuropil--the lamina--suggest that different species have approximately comparable cell types. However, such studies have been limited with regard to the types of neurons they identify and most omit their topographic relationships. It is also uncertain whether similarities, such as they are, are independent of visual ecologies. The present account describes and compares the morphologies and dispositions of monopolar and other efferent neurons as well as the organization of tangential and smaller centrifugal neurons in two grapsoid crabs, one from the South Atlantic, the other from the North Pacific. Because these species occupy significantly disparate ecologies we ask whether this might be reflected in differences of cell arrangements within the most peripheral levels of the visual system. The present study identifies such differences with respect to the organization of centrifugal neurons to the lamina. We also identify in both species neurons in the lamina that have hitherto not been identified in crustaceans and we draw specific comparisons between the layered organization of the grapsoid lamina and layered laminas of insects.

  15. Automatic diagnosis of abnormal macula in retinal optical coherence tomography images using wavelet-based convolutional neural network features and random forests classifier.

    Science.gov (United States)

    Rasti, Reza; Mehridehnavi, Alireza; Rabbani, Hossein; Hajizadeh, Fedra

    2018-03-01

    The present research intends to propose a fully automatic algorithm for the classification of three-dimensional (3-D) optical coherence tomography (OCT) scans of patients suffering from abnormal macula from normal candidates. The method proposed does not require any denoising, segmentation, retinal alignment processes to assess the intraretinal layers, as well as abnormalities or lesion structures. To classify abnormal cases from the control group, a two-stage scheme was utilized, which consists of automatic subsystems for adaptive feature learning and diagnostic scoring. In the first stage, a wavelet-based convolutional neural network (CNN) model was introduced and exploited to generate B-scan representative CNN codes in the spatial-frequency domain, and the cumulative features of 3-D volumes were extracted. In the second stage, the presence of abnormalities in 3-D OCTs was scored over the extracted features. Two different retinal SD-OCT datasets are used for evaluation of the algorithm based on the unbiased fivefold cross-validation (CV) approach. The first set constitutes 3-D OCT images of 30 normal subjects and 30 diabetic macular edema (DME) patients captured from the Topcon device. The second publicly available set consists of 45 subjects with a distribution of 15 patients in age-related macular degeneration, DME, and normal classes from the Heidelberg device. With the application of the algorithm on overall OCT volumes and 10 repetitions of the fivefold CV, the proposed scheme obtained an average precision of 99.33% on dataset1 as a two-class classification problem and 98.67% on dataset2 as a three-class classification task. (2018) COPYRIGHT Society of Photo-Optical Instrumentation Engineers (SPIE).

  16. A paradoxical improvement of misreaching in optic ataxia: new evidence for two separate neural systems for visual localization.

    Science.gov (United States)

    Milner, A D; Paulignan, Y; Dijkerman, H C; Michel, F; Jeannerod, M

    1999-11-07

    We tested a patient (A. T.) with bilateral brain damage to the parietal lobes, whose resulting 'optic ataxia' causes her to make large pointing errors when asked to locate single light emitting diodes presented in her visual field. We report here that, unlike normal individuals, A. T.'s pointing accuracy improved when she was required to wait for 5 s before responding. This counter-intuitive result is interpreted as reflecting the very brief time-scale on which visuomotor control systems in the superior parietal lobe operate. When an immediate response was required, A. T.'s damaged visuomotor system caused her to make large errors; but when a delay was required, a different, more flexible, visuospatial coding system--presumably relatively intact in her brain--came into play, resulting in much more accurate responses. The data are consistent with a dual processing theory whereby motor responses made directly to visual stimuli are guided by a dedicated system in the superior parietal and premotor cortices, while responses to remembered stimuli depend on perceptual processing and may thus crucially involve processing within the temporal neocortex.

  17. Dual Optical Recordings for Action Potentials and Calcium Handling in Induced Pluripotent Stem Cell Models of Cardiac Arrhythmias Using Genetically Encoded Fluorescent Indicators

    Science.gov (United States)

    Song, LouJin; Awari, Daniel W.; Han, Elizabeth Y.; Uche-Anya, Eugenia; Park, Seon-Hye E.; Yabe, Yoko A.; Chung, Wendy K.

    2015-01-01

    Reprogramming of human somatic cells to pluripotency has been used to investigate disease mechanisms and to identify potential therapeutics. However, the methods used for reprogramming, in vitro differentiation, and phenotyping are still complicated, expensive, and time-consuming. To address the limitations, we first optimized a protocol for reprogramming of human fibroblasts and keratinocytes into pluripotency using single lipofection and the episomal vectors in a 24-well plate format. This method allowed us to generate multiple lines of integration-free and feeder-free induced pluripotent stem cells (iPSCs) from seven patients with cardiac diseases and three controls. Second, we differentiated human iPSCs derived from patients with Timothy syndrome into cardiomyocytes using a monolayer differentiation method. We found that Timothy syndrome cardiomyocytes showed slower, irregular contractions and abnormal calcium handling compared with the controls. The results are consistent with previous reports using a retroviral method for reprogramming and an embryoid body-based method for cardiac differentiation. Third, we developed an efficient approach for recording the action potentials and calcium transients simultaneously in control and patient cardiomyocytes using genetically encoded fluorescent indicators, ArcLight and R-GECO1. The dual optical recordings enabled us to observe prolonged action potentials and abnormal calcium handling in Timothy syndrome cardiomyocytes. We confirmed that roscovitine rescued the phenotypes in Timothy syndrome cardiomyocytes and that these findings were consistent with previous studies using conventional electrophysiological recordings and calcium imaging with dyes. The approaches using our optimized methods and dual optical recordings will improve iPSC applicability for disease modeling to investigate mechanisms underlying cardiac arrhythmias and to test potential therapeutics. PMID:25769651

  18. Electronic Document Imaging and Optical Storage Systems for Local Governments: An Introduction. Local Government Records Technical Information Series. Number 21.

    Science.gov (United States)

    Schwartz, Stanley F.

    This publication introduces electronic document imaging systems and provides guidance for local governments in New York in deciding whether such systems should be adopted for their own records and information management purposes. It advises local governments on how to develop plans for using such technology by discussing its advantages and…

  19. Automatic diagnosis of abnormal macula in retinal optical coherence tomography images using wavelet-based convolutional neural network features and random forests classifier

    Science.gov (United States)

    Rasti, Reza; Mehridehnavi, Alireza; Rabbani, Hossein; Hajizadeh, Fedra

    2018-03-01

    The present research intends to propose a fully automatic algorithm for the classification of three-dimensional (3-D) optical coherence tomography (OCT) scans of patients suffering from abnormal macula from normal candidates. The method proposed does not require any denoising, segmentation, retinal alignment processes to assess the intraretinal layers, as well as abnormalities or lesion structures. To classify abnormal cases from the control group, a two-stage scheme was utilized, which consists of automatic subsystems for adaptive feature learning and diagnostic scoring. In the first stage, a wavelet-based convolutional neural network (CNN) model was introduced and exploited to generate B-scan representative CNN codes in the spatial-frequency domain, and the cumulative features of 3-D volumes were extracted. In the second stage, the presence of abnormalities in 3-D OCTs was scored over the extracted features. Two different retinal SD-OCT datasets are used for evaluation of the algorithm based on the unbiased fivefold cross-validation (CV) approach. The first set constitutes 3-D OCT images of 30 normal subjects and 30 diabetic macular edema (DME) patients captured from the Topcon device. The second publicly available set consists of 45 subjects with a distribution of 15 patients in age-related macular degeneration, DME, and normal classes from the Heidelberg device. With the application of the algorithm on overall OCT volumes and 10 repetitions of the fivefold CV, the proposed scheme obtained an average precision of 99.33% on dataset1 as a two-class classification problem and 98.67% on dataset2 as a three-class classification task.

  20. Statistical relationship between surface PM10 concentration and aerosol optical depth over the Sahel as a function of weather type, using neural network methodology

    Science.gov (United States)

    Yahi, H.; Marticorena, B.; Thiria, S.; Chatenet, B.; Schmechtig, C.; Rajot, J. L.; Crepon, M.

    2013-12-01

    work aims at assessing the capability of passive remote-sensed measurements such as aerosol optical depth (AOD) to monitor the surface dust concentration during the dry season in the Sahel region (West Africa). We processed continuous measurements of AODs and surface concentrations for the period (2006-2010) in Banizoumbou (Niger) and Cinzana (Mali). In order to account for the influence of meteorological condition on the relationship between PM10 surface concentration and AOD, we decomposed the mesoscale meteorological fields surrounding the stations into five weather types having similar 3-dimensional atmospheric characteristics. This classification was obtained by a clustering method based on nonlinear artificial neural networks, the so-called self-organizing map. The weather types were identified by processing tridimensional fields of meridional and zonal winds and air temperature obtained from European Centre for Medium-Range Weather Forecasts (ECMWF) model output centered on each measurement station. Five similar weather types have been identified at the two stations. Three of them are associated with the Harmattan flux; the other two correspond to northward inflow of the monsoon flow at the beginning or the end of the dry season. An improved relationship has been found between the surface PM10 concentrations and the AOD by using a dedicated statistical relationship for each weather type. The performances of the statistical inversion computed on the test data sets show satisfactory skills for most of the classes, much better than a linear regression. This should permit the inversion of the mineral dust concentration from AODs derived from satellite observations over the Sahel.

  1. A high-speed, reconfigurable, channel- and time-tagged photon arrival recording system for intensity-interferometry and quantum optics experiments

    Science.gov (United States)

    Girish, B. S.; Pandey, Deepak; Ramachandran, Hema

    2017-08-01

    We present a compact, inexpensive multichannel module, APODAS (Avalanche Photodiode Output Data Acquisition System), capable of detecting 0.8 billion photons per second and providing real-time recording on a computer hard-disk, of channel- and time-tagged information of the arrival of upto 0.4 billion photons per second. Built around a Virtex-5 Field Programmable Gate Array (FPGA) unit, APODAS offers a temporal resolution of 5 nanoseconds with zero deadtime in data acquisition, utilising an efficient scheme for time and channel tagging and employing Gigabit ethernet for the transfer of data. Analysis tools have been developed on a Linux platform for multi-fold coincidence studies and time-delayed intensity interferometry. As illustrative examples, the second-order intensity correlation function ( g 2) of light from two commonly used sources in quantum optics —a coherent laser source and a dilute atomic vapour emitting spontaneously, constituting a thermal source— are presented. With easy reconfigurability and with no restriction on the total record length, APODAS can be readily used for studies over various time scales. This is demonstrated by using APODAS to reveal Rabi oscillations on nanosecond time scales in the emission of ultracold atoms, on the one hand, and, on the other hand, to measure the second-order correlation function on the millisecond time scales from tailored light sources. The efficient and versatile performance of APODAS promises its utility in diverse fields, like quantum optics, quantum communication, nuclear physics, astrophysics and biology.

  2. High-speed, random-access fluorescence microscopy: I. High-resolution optical recording with voltage-sensitive dyes and ion indicators.

    Science.gov (United States)

    Bullen, A; Patel, S S; Saggau, P

    1997-07-01

    The design and implementation of a high-speed, random-access, laser-scanning fluorescence microscope configured to record fast physiological signals from small neuronal structures with high spatiotemporal resolution is presented. The laser-scanning capability of this nonimaging microscope is provided by two orthogonal acousto-optic deflectors under computer control. Each scanning point can be randomly accessed and has a positioning time of 3-5 microseconds. Sampling time is also computer-controlled and can be varied to maximize the signal-to-noise ratio. Acquisition rates up to 200k samples/s at 16-bit digitizing resolution are possible. The spatial resolution of this instrument is determined by the minimal spot size at the level of the preparation (i.e., 2-7 microns). Scanning points are selected interactively from a reference image collected with differential interference contrast optics and a video camera. Frame rates up to 5 kHz are easily attainable. Intrinsic variations in laser light intensity and scanning spot brightness are overcome by an on-line signal-processing scheme. Representative records obtained with this instrument by using voltage-sensitive dyes and calcium indicators demonstrate the ability to make fast, high-fidelity measurements of membrane potential and intracellular calcium at high spatial resolution (2 microns) without any temporal averaging.

  3. NOAA Climate Data Record (CDR) of Precipitation Estimation from Remotely Sensed Information using Artificial Neural Networks (PERSIANN-CDR), Version 1 Revision 1

    Data.gov (United States)

    National Oceanic and Atmospheric Administration, Department of Commerce — PERSIANN Precipitation Climate Data Record (PERSIANN-CDR) is a daily quasi-global precipitation product for the period of 1982 to 2011. The data covers from 60...

  4. Optical trapping of nanoparticles with significantly reduced laser powers by using counter-propagating beams (Presentation Recording)

    Science.gov (United States)

    Zhao, Chenglong; LeBrun, Thomas W.

    2015-08-01

    Gold nanoparticles (GNP) have wide applications ranging from nanoscale heating to cancer therapy and biological sensing. Optical trapping of GNPs as small as 18 nm has been successfully achieved with laser power as high as 855 mW, but such high powers can damage trapped particles (particularly biological systems) as well heat the fluid, thereby destabilizing the trap. In this article, we show that counter propagating beams (CPB) can successfully trap GNP with laser powers reduced by a factor of 50 compared to that with a single beam. The trapping position of a GNP inside a counter-propagating trap can be easily modulated by either changing the relative power or position of the two beams. Furthermore, we find that under our conditions while a single-beam most stably traps a single particle, the counter-propagating beam can more easily trap multiple particles. This (CPB) trap is compatible with the feedback control system we recently demonstrated to increase the trapping lifetimes of nanoparticles by more than an order of magnitude. Thus, we believe that the future development of advanced trapping techniques combining counter-propagating traps together with control systems should significantly extend the capabilities of optical manipulation of nanoparticles for prototyping and testing 3D nanodevices and bio-sensing.

  5. Optically stimulated luminescence dating as a tool for calculating sedimentation rates in Chinese loess: comparisons with grain-size records

    DEFF Research Database (Denmark)

    Stevens, Thomas; Lu, HY

    2009-01-01

    Understanding loess sedimentation rates is crucial for constraining past atmospheric dust dynamics, regional climatic change and local depositional environments. However, the derivation of loess sedimentation rates is complicated by the lack of available methods for independent calculation......) the influences on sediment grain-size and accumulation; and (ii) their relationship through time and across the depositional region. This uncertainty has led to the widespread use of assumptions concerning the relationship between sedimentation rate and grain-size in order to derive age models and climate...... reconstructions. To address this uncertainty, detailed independent age models, based on optically stimulated luminescence dating, undertaken at 10 to 40 cm intervals at five sections across the Loess Plateau in China, have been used to calculate sedimentation rates and make comparisons with grain-size changes...

  6. Rewritable phase-change optical recording in Ge2Sb2Te5 films induced by picosecond laser pulses

    International Nuclear Information System (INIS)

    Siegel, J.; Schropp, A.; Solis, J.; Afonso, C.N.; Wuttig, M.

    2004-01-01

    The phase transformation dynamics induced in Ge 2 Sb 2 Te 5 films by picosecond laser pulses were studied using real-time reflectivity measurements with subnanosecond resolution. Evidence was found that the thermal diffusivity of the substrate plays a crucial role in determining the ability of the films to crystallize and amorphize. A film/substrate configuration with optimized heat flow conditions for ultrafast phase cycling with picosecond laser pulses was designed and produced. In this system, we achieved reversible phase transformations with large optical contrast (>20%) using single laser pulses with a duration of 30 ps within well-defined fluence windows. The amorphization (writing) process is completed within less than 1 ns, whereas crystallization (erasing) needs approximately 13 ns to be completed

  7. Chronic neural probe for simultaneous recording of single-unit, multi-unit, and local field potential activity from multiple brain sites

    Science.gov (United States)

    Pothof, F.; Bonini, L.; Lanzilotto, M.; Livi, A.; Fogassi, L.; Orban, G. A.; Paul, O.; Ruther, P.

    2016-08-01

    Objective. Drug resistant focal epilepsy can be treated by resecting the epileptic focus requiring a precise focus localisation using stereoelectroencephalography (SEEG) probes. As commercial SEEG probes offer only a limited spatial resolution, probes of higher channel count and design freedom enabling the incorporation of macro and microelectrodes would help increasing spatial resolution and thus open new perspectives for investigating mechanisms underlying focal epilepsy and its treatment. This work describes a new fabrication process for SEEG probes with materials and dimensions similar to clinical probes enabling recording single neuron activity at high spatial resolution. Approach. Polyimide is used as a biocompatible flexible substrate into which platinum electrodes and leads are integrated with a minimal feature size of 5 μm. The polyimide foils are rolled into the cylindrical probe shape at a diameter of 0.8 mm. The resulting probe features match those of clinically approved devices. Tests in saline solution confirmed the probe stability and functionality. Probes were implanted into the brain of one monkey (Macaca mulatta), trained to perform different motor tasks. Suitable configurations including up to 128 electrode sites allow the recording of task-related neuronal signals. Main results. Probes with 32 and 64 electrode sites were implanted in the posterior parietal cortex. Local field potentials and multi-unit activity were recorded as early as one hour after implantation. Stable single-unit activity was achieved for up to 26 days after implantation of a 64-channel probe. All recorded signals showed modulation during task execution. Significance. With the novel probes it is possible to record stable biologically relevant data over a time span exceeding the usual time needed for epileptic focus localisation in human patients. This is the first time that single units are recorded along cylindrical polyimide probes chronically implanted 22 mm deep into the

  8. Resting-state hemodynamics are spatiotemporally coupled to synchronized and symmetric neural activity in excitatory neurons

    Science.gov (United States)

    Ma, Ying; Shaik, Mohammed A.; Kozberg, Mariel G.; Portes, Jacob P.; Timerman, Dmitriy

    2016-01-01

    Brain hemodynamics serve as a proxy for neural activity in a range of noninvasive neuroimaging techniques including functional magnetic resonance imaging (fMRI). In resting-state fMRI, hemodynamic fluctuations have been found to exhibit patterns of bilateral synchrony, with correlated regions inferred to have functional connectivity. However, the relationship between resting-state hemodynamics and underlying neural activity has not been well established, making the neural underpinnings of functional connectivity networks unclear. In this study, neural activity and hemodynamics were recorded simultaneously over the bilateral cortex of awake and anesthetized Thy1-GCaMP mice using wide-field optical mapping. Neural activity was visualized via selective expression of the calcium-sensitive fluorophore GCaMP in layer 2/3 and 5 excitatory neurons. Characteristic patterns of resting-state hemodynamics were accompanied by more rapidly changing bilateral patterns of resting-state neural activity. Spatiotemporal hemodynamics could be modeled by convolving this neural activity with hemodynamic response functions derived through both deconvolution and gamma-variate fitting. Simultaneous imaging and electrophysiology confirmed that Thy1-GCaMP signals are well-predicted by multiunit activity. Neurovascular coupling between resting-state neural activity and hemodynamics was robust and fast in awake animals, whereas coupling in urethane-anesthetized animals was slower, and in some cases included lower-frequency (resting-state hemodynamics in the awake and anesthetized brain are coupled to underlying patterns of excitatory neural activity. The patterns of bilaterally-symmetric spontaneous neural activity revealed by wide-field Thy1-GCaMP imaging may depict the neural foundation of functional connectivity networks detected in resting-state fMRI. PMID:27974609

  9. Effects of Surface Roughness and Mechanical Properties of Cover-Layer on Near-Field Optical Recording

    Science.gov (United States)

    Kim, Jin-Hong; Lee, Jun-Seok; Lim, Jungshik; Seo, Jung-Kyo

    2009-03-01

    Narrow gap distance in cover-layer incident near-field recording (NFR) configuration causes a collision problem in the interface between a solid immersion lens and a disk surface. A polymer cover-layer with smooth surface results in a stable gap servo while a nanocomposite cover-layer with high refractive index shows a collision problem during the gap servo test. Even though a dielectric cover-layer, in which the surface is rougher than the polymer, supplements the mechanical properties, an unclear eye pattern due to an unstable gap servo can be obtained after a chemical mechanical polishing. Not only smooth surface but also good mechanical properties of cover-layer are required for the stable gap servo in the NFR.

  10. Neural networks

    International Nuclear Information System (INIS)

    Denby, Bruce; Lindsey, Clark; Lyons, Louis

    1992-01-01

    The 1980s saw a tremendous renewal of interest in 'neural' information processing systems, or 'artificial neural networks', among computer scientists and computational biologists studying cognition. Since then, the growth of interest in neural networks in high energy physics, fueled by the need for new information processing technologies for the next generation of high energy proton colliders, can only be described as explosive

  11. New organic materials for optics: optical storage and nonlinear optics

    International Nuclear Information System (INIS)

    Gan, F.

    1996-01-01

    New organic materials have received considerable attention recently, due to their easy preparation and different variety. The most application fields in optics are optical storage and nonlinear optics. In optical storage the organic dyes have been used for example, in record able and erasable compact disks (CD-R, CD-E) nonlinear optical effects, such as nonlinear optical absorption, second and third order optical absorption, second and third order optical nonlinearities, can be applied for making optical limiters, optical modulators, as well as laser second and third harmonic generations. Due to high value of optical absorption and optical nonlinearity organic materials are always used as thin films in optical integration. In this paper the new experimental results have been presented, and future development has been also discussed. (author)

  12. Implantable Neural Interfaces for Sharks

    Science.gov (United States)

    2007-05-01

    technology for recording and stimulating from the auditory and olfactory sensory nervous systems of the awake, swimming nurse shark , G. cirratum (Figures...overlay of the central nervous system of the nurse shark on a horizontal MR image. Implantable Neural Interfaces for Sharks ...Neural Interfaces for Characterizing Population Responses to Odorants and Electrical Stimuli in the Nurse Shark , Ginglymostoma cirratum.” AChemS Abs

  13. Implantable neurotechnologies: a review of integrated circuit neural amplifiers.

    Science.gov (United States)

    Ng, Kian Ann; Greenwald, Elliot; Xu, Yong Ping; Thakor, Nitish V

    2016-01-01

    Neural signal recording is critical in modern day neuroscience research and emerging neural prosthesis programs. Neural recording requires the use of precise, low-noise amplifier systems to acquire and condition the weak neural signals that are transduced through electrode interfaces. Neural amplifiers and amplifier-based systems are available commercially or can be designed in-house and fabricated using integrated circuit (IC) technologies, resulting in very large-scale integration or application-specific integrated circuit solutions. IC-based neural amplifiers are now used to acquire untethered/portable neural recordings, as they meet the requirements of a miniaturized form factor, light weight and low power consumption. Furthermore, such miniaturized and low-power IC neural amplifiers are now being used in emerging implantable neural prosthesis technologies. This review focuses on neural amplifier-based devices and is presented in two interrelated parts. First, neural signal recording is reviewed, and practical challenges are highlighted. Current amplifier designs with increased functionality and performance and without penalties in chip size and power are featured. Second, applications of IC-based neural amplifiers in basic science experiments (e.g., cortical studies using animal models), neural prostheses (e.g., brain/nerve machine interfaces) and treatment of neuronal diseases (e.g., DBS for treatment of epilepsy) are highlighted. The review concludes with future outlooks of this technology and important challenges with regard to neural signal amplification.

  14. Neural Networks

    International Nuclear Information System (INIS)

    Smith, Patrick I.

    2003-01-01

    Physicists use large detectors to measure particles created in high-energy collisions at particle accelerators. These detectors typically produce signals indicating either where ionization occurs along the path of the particle, or where energy is deposited by the particle. The data produced by these signals is fed into pattern recognition programs to try to identify what particles were produced, and to measure the energy and direction of these particles. Ideally, there are many techniques used in this pattern recognition software. One technique, neural networks, is particularly suitable for identifying what type of particle caused by a set of energy deposits. Neural networks can derive meaning from complicated or imprecise data, extract patterns, and detect trends that are too complex to be noticed by either humans or other computer related processes. To assist in the advancement of this technology, Physicists use a tool kit to experiment with several neural network techniques. The goal of this research is interface a neural network tool kit into Java Analysis Studio (JAS3), an application that allows data to be analyzed from any experiment. As the final result, a physicist will have the ability to train, test, and implement a neural network with the desired output while using JAS3 to analyze the results or output. Before an implementation of a neural network can take place, a firm understanding of what a neural network is and how it works is beneficial. A neural network is an artificial representation of the human brain that tries to simulate the learning process [5]. It is also important to think of the word artificial in that definition as computer programs that use calculations during the learning process. In short, a neural network learns by representative examples. Perhaps the easiest way to describe the way neural networks learn is to explain how the human brain functions. The human brain contains billions of neural cells that are responsible for processing

  15. Evolvable synthetic neural system

    Science.gov (United States)

    Curtis, Steven A. (Inventor)

    2009-01-01

    An evolvable synthetic neural system includes an evolvable neural interface operably coupled to at least one neural basis function. Each neural basis function includes an evolvable neural interface operably coupled to a heuristic neural system to perform high-level functions and an autonomic neural system to perform low-level functions. In some embodiments, the evolvable synthetic neural system is operably coupled to one or more evolvable synthetic neural systems in a hierarchy.

  16. Neural constructivism or self-organization?

    NARCIS (Netherlands)

    van der Maas, H.L.J.; Molenaar, P.C.M.

    2000-01-01

    Comments on the article by S. R. Quartz et al (see record 1998-00749-001) which discussed the constructivist perspective of interaction between cognition and neural processes during development and consequences for theories of learning. Three arguments are given to show that neural constructivism

  17. Imposed Optical Defocus Induces Isoform-Specific Up-Regulation of TGFβ Gene Expression in Chick Retinal Pigment Epithelium and Choroid but Not Neural Retina

    Science.gov (United States)

    Zhang, Yan; Raychaudhuri, Suravi; Wildsoet, Christine F.

    2016-01-01

    Purpose This study investigated the gene expression of TGFβ isoforms and their receptors in chick retina, retinal pigment epithelium (RPE), and choroid and the effects of short-term imposed optical defocus. Methods The expression of TGFβ isoforms (TGF-β1, 2, 3) and TGFβ receptors (TGFBR1, 2, 3) was examined in the retina, RPE, and choroid of young White-Leghorn untreated chicks (19 days-old). The effects on the expression of the same genes of monocular +10 and -10 D defocusing lenses, worn for either 2 or 48 h by age-matched chicks, were also examined by comparing expression in treated and untreated fellow eyes. RNA was purified, characterized and then reverse transcribed to cDNA. Differential gene expression was quantified using real-time PCR. Results All 3 isoforms of TGFβ and all 3 receptor subtypes were found to be expressed in all 3 ocular tissues, with apparent tissue-dependent differences in expression profiles. Data are reported as mean normalized expression relative to GAPDH. Sign-dependent optical defocus effects were also observed. Optical defocus did not affect retinal gene expression but in the RPE, TGF-β2 expression was significantly up-regulated with +10 D lenses, worn for either 2 h (349% increase ± 88%, p < 0.01) or 48 h (752% increase ± 166%, p < 0.001), and in the choroid, the expression of TGF-β3 was up-regulated with -10 D lenses, worn for 48 h (147% increase ± 9%, p < 0.01). Conclusions The effects of short term exposure to optical defocus on TGFβ gene expression in the RPE and choroid, which were sign-dependent and isoform specific, provide further supporting evidence for important roles of members of the TGFβ family and these two tissues in local signal cascades regulating ocular growth. PMID:27214233

  18. A Morphometric Study of the Foramen of Diaphragma Sellae and Delineation of Its Relation to Optic Neural Pathways through Computer Aided Superimposition

    Directory of Open Access Journals (Sweden)

    Doris George Yohannan

    2015-01-01

    Full Text Available The diaphragma sellae (DS is a fold of dura that forms a partial roof over the pituitary gland. The foramen of the diaphragma sellae (FDS is thereby a pathway for suprasellar extension of pituitary tumors. The purpose of this study was to describe the anatomical dimensions of the DS and FDS and to understand the relationship of FDS with the overlying optic chiasma. The study was conducted in 100 autopsy cases. Measurements were taken using vernier calipers. Photographs, taken before and after removal of optic pathway, were superimposed using image processing software. The results showed that the mean A-P dimension of DS was 1.17 ± 0.48 cm; the lateral dimension of DS was 1.58 ± 0.60 cm. The mean A-P dimension of FDS was 0.66 ± 0.42 cm; the lateral dimension of FDS was 0.82 cm ± 0.54 cm. The shapes of FDS were irregular (40%, transversely oval (29%, circular (13%, sagittally oval (11%, or trapezoid with posterior dimension more than the anterior one (6% or anterior dimension more than the posterior one (1%. The margins of FDS were either well defined (31% or ill defined (69%. The positional relation of FDS to optic chiasma was also found out.

  19. NOAA Climate Data Record (CDR) of AVHRR Daily and Monthly Aerosol Optical Thickness (AOT) over Global Oceans, Version 3.0

    Data.gov (United States)

    National Oceanic and Atmospheric Administration, Department of Commerce — The product is the aerosol optical thickness (AOT) at 0.63 micron, which is retrieved from NOAA PATMOS-x level-2B orbital radinace and cloud CDR products. The...

  20. Versatile digital micromirror device-based method for the recording of multilevel optical diffractive elements in photosensitive chalcogenide layers (AMTIR-1).

    Science.gov (United States)

    Joerg, Alexandre; Vignaux, Mael; Lumeau, Julien

    2016-08-01

    A new alternative and versatile method for the production of diffractive optical elements (DOEs) with up to four phase levels in AMTIR-1 (Ge33As12Se55) layers is demonstrated. The developed method proposes the use of the photosensitive properties of the layers and a specific in situ optical monitoring coupled with a reverse engineering algorithm to control the trigger points of the writing of the different diffractive patterns. Examples of various volume DOEs are presented.

  1. NeuroMEMS: Neural Probe Microtechnologies

    Directory of Open Access Journals (Sweden)

    Sam Musallam

    2008-10-01

    Full Text Available Neural probe technologies have already had a significant positive effect on our understanding of the brain by revealing the functioning of networks of biological neurons. Probes are implanted in different areas of the brain to record and/or stimulate specific sites in the brain. Neural probes are currently used in many clinical settings for diagnosis of brain diseases such as seizers, epilepsy, migraine, Alzheimer’s, and dementia. We find these devices assisting paralyzed patients by allowing them to operate computers or robots using their neural activity. In recent years, probe technologies were assisted by rapid advancements in microfabrication and microelectronic technologies and thus are enabling highly functional and robust neural probes which are opening new and exciting avenues in neural sciences and brain machine interfaces. With a wide variety of probes that have been designed, fabricated, and tested to date, this review aims to provide an overview of the advances and recent progress in the microfabrication techniques of neural probes. In addition, we aim to highlight the challenges faced in developing and implementing ultralong multi-site recording probes that are needed to monitor neural activity from deeper regions in the brain. Finally, we review techniques that can improve the biocompatibility of the neural probes to minimize the immune response and encourage neural growth around the electrodes for long term implantation studies.

  2. Neural Networks

    Directory of Open Access Journals (Sweden)

    Schwindling Jerome

    2010-04-01

    Full Text Available This course presents an overview of the concepts of the neural networks and their aplication in the framework of High energy physics analyses. After a brief introduction on the concept of neural networks, the concept is explained in the frame of neuro-biology, introducing the concept of multi-layer perceptron, learning and their use as data classifer. The concept is then presented in a second part using in more details the mathematical approach focussing on typical use cases faced in particle physics. Finally, the last part presents the best way to use such statistical tools in view of event classifers, putting the emphasis on the setup of the multi-layer perceptron. The full article (15 p. corresponding to this lecture is written in french and is provided in the proceedings of the book SOS 2008.

  3. Memory and neural networks on the basis of color centers in solids.

    Science.gov (United States)

    Winnacker, Albrecht; Osvet, Andres

    2009-11-01

    Optical data recording is one of the most widely used and efficient systems of memory in the non-living world. The application of color centers in this context offers not only systems of high speed in writing and read-out due to a high degree of parallelism in data handling but also a possibility to set up models of neural networks. In this way, systems with a high potential for image processing, pattern recognition and logical operations can be constructed. A limitation to storage density is given by the diffraction limit of optical data recording. It is shown that this limitation can at least in principle be overcome by the principle of spectral hole burning, which results in systems of storage capacities close to the human brain system.

  4. Advances in optical information processing IV; Proceedings of the Meeting, Orlando, FL, Apr. 18-20, 1990

    Science.gov (United States)

    Pape, Dennis R.

    1990-09-01

    The present conference discusses topics in optical image processing, optical signal processing, acoustooptic spectrum analyzer systems and components, and optical computing. Attention is given to tradeoffs in nonlinearly recorded matched filters, miniature spatial light modulators, detection and classification using higher-order statistics of optical matched filters, rapid traversal of an image data base using binary synthetic discriminant filters, wideband signal processing for emitter location, an acoustooptic processor for autonomous SAR guidance, and sampling of Fresnel transforms. Also discussed are an acoustooptic RF signal-acquisition system, scanning acoustooptic spectrum analyzers, the effects of aberrations on acoustooptic systems, fast optical digital arithmetic processors, information utilization in analog and digital processing, optical processors for smart structures, and a self-organizing neural network for unsupervised learning.

  5. Blue laser phase change recording system

    International Nuclear Information System (INIS)

    Hofmann, Holger; Dambach, S.Soeren; Richter, Hartmut

    2002-01-01

    The migration paths from DVD phase change recording with red laser to the next generation optical disk formats with blue laser and high NA optics are discussed with respect to optical aberration margins and disc capacities. A test system for the evaluation of phase change disks with more than 20 GB capacity is presented and first results of the recording performance are shown

  6. Optics/Optical Diagnostics Laboratory

    Data.gov (United States)

    Federal Laboratory Consortium — The Optics/Optical Diagnostics Laboratory supports graduate instruction in optics, optical and laser diagnostics and electro-optics. The optics laboratory provides...

  7. Holographic Optical Data Storage

    Science.gov (United States)

    Timucin, Dogan A.; Downie, John D.; Norvig, Peter (Technical Monitor)

    2000-01-01

    Although the basic idea may be traced back to the earlier X-ray diffraction studies of Sir W. L. Bragg, the holographic method as we know it was invented by D. Gabor in 1948 as a two-step lensless imaging technique to enhance the resolution of electron microscopy, for which he received the 1971 Nobel Prize in physics. The distinctive feature of holography is the recording of the object phase variations that carry the depth information, which is lost in conventional photography where only the intensity (= squared amplitude) distribution of an object is captured. Since all photosensitive media necessarily respond to the intensity incident upon them, an ingenious way had to be found to convert object phase into intensity variations, and Gabor achieved this by introducing a coherent reference wave along with the object wave during exposure. Gabor's in-line recording scheme, however, required the object in question to be largely transmissive, and could provide only marginal image quality due to unwanted terms simultaneously reconstructed along with the desired wavefront. Further handicapped by the lack of a strong coherent light source, optical holography thus seemed fated to remain just another scientific curiosity, until the field was revolutionized in the early 1960s by some major breakthroughs: the proposition and demonstration of the laser principle, the introduction of off-axis holography, and the invention of volume holography. Consequently, the remainder of that decade saw an exponential growth in research on theory, practice, and applications of holography. Today, holography not only boasts a wide variety of scientific and technical applications (e.g., holographic interferometry for strain, vibration, and flow analysis, microscopy and high-resolution imagery, imaging through distorting media, optical interconnects, holographic optical elements, optical neural networks, three-dimensional displays, data storage, etc.), but has become a prominent am advertising

  8. Optical quality of the living cat eye.

    Science.gov (United States)

    Bonds, A B

    1974-12-01

    1. The optical quality of the living cat eye was measured under conditions similar to those of cat retinal ganglion cell experiments by recording the aerial image of a nearly monochromatic thin line of light.2. Experiments were performed to assess the nature of the fundal reflexion of the cat eye, which was found to behave essentially as a diffuser.3. The optical Modulation Transfer Function (MTF) was calculated from the measured aerial linespread using Fourier mathematics; the MTF of a ;typical' cat eye was averaged from data collected from ten eyes.4. The state of focus of the optical system, the pupil size and the angle of the light incident on the eye were all varied to determine their effect on image quality.5. By using an image rotator, the aerial linespread was measured for several orientations of the line; these measurements yielded an approximation of the two-dimensional pointspread completely characterizing the optical system.6. Evidence is reviewed to show that the optical resolution of the cat, albeit some 3-5 times worse than that of human, appears to be better than the neural resolution of its retina and its visual system as a whole.

  9. Neural Parallel Engine: A toolbox for massively parallel neural signal processing.

    Science.gov (United States)

    Tam, Wing-Kin; Yang, Zhi

    2018-05-01

    Large-scale neural recordings provide detailed information on neuronal activities and can help elicit the underlying neural mechanisms of the brain. However, the computational burden is also formidable when we try to process the huge data stream generated by such recordings. In this study, we report the development of Neural Parallel Engine (NPE), a toolbox for massively parallel neural signal processing on graphical processing units (GPUs). It offers a selection of the most commonly used routines in neural signal processing such as spike detection and spike sorting, including advanced algorithms such as exponential-component-power-component (EC-PC) spike detection and binary pursuit spike sorting. We also propose a new method for detecting peaks in parallel through a parallel compact operation. Our toolbox is able to offer a 5× to 110× speedup compared with its CPU counterparts depending on the algorithms. A user-friendly MATLAB interface is provided to allow easy integration of the toolbox into existing workflows. Previous efforts on GPU neural signal processing only focus on a few rudimentary algorithms, are not well-optimized and often do not provide a user-friendly programming interface to fit into existing workflows. There is a strong need for a comprehensive toolbox for massively parallel neural signal processing. A new toolbox for massively parallel neural signal processing has been created. It can offer significant speedup in processing signals from large-scale recordings up to thousands of channels. Copyright © 2018 Elsevier B.V. All rights reserved.

  10. 3D Monte Carlo model with direct photon flux recording for optimal optogenetic light delivery

    Science.gov (United States)

    Shin, Younghoon; Kim, Dongmok; Lee, Jihoon; Kwon, Hyuk-Sang

    2017-02-01

    Configuring the light power emitted from the optical fiber is an essential first step in planning in-vivo optogenetic experiments. However, diffusion theory, which was adopted for optogenetic research, precluded accurate estimates of light intensity in the semi-diffusive region where the primary locus of the stimulation is located. We present a 3D Monte Carlo model that provides an accurate and direct solution for light distribution in this region. Our method directly records the photon trajectory in the separate volumetric grid planes for the near-source recording efficiency gain, and it incorporates a 3D brain mesh to support both homogeneous and heterogeneous brain tissue. We investigated the light emitted from optical fibers in brain tissue in 3D, and we applied the results to design optimal light delivery parameters for precise optogenetic manipulation by considering the fiber output power, wavelength, fiber-to-target distance, and the area of neural tissue activation.

  11. Progress in optics

    CERN Document Server

    Wolf, Emil

    2015-01-01

    The Progress in Optics series contains more than 300 review articles by distinguished research workers, which have become permanent records for many important developments, helping optical scientists and optical engineers stay abreast of their fields. Comprehensive, in-depth reviewsEdited by the leading authority in the field

  12. OPTICAL TRANSIENT DETECTOR (OTD) LIGHTNING V1

    Data.gov (United States)

    National Aeronautics and Space Administration — The Optical Transient Detector (OTD) records optical measurements of global lightning events in the daytime and nighttime. The data includes individual point...

  13. Cracking the Neural Code for Sensory Perception by Combining Statistics, Intervention, and Behavior.

    Science.gov (United States)

    Panzeri, Stefano; Harvey, Christopher D; Piasini, Eugenio; Latham, Peter E; Fellin, Tommaso

    2017-02-08

    The two basic processes underlying perceptual decisions-how neural responses encode stimuli, and how they inform behavioral choices-have mainly been studied separately. Thus, although many spatiotemporal features of neural population activity, or "neural codes," have been shown to carry sensory information, it is often unknown whether the brain uses these features for perception. To address this issue, we propose a new framework centered on redefining the neural code as the neural features that carry sensory information used by the animal to drive appropriate behavior; that is, the features that have an intersection between sensory and choice information. We show how this framework leads to a new statistical analysis of neural activity recorded during behavior that can identify such neural codes, and we discuss how to combine intersection-based analysis of neural recordings with intervention on neural activity to determine definitively whether specific neural activity features are involved in a task. Copyright © 2017 Elsevier Inc. All rights reserved.

  14. Drift chamber tracking with neural networks

    International Nuclear Information System (INIS)

    Lindsey, C.S.; Denby, B.; Haggerty, H.

    1992-10-01

    We discuss drift chamber tracking with a commercial log VLSI neural network chip. Voltages proportional to the drift times in a 4-layer drift chamber were presented to the Intel ETANN chip. The network was trained to provide the intercept and slope of straight tracks traversing the chamber. The outputs were recorded and later compared off line to conventional track fits. Two types of network architectures were studied. Applications of neural network tracking to high energy physics detector triggers is discussed

  15. Laser color recording unit

    Science.gov (United States)

    Jung, E.

    1984-05-01

    A color recording unit was designed for output and control of digitized picture data within computer controlled reproduction and picture processing systems. In order to get a color proof picture of high quality similar to a color print, together with reduced time and material consumption, a photographic color film material was exposed pixelwise by modulated laser beams of three wavelengths for red, green and blue light. Components of different manufacturers for lasers, acousto-optic modulators and polygon mirrors were tested, also different recording methods as (continuous tone mode or screened mode and with a drum or flatbed recording principle). Besides the application for the graphic arts - the proof recorder CPR 403 with continuous tone color recording with a drum scanner - such a color hardcopy peripheral unit with large picture formats and high resolution can be used in medicine, communication, and satellite picture processing.

  16. Characterization of AVHRR global cloud detection sensitivity based on CALIPSO-CALIOP cloud optical thickness information: demonstration of results based on the CM SAF CLARA-A2 climate data record

    Science.gov (United States)

    Karlsson, Karl-Göran; Håkansson, Nina

    2018-02-01

    The sensitivity in detecting thin clouds of the cloud screening method being used in the CM SAF cloud, albedo and surface radiation data set from AVHRR data (CLARA-A2) cloud climate data record (CDR) has been evaluated using cloud information from the Cloud-Aerosol Lidar with Orthogonal Polarization (CALIOP) onboard the CALIPSO satellite. The sensitivity, including its global variation, has been studied based on collocations of Advanced Very High Resolution Radiometer (AVHRR) and CALIOP measurements over a 10-year period (2006-2015). The cloud detection sensitivity has been defined as the minimum cloud optical thickness for which 50 % of clouds could be detected, with the global average sensitivity estimated to be 0.225. After using this value to reduce the CALIOP cloud mask (i.e. clouds with optical thickness below this threshold were interpreted as cloud-free cases), cloudiness results were found to be basically unbiased over most of the globe except over the polar regions where a considerable underestimation of cloudiness could be seen during the polar winter. The overall probability of detecting clouds in the polar winter could be as low as 50 % over the highest and coldest parts of Greenland and Antarctica, showing that a large fraction of optically thick clouds also remains undetected here. The study included an in-depth analysis of the probability of detecting a cloud as a function of the vertically integrated cloud optical thickness as well as of the cloud's geographical position. Best results were achieved over oceanic surfaces at mid- to high latitudes where at least 50 % of all clouds with an optical thickness down to a value of 0.075 were detected. Corresponding cloud detection sensitivities over land surfaces outside of the polar regions were generally larger than 0.2 with maximum values of approximately 0.5 over the Sahara and the Arabian Peninsula. For polar land surfaces the values were close to 1 or higher with maximum values of 4.5 for the parts

  17. Progress in optics

    CERN Document Server

    Wolf, Emil

    2009-01-01

    In the fourty-seven years that have gone by since the first volume of Progress in Optics was published, optics has become one of the most dynamic fields of science. The volumes in this series which have appeared up to now contain more than 300 review articles by distinguished research workers, which have become permanent records for many important developments.- Backscattering and Anderson localization of light- Advances in oliton manipulation in optical lattices- Fundamental quantum noise in optical amplification- Invisibility cloaks

  18. Development and Evaluation of Micro-Electrocorticography Arrays for Neural Interfacing Applications

    Science.gov (United States)

    Schendel, Amelia Ann

    Neural interfaces have great promise for both electrophysiological research and therapeutic applications. Whether for the study of neural circuitry or for neural prosthetic or other therapeutic applications, micro-electrocorticography (micro-ECoG) arrays have proven extremely useful as neural interfacing devices. These devices strike a balance between invasiveness and signal resolution, an important step towards eventual human application. The objective of this research was to make design improvements to micro-ECoG devices to enhance both biocompatibility and device functionality. To best evaluate the effectiveness of these improvements, a cranial window imaging method for in vivo monitoring of the longitudinal tissue response post device implant was developed. Employment of this method provided valuable insight into the way tissue grows around micro-ECoG arrays after epidural implantation, spurring a study of the effects of substrate geometry on the meningeal tissue response. The results of the substrate footprint comparison suggest that a more open substrate geometry provides an easy path for the tissue to grow around to the top side of the device, whereas a solid device substrate encourages the tissue to thicken beneath the device, between the electrode sites and the brain. The formation of thick scar tissue between the recording electrode sites and the neural tissue is disadvantageous for long-term recorded signal quality, and thus future micro-ECoG device designs should incorporate open-architecture substrates for enhanced longitudinal in vivo function. In addition to investigating improvements for long-term device reliability, it was also desired to enhance the functionality of micro-ECoG devices for neural electrophysiology research applications. To achieve this goal, a completely transparent graphene-based device was fabricated for use with the cranial window imaging method and optogenetic techniques. The use of graphene as the conductive material provided

  19. Infrared neural stimulation (INS) inhibits electrically evoked neural responses in the deaf white cat

    Science.gov (United States)

    Richter, Claus-Peter; Rajguru, Suhrud M.; Robinson, Alan; Young, Hunter K.

    2014-03-01

    Infrared neural stimulation (INS) has been used in the past to evoke neural activity from hearing and partially deaf animals. All the responses were excitatory. In Aplysia californica, Duke and coworkers demonstrated that INS also inhibits neural responses [1], which similar observations were made in the vestibular system [2, 3]. In deaf white cats that have cochleae with largely reduced spiral ganglion neuron counts and a significant degeneration of the organ of Corti, no cochlear compound action potentials could be observed during INS alone. However, the combined electrical and optical stimulation demonstrated inhibitory responses during irradiation with infrared light.

  20. Realization of an optical interferometer based on holographic optics ...

    Indian Academy of Sciences (India)

    The paper describes a simple and cost effective method for the realization of an optical interferometer based on holographic optics, which use minimal bulk optical components. The optical arrangement in the proposed method involves a very simple alignment procedure and inexpensive holographic recording material is ...

  1. Optimal neural computations require analog processors

    Energy Technology Data Exchange (ETDEWEB)

    Beiu, V.

    1998-12-31

    This paper discusses some of the limitations of hardware implementations of neural networks. The authors start by presenting neural structures and their biological inspirations, while mentioning the simplifications leading to artificial neural networks. Further, the focus will be on hardware imposed constraints. They will present recent results for three different alternatives of parallel implementations of neural networks: digital circuits, threshold gate circuits, and analog circuits. The area and the delay will be related to the neurons` fan-in and to the precision of their synaptic weights. The main conclusion is that hardware-efficient solutions require analog computations, and suggests the following two alternatives: (i) cope with the limitations imposed by silicon, by speeding up the computation of the elementary silicon neurons; (2) investigate solutions which would allow the use of the third dimension (e.g. using optical interconnections).

  2. 1993 Department of Energy Records Management Conference

    Energy Technology Data Exchange (ETDEWEB)

    NONE

    1993-12-31

    This document consists of viewgraphs from the presentations at the conference. Topics included are: DOE records management overview, NIRMA and ARMA resources, NARA records management training, potential quality assurance records, filing systems, organizing and indexing technical records, DOE-HQ initiatives, IRM reviews, status of epidemiologic inventory, disposition of records and personal papers, inactive records storage, establishing administrative records, managing records at Hanford, electronic mail -- legal and records issues, NARA-GAO reports status, consultive selling, automated indexing, decentralized approach to scheduling at a DOE office, developing specific records management programs, storage and retrieval at Savannah River Plant, an optical disk case study, and special interest group reports.

  3. Compact all-fiber optical Faraday components using 65-wt%-terbium-doped fiber with a record Verdet constant of -32 rad/(Tm).

    Science.gov (United States)

    Sun, L; Jiang, S; Marciante, J R

    2010-06-07

    A compact all-fiber Faraday isolator and a Faraday mirror are demonstrated. At the core of each of these components is an all-fiber Faraday rotator made of a 4-cm-long, 65-wt%-terbium-doped silicate fiber. The effective Verdet constant of the terbium-doped fiber is measured to be -32 rad/(Tm), which is 27 x larger than that of silica fiber. This effective Verdet constant is the largest value measured to date in any fiber and is 83% of the Verdet constant of commercially available crystal used in bulk optics-based isolators. Combining the all-fiber Faraday rotator with fiber polarizers results in a fully fusion spliced all-fiber isolator whose isolation is measured to be 19 dB. Combining the all-fiber Faraday rotator with a fiber Bragg grating results in an all-fiber Faraday mirror that rotates the polarization state of the reflected light by 88 +/- 4 degrees .

  4. Optical materials

    International Nuclear Information System (INIS)

    Poker, D.B.; Ortiz, C.

    1989-01-01

    This book reports on: Diamond films, Synthesis of optical materials, Structure related optical properties, Radiation effects in optical materials, Characterization of optical materials, Deposition of optical thin films, and Optical fibers and waveguides

  5. Activity patterns of cultured neural networks on micro electrode arrays

    NARCIS (Netherlands)

    Rutten, Wim; van Pelt, J.

    2001-01-01

    A hybrid neuro-electronic interface is a cell-cultured micro electrode array, acting as a neural information transducer for stimulation and/or recording of neural activity in the brain or the spinal cord (ventral motor region or dorsal sensory region). It consists of an array of micro electrodes on

  6. Morphological neural networks

    Energy Technology Data Exchange (ETDEWEB)

    Ritter, G.X.; Sussner, P. [Univ. of Florida, Gainesville, FL (United States)

    1996-12-31

    The theory of artificial neural networks has been successfully applied to a wide variety of pattern recognition problems. In this theory, the first step in computing the next state of a neuron or in performing the next layer neural network computation involves the linear operation of multiplying neural values by their synaptic strengths and adding the results. Thresholding usually follows the linear operation in order to provide for nonlinearity of the network. In this paper we introduce a novel class of neural networks, called morphological neural networks, in which the operations of multiplication and addition are replaced by addition and maximum (or minimum), respectively. By taking the maximum (or minimum) of sums instead of the sum of products, morphological network computation is nonlinear before thresholding. As a consequence, the properties of morphological neural networks are drastically different than those of traditional neural network models. In this paper we consider some of these differences and provide some particular examples of morphological neural network.

  7. Neural Tube Defects

    Science.gov (United States)

    Neural tube defects are birth defects of the brain, spine, or spinal cord. They happen in the ... that she is pregnant. The two most common neural tube defects are spina bifida and anencephaly. In ...

  8. Neural tissue-spheres

    DEFF Research Database (Denmark)

    Andersen, Rikke K; Johansen, Mathias; Blaabjerg, Morten

    2007-01-01

    By combining new and established protocols we have developed a procedure for isolation and propagation of neural precursor cells from the forebrain subventricular zone (SVZ) of newborn rats. Small tissue blocks of the SVZ were dissected and propagated en bloc as free-floating neural tissue...... content, thus allowing experimental studies of neural precursor cells and their niche...

  9. Neural Correlates of Boredom in Music Perception

    Directory of Open Access Journals (Sweden)

    Ashkan Fakhr Tabatabaie

    2014-11-01

    Full Text Available Introduction: Music can elicit powerful emotional responses, the neural correlates of which have not been properly understood. An important aspect about the quality of any musical piece is its ability to elicit a sense of excitement in the listeners. In this study, we investigated the neural correlates of boredom evoked by music in human subjects. Methods: We used EEG recording in nine subjects while they were listening to total number of 10 short-length (83 sec musical pieces with various boredom indices. Subjects evaluated boringness of musical pieces while their EEG was recording. Results: Using short time Fourier analysis, we found that beta2 rhythm was (16-20 Hz significantly lower whenever the subjects rated the music as boring in comparison to nonboring. Discussion: The results demonstrate that the music modulates neural activity of various partsof the brain and can be measured using EEG.

  10. Optical Pattern Recognition

    Science.gov (United States)

    Yu, Francis T. S.; Jutamulia, Suganda

    2008-10-01

    Contributors; Preface; 1. Pattern recognition with optics Francis T. S. Yu and Don A. Gregory; 2. Hybrid neural networks for nonlinear pattern recognition Taiwei Lu; 3. Wavelets, optics, and pattern recognition Yao Li and Yunglong Sheng; 4. Applications of the fractional Fourier transform to optical pattern recognition David Mendlovic, Zeev Zalesky and Haldum M. Oxaktas; 5. Optical implementation of mathematical morphology Tien-Hsin Chao; 6. Nonlinear optical correlators with improved discrimination capability for object location and recognition Leonid P. Yaroslavsky; 7. Distortion-invariant quadratic filters Gregory Gheen; 8. Composite filter synthesis as applied to pattern recognition Shizhou Yin and Guowen Lu; 9. Iterative procedures in electro-optical pattern recognition Joseph Shamir; 10. Optoelectronic hybrid system for three-dimensional object pattern recognition Guoguang Mu, Mingzhe Lu and Ying Sun; 11. Applications of photrefractive devices in optical pattern recognition Ziangyang Yang; 12. Optical pattern recognition with microlasers Eung-Gi Paek; 13. Optical properties and applications of bacteriorhodopsin Q. Wang Song and Yu-He Zhang; 14. Liquid-crystal spatial light modulators Aris Tanone and Suganda Jutamulia; 15. Representations of fully complex functions on real-time spatial light modulators Robert W. Cohn and Laurence G. Hassbrook; Index.

  11. Neural electrical activity and neural network growth.

    Science.gov (United States)

    Gafarov, F M

    2018-05-01

    The development of central and peripheral neural system depends in part on the emergence of the correct functional connectivity in its input and output pathways. Now it is generally accepted that molecular factors guide neurons to establish a primary scaffold that undergoes activity-dependent refinement for building a fully functional circuit. However, a number of experimental results obtained recently shows that the neuronal electrical activity plays an important role in the establishing of initial interneuronal connections. Nevertheless, these processes are rather difficult to study experimentally, due to the absence of theoretical description and quantitative parameters for estimation of the neuronal activity influence on growth in neural networks. In this work we propose a general framework for a theoretical description of the activity-dependent neural network growth. The theoretical description incorporates a closed-loop growth model in which the neural activity can affect neurite outgrowth, which in turn can affect neural activity. We carried out the detailed quantitative analysis of spatiotemporal activity patterns and studied the relationship between individual cells and the network as a whole to explore the relationship between developing connectivity and activity patterns. The model, developed in this work will allow us to develop new experimental techniques for studying and quantifying the influence of the neuronal activity on growth processes in neural networks and may lead to a novel techniques for constructing large-scale neural networks by self-organization. Copyright © 2018 Elsevier Ltd. All rights reserved.

  12. Laboratory testing & measurement on optical imaging systems

    CSIR Research Space (South Africa)

    Theron, B

    2013-04-01

    Full Text Available on Optical Imaging Systems Bertus Theron 27 April 2013 presented at SIECPC 2013, Riyadh, Saudi Arabia Overview of Workshop Part 1. Introduction & Context  Some history of Arabic Optics  Context: Global vs Local optical testing... of Arabic Optics 1 See [4]  Arabic records of study of geometrical optics  Traced to Hellenistic (Greek) optics  Translated to Arabic  9th century  Arabic contribution to geometric optics  Not just translation to Arabic  Innovative research...

  13. Progress in optics

    CERN Document Server

    Wolf, Emil

    2008-01-01

    In the fourty-six years that have gone by since the first volume of Progress in Optics was published, optics has become one of the most dynamic fields of science. The volumes in this series which have appeared up to now contain more than 300 review articles by distinguished research workers, which have become permanent records for many important developments.- Metamaterials- Polarization Techniques- Linear Baisotropic Mediums- Ultrafast Optical Pulses- Quantum Imaging- Point-Spread Funcions- Discrete Wigner Functions

  14. Phenological Records

    Data.gov (United States)

    National Oceanic and Atmospheric Administration, Department of Commerce — Phenology is the scientific study of periodic biological phenomena, such as flowering, breeding, and migration, in relation to climatic conditions. The few records...

  15. Optical spectra analysis for breast cancer diagnostics

    Science.gov (United States)

    Belkov, S. A.; Kochemasov, G. G.; Lyubynskaya, T. E.; Maslov, N. V.; Nuzhny, A. S.; da Silva, L. B.; Rubenchik, A.

    2011-11-01

    Minimally invasive probe and optical biopsy system based on optical spectra recording and analysis seem to be a promising tool for early diagnostics of breast cancer. Light scattering and absorption spectra are generated continuously as far as the needle-like probe with one emitting and several collecting optical fibers penetrates through the tissues toward to the suspicious area. That allows analyzing not only the state of local site, but also the structure of tissues along the needle trace. The suggested method has the advantages of automated on-line diagnosing and minimal tissue destruction and in parallel with the conventional diagnostic procedures provides the ground for decision-making. 165 medical trials were completed in Nizhny Novgorod Regional Oncology Centre, Russia. Independent diagnoses were the results of fine biopsy and histology. Application of wavelet expansion and clasterization techniques for spectra analysis revealed several main spectral types for malignant and benign tumors. Automatic classification algorithm demonstrated specificity ˜90% and sensitivity ˜91%. Large amount of information, fuzziness in criteria and data noisiness make neural networks to be an attractive analytic tool. The model based on three-layer perceptron was tested over the sample of 29 `cancer' and 29 `non-cancer' cases and demonstrated total separation.

  16. Optical stimulation of peripheral nerves in vivo

    Science.gov (United States)

    Wells, Jonathon D.

    This dissertation documents the emergence and validation of a new clinical tool that bridges the fields of biomedical optics and neuroscience. The research herein describes an innovative method for direct neurostimulation with pulsed infrared laser light. Safety and effectiveness of this technique are first demonstrated through functional stimulation of the rat sciatic nerve in vivo. The Holmium:YAG laser (lambda = 2.12 mum) is shown to operate at an optimal wavelength for peripheral nerve stimulation with advantages over standard electrical neural stimulation; including contact-free stimulation, high spatial selectivity, and lack of a stimulation artifact. The underlying biophysical mechanism responsible for transient optical nerve stimulation appears to be a small, absorption driven thermal gradient sustained at the axonal layer of nerve. Results explicitly prove that low frequency optical stimulation can reliably stimulate without resulting in tissue thermal damage. Based on the positive results from animal studies, these optimal laser parameters were utilized to move this research into the clinic with a combined safety and efficacy study in human subjects undergoing selective dorsal rhizotomy. The clinical Holmium:YAG laser was used to effectively stimulate human dorsal spinal roots and elicit functional muscle responses recorded during surgery without evidence of nerve damage. Overall these results predict that this technology can be a valuable clinical tool in various neurosurgical applications.

  17. Optic neuritis

    Science.gov (United States)

    Retro-bulbar neuritis; Multiple sclerosis - optic neuritis; Optic nerve - optic neuritis ... The exact cause of optic neuritis is unknown. The optic nerve carries visual information from your eye to the brain. The nerve can swell when ...

  18. An Overview of Bayesian Methods for Neural Spike Train Analysis

    Directory of Open Access Journals (Sweden)

    Zhe Chen

    2013-01-01

    Full Text Available Neural spike train analysis is an important task in computational neuroscience which aims to understand neural mechanisms and gain insights into neural circuits. With the advancement of multielectrode recording and imaging technologies, it has become increasingly demanding to develop statistical tools for analyzing large neuronal ensemble spike activity. Here we present a tutorial overview of Bayesian methods and their representative applications in neural spike train analysis, at both single neuron and population levels. On the theoretical side, we focus on various approximate Bayesian inference techniques as applied to latent state and parameter estimation. On the application side, the topics include spike sorting, tuning curve estimation, neural encoding and decoding, deconvolution of spike trains from calcium imaging signals, and inference of neuronal functional connectivity and synchrony. Some research challenges and opportunities for neural spike train analysis are discussed.

  19. A review of organic and inorganic biomaterials for neural interfaces.

    Science.gov (United States)

    Fattahi, Pouria; Yang, Guang; Kim, Gloria; Abidian, Mohammad Reza

    2014-03-26

    Recent advances in nanotechnology have generated wide interest in applying nanomaterials for neural prostheses. An ideal neural interface should create seamless integration into the nervous system and performs reliably for long periods of time. As a result, many nanoscale materials not originally developed for neural interfaces become attractive candidates to detect neural signals and stimulate neurons. In this comprehensive review, an overview of state-of-the-art microelectrode technologies provided fi rst, with focus on the material properties of these microdevices. The advancements in electro active nanomaterials are then reviewed, including conducting polymers, carbon nanotubes, graphene, silicon nanowires, and hybrid organic-inorganic nanomaterials, for neural recording, stimulation, and growth. Finally, technical and scientific challenges are discussed regarding biocompatibility, mechanical mismatch, and electrical properties faced by these nanomaterials for the development of long-lasting functional neural interfaces.

  20. Chaotic diagonal recurrent neural network

    International Nuclear Information System (INIS)

    Wang Xing-Yuan; Zhang Yi

    2012-01-01

    We propose a novel neural network based on a diagonal recurrent neural network and chaos, and its structure and learning algorithm are designed. The multilayer feedforward neural network, diagonal recurrent neural network, and chaotic diagonal recurrent neural network are used to approach the cubic symmetry map. The simulation results show that the approximation capability of the chaotic diagonal recurrent neural network is better than the other two neural networks. (interdisciplinary physics and related areas of science and technology)

  1. Radiation optic neuropathy

    International Nuclear Information System (INIS)

    Kline, L.B.; Kim, J.Y.; Ceballos, R.

    1985-01-01

    Following surgery for pituitary adenoma, radiation therapy is an accepted treatment in reducing tumor recurrence. However, a potential therapeutic complication is delayed radionecrosis of perisellar neural structures, including the optic nerves and chiasm. This particular cause of visual loss, radiation optic neuropathy (RON), has not been emphasized in the ophthalmologic literature. Four cases of RON seen in the past five years are reported. Diagnostic criteria include: (1) acute visual loss (monocular or binocular), (2) visual field defects indicating optic nerve or chiasmal dysfunction, (3) absence of optic disc edema, (4) onset usually within three years of therapy (peak: 1-1 1/2 years), and (5) no computed tomographic evidence of visual pathway compression. Pathologic findings, differential diagnosis and therapy will be discussed in outlining the clinical profile of RON

  2. Evolvable Neural Software System

    Science.gov (United States)

    Curtis, Steven A.

    2009-01-01

    The Evolvable Neural Software System (ENSS) is composed of sets of Neural Basis Functions (NBFs), which can be totally autonomously created and removed according to the changing needs and requirements of the software system. The resulting structure is both hierarchical and self-similar in that a given set of NBFs may have a ruler NBF, which in turn communicates with other sets of NBFs. These sets of NBFs may function as nodes to a ruler node, which are also NBF constructs. In this manner, the synthetic neural system can exhibit the complexity, three-dimensional connectivity, and adaptability of biological neural systems. An added advantage of ENSS over a natural neural system is its ability to modify its core genetic code in response to environmental changes as reflected in needs and requirements. The neural system is fully adaptive and evolvable and is trainable before release. It continues to rewire itself while on the job. The NBF is a unique, bilevel intelligence neural system composed of a higher-level heuristic neural system (HNS) and a lower-level, autonomic neural system (ANS). Taken together, the HNS and the ANS give each NBF the complete capabilities of a biological neural system to match sensory inputs to actions. Another feature of the NBF is the Evolvable Neural Interface (ENI), which links the HNS and ANS. The ENI solves the interface problem between these two systems by actively adapting and evolving from a primitive initial state (a Neural Thread) to a complicated, operational ENI and successfully adapting to a training sequence of sensory input. This simulates the adaptation of a biological neural system in a developmental phase. Within the greater multi-NBF and multi-node ENSS, self-similar ENI s provide the basis for inter-NBF and inter-node connectivity.

  3. Study of neutrino production in the Cannonball model of Gamma ray bursts: possibility of observation of these neutrinos with the Antares neutrinos telescope, and study of the optical background recorded with the prototype sector line

    International Nuclear Information System (INIS)

    Ferry, S.

    2004-09-01

    ANTARES is a future neutrino telescope which will be build at 40 km off the french coast (Toulon), at a 2500 m depth. The interaction of a neutrino with matter produces a muon which emits Cerenkov light while propagating in water. This light is detected with 900 photomultipliers distributed over 12 lines. Gamma ray bursts (GRB) are violent cosmological phenomenon observed once per day. In the Cannonball Model, bursts are produced by the interaction of a jet made of cannonballs (CB) with a supernova remnant (SNR). Forward shocks propagate in the SNR, reverse ones in the CB and neutrinos are produced at the shock fronts. An estimation of the neutrino production is given and is studied over a large parameter range. For a typical GRB, 0.002 to 0.3 v μ , cm -2 can be produced. Depending on the viewing angle, ANTARES could detect 1 to 10 v μ per year in correlation with GRBs. The ambient optical background has been recorded by the ANTARES prototype sector line. The analysis is about the background influence on the detector performance and about the organisms activity which produces it. For example, it appears a 17.6 to 20.4 h periodicity which is compatible with the liquid masses movement imposed by the Coriolis force at the ANTARES latitude. (author)

  4. Chronic multiunit recordings in behaving animals: advantages and limitations

    NARCIS (Netherlands)

    Supèr, Hans; Roelfsema, Pieter R.

    2005-01-01

    By simultaneous recording from neural responses at many different loci at the same time, we can understand the interaction between neurons, and thereby gain insight into the network properties of neural processing, instead of the functioning of individual neurons. Here we will discuss a method for

  5. Development of an Optical Disc Recorder

    Science.gov (United States)

    1977-02-01

    Kenney , F / Zernike D /Lou ,~ R,’Harp:r 1 ( Li, ‘~~~~~~~~~~~~~~~~~~~~~~ _ _ ~~ _ ~~~~~~~~~~~~~~ I R. McFarlane - - ____________________________ 9. PER...7 371 4 0 “7 4 :4 7-7 / 99 c crc 7i 3d ) -75, 375 331 4 7 Cl 4 :53 2177 70 Ci 0 0 2 ) 2 2-37 3172 FIGURE 4 . 1 S I M I I I A T 1 ON RESUl TS FOR

  6. Ultra-High Density Optical Recording

    National Research Council Canada - National Science Library

    Kryder, Mark

    1999-01-01

    .... The work was directed at developing an understanding of the cyclability of phase change media, the fabrication of solid immersion lens, the development of improved integrated engineering test beds...

  7. High speed digital interfacing for a neural data acquisition system

    Directory of Open Access Journals (Sweden)

    Bahr Andreas

    2016-09-01

    Full Text Available Diseases like schizophrenia and genetic epilepsy are supposed to be caused by disorders in the early development of the brain. For the further investigation of these relationships a custom designed application specific integrated circuit (ASIC was developed that is optimized for the recording from neonatal mice [Bahr A, Abu-Saleh L, Schroeder D, Krautschneider W. 16 Channel Neural Recording Integrated Circuit with SPI Interface and Error Correction Coding. Proc. 9th BIOSTEC 2016. Biodevices: Rome, Italy, 2016; 1: 263; Bahr A, Abu-Saleh L, Schroeder D, Krautschneider W. Development of a neural recording mixed signal integrated circuit for biomedical signal acquisition. Biomed Eng Biomed Tech Abstracts 2015; 60(S1: 298–299; Bahr A, Abu-Saleh L, Schroeder D, Krautschneider WH. 16 Channel Neural Recording Mixed Signal ASIC. CDNLive EMEA 2015 Conference Proceedings, 2015.]. To enable the live display of the neural signals a multichannel neural data acquisition system with live display functionality is presented. It implements a high speed data transmission from the ASIC to a computer with a live display functionality. The system has been successfully implemented and was used in a neural recording of a head-fixed mouse.

  8. Optic pathway glioma associated with orbital rhabdomyosarcoma and bilateral optic nerve sheath dural ectasia in a child with neurofibromatosis-1

    International Nuclear Information System (INIS)

    Nikas, Ioannis; Theofanopoulou, Maria; Lampropoulou, Penelope; Hadjigeorgi, Christiana; Pourtsidis, Apostolos; Kosmidis, Helen

    2006-01-01

    Neurofibromatosis-1 (NF-1) is a multisystem disorder presenting with a variety of clinical and imaging manifestations. Neural and non-neural tumours, and unusual benign miscellaneous conditions, separately or combined, are encountered in variable locations. We present a 21/2-year-old boy with NF-1 who demonstrated coexisting optic pathway glioma with involvement of the chiasm and optic nerve, orbital alveolar rhabdomyosarcoma and bilateral optic nerve sheath dural ectasia. (orig.)

  9. Bidirectional neural interface: Closed-loop feedback control for hybrid neural systems.

    Science.gov (United States)

    Chou, Zane; Lim, Jeffrey; Brown, Sophie; Keller, Melissa; Bugbee, Joseph; Broccard, Frédéric D; Khraiche, Massoud L; Silva, Gabriel A; Cauwenberghs, Gert

    2015-01-01

    Closed-loop neural prostheses enable bidirectional communication between the biological and artificial components of a hybrid system. However, a major challenge in this field is the limited understanding of how these components, the two separate neural networks, interact with each other. In this paper, we propose an in vitro model of a closed-loop system that allows for easy experimental testing and modification of both biological and artificial network parameters. The interface closes the system loop in real time by stimulating each network based on recorded activity of the other network, within preset parameters. As a proof of concept we demonstrate that the bidirectional interface is able to establish and control network properties, such as synchrony, in a hybrid system of two neural networks more significantly more effectively than the same system without the interface or with unidirectional alternatives. This success holds promise for the application of closed-loop systems in neural prostheses, brain-machine interfaces, and drug testing.

  10. A neural flow estimator

    DEFF Research Database (Denmark)

    Jørgensen, Ivan Harald Holger; Bogason, Gudmundur; Bruun, Erik

    1995-01-01

    This paper proposes a new way to estimate the flow in a micromechanical flow channel. A neural network is used to estimate the delay of random temperature fluctuations induced in a fluid. The design and implementation of a hardware efficient neural flow estimator is described. The system...... is implemented using switched-current technique and is capable of estimating flow in the μl/s range. The neural estimator is built around a multiplierless neural network, containing 96 synaptic weights which are updated using the LMS1-algorithm. An experimental chip has been designed that operates at 5 V...

  11. Neural Systems Laboratory

    Data.gov (United States)

    Federal Laboratory Consortium — As part of the Electrical and Computer Engineering Department and The Institute for System Research, the Neural Systems Laboratory studies the functionality of the...

  12. RECORDS REACHING RECORDING DATA TECHNOLOGIES

    Directory of Open Access Journals (Sweden)

    G. W. L. Gresik

    2013-07-01

    Full Text Available The goal of RECORDS (Reaching Recording Data Technologies is the digital capturing of buildings and cultural heritage objects in hard-to-reach areas and the combination of data. It is achieved by using a modified crane from film industry, which is able to carry different measuring systems. The low-vibration measurement should be guaranteed by a gyroscopic controlled advice that has been , developed for the project. The data were achieved by using digital photography, UV-fluorescence photography, infrared reflectography, infrared thermography and shearography. Also a terrestrial 3D laser scanner and a light stripe topography scanner have been used The combination of the recorded data should ensure a complementary analysis of monuments and buildings.

  13. Records Reaching Recording Data Technologies

    Science.gov (United States)

    Gresik, G. W. L.; Siebe, S.; Drewello, R.

    2013-07-01

    The goal of RECORDS (Reaching Recording Data Technologies) is the digital capturing of buildings and cultural heritage objects in hard-to-reach areas and the combination of data. It is achieved by using a modified crane from film industry, which is able to carry different measuring systems. The low-vibration measurement should be guaranteed by a gyroscopic controlled advice that has been , developed for the project. The data were achieved by using digital photography, UV-fluorescence photography, infrared reflectography, infrared thermography and shearography. Also a terrestrial 3D laser scanner and a light stripe topography scanner have been used The combination of the recorded data should ensure a complementary analysis of monuments and buildings.

  14. Multiple spectral channels in branchiopods. I. Vision in dim light and neural correlates.

    Science.gov (United States)

    Lessios, Nicolas; Rutowski, Ronald L; Cohen, Jonathan H; Sayre, Marcel E; Strausfeld, Nicholas J

    2018-05-22

    Animals that have true color vision possess several spectral classes of photoreceptors. Pancrustaceans (Hexapoda+Crustacea) that integrate spectral information about their reconstructed visual world do so from photoreceptor terminals supplying their second optic neuropils, with subsequent participation of the third (lobula) and deeper centers (optic foci). Here, we describe experiments and correlative neural arrangements underlying convergent visual pathways in two species of branchiopod crustaceans that have to cope with a broad range of spectral ambience and illuminance in ephemeral pools, yet possess just two optic neuropils, the lamina and the optic tectum. Electroretinographic recordings and multimodel inference based on modeled spectral absorptance were used to identify the most likely number of spectral photoreceptor classes in their compound eyes. Recordings from the retina provide support for four color channels. Neuroanatomical observations resolve arrangements in their laminas that suggest signal summation at low light intensities, incorporating chromatic channels. Neuroanatomical observations demonstrate that spatial summation in the lamina of the two species are mediated by quite different mechanisms, both of which allow signals from several ommatidia to be pooled at single lamina monopolar cells. We propose that such summation provides sufficient signal for vision at intensities equivalent to those experienced by insects in terrestrial habitats under dim starlight. Our findings suggest that despite the absence of optic lobe neuropils necessary for spectral discrimination utilized by true color vision, four spectral photoreceptor classes have been maintained in Branchiopoda for vision at very low light intensities at variable ambient wavelengths that typify conditions in ephemeral freshwater habitats. © 2018. Published by The Company of Biologists Ltd.

  15. Neural Networks: Implementations and Applications

    OpenAIRE

    Vonk, E.; Veelenturf, L.P.J.; Jain, L.C.

    1996-01-01

    Artificial neural networks, also called neural networks, have been used successfully in many fields including engineering, science and business. This paper presents the implementation of several neural network simulators and their applications in character recognition and other engineering areas

  16. Critical Branching Neural Networks

    Science.gov (United States)

    Kello, Christopher T.

    2013-01-01

    It is now well-established that intrinsic variations in human neural and behavioral activity tend to exhibit scaling laws in their fluctuations and distributions. The meaning of these scaling laws is an ongoing matter of debate between isolable causes versus pervasive causes. A spiking neural network model is presented that self-tunes to critical…

  17. Consciousness and neural plasticity

    DEFF Research Database (Denmark)

    changes or to abandon the strong identity thesis altogether. Were one to pursue a theory according to which consciousness is not an epiphenomenon to brain processes, consciousness may in fact affect its own neural basis. The neural correlate of consciousness is often seen as a stable structure, that is...

  18. Vinyl Record

    DEFF Research Database (Denmark)

    Bartmanski, Dominik; Woodward, Ian

    2018-01-01

    . This relational process means that both the material affordances and entanglements of vinyl allow us to feel, handle, experience, project, and share its iconicity. The materially mediated meanings of vinyl enabled it to retain currency in independent and collector’s markets and thus resist the planned......In this paper, we use the case of the vinyl record to show that iconic objects become meaningful via a dual process. First, they offer immersive engagements which structure user interpretations through various material experiences of handling, use, and extension. Second, they always work via...

  19. Estimation of neural energy in microelectrode signals

    Science.gov (United States)

    Gaumond, R. P.; Clement, R.; Silva, R.; Sander, D.

    2004-09-01

    We considered the problem of determining the neural contribution to the signal recorded by an intracortical electrode. We developed a linear least-squares approach to determine the energy fraction of a signal attributable to an arbitrary number of autocorrelation-defined signals buried in noise. Application of the method requires estimation of autocorrelation functions Rap(tgr) characterizing the action potential (AP) waveforms and Rn(tgr) characterizing background noise. This method was applied to the analysis of chronically implanted microelectrode signals from motor cortex of rat. We found that neural (AP) energy consisted of a large-signal component which grows linearly with the number of threshold-detected neural events and a small-signal component unrelated to the count of threshold-detected AP signals. The addition of pseudorandom noise to electrode signals demonstrated the algorithm's effectiveness for a wide range of noise-to-signal energy ratios (0.08 to 39). We suggest, therefore, that the method could be of use in providing a measure of neural response in situations where clearly identified spike waveforms cannot be isolated, or in providing an additional 'background' measure of microelectrode neural activity to supplement the traditional AP spike count.

  20. Simultaneous recording of fluorescence and electrical signals by photometric patch electrode in deep brain regions in vivo.

    Science.gov (United States)

    Hirai, Yasuharu; Nishino, Eri; Ohmori, Harunori

    2015-06-01

    Despite its widespread use, high-resolution imaging with multiphoton microscopy to record neuronal signals in vivo is limited to the surface of brain tissue because of limited light penetration. Moreover, most imaging studies do not simultaneously record electrical neural activity, which is, however, crucial to understanding brain function. Accordingly, we developed a photometric patch electrode (PME) to overcome the depth limitation of optical measurements and also enable the simultaneous recording of neural electrical responses in deep brain regions. The PME recoding system uses a patch electrode to excite a fluorescent dye and to measure the fluorescence signal as a light guide, to record electrical signal, and to apply chemicals to the recorded cells locally. The optical signal was analyzed by either a spectrometer of high light sensitivity or a photomultiplier tube depending on the kinetics of the responses. We used the PME in Oregon Green BAPTA-1 AM-loaded avian auditory nuclei in vivo to monitor calcium signals and electrical responses. We demonstrated distinct response patterns in three different nuclei of the ascending auditory pathway. On acoustic stimulation, a robust calcium fluorescence response occurred in auditory cortex (field L) neurons that outlasted the electrical response. In the auditory midbrain (inferior colliculus), both responses were transient. In the brain-stem cochlear nucleus magnocellularis, calcium response seemed to be effectively suppressed by the activity of metabotropic glutamate receptors. In conclusion, the PME provides a powerful tool to study brain function in vivo at a tissue depth inaccessible to conventional imaging devices. Copyright © 2015 the American Physiological Society.

  1. Dynamic neural network-based methods for compensation of nonlinear effects in multimode communication lines

    Science.gov (United States)

    Sidelnikov, O. S.; Redyuk, A. A.; Sygletos, S.

    2017-12-01

    We consider neural network-based schemes of digital signal processing. It is shown that the use of a dynamic neural network-based scheme of signal processing ensures an increase in the optical signal transmission quality in comparison with that provided by other methods for nonlinear distortion compensation.

  2. Record Club

    CERN Multimedia

    Record Club

    2011-01-01

    http://cern.ch/Record.Club November  Selections Just in time for the holiday season, we have added a number of new CDs and DVDs into the Club. You will find the full lists at http://cern.ch/record.club; select the "Discs of the Month" button on the left side on the left panel of the web page and then Nov 2011. New films include the all 5 episodes of Fast and Furious, many of the most famous films starring Jean-Paul Belmondo and those of Louis de Funes and some more recent films such as The Lincoln Lawyer and, according to some critics, Woody Allen’s best film for years – Midnight in Paris. For the younger generation there is Cars 2 and Kung Fu Panda 2. New CDs include the latest releases by Adele, Coldplay and the Red Hot Chili Peppers. We have also added the new Duets II CD featuring Tony Bennett singing with some of today’s pop stars including Lady Gaga, Amy Winehouse and Willy Nelson. The Club is now open every Monday, Wednesday and Friday ...

  3. Record Club

    CERN Multimedia

    Record Club

    2011-01-01

    http://cern.ch/Record.Club June Selections We have put a significant number of new CDs and DVDs into the Club You will find the full lists at http://cern.ch/record.club and select the «Discs of the Month» button on the left side on the left panel of the web page and then June 2011. New films include the latest Action, Suspense and Science Fiction film hits, general drama movies including the Oscar-winning The King’s Speech, comedies including both chapter of Bridget Jones’s Diary, seven films for children and a musical. Other highlights include the latest Harry Potter release and some movies from the past you may have missed including the first in the Terminator series. New CDs include the latest releases by Michel Sardou, Mylene Farmer, Jennifer Lopez, Zucchero and Britney Spears. There is also a hits collection from NRJ. Don’t forget that the Club is now open every Monday, Wednesday and Friday lunchtimes from 12h30 to 13h00 in Restaurant 2, Building 504. (C...

  4. Record club

    CERN Document Server

    Record club

    2010-01-01

      Bonjour a tous, Voici les 24 nouveaux DVD de Juillet disponibles depuis quelques jours, sans oublier les 5 CD Pop musique. Découvrez la saga du terroriste Carlos, la vie de Gainsbourg et les aventures de Lucky Luke; angoissez avec Paranormal Activity et évadez vous sur Pandora dans la peau d’Avatar. Toutes les nouveautés sont à découvrir directement au club. Pour en connaître la liste complète ainsi que le reste de la collection du Record Club, nous vous invitons sur notre site web: http://cern.ch/crc. Toutes les dernières nouveautés sont dans la rubrique « Discs of the Month ». Rappel : le club est ouvert les Lundis, Mercredis, Vendredis de 12h30 à 13h00 au restaurant n°2, bâtiment 504. A bientôt chers Record Clubbers.  

  5. Record Club

    CERN Multimedia

    Record Club

    2011-01-01

    http://cern.ch/Record.Club Nouveautés été 2011 Le club de location de CDs et de DVDs vient d’ajouter un grand nombre de disques pour l’été 2011. Parmi eux, Le Discours d’un Roi, oscar 2011 du meilleur film et Harry Potter les reliques de la mort (1re partie). Ce n’est pas moins de 48 DVDs et 10 CDs nouveaux qui vous sont proposés à la location. Il y en a pour tous les genres. Alors n’hésitez pas à consulter notre site http://cern.ch/record.club, voir Disc Catalogue, Discs of the month pour avoir la liste complète. Le club est ouvert tous les Lundi, Mercredi, Vendredi de 12h30 à 13h dans le bâtiment du restaurent N°2 (Cf. URL: http://www.cern.ch/map/building?bno=504) A très bientôt.  

  6. Optical Interconnection Via Computer-Generated Holograms

    Science.gov (United States)

    Liu, Hua-Kuang; Zhou, Shaomin

    1995-01-01

    Method of free-space optical interconnection developed for data-processing applications like parallel optical computing, neural-network computing, and switching in optical communication networks. In method, multiple optical connections between multiple sources of light in one array and multiple photodetectors in another array made via computer-generated holograms in electrically addressed spatial light modulators (ESLMs). Offers potential advantages of massive parallelism, high space-bandwidth product, high time-bandwidth product, low power consumption, low cross talk, and low time skew. Also offers advantage of programmability with flexibility of reconfiguration, including variation of strengths of optical connections in real time.

  7. Dynamics of neural cryptography.

    Science.gov (United States)

    Ruttor, Andreas; Kinzel, Wolfgang; Kanter, Ido

    2007-05-01

    Synchronization of neural networks has been used for public channel protocols in cryptography. In the case of tree parity machines the dynamics of both bidirectional synchronization and unidirectional learning is driven by attractive and repulsive stochastic forces. Thus it can be described well by a random walk model for the overlap between participating neural networks. For that purpose transition probabilities and scaling laws for the step sizes are derived analytically. Both these calculations as well as numerical simulations show that bidirectional interaction leads to full synchronization on average. In contrast, successful learning is only possible by means of fluctuations. Consequently, synchronization is much faster than learning, which is essential for the security of the neural key-exchange protocol. However, this qualitative difference between bidirectional and unidirectional interaction vanishes if tree parity machines with more than three hidden units are used, so that those neural networks are not suitable for neural cryptography. In addition, the effective number of keys which can be generated by the neural key-exchange protocol is calculated using the entropy of the weight distribution. As this quantity increases exponentially with the system size, brute-force attacks on neural cryptography can easily be made unfeasible.

  8. Dynamics of neural cryptography

    International Nuclear Information System (INIS)

    Ruttor, Andreas; Kinzel, Wolfgang; Kanter, Ido

    2007-01-01

    Synchronization of neural networks has been used for public channel protocols in cryptography. In the case of tree parity machines the dynamics of both bidirectional synchronization and unidirectional learning is driven by attractive and repulsive stochastic forces. Thus it can be described well by a random walk model for the overlap between participating neural networks. For that purpose transition probabilities and scaling laws for the step sizes are derived analytically. Both these calculations as well as numerical simulations show that bidirectional interaction leads to full synchronization on average. In contrast, successful learning is only possible by means of fluctuations. Consequently, synchronization is much faster than learning, which is essential for the security of the neural key-exchange protocol. However, this qualitative difference between bidirectional and unidirectional interaction vanishes if tree parity machines with more than three hidden units are used, so that those neural networks are not suitable for neural cryptography. In addition, the effective number of keys which can be generated by the neural key-exchange protocol is calculated using the entropy of the weight distribution. As this quantity increases exponentially with the system size, brute-force attacks on neural cryptography can easily be made unfeasible

  9. Dynamics of neural cryptography

    Science.gov (United States)

    Ruttor, Andreas; Kinzel, Wolfgang; Kanter, Ido

    2007-05-01

    Synchronization of neural networks has been used for public channel protocols in cryptography. In the case of tree parity machines the dynamics of both bidirectional synchronization and unidirectional learning is driven by attractive and repulsive stochastic forces. Thus it can be described well by a random walk model for the overlap between participating neural networks. For that purpose transition probabilities and scaling laws for the step sizes are derived analytically. Both these calculations as well as numerical simulations show that bidirectional interaction leads to full synchronization on average. In contrast, successful learning is only possible by means of fluctuations. Consequently, synchronization is much faster than learning, which is essential for the security of the neural key-exchange protocol. However, this qualitative difference between bidirectional and unidirectional interaction vanishes if tree parity machines with more than three hidden units are used, so that those neural networks are not suitable for neural cryptography. In addition, the effective number of keys which can be generated by the neural key-exchange protocol is calculated using the entropy of the weight distribution. As this quantity increases exponentially with the system size, brute-force attacks on neural cryptography can easily be made unfeasible.

  10. Photosensitive-polyimide based method for fabricating various neural electrode architectures

    Directory of Open Access Journals (Sweden)

    Yasuhiro X Kato

    2012-06-01

    Full Text Available An extensive photosensitive polyimide (PSPI-based method for designing and fabricating various neural electrode architectures was developed. The method aims to broaden the design flexibility and expand the fabrication capability for neural electrodes to improve the quality of recorded signals and integrate other functions. After characterizing PSPI’s properties for micromachining processes, we successfully designed and fabricated various neural electrodes even on a non-flat substrate using only one PSPI as an insulation material and without the time-consuming dry etching processes. The fabricated neural electrodes were an electrocorticogram electrode, a mesh intracortical electrode with a unique lattice-like mesh structure to fixate neural tissue, and a guide cannula electrode with recording microelectrodes placed on the curved surface of a guide cannula as a microdialysis probe. In vivo neural recordings using anesthetized rats demonstrated that these electrodes can be used to record neural activities repeatedly without any breakage and mechanical failures, which potentially promises stable recordings for long periods of time. These successes make us believe that this PSPI-based fabrication is a powerful method, permitting flexible design and easy optimization of electrode architectures for a variety of electrophysiological experimental research with improved neural recording performance.

  11. RECORD CLUB

    CERN Multimedia

    Record Club

    2010-01-01

    DVD James Bond – Series Complete To all Record Club Members, to start the new year, we have taken advantage of a special offer to add copies of all the James Bond movies to date, from the very first - Dr. No - to the latest - Quantum of Solace. No matter which of the successive 007s you prefer (Sean Connery, George Lazenby, Roger Moore, Timothy Dalton, Pierce Brosnan or Daniel Craig), they are all there. Or perhaps you have a favourite Bond Girl, or even perhaps a favourite villain. Take your pick. You can find the full selection listed on the club web site http://cern.ch/crc; use the panel on the left of the page “Discs of the Month” and select Jan 2010. We remind you that we are open on Mondays, Wednesdays and Fridays from 12:30 to 13:00 in Restaurant 2 (Bldg 504).

  12. Record dynamics

    DEFF Research Database (Denmark)

    Robe, Dominic M.; Boettcher, Stefan; Sibani, Paolo

    2016-01-01

    When quenched rapidly beyond their glass transition, colloidal suspensions fall out of equilibrium. The pace of their dynamics then slows down with the system age, i.e., with the time elapsed after the quench. This breaking of time translational invariance is associated with dynamical observables...... which depend on two time-arguments. The phenomenology is shared by a broad class of aging systems and calls for an equally broad theoretical description. The key idea is that, independent of microscopic details, aging systems progress through rare intermittent structural relaxations that are de......-facto irreversible and become increasingly harder to achieve. Thus, a progression of record-sized dynamical barriers are traversed in the approach to equilibration. Accordingly, the statistics of the events is closely described by a log-Poisson process. Originally developed for relaxation in spin glasses...

  13. Record breakers

    CERN Multimedia

    Antonella Del Rosso

    2012-01-01

    In the sixties, CERN’s Fellows were but a handful of about 50 young experimentalists present on site to complete their training. Today, their number has increased to a record-breaking 500. They come from many different fields and are spread across CERN’s different activity areas.   “Diversifying the Fellowship programme has been the key theme in recent years,” comments James Purvis, Head of the Recruitment, Programmes and Monitoring group in the HR Department. “In particular, the 2005 five-yearly review introduced the notion of ‘senior’ and ‘junior’ Fellowships, broadening the target audience to include those with Bachelor-level qualifications.” Diversification made CERN’s Fellowship programme attractive to a wider audience but the number of Fellows on site could not have increased so much without the support of EU-funded projects, which were instrumental in the growth of the programme. ...

  14. ANT Advanced Neural Tool

    Energy Technology Data Exchange (ETDEWEB)

    Labrador, I.; Carrasco, R.; Martinez, L.

    1996-07-01

    This paper describes a practical introduction to the use of Artificial Neural Networks. Artificial Neural Nets are often used as an alternative to the traditional symbolic manipulation and first order logic used in Artificial Intelligence, due the high degree of difficulty to solve problems that can not be handled by programmers using algorithmic strategies. As a particular case of Neural Net a Multilayer Perception developed by programming in C language on OS9 real time operating system is presented. A detailed description about the program structure and practical use are included. Finally, several application examples that have been treated with the tool are presented, and some suggestions about hardware implementations. (Author) 15 refs.

  15. ANT Advanced Neural Tool

    International Nuclear Information System (INIS)

    Labrador, I.; Carrasco, R.; Martinez, L.

    1996-01-01

    This paper describes a practical introduction to the use of Artificial Neural Networks. Artificial Neural Nets are often used as an alternative to the traditional symbolic manipulation and first order logic used in Artificial Intelligence, due the high degree of difficulty to solve problems that can not be handled by programmers using algorithmic strategies. As a particular case of Neural Net a Multilayer Perception developed by programming in C language on OS9 real time operating system is presented. A detailed description about the program structure and practical use are included. Finally, several application examples that have been treated with the tool are presented, and some suggestions about hardware implementations. (Author) 15 refs

  16. Optical neuron by use of a laser diode with injection seeding and external optical feedback

    NARCIS (Netherlands)

    Mos, E.C.; Hoppenbrouwers, J.J.L.; Hill, M.T.; Blum, M.W.; Schleipen, J.J.H.B.; Waardt, de H.

    2000-01-01

    We present an all-optical neuron by use of a multimode laser diode that is subjected to external optical feedback and light injection. The shape of the threshold function, that is needed for neural operation, is controlled by adjusting the external feedback level for two longitudinal cavity modes of

  17. Neural System Prediction and Identification Challenge

    Directory of Open Access Journals (Sweden)

    Ioannis eVlachos

    2013-12-01

    Full Text Available Can we infer the function of a biological neural network (BNN if we know the connectivity and activity of all its constituent neurons? This question is at the core of neuroscience and, accordingly, various methods have been developed to record the activity and connectivity of as many neurons as possible. Surprisingly, there is no theoretical or computational demonstration that neuronal activity and connectivity are indeed sufficient to infer the function of a BNN. Therefore, we pose the Neural Systems Identification and Prediction Challenge (nuSPIC. We provide the connectivity and activity of all neurons and invite participants (i to infer the functions implemented (hard-wired in spiking neural networks (SNNs by stimulating and recording the activity of neurons and, (ii to implement predefined mathematical/biological functions using SNNs. The nuSPICs can be accessed via a web-interface to the NEST simulator and the user is not required to know any specific programming language. Furthermore, the nuSPICs can be used as a teaching tool. Finally, nuSPICs use the crowd-sourcing model to address scientific issues. With this computational approach we aim to identify which functions can be inferred by systematic recordings of neuronal activity and connectivity. In addition, nuSPICs will help the design and application of new experimental paradigms based on the structure of the SNN and the presumed function which is to be discovered.

  18. Neural system prediction and identification challenge.

    Science.gov (United States)

    Vlachos, Ioannis; Zaytsev, Yury V; Spreizer, Sebastian; Aertsen, Ad; Kumar, Arvind

    2013-01-01

    Can we infer the function of a biological neural network (BNN) if we know the connectivity and activity of all its constituent neurons?This question is at the core of neuroscience and, accordingly, various methods have been developed to record the activity and connectivity of as many neurons as possible. Surprisingly, there is no theoretical or computational demonstration that neuronal activity and connectivity are indeed sufficient to infer the function of a BNN. Therefore, we pose the Neural Systems Identification and Prediction Challenge (nuSPIC). We provide the connectivity and activity of all neurons and invite participants (1) to infer the functions implemented (hard-wired) in spiking neural networks (SNNs) by stimulating and recording the activity of neurons and, (2) to implement predefined mathematical/biological functions using SNNs. The nuSPICs can be accessed via a web-interface to the NEST simulator and the user is not required to know any specific programming language. Furthermore, the nuSPICs can be used as a teaching tool. Finally, nuSPICs use the crowd-sourcing model to address scientific issues. With this computational approach we aim to identify which functions can be inferred by systematic recordings of neuronal activity and connectivity. In addition, nuSPICs will help the design and application of new experimental paradigms based on the structure of the SNN and the presumed function which is to be discovered.

  19. Hidden neural networks

    DEFF Research Database (Denmark)

    Krogh, Anders Stærmose; Riis, Søren Kamaric

    1999-01-01

    A general framework for hybrids of hidden Markov models (HMMs) and neural networks (NNs) called hidden neural networks (HNNs) is described. The article begins by reviewing standard HMMs and estimation by conditional maximum likelihood, which is used by the HNN. In the HNN, the usual HMM probability...... parameters are replaced by the outputs of state-specific neural networks. As opposed to many other hybrids, the HNN is normalized globally and therefore has a valid probabilistic interpretation. All parameters in the HNN are estimated simultaneously according to the discriminative conditional maximum...... likelihood criterion. The HNN can be viewed as an undirected probabilistic independence network (a graphical model), where the neural networks provide a compact representation of the clique functions. An evaluation of the HNN on the task of recognizing broad phoneme classes in the TIMIT database shows clear...

  20. Neural networks for aircraft control

    Science.gov (United States)

    Linse, Dennis

    1990-01-01

    Current research in Artificial Neural Networks indicates that networks offer some potential advantages in adaptation and fault tolerance. This research is directed at determining the possible applicability of neural networks to aircraft control. The first application will be to aircraft trim. Neural network node characteristics, network topology and operation, neural network learning and example histories using neighboring optimal control with a neural net are discussed.

  1. Active Neural Localization

    OpenAIRE

    Chaplot, Devendra Singh; Parisotto, Emilio; Salakhutdinov, Ruslan

    2018-01-01

    Localization is the problem of estimating the location of an autonomous agent from an observation and a map of the environment. Traditional methods of localization, which filter the belief based on the observations, are sub-optimal in the number of steps required, as they do not decide the actions taken by the agent. We propose "Active Neural Localizer", a fully differentiable neural network that learns to localize accurately and efficiently. The proposed model incorporates ideas of tradition...

  2. Neural cryptography with feedback.

    Science.gov (United States)

    Ruttor, Andreas; Kinzel, Wolfgang; Shacham, Lanir; Kanter, Ido

    2004-04-01

    Neural cryptography is based on a competition between attractive and repulsive stochastic forces. A feedback mechanism is added to neural cryptography which increases the repulsive forces. Using numerical simulations and an analytic approach, the probability of a successful attack is calculated for different model parameters. Scaling laws are derived which show that feedback improves the security of the system. In addition, a network with feedback generates a pseudorandom bit sequence which can be used to encrypt and decrypt a secret message.

  3. Record Club

    CERN Document Server

    Record Club

    2012-01-01

      March  Selections By the time this appears, we will have added a number of new CDs and DVDs into the Club. You will find the full lists at http://cern.ch/record.club; select the "Discs of the Month" button on the left panel of the web page and then Mar 2012. New films include recent releases such as Johnny English 2, Bad Teacher, Cowboys vs Aliens, and Super 8. We are also starting to acquire some of the classic films we missed when we initiated the DVD section of the club, such as appeared in a recent Best 100 Films published by a leading UK magazine; this month we have added Spielberg’s Jaws and Scorsese’s Goodfellas. If you have your own ideas on what we are missing, let us know. For children we have no less than 8 Tin-Tin DVDs. And if you like fast moving pop music, try the Beyonce concert DVD. New CDs include the latest releases from Paul McCartney, Rihanna and Amy Winehouse. There is a best of Mylene Farmer, a compilation from the NRJ 201...

  4. Scalable optical quantum computer

    Energy Technology Data Exchange (ETDEWEB)

    Manykin, E A; Mel' nichenko, E V [Institute for Superconductivity and Solid-State Physics, Russian Research Centre ' Kurchatov Institute' , Moscow (Russian Federation)

    2014-12-31

    A way of designing a scalable optical quantum computer based on the photon echo effect is proposed. Individual rare earth ions Pr{sup 3+}, regularly located in the lattice of the orthosilicate (Y{sub 2}SiO{sub 5}) crystal, are suggested to be used as optical qubits. Operations with qubits are performed using coherent and incoherent laser pulses. The operation protocol includes both the method of measurement-based quantum computations and the technique of optical computations. Modern hybrid photon echo protocols, which provide a sufficient quantum efficiency when reading recorded states, are considered as most promising for quantum computations and communications. (quantum computer)

  5. Scalable optical quantum computer

    International Nuclear Information System (INIS)

    Manykin, E A; Mel'nichenko, E V

    2014-01-01

    A way of designing a scalable optical quantum computer based on the photon echo effect is proposed. Individual rare earth ions Pr 3+ , regularly located in the lattice of the orthosilicate (Y 2 SiO 5 ) crystal, are suggested to be used as optical qubits. Operations with qubits are performed using coherent and incoherent laser pulses. The operation protocol includes both the method of measurement-based quantum computations and the technique of optical computations. Modern hybrid photon echo protocols, which provide a sufficient quantum efficiency when reading recorded states, are considered as most promising for quantum computations and communications. (quantum computer)

  6. Recording Spikes Activity in Cultured Hippocampal Neurons Using Flexible or Transparent Graphene Transistors

    Directory of Open Access Journals (Sweden)

    Farida Veliev

    2017-08-01

    Full Text Available The emergence of nanoelectronics applied to neural interfaces has started few decades ago, and aims to provide new tools for replacing or restoring disabled functions of the nervous systems as well as further understanding the evolution of such complex organization. As the same time, graphene and other 2D materials have offered new possibilities for integrating micro and nano-devices on flexible, transparent, and biocompatible substrates, promising for bio and neuro-electronics. In addition to many bio-suitable features of graphene interface, such as, chemical inertness and anti-corrosive properties, its optical transparency enables multimodal approach of neuronal based systems, the electrical layer being compatible with additional microfluidics and optical manipulation ports. The convergence of these fields will provide a next generation of neural interfaces for the reliable detection of single spike and record with high fidelity activity patterns of neural networks. Here, we report on the fabrication of graphene field effect transistors (G-FETs on various substrates (silicon, sapphire, glass coverslips, and polyimide deposited onto Si/SiO2 substrates, exhibiting high sensitivity (4 mS/V, close to the Dirac point at VLG < VD and low noise level (10−22 A2/Hz, at VLG = 0 V. We demonstrate the in vitro detection of the spontaneous activity of hippocampal neurons in-situ-grown on top of the graphene sensors during several weeks in a millimeter size PDMS fluidics chamber (8 mm wide. These results provide an advance toward the realization of biocompatible devices for reliable and high spatio-temporal sensing of neuronal activity for both in vitro and in vivo applications.

  7. Design Optimization of Transistors Used for Neural Recording

    Directory of Open Access Journals (Sweden)

    Eric Basham

    2012-01-01

    Full Text Available Neurons cultured directly over open-gate field-effect transistors result in a hybrid device, the neuron-FET. Neuron-FET amplifier circuits reported in the literature employ the neuron-FET transducer as a current-mode device in conjunction with a transimpedance amplifier. In this configuration, the transducer does not provide any signal gain, and characterization of the transducer out of the amplification circuit is required. Furthermore, the circuit requires a complex biasing scheme that must be retuned to compensate for drift. Here we present an alternative strategy based on the gm/Id design approach to optimize a single-stage common-source amplifier design. The gm/Id design approach facilitates in circuit characterization of the neuron-FET and provides insight into approaches to improving the transistor process design for application as a neuron-FET transducer. Simulation data for a test case demonstrates optimization of the transistor design and significant increase in gain over a current mode implementation.

  8. Progress In Optical Memory Technology

    Science.gov (United States)

    Tsunoda, Yoshito

    1987-01-01

    More than 20 years have passed since the concept of optical memory was first proposed in 1966. Since then considerable progress has been made in this area together with the creation of completely new markets of optical memory in consumer and computer application areas. The first generation of optical memory was mainly developed with holographic recording technology in late 1960s and early 1970s. Considerable number of developments have been done in both analog and digital memory applications. Unfortunately, these technologies did not meet a chance to be a commercial product. The second generation of optical memory started at the beginning of 1970s with bit by bit recording technology. Read-only type optical memories such as video disks and compact audio disks have extensively investigated. Since laser diodes were first applied to optical video disk read out in 1976, there have been extensive developments of laser diode pick-ups for optical disk memory systems. The third generation of optical memory started in 1978 with bit by bit read/write technology using laser diodes. Developments of recording materials including both write-once and erasable have been actively pursued at several research institutes. These technologies are mainly focused on the optical memory systems for computer application. Such practical applications of optical memory technology has resulted in the creation of such new products as compact audio disks and computer file memories.

  9. Multichannel brain recordings in behaving Drosophila reveal oscillatory activity and local coherence in response to sensory stimulation and circuit activation

    Science.gov (United States)

    Paulk, Angelique C.; Zhou, Yanqiong; Stratton, Peter; Liu, Li

    2013-01-01

    Neural networks in vertebrates exhibit endogenous oscillations that have been associated with functions ranging from sensory processing to locomotion. It remains unclear whether oscillations may play a similar role in the insect brain. We describe a novel “whole brain” readout for Drosophila melanogaster using a simple multichannel recording preparation to study electrical activity across the brain of flies exposed to different sensory stimuli. We recorded local field potential (LFP) activity from >2,000 registered recording sites across the fly brain in >200 wild-type and transgenic animals to uncover specific LFP frequency bands that correlate with: 1) brain region; 2) sensory modality (olfactory, visual, or mechanosensory); and 3) activity in specific neural circuits. We found endogenous and stimulus-specific oscillations throughout the fly brain. Central (higher-order) brain regions exhibited sensory modality-specific increases in power within narrow frequency bands. Conversely, in sensory brain regions such as the optic or antennal lobes, LFP coherence, rather than power, best defined sensory responses across modalities. By transiently activating specific circuits via expression of TrpA1, we found that several circuits in the fly brain modulate LFP power and coherence across brain regions and frequency domains. However, activation of a neuromodulatory octopaminergic circuit specifically increased neuronal coherence in the optic lobes during visual stimulation while decreasing coherence in central brain regions. Our multichannel recording and brain registration approach provides an effective way to track activity simultaneously across the fly brain in vivo, allowing investigation of functional roles for oscillations in processing sensory stimuli and modulating behavior. PMID:23864378

  10. Multichannel brain recordings in behaving Drosophila reveal oscillatory activity and local coherence in response to sensory stimulation and circuit activation.

    Science.gov (United States)

    Paulk, Angelique C; Zhou, Yanqiong; Stratton, Peter; Liu, Li; van Swinderen, Bruno

    2013-10-01

    Neural networks in vertebrates exhibit endogenous oscillations that have been associated with functions ranging from sensory processing to locomotion. It remains unclear whether oscillations may play a similar role in the insect brain. We describe a novel "whole brain" readout for Drosophila melanogaster using a simple multichannel recording preparation to study electrical activity across the brain of flies exposed to different sensory stimuli. We recorded local field potential (LFP) activity from >2,000 registered recording sites across the fly brain in >200 wild-type and transgenic animals to uncover specific LFP frequency bands that correlate with: 1) brain region; 2) sensory modality (olfactory, visual, or mechanosensory); and 3) activity in specific neural circuits. We found endogenous and stimulus-specific oscillations throughout the fly brain. Central (higher-order) brain regions exhibited sensory modality-specific increases in power within narrow frequency bands. Conversely, in sensory brain regions such as the optic or antennal lobes, LFP coherence, rather than power, best defined sensory responses across modalities. By transiently activating specific circuits via expression of TrpA1, we found that several circuits in the fly brain modulate LFP power and coherence across brain regions and frequency domains. However, activation of a neuromodulatory octopaminergic circuit specifically increased neuronal coherence in the optic lobes during visual stimulation while decreasing coherence in central brain regions. Our multichannel recording and brain registration approach provides an effective way to track activity simultaneously across the fly brain in vivo, allowing investigation of functional roles for oscillations in processing sensory stimuli and modulating behavior.

  11. Fiber-optic laser sensor for mine detection and verification

    International Nuclear Information System (INIS)

    Bohling, Christian; Scheel, Dirk; Hohmann, Konrad; Schade, Wolfgang; Reuter, Matthias; Holl, Gerhard

    2006-01-01

    What we believe to be a new optical approach for the identification of mines and explosives by analyzing the surface materials and not only bulk is developed. A conventional manually operated mine prodder is upgraded by laser-induced breakdown spectroscopy (LIBS). In situ and real-time information of materials that are in front of the prodder are obtained during the demining process in order to optimize the security aspects and the speed of demining. A Cr4+:Nd3+:YAG microchip laser is used as a seed laser for an ytterbium-fiber amplifier to generate high-power laser pulses at 1064 nm with pulse powers up to Ep=1 mJ, a repetition rate of frep.=2-20 kHz and a pulse duration of tp=620 ps. The recorded LIBS signals are analyzed by applying neural networks for the data analysis

  12. Nonlinear optics

    International Nuclear Information System (INIS)

    Boyd, R.W.

    1992-01-01

    Nonlinear optics is the study of the interaction of intense laser light with matter. This book is a textbook on nonlinear optics at the level of a beginning graduate student. The intent of the book is to provide an introduction to the field of nonlinear optics that stresses fundamental concepts and that enables the student to go on to perform independent research in this field. This book covers the areas of nonlinear optics, quantum optics, quantum electronics, laser physics, electrooptics, and modern optics

  13. Physical optics

    International Nuclear Information System (INIS)

    Kim Il Gon; Lee, Seong Su; Jang, Gi Wan

    2012-07-01

    This book indicates physical optics with properties and transmission of light, mathematical expression of wave like harmonic wave and cylindrical wave, electromagnetic theory and light, transmission of light with Fermat principle and Fresnel equation, geometrical optics I, geometrical optics II, optical instrument such as stops, glasses and camera, polarized light like double refraction by polarized light, interference, interference by multiple reflections, diffraction, solid optics, crystal optics such as Faraday rotation and Kerr effect and measurement of light. Each chapter has an exercise.

  14. Physical optics

    Energy Technology Data Exchange (ETDEWEB)

    Kim Il Gon; Lee, Seong Su; Jang, Gi Wan

    2012-07-15

    This book indicates physical optics with properties and transmission of light, mathematical expression of wave like harmonic wave and cylindrical wave, electromagnetic theory and light, transmission of light with Fermat principle and Fresnel equation, geometrical optics I, geometrical optics II, optical instrument such as stops, glasses and camera, polarized light like double refraction by polarized light, interference, interference by multiple reflections, diffraction, solid optics, crystal optics such as Faraday rotation and Kerr effect and measurement of light. Each chapter has an exercise.

  15. Brain states recognition during visual perception by means of artificial neural network in the different EEG frequency ranges

    Science.gov (United States)

    Musatov, V. Yu.; Runnova, A. E.; Andreev, A. V.; Zhuravlev, M. O.

    2018-04-01

    In the present paper, the possibility of classification by artificial neural networks of a certain architecture of ambiguous images is investigated using the example of the Necker cube from the experimentally obtained EEG recording data of several operators. The possibilities of artificial neural network classification of ambiguous images are investigated in the different frequency ranges of EEG recording signals.

  16. Quantum optics

    National Research Council Canada - National Science Library

    Agarwal, G. S

    2013-01-01

    .... Focusing on applications of quantum optics, the textbook covers recent developments such as engineering of quantum states, quantum optics on a chip, nano-mechanical mirrors, quantum entanglement...

  17. Effect of neural connectivity on autocovariance and cross covariance estimates

    Directory of Open Access Journals (Sweden)

    Stecker Mark M

    2007-01-01

    Full Text Available Abstract Background Measurements of auto and cross covariance functions are frequently used to investigate neural systems. In interpreting this data, it is commonly assumed that the largest contribution to the recordings comes from sources near the electrode. However, the potential recorded at an electrode represents the superimposition of the potentials generated by large numbers of active neural structures. This creates situations under which the measured auto and cross covariance functions are dominated by the activity in structures far from the electrode and in which the distance dependence of the cross-covariance function differs significantly from that describing the activity in the actual neural structures. Methods Direct application of electrostatics to calculate the theoretical auto and cross covariance functions that would be recorded from electrodes immersed in a large volume filled with active neural structures with specific statistical properties. Results It is demonstrated that the potentials recorded from a monopolar electrode surrounded by dipole sources in a uniform medium are predominantly due to activity in neural structures far from the electrode when neuronal correlations drop more slowly than 1/r3 or when the size of the neural system is much smaller than a known correlation distance. Recordings from quadrupolar sources are strongly dependent on distant neurons when correlations drop more slowly than 1/r or the size of the system is much smaller than the correlation distance. Differences between bipolar and monopolar recordings are discussed. It is also demonstrated that the cross covariance of the recorded in two spatially separated electrodes declines as a power-law function of the distance between them even when the electrical activity from different neuronal structures is uncorrelated. Conclusion When extracellular electrophysiologic recordings are made from systems containing large numbers of neural structures, it is

  18. Altered Neural Activity Associated with Mindfulness during Nociception: A Systematic Review of Functional MRI.

    Science.gov (United States)

    Bilevicius, Elena; Kolesar, Tiffany A; Kornelsen, Jennifer

    2016-04-19

    To assess the neural activity associated with mindfulness-based alterations of pain perception. The Cochrane Central, EMBASE, Ovid Medline, PsycINFO, Scopus, and Web of Science databases were searched on 2 February 2016. Titles, abstracts, and full-text articles were independently screened by two reviewers. Data were independently extracted from records that included topics of functional neuroimaging, pain, and mindfulness interventions. The literature search produced 946 total records, of which five met the inclusion criteria. Records reported pain in terms of anticipation (n = 2), unpleasantness (n = 5), and intensity (n = 5), and how mindfulness conditions altered the neural activity during noxious stimulation accordingly. Although the studies were inconsistent in relating pain components to neural activity, in general, mindfulness was able to reduce pain anticipation and unpleasantness ratings, as well as alter the corresponding neural activity. The major neural underpinnings of mindfulness-based pain reduction consisted of altered activity in the anterior cingulate cortex, insula, and dorsolateral prefrontal cortex.

  19. Training Deep Spiking Neural Networks Using Backpropagation.

    Science.gov (United States)

    Lee, Jun Haeng; Delbruck, Tobi; Pfeiffer, Michael

    2016-01-01

    Deep spiking neural networks (SNNs) hold the potential for improving the latency and energy efficiency of deep neural networks through data-driven event-based computation. However, training such networks is difficult due to the non-differentiable nature of spike events. In this paper, we introduce a novel technique, which treats the membrane potentials of spiking neurons as differentiable signals, where discontinuities at spike times are considered as noise. This enables an error backpropagation mechanism for deep SNNs that follows the same principles as in conventional deep networks, but works directly on spike signals and membrane potentials. Compared with previous methods relying on indirect training and conversion, our technique has the potential to capture the statistics of spikes more precisely. We evaluate the proposed framework on artificially generated events from the original MNIST handwritten digit benchmark, and also on the N-MNIST benchmark recorded with an event-based dynamic vision sensor, in which the proposed method reduces the error rate by a factor of more than three compared to the best previous SNN, and also achieves a higher accuracy than a conventional convolutional neural network (CNN) trained and tested on the same data. We demonstrate in the context of the MNIST task that thanks to their event-driven operation, deep SNNs (both fully connected and convolutional) trained with our method achieve accuracy equivalent with conventional neural networks. In the N-MNIST example, equivalent accuracy is achieved with about five times fewer computational operations.

  20. Parallel consensual neural networks.

    Science.gov (United States)

    Benediktsson, J A; Sveinsson, J R; Ersoy, O K; Swain, P H

    1997-01-01

    A new type of a neural-network architecture, the parallel consensual neural network (PCNN), is introduced and applied in classification/data fusion of multisource remote sensing and geographic data. The PCNN architecture is based on statistical consensus theory and involves using stage neural networks with transformed input data. The input data are transformed several times and the different transformed data are used as if they were independent inputs. The independent inputs are first classified using the stage neural networks. The output responses from the stage networks are then weighted and combined to make a consensual decision. In this paper, optimization methods are used in order to weight the outputs from the stage networks. Two approaches are proposed to compute the data transforms for the PCNN, one for binary data and another for analog data. The analog approach uses wavelet packets. The experimental results obtained with the proposed approach show that the PCNN outperforms both a conjugate-gradient backpropagation neural network and conventional statistical methods in terms of overall classification accuracy of test data.

  1. Higher-order neural processing tunes motion neurons to visual ecology in three species of hawkmoths.

    Science.gov (United States)

    Stöckl, A L; O'Carroll, D; Warrant, E J

    2017-06-28

    To sample information optimally, sensory systems must adapt to the ecological demands of each animal species. These adaptations can occur peripherally, in the anatomical structures of sensory organs and their receptors; and centrally, as higher-order neural processing in the brain. While a rich body of investigations has focused on peripheral adaptations, our understanding is sparse when it comes to central mechanisms. We quantified how peripheral adaptations in the eyes, and central adaptations in the wide-field motion vision system, set the trade-off between resolution and sensitivity in three species of hawkmoths active at very different light levels: nocturnal Deilephila elpenor, crepuscular Manduca sexta , and diurnal Macroglossum stellatarum. Using optical measurements and physiological recordings from the photoreceptors and wide-field motion neurons in the lobula complex, we demonstrate that all three species use spatial and temporal summation to improve visual performance in dim light. The diurnal Macroglossum relies least on summation, but can only see at brighter intensities. Manduca, with large sensitive eyes, relies less on neural summation than the smaller eyed Deilephila , but both species attain similar visual performance at nocturnal light levels. Our results reveal how the visual systems of these three hawkmoth species are intimately matched to their visual ecologies. © 2017 The Author(s).

  2. Resonator memories and optical novelty filters

    Science.gov (United States)

    Anderson, Dana Z.; Erle, Marie C.

    Optical resonators having holographic elements are potential candidates for storing information that can be accessed through content addressable or associative recall. Closely related to the resonator memory is the optical novelty filter, which can detect the differences between a test object and a set of reference objects. We discuss implementations of these devices using continuous optical media such as photorefractive materials. The discussion is framed in the context of neural network models. There are both formal and qualitative similarities between the resonator memory and optical novelty filter and network models. Mode competition arises in the theory of the resonator memory, much as it does in some network models. We show that the role of the phenomena of "daydreaming" in the real-time programmable optical resonator is very much akin to the role of "unlearning" in neural network memories. The theory of programming the real-time memory for a single mode is given in detail. This leads to a discussion of the optical novelty filter. Experimental results for the resonator memory, the real-time programmable memory, and the optical tracking novelty filter are reviewed. We also point to several issues that need to be addressed in order to implement more formal models of neural networks.

  3. Loop-mirror laser neural network using a fast liquid-crystal display

    NARCIS (Netherlands)

    Mos, E.C.; Schleipen, J.J.H.B.; Waardt, de H.; Khoe, G.D.

    1999-01-01

    In our laser neural network (LNN) all-optical threshold action is obtained by application of controlled optical feedback to a laser diode. Here an extended experimental LNN is presented with as many as 32 neurons and 12 inputs. In the setup we use a fast liquid-crystal display to implement an

  4. Correlation in stimulated respiratory neural noise

    Science.gov (United States)

    Hoop, Bernard; Burton, Melvin D.; Kazemi, Homayoun; Liebovitch, Larry S.

    1995-09-01

    Noise in spontaneous respiratory neural activity of the neonatal rat isolated brainstem-spinal cord preparation stimulated with acetylcholine (ACh) exhibits positive correlation. Neural activity from the C4 (phrenic) ventral spinal rootlet, integrated and corrected for slowly changing trend, is interpreted as a fractal record in time by rescaled range, relative dispersional, and power spectral analyses. The Hurst exponent H measured from time series of 64 consecutive signal levels recorded at 2 s intervals during perfusion of the preparation with artificial cerebrospinal fluid containing ACh at concentrations 62.5 to 1000 μM increases to a maximum of 0.875±0.087 (SD) at 250 μM ACh and decreases with higher ACh concentration. Corrections for bias in measurement of H were made using two different kinds of simulated fractional Gaussian noise. Within limits of experimental procedure and short data series, we conclude that in the presence of added ACh of concentration 250 to 500 μM, noise which occurs in spontaneous respiratory-related neural activity in the isolated brainstem-spinal cord preparation observed at uniform time intervals exhibits positive correlation.

  5. Children's Brain Responses to Optic Flow Vary by Pattern Type and Motion Speed.

    Directory of Open Access Journals (Sweden)

    Rick O Gilmore

    Full Text Available Structured patterns of global visual motion called optic flow provide crucial information about an observer's speed and direction of self-motion and about the geometry of the environment. Brain and behavioral responses to optic flow undergo considerable postnatal maturation, but relatively little brain imaging evidence describes the time course of development in motion processing systems in early to middle childhood, a time when psychophysical data suggest that there are changes in sensitivity. To fill this gap, electroencephalographic (EEG responses were recorded in 4- to 8-year-old children who viewed three time-varying optic flow patterns (translation, rotation, and radial expansion/contraction at three different speeds (2, 4, and 8 deg/s. Modulations of global motion coherence evoked coherent EEG responses at the first harmonic that differed by flow pattern and responses at the third harmonic and dot update rate that varied by speed. Pattern-related responses clustered over right lateral channels while speed-related responses clustered over midline channels. Both children and adults show widespread responses to modulations of motion coherence at the second harmonic that are not selective for pattern or speed. The results suggest that the developing brain segregates the processing of optic flow pattern from speed and that an adult-like pattern of neural responses to optic flow has begun to emerge by early to middle childhood.

  6. Neural Architectures for Control

    Science.gov (United States)

    Peterson, James K.

    1991-01-01

    The cerebellar model articulated controller (CMAC) neural architectures are shown to be viable for the purposes of real-time learning and control. Software tools for the exploration of CMAC performance are developed for three hardware platforms, the MacIntosh, the IBM PC, and the SUN workstation. All algorithm development was done using the C programming language. These software tools were then used to implement an adaptive critic neuro-control design that learns in real-time how to back up a trailer truck. The truck backer-upper experiment is a standard performance measure in the neural network literature, but previously the training of the controllers was done off-line. With the CMAC neural architectures, it was possible to train the neuro-controllers on-line in real-time on a MS-DOS PC 386. CMAC neural architectures are also used in conjunction with a hierarchical planning approach to find collision-free paths over 2-D analog valued obstacle fields. The method constructs a coarse resolution version of the original problem and then finds the corresponding coarse optimal path using multipass dynamic programming. CMAC artificial neural architectures are used to estimate the analog transition costs that dynamic programming requires. The CMAC architectures are trained in real-time for each obstacle field presented. The coarse optimal path is then used as a baseline for the construction of a fine scale optimal path through the original obstacle array. These results are a very good indication of the potential power of the neural architectures in control design. In order to reach as wide an audience as possible, we have run a seminar on neuro-control that has met once per week since 20 May 1991. This seminar has thoroughly discussed the CMAC architecture, relevant portions of classical control, back propagation through time, and adaptive critic designs.

  7. Sacred or Neural?

    DEFF Research Database (Denmark)

    Runehov, Anne Leona Cesarine

    Are religious spiritual experiences merely the product of the human nervous system? Anne L.C. Runehov investigates the potential of contemporary neuroscience to explain religious experiences. Following the footsteps of Michael Persinger, Andrew Newberg and Eugene d'Aquili she defines...... the terminological bounderies of "religious experiences" and explores the relevant criteria for the proper evaluation of scientific research, with a particular focus on the validity of reductionist models. Runehov's theis is that the perspectives looked at do not necessarily exclude each other but can be merged....... The question "sacred or neural?" becomes a statement "sacred and neural". The synergies thus produced provide manifold opportunities for interdisciplinary dialogue and research....

  8. Deconvolution using a neural network

    Energy Technology Data Exchange (ETDEWEB)

    Lehman, S.K.

    1990-11-15

    Viewing one dimensional deconvolution as a matrix inversion problem, we compare a neural network backpropagation matrix inverse with LMS, and pseudo-inverse. This is a largely an exercise in understanding how our neural network code works. 1 ref.

  9. Introduction to Artificial Neural Networks

    DEFF Research Database (Denmark)

    Larsen, Jan

    1999-01-01

    The note addresses introduction to signal analysis and classification based on artificial feed-forward neural networks.......The note addresses introduction to signal analysis and classification based on artificial feed-forward neural networks....

  10. Long-term stability of intracortical recordings using perforated and arrayed Parylene sheath electrodes

    Science.gov (United States)

    Hara, Seth A.; Kim, Brian J.; Kuo, Jonathan T. W.; Lee, Curtis D.; Meng, Ellis; Pikov, Victor

    2016-12-01

    Objective. Acquisition of reliable and robust neural recordings with intracortical neural probes is a persistent challenge in the field of neuroprosthetics. We developed a multielectrode array technology to address chronic intracortical recording reliability and present in vivo recording results. Approach. The 2 × 2 Parylene sheath electrode array (PSEA) was microfabricated and constructed from only Parylene C and platinum. The probe includes a novel three-dimensional sheath structure, perforations, and bioactive coatings that improve tissue integration and manage immune response. Coatings were applied using a sequential dip-coating method that provided coverage over the entire probe surface and interior of the sheath structure. A sharp probe tip taper facilitated insertion with minimal trauma. Fabricated probes were subject to examination by optical and electron microscopy and electrochemical testing prior to implantation. Main results. 1 × 2 arrays were successfully fabricated on wafer and then packaged together to produce 2 × 2 arrays. Then, probes having electrode sites with adequate electrochemical properties were selected. A subset of arrays was treated with bioactive coatings to encourage neuronal growth and suppress inflammation and another subset of arrays was implanted in conjunction with a virally mediated expression of Caveolin-1. Arrays were attached to a custom-made insertion shuttle to facilitate precise insertion into the rat motor cortex. Stable electrophysiological recordings were obtained during the period of implantation up to 12 months. Immunohistochemical evaluation of cortical tissue around individual probes indicated a strong correlation between the electrophysiological performance of the probes and histologically observable proximity of neurons and dendritic sprouting. Significance. The PSEA demonstrates the scalability of sheath electrode technology and provides higher electrode count and density to access a greater volume for recording

  11. Optical Computing

    OpenAIRE

    Woods, Damien; Naughton, Thomas J.

    2008-01-01

    We consider optical computers that encode data using images and compute by transforming such images. We give an overview of a number of such optical computing architectures, including descriptions of the type of hardware commonly used in optical computing, as well as some of the computational efficiencies of optical devices. We go on to discuss optical computing from the point of view of computational complexity theory, with the aim of putting some old, and some very recent, re...

  12. Records Management Directive

    Data.gov (United States)

    Office of Personnel Management — The Office of Personnel Management (OPM) Records Management Directive provides guidelines for the management of OPM records, and identifies the records management...

  13. Ultra-low noise miniaturized neural amplifier with hardware averaging.

    Science.gov (United States)

    Dweiri, Yazan M; Eggers, Thomas; McCallum, Grant; Durand, Dominique M

    2015-08-01

    Peripheral nerves carry neural signals that could be used to control hybrid bionic systems. Cuff electrodes provide a robust and stable interface but the recorded signal amplitude is small (concept of hardware averaging to nerve recordings obtained with cuff electrodes. An optimization procedure is developed to minimize noise and power simultaneously. The novel design was based on existing neural amplifiers (Intan Technologies, LLC) and is validated with signals obtained from the FINE in chronic dog experiments. We showed that hardware averaging leads to a reduction in the total recording noise by a factor of 1/√N or less depending on the source resistance. Chronic recording of physiological activity with FINE using the presented design showed significant improvement on the recorded baseline noise with at least two parallel operation transconductance amplifiers leading to a 46.1% reduction at N = 8. The functionality of these recordings was quantified by the SNR improvement and shown to be significant for N = 3 or more. The present design was shown to be capable of generating hardware averaging on noise improvement for neural recording with cuff electrodes, and can accommodate the presence of high source impedances that are associated with the miniaturized contacts and the high channel count in electrode arrays. This technique can be adopted for other applications where miniaturized and implantable multichannel acquisition systems with ultra-low noise and low power are required.

  14. Morphosyntactic Neural Analysis for Generalized Lexical Normalization

    Science.gov (United States)

    Leeman-Munk, Samuel Paul

    2016-01-01

    The phenomenal growth of social media, web forums, and online reviews has spurred a growing interest in automated analysis of user-generated text. At the same time, a proliferation of voice recordings and efforts to archive culture heritage documents are fueling demand for effective automatic speech recognition (ASR) and optical character…

  15. A canonical neural mechanism for behavioral variability

    Science.gov (United States)

    Darshan, Ran; Wood, William E.; Peters, Susan; Leblois, Arthur; Hansel, David

    2017-05-01

    The ability to generate variable movements is essential for learning and adjusting complex behaviours. This variability has been linked to the temporal irregularity of neuronal activity in the central nervous system. However, how neuronal irregularity actually translates into behavioural variability is unclear. Here we combine modelling, electrophysiological and behavioural studies to address this issue. We demonstrate that a model circuit comprising topographically organized and strongly recurrent neural networks can autonomously generate irregular motor behaviours. Simultaneous recordings of neurons in singing finches reveal that neural correlations increase across the circuit driving song variability, in agreement with the model predictions. Analysing behavioural data, we find remarkable similarities in the babbling statistics of 5-6-month-old human infants and juveniles from three songbird species and show that our model naturally accounts for these `universal' statistics.

  16. Dynamical networks: Finding, measuring, and tracking neural population activity using network science

    Directory of Open Access Journals (Sweden)

    Mark D. Humphries

    2017-12-01

    Full Text Available Systems neuroscience is in a headlong rush to record from as many neurons at the same time as possible. As the brain computes and codes using neuron populations, it is hoped these data will uncover the fundamentals of neural computation. But with hundreds, thousands, or more simultaneously recorded neurons come the inescapable problems of visualizing, describing, and quantifying their interactions. Here I argue that network science provides a set of scalable, analytical tools that already solve these problems. By treating neurons as nodes and their interactions as links, a single network can visualize and describe an arbitrarily large recording. I show that with this description we can quantify the effects of manipulating a neural circuit, track changes in population dynamics over time, and quantitatively define theoretical concepts of neural populations such as cell assemblies. Using network science as a core part of analyzing population recordings will thus provide both qualitative and quantitative advances to our understanding of neural computation.

  17. Neural Network Ensembles

    DEFF Research Database (Denmark)

    Hansen, Lars Kai; Salamon, Peter

    1990-01-01

    We propose several means for improving the performance an training of neural networks for classification. We use crossvalidation as a tool for optimizing network parameters and architecture. We show further that the remaining generalization error can be reduced by invoking ensembles of similar...... networks....

  18. Neural correlates of consciousness

    African Journals Online (AJOL)

    neural cells.1 Under this approach, consciousness is believed to be a product of the ... possible only when the 40 Hz electrical hum is sustained among the brain circuits, ... expect the brain stem ascending reticular activating system. (ARAS) and the ... related synchrony of cortical neurons.11 Indeed, stimulation of brainstem ...

  19. Neural Networks and Micromechanics

    Science.gov (United States)

    Kussul, Ernst; Baidyk, Tatiana; Wunsch, Donald C.

    The title of the book, "Neural Networks and Micromechanics," seems artificial. However, the scientific and technological developments in recent decades demonstrate a very close connection between the two different areas of neural networks and micromechanics. The purpose of this book is to demonstrate this connection. Some artificial intelligence (AI) methods, including neural networks, could be used to improve automation system performance in manufacturing processes. However, the implementation of these AI methods within industry is rather slow because of the high cost of conducting experiments using conventional manufacturing and AI systems. To lower the cost, we have developed special micromechanical equipment that is similar to conventional mechanical equipment but of much smaller size and therefore of lower cost. This equipment could be used to evaluate different AI methods in an easy and inexpensive way. The proved methods could be transferred to industry through appropriate scaling. In this book, we describe the prototypes of low cost microequipment for manufacturing processes and the implementation of some AI methods to increase precision, such as computer vision systems based on neural networks for microdevice assembly and genetic algorithms for microequipment characterization and the increase of microequipment precision.

  20. Introduction to neural networks

    International Nuclear Information System (INIS)

    Pavlopoulos, P.

    1996-01-01

    This lecture is a presentation of today's research in neural computation. Neural computation is inspired by knowledge from neuro-science. It draws its methods in large degree from statistical physics and its potential applications lie mainly in computer science and engineering. Neural networks models are algorithms for cognitive tasks, such as learning and optimization, which are based on concepts derived from research into the nature of the brain. The lecture first gives an historical presentation of neural networks development and interest in performing complex tasks. Then, an exhaustive overview of data management and networks computation methods is given: the supervised learning and the associative memory problem, the capacity of networks, the Perceptron networks, the functional link networks, the Madaline (Multiple Adalines) networks, the back-propagation networks, the reduced coulomb energy (RCE) networks, the unsupervised learning and the competitive learning and vector quantization. An example of application in high energy physics is given with the trigger systems and track recognition system (track parametrization, event selection and particle identification) developed for the CPLEAR experiment detectors from the LEAR at CERN. (J.S.). 56 refs., 20 figs., 1 tab., 1 appendix

  1. Learning from neural control.

    Science.gov (United States)

    Wang, Cong; Hill, David J

    2006-01-01

    One of the amazing successes of biological systems is their ability to "learn by doing" and so adapt to their environment. In this paper, first, a deterministic learning mechanism is presented, by which an appropriately designed adaptive neural controller is capable of learning closed-loop system dynamics during tracking control to a periodic reference orbit. Among various neural network (NN) architectures, the localized radial basis function (RBF) network is employed. A property of persistence of excitation (PE) for RBF networks is established, and a partial PE condition of closed-loop signals, i.e., the PE condition of a regression subvector constructed out of the RBFs along a periodic state trajectory, is proven to be satisfied. Accurate NN approximation for closed-loop system dynamics is achieved in a local region along the periodic state trajectory, and a learning ability is implemented during a closed-loop feedback control process. Second, based on the deterministic learning mechanism, a neural learning control scheme is proposed which can effectively recall and reuse the learned knowledge to achieve closed-loop stability and improved control performance. The significance of this paper is that the presented deterministic learning mechanism and the neural learning control scheme provide elementary components toward the development of a biologically-plausible learning and control methodology. Simulation studies are included to demonstrate the effectiveness of the approach.

  2. Neural systems for control

    National Research Council Canada - National Science Library

    Omidvar, Omid; Elliott, David L

    1997-01-01

    ... is reprinted with permission from A. Barto, "Reinforcement Learning," Handbook of Brain Theory and Neural Networks, M.A. Arbib, ed.. The MIT Press, Cambridge, MA, pp. 804-809, 1995. Chapter 4, Figures 4-5 and 7-9 and Tables 2-5, are reprinted with permission, from S. Cho, "Map Formation in Proprioceptive Cortex," International Jour...

  3. Neural underpinnings of music

    DEFF Research Database (Denmark)

    Vuust, Peter; Gebauer, Line K; Witek, Maria A G

    2014-01-01

    . According to this theory, perception and learning is manifested through the brain’s Bayesian minimization of the error between the input to the brain and the brain’s prior expectations. Fourth, empirical studies of neural and behavioral effects of syncopation, polyrhythm and groove will be reported, and we...

  4. SU-8-based microneedles for in vitro neural applications

    International Nuclear Information System (INIS)

    Altuna, Ane; Tijero, María; Berganzo, Javier; Salido, Rafa; Fernández, Luis J; Gabriel, Gemma; Guimerá, Anton; Villa, Rosa; Menéndez de la Prida, Liset

    2010-01-01

    This paper presents novel design, fabrication, packaging and the first in vitro neural activity recordings of SU-8-based microneedles. The polymer SU-8 was chosen because it provides excellent features for the fabrication of flexible and thin probes. A microprobe was designed in order to allow a clean insertion and to minimize the damage caused to neural tissue during in vitro applications. In addition, a tetrode is patterned at the tip of the needle to obtain fine-scale measurements of small neuronal populations within a radius of 100 µm. Impedance characterization of the electrodes has been carried out to demonstrate their viability for neural recording. Finally, probes are inserted into 400 µm thick hippocampal slices, and simultaneous action potentials with peak-to-peak amplitudes of 200–250 µV are detected.

  5. Engineering Optics

    CERN Document Server

    Iizuka, Keigo

    2008-01-01

    Engineering Optics is a book for students who want to apply their knowledge of optics to engineering problems, as well as for engineering students who want to acquire the basic principles of optics. It covers such important topics as optical signal processing, holography, tomography, holographic radars, fiber optical communication, electro- and acousto-optic devices, and integrated optics (including optical bistability). As a basis for understanding these topics, the first few chapters give easy-to-follow explanations of diffraction theory, Fourier transforms, and geometrical optics. Practical examples, such as the video disk, the Fresnel zone plate, and many more, appear throughout the text, together with numerous solved exercises. There is an entirely new section in this updated edition on 3-D imaging.

  6. A Decline in Response Variability Improves Neural Signal Detection during Auditory Task Performance.

    Science.gov (United States)

    von Trapp, Gardiner; Buran, Bradley N; Sen, Kamal; Semple, Malcolm N; Sanes, Dan H

    2016-10-26

    The detection of a sensory stimulus arises from a significant change in neural activity, but a sensory neuron's response is rarely identical to successive presentations of the same stimulus. Large trial-to-trial variability would limit the central nervous system's ability to reliably detect a stimulus, presumably affecting perceptual performance. However, if response variability were to decrease while firing rate remained constant, then neural sensitivity could improve. Here, we asked whether engagement in an auditory detection task can modulate response variability, thereby increasing neural sensitivity. We recorded telemetrically from the core auditory cortex of gerbils, both while they engaged in an amplitude-modulation detection task and while they sat quietly listening to the identical stimuli. Using a signal detection theory framework, we found that neural sensitivity was improved during task performance, and this improvement was closely associated with a decrease in response variability. Moreover, units with the greatest change in response variability had absolute neural thresholds most closely aligned with simultaneously measured perceptual thresholds. Our findings suggest that the limitations imposed by response variability diminish during task performance, thereby improving the sensitivity of neural encoding and potentially leading to better perceptual sensitivity. The detection of a sensory stimulus arises from a significant change in neural activity. However, trial-to-trial variability of the neural response may limit perceptual performance. If the neural response to a stimulus is quite variable, then the response on a given trial could be confused with the pattern of neural activity generated when the stimulus is absent. Therefore, a neural mechanism that served to reduce response variability would allow for better stimulus detection. By recording from the cortex of freely moving animals engaged in an auditory detection task, we found that variability

  7. Electron optics

    CERN Document Server

    Grivet, Pierre; Bertein, F; Castaing, R; Gauzit, M; Septier, Albert L

    1972-01-01

    Electron Optics, Second English Edition, Part I: Optics is a 10-chapter book that begins by elucidating the fundamental features and basic techniques of electron optics, as well as the distribution of potential and field in electrostatic lenses. This book then explains the field distribution in magnetic lenses; the optical properties of electrostatic and magnetic lenses; and the similarities and differences between glass optics and electron optics. Subsequent chapters focus on lens defects; some electrostatic lenses and triode guns; and magnetic lens models. The strong focusing lenses and pris

  8. PEAK TRACKING WITH A NEURAL NETWORK FOR SPECTRAL RECOGNITION

    NARCIS (Netherlands)

    COENEGRACHT, PMJ; METTING, HJ; VANLOO, EM; SNOEIJER, GJ; DOORNBOS, DA

    1993-01-01

    A peak tracking method based on a simulated feed-forward neural network with back-propagation is presented. The network uses the normalized UV spectra and peak areas measured in one chromatogram for peak recognition. It suffices to train the network with only one set of spectra recorded in one

  9. Deep convolutional neural networks for detection of rail surface defects

    NARCIS (Netherlands)

    Faghih Roohi, S.; Hajizadeh, S.; Nunez Vicencio, Alfredo; Babuska, R.; De Schutter, B.H.K.; Estevez, Pablo A.; Angelov, Plamen P.; Del Moral Hernandez, Emilio

    2016-01-01

    In this paper, we propose a deep convolutional neural network solution to the analysis of image data for the detection of rail surface defects. The images are obtained from many hours of automated video recordings. This huge amount of data makes it impossible to manually inspect the images and

  10. Bioprinting for Neural Tissue Engineering.

    Science.gov (United States)

    Knowlton, Stephanie; Anand, Shivesh; Shah, Twisha; Tasoglu, Savas

    2018-01-01

    Bioprinting is a method by which a cell-encapsulating bioink is patterned to create complex tissue architectures. Given the potential impact of this technology on neural research, we review the current state-of-the-art approaches for bioprinting neural tissues. While 2D neural cultures are ubiquitous for studying neural cells, 3D cultures can more accurately replicate the microenvironment of neural tissues. By bioprinting neuronal constructs, one can precisely control the microenvironment by specifically formulating the bioink for neural tissues, and by spatially patterning cell types and scaffold properties in three dimensions. We review a range of bioprinted neural tissue models and discuss how they can be used to observe how neurons behave, understand disease processes, develop new therapies and, ultimately, design replacement tissues. Copyright © 2017 Elsevier Ltd. All rights reserved.

  11. Exploring Neural Cell Dynamics with Digital Holographic Microscopy

    KAUST Repository

    Marquet, Pierre; Jourdain, Pascal; Boss, Daniel; Depeursinge, Christian D.; Magistretti, Pierre J.

    2013-01-01

    In this talk, I will present how digital holographic microscopy, as a powerful quantitative phase technique, can non-invasively measure cell dynamics and especially resolve local neuronal network activity through simultaneous multiple site optical recording.

  12. Exploring Neural Cell Dynamics with Digital Holographic Microscopy

    KAUST Repository

    Marquet, Pierre

    2013-04-21

    In this talk, I will present how digital holographic microscopy, as a powerful quantitative phase technique, can non-invasively measure cell dynamics and especially resolve local neuronal network activity through simultaneous multiple site optical recording.

  13. Applied optics

    International Nuclear Information System (INIS)

    Orszag, A.; Antonetti, A.

    1988-01-01

    The 1988 progress report, of the Applied Optics laboratory, of the (Polytechnic School, France), is presented. The optical fiber activities are focused on the development of an optical gyrometer, containing a resonance cavity. The following domains are included, in the research program: the infrared laser physics, the laser sources, the semiconductor physics, the multiple-photon ionization and the nonlinear optics. Investigations on the biomedical, the biological and biophysical domains are carried out. The published papers and the congress communications are listed [fr

  14. SPR imaging combined with cyclic voltammetry for the detection of neural activity

    Directory of Open Access Journals (Sweden)

    Hui Li

    2014-03-01

    Full Text Available Surface plasmon resonance (SPR detects changes in refractive index at a metal-dielectric interface. In this study, SPR imaging (SPRi combined with cyclic voltammetry (CV was applied to detect neural activity in isolated bullfrog sciatic nerves. The neural activities induced by chemical and electrical stimulation led to an SPR response, and the activities were recorded in real time. The activities of different parts of the sciatic nerve were recorded and compared. The results demonstrated that SPR imaging combined with CV is a powerful tool for the investigation of neural activity.

  15. Temporal Correlations and Neural Spike Train Entropy

    International Nuclear Information System (INIS)

    Schultz, Simon R.; Panzeri, Stefano

    2001-01-01

    Sampling considerations limit the experimental conditions under which information theoretic analyses of neurophysiological data yield reliable results. We develop a procedure for computing the full temporal entropy and information of ensembles of neural spike trains, which performs reliably for limited samples of data. This approach also yields insight to the role of correlations between spikes in temporal coding mechanisms. The method, when applied to recordings from complex cells of the monkey primary visual cortex, results in lower rms error information estimates in comparison to a 'brute force' approach

  16. Optic nerve invasion of uveal melanoma

    DEFF Research Database (Denmark)

    Lindegaard, Jens; Isager, Peter; Prause, Jan Ulrik

    2007-01-01

    in Denmark between 1942 and 2001 were reviewed (n=157). Histopathological characteristics and depth of optic nerve invasion were recorded. The material was compared with a control material from the same period consisting of 85 cases randomly drawn from all choroidal/ciliary body melanomas without optic nerve...... juxtapapillary tumors invading the optic nerve because of simple proximity to the nerve. A neurotropic subtype invades the optic nerve and retina in a diffuse fashion unrelated to tumor size or location. Udgivelsesdato: 2007-Jan...

  17. Analysis of neural data

    CERN Document Server

    Kass, Robert E; Brown, Emery N

    2014-01-01

    Continual improvements in data collection and processing have had a huge impact on brain research, producing data sets that are often large and complicated. By emphasizing a few fundamental principles, and a handful of ubiquitous techniques, Analysis of Neural Data provides a unified treatment of analytical methods that have become essential for contemporary researchers. Throughout the book ideas are illustrated with more than 100 examples drawn from the literature, ranging from electrophysiology, to neuroimaging, to behavior. By demonstrating the commonality among various statistical approaches the authors provide the crucial tools for gaining knowledge from diverse types of data. Aimed at experimentalists with only high-school level mathematics, as well as computationally-oriented neuroscientists who have limited familiarity with statistics, Analysis of Neural Data serves as both a self-contained introduction and a reference work.

  18. 34 CFR 668.24 - Record retention and examinations.

    Science.gov (United States)

    2010-07-01

    ... representative. (3) An institution may keep required records in hard copy or in microform, computer file, optical disk, CD-ROM, or other media formats, provided that— (i) Except for the records described in paragraph (d)(3)(ii) of this section, all record information must be retrievable in a coherent hard copy format...

  19. Cognon Neural Model Software Verification and Hardware Implementation Design

    Science.gov (United States)

    Haro Negre, Pau

    Little is known yet about how the brain can recognize arbitrary sensory patterns within milliseconds using neural spikes to communicate information between neurons. In a typical brain there are several layers of neurons, with each neuron axon connecting to ˜104 synapses of neurons in an adjacent layer. The information necessary for cognition is contained in theses synapses, which strengthen during the learning phase in response to newly presented spike patterns. Continuing on the model proposed in "Models for Neural Spike Computation and Cognition" by David H. Staelin and Carl H. Staelin, this study seeks to understand cognition from an information theoretic perspective and develop potential models for artificial implementation of cognition based on neuronal models. To do so we focus on the mathematical properties and limitations of spike-based cognition consistent with existing neurological observations. We validate the cognon model through software simulation and develop concepts for an optical hardware implementation of a network of artificial neural cognons.

  20. Deep Neural Yodelling

    OpenAIRE

    Pfäffli, Daniel (Autor/in)

    2018-01-01

    Yodel music differs from most other genres by exercising the transition from chest voice to falsetto with an audible glottal stop which is recognised even by laymen. Yodel often consists of a yodeller with a choir accompaniment. In Switzerland, it is differentiated between the natural yodel and yodel songs. Today's approaches to music generation with machine learning algorithms are based on neural networks, which are best described by stacked layers of neurons which are connected with neurons...

  1. Neural networks for triggering

    International Nuclear Information System (INIS)

    Denby, B.; Campbell, M.; Bedeschi, F.; Chriss, N.; Bowers, C.; Nesti, F.

    1990-01-01

    Two types of neural network beauty trigger architectures, based on identification of electrons in jets and recognition of secondary vertices, have been simulated in the environment of the Fermilab CDF experiment. The efficiencies for B's and rejection of background obtained are encouraging. If hardware tests are successful, the electron identification architecture will be tested in the 1991 run of CDF. 10 refs., 5 figs., 1 tab

  2. Artificial neural network modelling

    CERN Document Server

    Samarasinghe, Sandhya

    2016-01-01

    This book covers theoretical aspects as well as recent innovative applications of Artificial Neural networks (ANNs) in natural, environmental, biological, social, industrial and automated systems. It presents recent results of ANNs in modelling small, large and complex systems under three categories, namely, 1) Networks, Structure Optimisation, Robustness and Stochasticity 2) Advances in Modelling Biological and Environmental Systems and 3) Advances in Modelling Social and Economic Systems. The book aims at serving undergraduates, postgraduates and researchers in ANN computational modelling. .

  3. Rotation Invariance Neural Network

    OpenAIRE

    Li, Shiyuan

    2017-01-01

    Rotation invariance and translation invariance have great values in image recognition tasks. In this paper, we bring a new architecture in convolutional neural network (CNN) named cyclic convolutional layer to achieve rotation invariance in 2-D symbol recognition. We can also get the position and orientation of the 2-D symbol by the network to achieve detection purpose for multiple non-overlap target. Last but not least, this architecture can achieve one-shot learning in some cases using thos...

  4. Neural Mechanisms of Foraging

    OpenAIRE

    Kolling, Nils; Behrens, Timothy EJ; Mars, Rogier B; Rushworth, Matthew FS

    2012-01-01

    Behavioural economic studies, involving limited numbers of choices, have provided key insights into neural decision-making mechanisms. By contrast, animals’ foraging choices arise in the context of sequences of encounters with prey/food. On each encounter the animal chooses to engage or whether the environment is sufficiently rich that searching elsewhere is merited. The cost of foraging is also critical. We demonstrate humans can alternate between two modes of choice, comparative decision-ma...

  5. Optimization of multilayer neural network parameters for speaker recognition

    Science.gov (United States)

    Tovarek, Jaromir; Partila, Pavol; Rozhon, Jan; Voznak, Miroslav; Skapa, Jan; Uhrin, Dominik; Chmelikova, Zdenka

    2016-05-01

    This article discusses the impact of multilayer neural network parameters for speaker identification. The main task of speaker identification is to find a specific person in the known set of speakers. It means that the voice of an unknown speaker (wanted person) belongs to a group of reference speakers from the voice database. One of the requests was to develop the text-independent system, which means to classify wanted person regardless of content and language. Multilayer neural network has been used for speaker identification in this research. Artificial neural network (ANN) needs to set parameters like activation function of neurons, steepness of activation functions, learning rate, the maximum number of iterations and a number of neurons in the hidden and output layers. ANN accuracy and validation time are directly influenced by the parameter settings. Different roles require different settings. Identification accuracy and ANN validation time were evaluated with the same input data but different parameter settings. The goal was to find parameters for the neural network with the highest precision and shortest validation time. Input data of neural networks are a Mel-frequency cepstral coefficients (MFCC). These parameters describe the properties of the vocal tract. Audio samples were recorded for all speakers in a laboratory environment. Training, testing and validation data set were split into 70, 15 and 15 %. The result of the research described in this article is different parameter setting for the multilayer neural network for four speakers.

  6. Fluidic optics

    Science.gov (United States)

    Whitesides, George M.; Tang, Sindy K. Y.

    2006-09-01

    Fluidic optics is a new class of optical system with real-time tunability and reconfigurability enabled by the introduction of fluidic components into the optical path. We describe the design, fabrication, operation of a number of fluidic optical systems, and focus on three devices, liquid-core/liquid-cladding (L2) waveguides, microfluidic dye lasers, and diffraction gratings based on flowing, crystalline lattices of bubbles, to demonstrate the integration of microfluidics and optics. We fabricate these devices in poly(dimethylsiloxane) (PDMS) with soft-lithographic techniques. They are simple to construct, and readily integrable with microanalytical or lab-on-a-chip systems.

  7. Optical fibres

    CERN Document Server

    Geisler, J; Boutruche, J P

    1986-01-01

    Optical Fibers covers numerous research works on the significant advances in optical fibers, with particular emphasis on their application.This text is composed of three parts encompassing 15 chapters. The first part deals with the manufacture of optical fibers and the materials used in their production. The second part describes optical-fiber connectors, terminals and branches. The third part is concerned with the major optoelectronic components encountered in optical-communication systems.This book will be of value to research scientists, engineers, and patent workers.

  8. Atom optics

    International Nuclear Information System (INIS)

    Balykin, V. I.; Jhe, W.

    1999-01-01

    Atom optics, in analogy to neutron and electron optics, deals with the realization of as a traditional elements, such as lenes, mirrors, beam splitters and atom interferometers, as well as a new 'dissipative' elements such as a slower and a cooler, which have no analogy in an another types of optics. Atom optics made the development of atom interferometer with high sensitivity for measurement of acceleration and rotational possible. The practical interest in atom optics lies in the opportunities to create atom microprobe with atom-size resolution and minimum damage of investigated objects. (Cho, G. S.)

  9. Optical interconnects

    CERN Document Server

    Chen, Ray T

    2006-01-01

    This book describes fully embedded board level optical interconnect in detail including the fabrication of the thin-film VCSEL array, its characterization, thermal management, the fabrication of optical interconnection layer, and the integration of devices on a flexible waveguide film. All the optical components are buried within electrical PCB layers in a fully embedded board level optical interconnect. Therefore, we can save foot prints on the top real estate of the PCB and relieve packaging difficulty reduced by separating fabrication processes. To realize fully embedded board level optical

  10. Nonlinear optics

    CERN Document Server

    Boyd, Robert W

    2013-01-01

    Nonlinear Optics is an advanced textbook for courses dealing with nonlinear optics, quantum electronics, laser physics, contemporary and quantum optics, and electrooptics. Its pedagogical emphasis is on fundamentals rather than particular, transitory applications. As a result, this textbook will have lasting appeal to a wide audience of electrical engineering, physics, and optics students, as well as those in related fields such as materials science and chemistry.Key Features* The origin of optical nonlinearities, including dependence on the polarization of light* A detailed treatment of the q

  11. Paleofloods records in Himalaya

    Science.gov (United States)

    Srivastava, P.; Kumar, A.; Chaudhary, S.; Meena, N.; Sundriyal, Y. P.; Rawat, S.; Rana, N.; Perumal, R. J.; Bisht, P.; Sharma, D.; Agnihotri, R.; Bagri, D. S.; Juyal, N.; Wasson, R. J.; Ziegler, A. D.

    2017-05-01

    We use paleoflood deposits to reconstruct a record of past floods for the Alaknanda-Mandakini Rivers (Garhwal Himalaya), the Indus River (Ladakh, NW Himalaya) and the Brahmaputra River (NE Himalaya). The deposits are characterized by sand-silt couplets, massive sand beds, and from debris flow sediment. The chronology of paleoflood deposits, established by Optically Stimulated Luminescence (OSL) and 14C AMS dating techniques, indicates the following: (i) The Alaknanda-Mandakini Rivers experienced large floods during the wet and warm Medieval Climate Anomaly (MCA); (ii) the Indus River experienced at least 14 large floods during the Holocene climatic optimum, when flood discharges were likely an order of magnitude higher than those of modern floods; and (iii) the Brahmaputra River experienced a megaflood between 8 and 6 ka. Magnetic susceptibility of flood sediments indicates that 10 out of 14 floods on the Indus River originated in the catchments draining the Ladakh Batholith, indicating the potential role of glacial lake outbursts (GLOFs) and/or landslide lake outbursts (LLOFs) in compounding flood magnitudes. Pollen recovered from debris flow deposits located in the headwaters of the Mandakini River showed the presence of warmth-loving trees and marshy taxa, thereby corroborating the finding that floods occurred during relatively warm periods. Collectively, our new data indicate that floods in the Himalaya largely occur during warm and wet climatic phases. Further, the evidence supports the notion that the Indian Summer Monsoon front may have penetrated into the Ladakh area during the Holocene climatic optimum.

  12. Quality assurance records and records' system

    International Nuclear Information System (INIS)

    Link, M.; Martinek, J.

    1980-01-01

    For nuclear power plants extensive proof of quality is required which has to be documented reliably by quality records. With respect to the paper volume it is the most comprehensive 'curriculum vitae' of the technique. Traditional methods of information and recording are unsatisfactory for meeting regulatory requirements for maintaining the QA-aspects of status reporting, completeness, traceability and retrieval. Therefore KWU has established a record (documentation) subsystem within the overall component qualification system. Examples of the general documentation requirements, the procedure and handling in accordance with this subsystem for mechanical equipment are to be described examplarily. Topics are: - National and international requirements - Definition of QA records - Modular and product orientated KWU-record subsystem - Criteria for developing records - Record control, distribution, collection, storage - New documentation techniques (microfilm, data processing) - Education and training of personnel. (orig./RW)

  13. Neural Based Orthogonal Data Fitting The EXIN Neural Networks

    CERN Document Server

    Cirrincione, Giansalvo

    2008-01-01

    Written by three leaders in the field of neural based algorithms, Neural Based Orthogonal Data Fitting proposes several neural networks, all endowed with a complete theory which not only explains their behavior, but also compares them with the existing neural and traditional algorithms. The algorithms are studied from different points of view, including: as a differential geometry problem, as a dynamic problem, as a stochastic problem, and as a numerical problem. All algorithms have also been analyzed on real time problems (large dimensional data matrices) and have shown accurate solutions. Wh

  14. Neural principles of memory and a neural theory of analogical insight

    Science.gov (United States)

    Lawson, David I.; Lawson, Anton E.

    1993-12-01

    Grossberg's principles of neural modeling are reviewed and extended to provide a neural level theory to explain how analogies greatly increase the rate of learning and can, in fact, make learning and retention possible. In terms of memory, the key point is that the mind is able to recognize and recall when it is able to match sensory input from new objects, events, or situations with past memory records of similar objects, events, or situations. When a match occurs, an adaptive resonance is set up in which the synaptic strengths of neurons are increased; thus a long term record of the new input is formed in memory. Systems of neurons called outstars and instars are presumably the underlying units that enable this to occur. Analogies can greatly facilitate learning and retention because they activate the outstars (i.e., the cells that are sampling the to-be-learned pattern) and cause the neural activity to grow exponentially by forming feedback loops. This increased activity insures the boost in synaptic strengths of neurons, thus causing storage and retention in long-term memory (i.e., learning).

  15. Preserving information in neural transmission.

    Science.gov (United States)

    Sincich, Lawrence C; Horton, Jonathan C; Sharpee, Tatyana O

    2009-05-13

    Along most neural pathways, the spike trains transmitted from one neuron to the next are altered. In the process, neurons can either achieve a more efficient stimulus representation, or extract some biologically important stimulus parameter, or succeed at both. We recorded the inputs from single retinal ganglion cells and the outputs from connected lateral geniculate neurons in the macaque to examine how visual signals are relayed from retina to cortex. We found that geniculate neurons re-encoded multiple temporal stimulus features to yield output spikes that carried more information about stimuli than was available in each input spike. The coding transformation of some relay neurons occurred with no decrement in information rate, despite output spike rates that averaged half the input spike rates. This preservation of transmitted information was achieved by the short-term summation of inputs that geniculate neurons require to spike. A reduced model of the retinal and geniculate visual responses, based on two stimulus features and their associated nonlinearities, could account for >85% of the total information available in the spike trains and the preserved information transmission. These results apply to neurons operating on a single time-varying input, suggesting that synaptic temporal integration can alter the temporal receptive field properties to create a more efficient representation of visual signals in the thalamus than the retina.

  16. Neural correlates of rhythmic expectancy

    Directory of Open Access Journals (Sweden)

    Theodore P. Zanto

    2006-01-01

    Full Text Available Temporal expectancy is thought to play a fundamental role in the perception of rhythm. This review summarizes recent studies that investigated rhythmic expectancy by recording neuroelectric activity with high temporal resolution during the presentation of rhythmic patterns. Prior event-related brain potential (ERP studies have uncovered auditory evoked responses that reflect detection of onsets, offsets, sustains,and abrupt changes in acoustic properties such as frequency, intensity, and spectrum, in addition to indexing higher-order processes such as auditory sensory memory and the violation of expectancy. In our studies of rhythmic expectancy, we measured emitted responses - a type of ERP that occurs when an expected event is omitted from a regular series of stimulus events - in simple rhythms with temporal structures typical of music. Our observations suggest that middle-latency gamma band (20-60 Hz activity (GBA plays an essential role in auditory rhythm processing. Evoked (phase-locked GBA occurs in the presence of physically presented auditory events and reflects the degree of accent. Induced (non-phase-locked GBA reflects temporally precise expectancies for strongly and weakly accented events in sound patterns. Thus far, these findings support theories of rhythm perception that posit temporal expectancies generated by active neural processes.

  17. Human motor cortical activity recorded with Micro-ECoG electrodes, during individual finger movements.

    Science.gov (United States)

    Wang, W; Degenhart, A D; Collinger, J L; Vinjamuri, R; Sudre, G P; Adelson, P D; Holder, D L; Leuthardt, E C; Moran, D W; Boninger, M L; Schwartz, A B; Crammond, D J; Tyler-Kabara, E C; Weber, D J

    2009-01-01

    In this study human motor cortical activity was recorded with a customized micro-ECoG grid during individual finger movements. The quality of the recorded neural signals was characterized in the frequency domain from three different perspectives: (1) coherence between neural signals recorded from different electrodes, (2) modulation of neural signals by finger movement, and (3) accuracy of finger movement decoding. It was found that, for the high frequency band (60-120 Hz), coherence between neighboring micro-ECoG electrodes was 0.3. In addition, the high frequency band showed significant modulation by finger movement both temporally and spatially, and a classification accuracy of 73% (chance level: 20%) was achieved for individual finger movement using neural signals recorded from the micro-ECoG grid. These results suggest that the micro-ECoG grid presented here offers sufficient spatial and temporal resolution for the development of minimally-invasive brain-computer interface applications.

  18. Kodak phase-change media for optical tape applications

    Science.gov (United States)

    Tyan, Yuan-Sheng; Preuss, Donald R.; Olin, George R.; Vazan, Fridrich; Pan, Kee-Chuan; Raychaudhuri, Pranab. K.

    1993-01-01

    The SbInSn phase-change write-once optical medium developed by Eastman Kodak Company is particularly suitable for development into the next generation optical tape media. Its performance for optical recording has already been demonstrated in some of the highest performance optical disk systems. Some of the key performance features are presented.

  19. Pattern recognition neural-net by spatial mapping of biology visual field

    Science.gov (United States)

    Lin, Xin; Mori, Masahiko

    2000-05-01

    The method of spatial mapping in biology vision field is applied to artificial neural networks for pattern recognition. By the coordinate transform that is called the complex-logarithm mapping and Fourier transform, the input images are transformed into scale- rotation- and shift- invariant patterns, and then fed into a multilayer neural network for learning and recognition. The results of computer simulation and an optical experimental system are described.

  20. Coding and signal processing for magnetic recording systems

    CERN Document Server

    Vasic, Bane

    2004-01-01

    RECORDING SYSTEMSA BriefHistory of Magnetic Storage, Dean PalmerPhysics of Longitudinal and Perpendicular Recording, Hong Zhou, Tom Roscamp, Roy Gustafson, Eric Boernern, and Roy ChantrellThe Physics of Optical Recording, William A. Challener and Terry W. McDanielHead Design Techniques for Recording Devices, Robert E. RottmayerCOMMUNICATION AND INFORMATION THEORY OF MAGNETIC RECORDING CHANNELSModeling the Recording Channel, Jaekyun MoonSignal and Noise Generation for Magnetic Recording Channel Simulations, Xueshi Yang and Erozan M. KurtasStatistical Analysis of Digital Signals and Systems, Dra

  1. Understanding the Implications of Neural Population Activity on Behavior

    Science.gov (United States)

    Briguglio, John

    Learning how neural activity in the brain leads to the behavior we exhibit is one of the fundamental questions in Neuroscience. In this dissertation, several lines of work are presented to that use principles of neural coding to understand behavior. In one line of work, we formulate the efficient coding hypothesis in a non-traditional manner in order to test human perceptual sensitivity to complex visual textures. We find a striking agreement between how variable a particular texture signal is and how sensitive humans are to its presence. This reveals that the efficient coding hypothesis is still a guiding principle for neural organization beyond the sensory periphery, and that the nature of cortical constraints differs from the peripheral counterpart. In another line of work, we relate frequency discrimination acuity to neural responses from auditory cortex in mice. It has been previously observed that optogenetic manipulation of auditory cortex, in addition to changing neural responses, evokes changes in behavioral frequency discrimination. We are able to account for changes in frequency discrimination acuity on an individual basis by examining the Fisher information from the neural population with and without optogenetic manipulation. In the third line of work, we address the question of what a neural population should encode given that its inputs are responses from another group of neurons. Drawing inspiration from techniques in machine learning, we train Deep Belief Networks on fake retinal data and show the emergence of Garbor-like filters, reminiscent of responses in primary visual cortex. In the last line of work, we model the state of a cortical excitatory-inhibitory network during complex adaptive stimuli. Using a rate model with Wilson-Cowan dynamics, we demonstrate that simple non-linearities in the signal transferred from inhibitory to excitatory neurons can account for real neural recordings taken from auditory cortex. This work establishes and tests

  2. Performance evaluation of coherent Ising machines against classical neural networks

    Science.gov (United States)

    Haribara, Yoshitaka; Ishikawa, Hitoshi; Utsunomiya, Shoko; Aihara, Kazuyuki; Yamamoto, Yoshihisa

    2017-12-01

    The coherent Ising machine is expected to find a near-optimal solution in various combinatorial optimization problems, which has been experimentally confirmed with optical parametric oscillators and a field programmable gate array circuit. The similar mathematical models were proposed three decades ago by Hopfield et al in the context of classical neural networks. In this article, we compare the computational performance of both models.

  3. Presidential Electronic Records Library

    Data.gov (United States)

    National Archives and Records Administration — PERL (Presidential Electronic Records Library) used to ingest and provide internal access to the Presidential electronic Records of the Reagan, Bush, and Clinton...

  4. CMS Records Schedule

    Data.gov (United States)

    U.S. Department of Health & Human Services — The CMS Records Schedule provides disposition authorizations approved by the National Archives and Records Administration (NARA) for CMS program-related records...

  5. Trimaran Resistance Artificial Neural Network

    Science.gov (United States)

    2011-01-01

    11th International Conference on Fast Sea Transportation FAST 2011, Honolulu, Hawaii, USA, September 2011 Trimaran Resistance Artificial Neural Network Richard...Trimaran Resistance Artificial Neural Network 5a. CONTRACT NUMBER 5b. GRANT NUMBER 5c. PROGRAM ELEMENT NUMBER 6. AUTHOR(S) 5d. PROJECT NUMBER 5e... Artificial Neural Network and is restricted to the center and side-hull configurations tested. The value in the parametric model is that it is able to

  6. EEG Artifact Removal Using a Wavelet Neural Network

    Science.gov (United States)

    Nguyen, Hoang-Anh T.; Musson, John; Li, Jiang; McKenzie, Frederick; Zhang, Guangfan; Xu, Roger; Richey, Carl; Schnell, Tom

    2011-01-01

    !n this paper we developed a wavelet neural network. (WNN) algorithm for Electroencephalogram (EEG) artifact removal without electrooculographic (EOG) recordings. The algorithm combines the universal approximation characteristics of neural network and the time/frequency property of wavelet. We. compared the WNN algorithm with .the ICA technique ,and a wavelet thresholding method, which was realized by using the Stein's unbiased risk estimate (SURE) with an adaptive gradient-based optimal threshold. Experimental results on a driving test data set show that WNN can remove EEG artifacts effectively without diminishing useful EEG information even for very noisy data.

  7. Applied optics and optical design

    CERN Document Server

    Conrady, Alexander Eugen

    1957-01-01

    ""For the optical engineer it is an indispensable work."" - Journal, Optical Society of America""As a practical guide this book has no rival."" - Transactions, Optical Society""A noteworthy contribution,"" - Nature (London)Part I covers all ordinary ray-tracing methods, together with the complete theory of primary aberrations and as much of higher aberration as is needed for the design of telescopes, low-power microscopes and simple optical systems. Chapters: Fundamental Equations, Spherical Aberration, Physical Aspect of Optical Images, Chromatic Aberration, Design of Achromatic Object-Glass

  8. Fabry-Perot confocal resonator optical associative memory

    Science.gov (United States)

    Burns, Thomas J.; Rogers, Steven K.; Vogel, George A.

    1993-03-01

    A unique optical associative memory architecture is presented that combines the optical processing environment of a Fabry-Perot confocal resonator with the dynamic storage and recall properties of volume holograms. The confocal resonator reduces the size and complexity of previous associative memory architectures by folding a large number of discrete optical components into an integrated, compact optical processing environment. Experimental results demonstrate the system is capable of recalling a complete object from memory when presented with partial information about the object. A Fourier optics model of the system's operation shows it implements a spatially continuous version of a discrete, binary Hopfield neural network associative memory.

  9. Optical pattern recognition III; Proceedings of the Meeting, Orlando, FL, Apr. 21, 22, 1992

    Science.gov (United States)

    Casasent, David P. (Editor); Chao, Tien-Hsin (Editor)

    1992-01-01

    Consideration is given to transitioning of optical processing into systems (TOPS), optical correlator hardware, phase-only optical correlation filters, optical distortion-invariant correlation filters, and optical neural networks. Particular attention is given to a test target for optical correlators, a TOPS electronic warfare channelizer program, a portable video-rate optical correlator, a joint transform correlator employing electron trapping materials, a novelty filtered optical correlator using a photorefractive crystal, a comparison of correlation performance of smart ternary phase-amplitude filters with gray-scale and binary input scenes, real-time distortion-tolerant composite filters for automatic target identification, landscaping the correlation surface, fast designing of a circular harmonic filter using simulated annealing, feature-based correlation filters for distortion invariance, automatic target recognition using a feature-based optical neural network, and a holographic inner-product processor for pattern recognition.

  10. Evaluation of insertion characteristics of less invasive Si optoneural probe with embedded optical fiber

    Science.gov (United States)

    Morikawa, Takumi; Harashima, Takuya; Kino, Hisashi; Fukushima, Takafumi; Tanaka, Tetsu

    2017-04-01

    A less invasive Si optoneural probe with an embedded optical fiber was proposed and successfully fabricated. The diameter of the optical fiber was completely controlled by hydrogen fluoride etching, and the thinned optical fiber can propagate light without any leakage. This optical fiber was embedded in a trench formed inside a probe shank, which causes less damage to tissues. In addition, it was confirmed that the optical fiber embedded in the probe shank successfully irradiated light to optically stimulate gene transfected neurons. The electrochemical impedance of the probe did not change despite the light irradiation. Furthermore, probe insertion characteristics were evaluated in detail and less invasive insertion was clearly indicated for the Si optoneural probe with the embedded optical fiber compared with conventional optical neural probes. This neural probe with the embedded optical fiber can be used as a simple and easy tool for optogenetics and brain science.

  11. Artificial Neural Network applied to lightning flashes

    Science.gov (United States)

    Gin, R. B.; Guedes, D.; Bianchi, R.

    2013-05-01

    The development of video cameras enabled cientists to study lightning discharges comportment with more precision. The main goal of this project is to create a system able to detect images of lightning discharges stored in videos and classify them using an Artificial Neural Network (ANN)using C Language and OpenCV libraries. The developed system, can be split in two different modules: detection module and classification module. The detection module uses OpenCV`s computer vision libraries and image processing techniques to detect if there are significant differences between frames in a sequence, indicating that something, still not classified, occurred. Whenever there is a significant difference between two consecutive frames, two main algorithms are used to analyze the frame image: brightness and shape algorithms. These algorithms detect both shape and brightness of the event, removing irrelevant events like birds, as well as detecting the relevant events exact position, allowing the system to track it over time. The classification module uses a neural network to classify the relevant events as horizontal or vertical lightning, save the event`s images and calculates his number of discharges. The Neural Network was implemented using the backpropagation algorithm, and was trained with 42 training images , containing 57 lightning events (one image can have more than one lightning). TheANN was tested with one to five hidden layers, with up to 50 neurons each. The best configuration achieved a success rate of 95%, with one layer containing 20 neurons (33 test images with 42 events were used in this phase). This configuration was implemented in the developed system to analyze 20 video files, containing 63 lightning discharges previously manually detected. Results showed that all the lightning discharges were detected, many irrelevant events were unconsidered, and the event's number of discharges was correctly computed. The neural network used in this project achieved a

  12. 2D neural hardware versus 3D biological ones

    Energy Technology Data Exchange (ETDEWEB)

    Beiu, V.

    1998-12-31

    This paper will present important limitations of hardware neural nets as opposed to biological neural nets (i.e. the real ones). The author starts by discussing neural structures and their biological inspirations, while mentioning the simplifications leading to artificial neural nets. Going further, the focus will be on hardware constraints. The author will present recent results for three different alternatives of implementing neural networks: digital, threshold gate, and analog, while the area and the delay will be related to neurons' fan-in and weights' precision. Based on all of these, it will be shown why hardware implementations cannot cope with their biological inspiration with respect to their power of computation: the mapping onto silicon lacking the third dimension of biological nets. This translates into reduced fan-in, and leads to reduced precision. The main conclusion is that one is faced with the following alternatives: (1) try to cope with the limitations imposed by silicon, by speeding up the computation of the elementary silicon neurons; (2) investigate solutions which would allow one to use the third dimension, e.g. using optical interconnections.

  13. Leader emergence through interpersonal neural synchronization.

    Science.gov (United States)

    Jiang, Jing; Chen, Chuansheng; Dai, Bohan; Shi, Guang; Ding, Guosheng; Liu, Li; Lu, Chunming

    2015-04-07

    The neural mechanism of leader emergence is not well understood. This study investigated (i) whether interpersonal neural synchronization (INS) plays an important role in leader emergence, and (ii) whether INS and leader emergence are associated with the frequency or the quality of communications. Eleven three-member groups were asked to perform a leaderless group discussion (LGD) task, and their brain activities were recorded via functional near infrared spectroscopy (fNIRS)-based hyperscanning. Video recordings of the discussions were coded for leadership and communication. Results showed that the INS for the leader-follower (LF) pairs was higher than that for the follower-follower (FF) pairs in the left temporo-parietal junction (TPJ), an area important for social mentalizing. Although communication frequency was higher for the LF pairs than for the FF pairs, the frequency of leader-initiated and follower-initiated communication did not differ significantly. Moreover, INS for the LF pairs was significantly higher during leader-initiated communication than during follower-initiated communications. In addition, INS for the LF pairs during leader-initiated communication was significantly correlated with the leaders' communication skills and competence, but not their communication frequency. Finally, leadership could be successfully predicted based on INS as well as communication frequency early during the LGD (before half a minute into the task). In sum, this study found that leader emergence was characterized by high-level neural synchronization between the leader and followers and that the quality, rather than the frequency, of communications was associated with synchronization. These results suggest that leaders emerge because they are able to say the right things at the right time.

  14. The characteristic patterns of neuronal avalanches in mice under anesthesia and at rest: An investigation using constrained artificial neural networks

    Science.gov (United States)

    Knöpfel, Thomas; Leech, Robert

    2018-01-01

    Local perturbations within complex dynamical systems can trigger cascade-like events that spread across significant portions of the system. Cascades of this type have been observed across a broad range of scales in the brain. Studies of these cascades, known as neuronal avalanches, usually report the statistics of large numbers of avalanches, without probing the characteristic patterns produced by the avalanches themselves. This is partly due to limitations in the extent or spatiotemporal resolution of commonly used neuroimaging techniques. In this study, we overcome these limitations by using optical voltage (genetically encoded voltage indicators) imaging. This allows us to record cortical activity in vivo across an entire cortical hemisphere, at both high spatial (~30um) and temporal (~20ms) resolution in mice that are either in an anesthetized or awake state. We then use artificial neural networks to identify the characteristic patterns created by neuronal avalanches in our data. The avalanches in the anesthetized cortex are most accurately classified by an artificial neural network architecture that simultaneously connects spatial and temporal information. This is in contrast with the awake cortex, in which avalanches are most accurately classified by an architecture that treats spatial and temporal information separately, due to the increased levels of spatiotemporal complexity. This is in keeping with reports of higher levels of spatiotemporal complexity in the awake brain coinciding with features of a dynamical system operating close to criticality. PMID:29795654

  15. Optical electronics

    CERN Document Server

    Yariv, Amnon

    1991-01-01

    This classic text introduces engineering students to the first principles of major phenomena and devices of optoelectronics and optical communication technology. Yariv's "first principles" approach employs real-life examples and extensive problems. The text includes separate chapters on quantum well and semiconductor lasers, as well as phase conjugation and its applications. Optical fiber amplification, signal and noise considerations in optical fiber systems, laser arrays and distributed feedback lasers all are covered extensively in major sections within chapters.

  16. EDITORIAL: Special issue on applied neurodynamics: from neural dynamics to neural engineering Special issue on applied neurodynamics: from neural dynamics to neural engineering

    Science.gov (United States)

    Chiel, Hillel J.; Thomas, Peter J.

    2011-12-01

    -LXIII (London: Royal Society) Ralph T C and Pryde G J 2010 Progress in Optics vol 54, ed E Wolf (New York: Elsevier) pp 209-79 (arXiv:1103.6071) Rashevsky N 1960 Mathematical Biophysics: Physico-Mathematical Foundations of Biology vol 1 3rd edn (New York: Dover) pp 375-462 (first edition 1938) Rinzel J and Ermentrout G B 1989 Analysis of neuronal excitability and oscillations Methods in Neuronal Modeling ed C Koch and I Segev (Cambridge, MA: MIT Press) pp 135-69 Rosin B, Nevet A, Elias S, Rivlin-Etzion M, Israel Z and Bergman H 2007 Physiology and pathophysiology of the basal ganglia-thalamo-cortical networks Parkinsonism Relat. Disord. 13 S437-9 Spardy L E, Markin S N, Shevtsova N A, Prilutsky B I, Rybak I A and Rubin J E 2011a A dynamical systems analysis of afferent control in a neuromechanical model of locomotion: I. Rhythm generation J. Neural Eng. 8 065003 Spardy L E, Markin S N, Shevtsova N A, Prilutsky B I, Rybak I A and Rubin J E 2011b A dynamical systems analysis of afferent control in a neuromechanical model of locomotion: II. Phase asymmetry J. Neural Eng. 8 065004 Steane A 1998 Quantum computing Rep. Prog. Phys. 61 117-73 Strogatz S H 1994 Nonlinear Dynamics and Chaos: with Applications to Physics, Biology, Chemistry, and Engineering (Cambridge, MA: Perseus) Thomas P J 2011 A lower bound for the first passage time density of the suprathreshold Ornstein-Uhlenbeck process J. Appl. Probab. 48 420-34 White J A, Rubinstein J T and Kay A R 2000 Channel noise in neurons Trends Neurosci. 23 131-7 Wilson H R and Cowan J D 1972 Excitatory and inhibitory interactions in localized populations of model neurons Biophys. J. 12 1-24 Wilson H R and Cowan J D 1973 A mathematical theory of the functional dynamics of cortical and thalamic nervous tissue Biol. Cybern. 13 55-80

  17. Optical computing.

    Science.gov (United States)

    Stroke, G. W.

    1972-01-01

    Applications of the optical computer include an approach for increasing the sharpness of images obtained from the most powerful electron microscopes and fingerprint/credit card identification. The information-handling capability of the various optical computing processes is very great. Modern synthetic-aperture radars scan upward of 100,000 resolvable elements per second. Fields which have assumed major importance on the basis of optical computing principles are optical image deblurring, coherent side-looking synthetic-aperture radar, and correlative pattern recognition. Some examples of the most dramatic image deblurring results are shown.

  18. What is refractive optical bistability

    International Nuclear Information System (INIS)

    Dzhehov, Tomislav

    1993-01-01

    The basic elements of the theory of refractive optical bistability, assuming mediums with linear absorption are given. Special attention is paid to bistable etalons of semiconductor materials an oxide glasses, since some of them are considered as promising components for optical bistability applications. The design optimization of such devices for minimum switching intensity is analyzed. Computer simulation of the transfer characteristic recording for two InSb etalons is presented. (author)

  19. Surgical medical record

    DEFF Research Database (Denmark)

    Bulow, S.

    2008-01-01

    A medical record is presented on the basis of selected linguistic pearls collected over the years from surgical case records Udgivelsesdato: 2008/12/15......A medical record is presented on the basis of selected linguistic pearls collected over the years from surgical case records Udgivelsesdato: 2008/12/15...

  20. Analysis of neural networks

    CERN Document Server

    Heiden, Uwe

    1980-01-01

    The purpose of this work is a unified and general treatment of activity in neural networks from a mathematical pOint of view. Possible applications of the theory presented are indica­ ted throughout the text. However, they are not explored in de­ tail for two reasons : first, the universal character of n- ral activity in nearly all animals requires some type of a general approach~ secondly, the mathematical perspicuity would suffer if too many experimental details and empirical peculiarities were interspersed among the mathematical investigation. A guide to many applications is supplied by the references concerning a variety of specific issues. Of course the theory does not aim at covering all individual problems. Moreover there are other approaches to neural network theory (see e.g. Poggio-Torre, 1978) based on the different lev­ els at which the nervous system may be viewed. The theory is a deterministic one reflecting the average be­ havior of neurons or neuron pools. In this respect the essay is writt...