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Sample records for efficient neural stimulation

  1. Energy efficient neural stimulation: coupling circuit design and membrane biophysics.

    Science.gov (United States)

    Foutz, Thomas J; Ackermann, D Michael; Kilgore, Kevin L; McIntyre, Cameron C

    2012-01-01

    The delivery of therapeutic levels of electrical current to neural tissue is a well-established treatment for numerous indications such as Parkinson's disease and chronic pain. While the neuromodulation medical device industry has experienced steady clinical growth over the last two decades, much of the core technology underlying implanted pulse generators remain unchanged. In this study we propose some new methods for achieving increased energy-efficiency during neural stimulation. The first method exploits the biophysical features of excitable tissue through the use of a centered-triangular stimulation waveform. Neural activation with this waveform is achieved with a statistically significant reduction in energy compared to traditional rectangular waveforms. The second method demonstrates energy savings that could be achieved by advanced circuitry design. We show that the traditional practice of using a fixed compliance voltage for constant-current stimulation results in substantial energy loss. A portion of this energy can be recuperated by adjusting the compliance voltage to real-time requirements. Lastly, we demonstrate the potential impact of axon fiber diameter on defining the energy-optimal pulse-width for stimulation. When designing implantable pulse generators for energy efficiency, we propose that the future combination of a variable compliance system, a centered-triangular stimulus waveform, and an axon diameter specific stimulation pulse-width has great potential to reduce energy consumption and prolong battery life in neuromodulation devices.

  2. Energy efficient neural stimulation: coupling circuit design and membrane biophysics.

    Directory of Open Access Journals (Sweden)

    Thomas J Foutz

    Full Text Available The delivery of therapeutic levels of electrical current to neural tissue is a well-established treatment for numerous indications such as Parkinson's disease and chronic pain. While the neuromodulation medical device industry has experienced steady clinical growth over the last two decades, much of the core technology underlying implanted pulse generators remain unchanged. In this study we propose some new methods for achieving increased energy-efficiency during neural stimulation. The first method exploits the biophysical features of excitable tissue through the use of a centered-triangular stimulation waveform. Neural activation with this waveform is achieved with a statistically significant reduction in energy compared to traditional rectangular waveforms. The second method demonstrates energy savings that could be achieved by advanced circuitry design. We show that the traditional practice of using a fixed compliance voltage for constant-current stimulation results in substantial energy loss. A portion of this energy can be recuperated by adjusting the compliance voltage to real-time requirements. Lastly, we demonstrate the potential impact of axon fiber diameter on defining the energy-optimal pulse-width for stimulation. When designing implantable pulse generators for energy efficiency, we propose that the future combination of a variable compliance system, a centered-triangular stimulus waveform, and an axon diameter specific stimulation pulse-width has great potential to reduce energy consumption and prolong battery life in neuromodulation devices.

  3. Design of efficient and safe neural stimulators a multidisciplinary approach

    CERN Document Server

    van Dongen, Marijn

    2016-01-01

    This book discusses the design of neural stimulator systems which are used for the treatment of a wide variety of brain disorders such as Parkinson’s, depression and tinnitus. Whereas many existing books treating neural stimulation focus on one particular design aspect, such as the electrical design of the stimulator, this book uses a multidisciplinary approach: by combining the fields of neuroscience, electrophysiology and electrical engineering a thorough understanding of the complete neural stimulation chain is created (from the stimulation IC down to the neural cell). This multidisciplinary approach enables readers to gain new insights into stimulator design, while context is provided by presenting innovative design examples. Provides a single-source, multidisciplinary reference to the field of neural stimulation, bridging an important knowledge gap among the fields of bioelectricity, neuroscience, neuroengineering and microelectronics;Uses a top-down approach to understanding the neural activation proc...

  4. Compact, Energy-Efficient High-Frequency Switched Capacitor Neural Stimulator With Active Charge Balancing.

    Science.gov (United States)

    Hsu, Wen-Yang; Schmid, Alexandre

    2017-08-01

    Safety and energy efficiency are two major concerns for implantable neural stimulators. This paper presents a novel high-frequency, switched capacitor (HFSC) stimulation and active charge balancing scheme, which achieves high energy efficiency and well-controlled stimulation charge in the presence of large electrode impedance variations. Furthermore, the HFSC can be implemented in a compact size without any external component to simultaneously enable multichannel stimulation by deploying multiple stimulators. The theoretical analysis shows significant benefits over the constant-current and voltage-mode stimulation methods. The proposed solution was fabricated using a 0.18 μm high-voltage technology, and occupies only 0.035 mm 2 for a single stimulator. The measurement result shows 50% peak energy efficiency and confirms the effectiveness of active charge balancing to prevent the electrode dissolution.

  5. A distributed current stimulator ASIC for high density neural stimulation.

    Science.gov (United States)

    Jeong Hoan Park; Chaebin Kim; Seung-Hee Ahn; Tae Mok Gwon; Joonsoo Jeong; Sang Beom Jun; Sung June Kim

    2016-08-01

    This paper presents a novel distributed neural stimulator scheme. Instead of a single stimulator ASIC in the package, multiple ASICs are embedded at each electrode site for stimulation with a high density electrode array. This distributed architecture enables the simplification of wiring between electrodes and stimulator ASIC that otherwise could become too complex as the number of electrode increases. The individual ASIC chip is designed to have a shared data bus that independently controls multiple stimulating channels. Therefore, the number of metal lines is determined by the distributed ASICs, not by the channel number. The function of current steering is also implemented within each ASIC in order to increase the effective number of channels via pseudo channel stimulation. Therefore, the chip area can be used more efficiently. The designed chip was fabricated with area of 0.3 mm2 using 0.18 μm BCDMOS process, and the bench-top test was also conducted to validate chip performance.

  6. Non-invasive neural stimulation

    Science.gov (United States)

    Tyler, William J.; Sanguinetti, Joseph L.; Fini, Maria; Hool, Nicholas

    2017-05-01

    Neurotechnologies for non-invasively interfacing with neural circuits have been evolving from those capable of sensing neural activity to those capable of restoring and enhancing human brain function. Generally referred to as non-invasive neural stimulation (NINS) methods, these neuromodulation approaches rely on electrical, magnetic, photonic, and acoustic or ultrasonic energy to influence nervous system activity, brain function, and behavior. Evidence that has been surmounting for decades shows that advanced neural engineering of NINS technologies will indeed transform the way humans treat diseases, interact with information, communicate, and learn. The physics underlying the ability of various NINS methods to modulate nervous system activity can be quite different from one another depending on the energy modality used as we briefly discuss. For members of commercial and defense industry sectors that have not traditionally engaged in neuroscience research and development, the science, engineering and technology required to advance NINS methods beyond the state-of-the-art presents tremendous opportunities. Within the past few years alone there have been large increases in global investments made by federal agencies, foundations, private investors and multinational corporations to develop advanced applications of NINS technologies. Driven by these efforts NINS methods and devices have recently been introduced to mass markets via the consumer electronics industry. Further, NINS continues to be explored in a growing number of defense applications focused on enhancing human dimensions. The present paper provides a brief introduction to the field of non-invasive neural stimulation by highlighting some of the more common methods in use or under current development today.

  7. A Chip for an Implantable Neural Stimulator

    DEFF Research Database (Denmark)

    Gudnason, Gunnar; Bruun, Erik; Haugland, Morten

    2000-01-01

    This paper describes a chip for a multichannel neural stimulator for functional electrical stimulation (FES). The purpose of FES is to restore muscular control in disabled patients. The chip performs all the signal processing required in an implanted neural stimulator. The power and digital data...

  8. Neural adaptations to electrical stimulation strength training

    NARCIS (Netherlands)

    Hortobagyi, Tibor; Maffiuletti, Nicola A.

    2011-01-01

    This review provides evidence for the hypothesis that electrostimulation strength training (EST) increases the force of a maximal voluntary contraction (MVC) through neural adaptations in healthy skeletal muscle. Although electrical stimulation and voluntary effort activate muscle differently, there

  9. A fully implantable rodent neural stimulator

    Science.gov (United States)

    Perry, D. W. J.; Grayden, D. B.; Shepherd, R. K.; Fallon, J. B.

    2012-02-01

    The ability to electrically stimulate neural and other excitable tissues in behaving experimental animals is invaluable for both the development of neural prostheses and basic neurological research. We developed a fully implantable neural stimulator that is able to deliver two channels of intra-cochlear electrical stimulation in the rat. It is powered via a novel omni-directional inductive link and includes an on-board microcontroller with integrated radio link, programmable current sources and switching circuitry to generate charge-balanced biphasic stimulation. We tested the implant in vivo and were able to elicit both neural and behavioural responses. The implants continued to function for up to five months in vivo. While targeted to cochlear stimulation, with appropriate electrode arrays the stimulator is well suited to stimulating other neurons within the peripheral or central nervous systems. Moreover, it includes significant on-board data acquisition and processing capabilities, which could potentially make it a useful platform for telemetry applications, where there is a need to chronically monitor physiological variables in unrestrained animals.

  10. 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.

  11. Neural dynamics during repetitive visual stimulation

    Science.gov (United States)

    Tsoneva, Tsvetomira; Garcia-Molina, Gary; Desain, Peter

    2015-12-01

    Objective. Steady-state visual evoked potentials (SSVEPs), the brain responses to repetitive visual stimulation (RVS), are widely utilized in neuroscience. Their high signal-to-noise ratio and ability to entrain oscillatory brain activity are beneficial for their applications in brain-computer interfaces, investigation of neural processes underlying brain rhythmic activity (steady-state topography) and probing the causal role of brain rhythms in cognition and emotion. This paper aims at analyzing the space and time EEG dynamics in response to RVS at the frequency of stimulation and ongoing rhythms in the delta, theta, alpha, beta, and gamma bands. Approach.We used electroencephalography (EEG) to study the oscillatory brain dynamics during RVS at 10 frequencies in the gamma band (40-60 Hz). We collected an extensive EEG data set from 32 participants and analyzed the RVS evoked and induced responses in the time-frequency domain. Main results. Stable SSVEP over parieto-occipital sites was observed at each of the fundamental frequencies and their harmonics and sub-harmonics. Both the strength and the spatial propagation of the SSVEP response seem sensitive to stimulus frequency. The SSVEP was more localized around the parieto-occipital sites for higher frequencies (>54 Hz) and spread to fronto-central locations for lower frequencies. We observed a strong negative correlation between stimulation frequency and relative power change at that frequency, the first harmonic and the sub-harmonic components over occipital sites. Interestingly, over parietal sites for sub-harmonics a positive correlation of relative power change and stimulation frequency was found. A number of distinct patterns in delta (1-4 Hz), theta (4-8 Hz), alpha (8-12 Hz) and beta (15-30 Hz) bands were also observed. The transient response, from 0 to about 300 ms after stimulation onset, was accompanied by increase in delta and theta power over fronto-central and occipital sites, which returned to baseline

  12. An Implantable Mixed Analog/Digital Neural Stimulator Circuit

    DEFF Research Database (Denmark)

    Gudnason, Gunnar; Bruun, Erik; Haugland, Morten

    1999-01-01

    This paper describes a chip for a multichannel neural stimulator for functional electrical stimulation. The chip performs all the signal processing required in an implanted neural stimulator. The power and signal transmission to the stimulator is carried out via an inductive link. From the signals...... electrical stimulation is to restore various bodily functions (e.g. motor functions) in patients who have lost them due to injury or disease....

  13. 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.

  14. Consecutive Acupuncture Stimulations Lead to Significantly Decreased Neural Responses

    NARCIS (Netherlands)

    Yeo, S.; Choe, I.H.; Noort, M.W.M.L. van den; Bosch, M.P.C.; Lim, S.

    2010-01-01

    Objective: Functional magnetic resonance imaging (fMRI), in combination with block design paradigms with consecutive acupuncture stimulations, has often been used to investigate the neural responses to acupuncture. In this study, we investigated whether previous acupuncture stimulations can affect

  15. Harmine stimulates proliferation of human neural progenitors

    Directory of Open Access Journals (Sweden)

    Vanja Dakic

    2016-12-01

    Full Text Available Harmine is the β-carboline alkaloid with the highest concentration in the psychotropic plant decoction Ayahuasca. In rodents, classical antidepressants reverse the symptoms of depression by stimulating neuronal proliferation. It has been shown that Ayahuasca presents antidepressant effects in patients with depressive disorder. In the present study, we investigated the effects of harmine in cell cultures containing human neural progenitor cells (hNPCs, 97% nestin-positive derived from pluripotent stem cells. After 4 days of treatment, the pool of proliferating hNPCs increased by 71.5%. Harmine has been reported as a potent inhibitor of the dual specificity tyrosine-phosphorylation-regulated kinase (DYRK1A, which regulates cell proliferation and brain development. We tested the effect of analogs of harmine, an inhibitor of DYRK1A (INDY, and an irreversible selective inhibitor of monoamine oxidase (MAO but not DYRK1A (pargyline. INDY but not pargyline induced proliferation of hNPCs similarly to harmine, suggesting that inhibition of DYRK1A is a possible mechanism to explain harmine effects upon the proliferation of hNPCs. Our findings show that harmine enhances proliferation of hNPCs and suggest that inhibition of DYRK1A may explain its effects upon proliferation in vitro and antidepressant effects in vivo.

  16. Evaluation of intradural stimulation efficiency and selectivity in a computational model of spinal cord stimulation.

    Directory of Open Access Journals (Sweden)

    Bryan Howell

    Full Text Available Spinal cord stimulation (SCS is an alternative or adjunct therapy to treat chronic pain, a prevalent and clinically challenging condition. Although SCS has substantial clinical success, the therapy is still prone to failures, including lead breakage, lead migration, and poor pain relief. The goal of this study was to develop a computational model of SCS and use the model to compare activation of neural elements during intradural and extradural electrode placement. We constructed five patient-specific models of SCS. Stimulation thresholds predicted by the model were compared to stimulation thresholds measured intraoperatively, and we used these models to quantify the efficiency and selectivity of intradural and extradural SCS. Intradural placement dramatically increased stimulation efficiency and reduced the power required to stimulate the dorsal columns by more than 90%. Intradural placement also increased selectivity, allowing activation of a greater proportion of dorsal column fibers before spread of activation to dorsal root fibers, as well as more selective activation of individual dermatomes at different lateral deviations from the midline. Further, the results suggest that current electrode designs used for extradural SCS are not optimal for intradural SCS, and a novel azimuthal tripolar design increased stimulation selectivity, even beyond that achieved with an intradural paddle array. Increased stimulation efficiency is expected to increase the battery life of implantable pulse generators, increase the recharge interval of rechargeable implantable pulse generators, and potentially reduce stimulator volume. The greater selectivity of intradural stimulation may improve the success rate of SCS by mitigating the sensitivity of pain relief to malpositioning of the electrode. The outcome of this effort is a better quantitative understanding of how intradural electrode placement can potentially increase the selectivity and efficiency of SCS

  17. Using Brain Stimulation to Disentangle Neural Correlates of Conscious Vision

    Directory of Open Access Journals (Sweden)

    Tom Alexander de Graaf

    2014-09-01

    Full Text Available Research into the neural correlates of consciousness (NCCs has blossomed, due to the advent of new and increasingly sophisticated brain research tools. Neuroimaging has uncovered a variety of brain processes that relate to conscious perception, obtained in a range of experimental paradigms. But methods such as fMRI or EEG do not always afford inference on the role these brain processes play in conscious vision. Such empirical neural correlates of consciousness could reflect neural prerequisites, neural consequences, or neural substrates of a conscious experience. Here, we take a closer look at the use of non-invasive brain stimulation (NIBS techniques in this context. We discuss and review how NIBS methodology can enlighten our understanding of brain mechanisms underlying conscious vision by disentangling the empirical neural correlates of consciousness.

  18. 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

  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. Stimulated Deep Neural Network for Speech Recognition

    Science.gov (United States)

    2016-09-08

    similarities. As illustrated in Figure 1(b), the network grid behaves as a smooth surface on each layer of a stimulated DNN. The nearby nodes in the...for HTK version 3.5),” 2015. [19] S. Tranter, M. Gales, R. Sinha, S. Umesh, and P. Woodland, “The development of the Cambridge University RT-04

  1. Stimulation Efficiency With Decaying Exponential Waveforms in a Wirelessly Powered Switched-Capacitor Discharge Stimulation System.

    Science.gov (United States)

    Lee, Hyung-Min; Howell, Bryan; Grill, Warren M; Ghovanloo, Maysam

    2018-05-01

    The purpose of this study was to test the feasibility of using a switched-capacitor discharge stimulation (SCDS) system for electrical stimulation, and, subsequently, determine the overall energy saved compared to a conventional stimulator. We have constructed a computational model by pairing an image-based volume conductor model of the cat head with cable models of corticospinal tract (CST) axons and quantified the theoretical stimulation efficiency of rectangular and decaying exponential waveforms, produced by conventional and SCDS systems, respectively. Subsequently, the model predictions were tested in vivo by activating axons in the posterior internal capsule and recording evoked electromyography (EMG) in the contralateral upper arm muscles. Compared to rectangular waveforms, decaying exponential waveforms with time constants >500 μs were predicted to require 2%-4% less stimulus energy to activate directly models of CST axons and 0.4%-2% less stimulus energy to evoke EMG activity in vivo. Using the calculated wireless input energy of the stimulation system and the measured stimulus energies required to evoke EMG activity, we predict that an SCDS implantable pulse generator (IPG) will require 40% less input energy than a conventional IPG to activate target neural elements. A wireless SCDS IPG that is more energy efficient than a conventional IPG will reduce the size of an implant, require that less wireless energy be transmitted through the skin, and extend the lifetime of the battery in the external power transmitter.

  2. 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

  3. Locally optimal extracellular stimulation for chaotic desynchronization of neural populations.

    Science.gov (United States)

    Wilson, Dan; Moehlis, Jeff

    2014-10-01

    We use optimal control theory to design a methodology to find locally optimal stimuli for desynchronization of a model of neurons with extracellular stimulation. This methodology yields stimuli which lead to positive Lyapunov exponents, and hence desynchronizes a neural population. We analyze this methodology in the presence of interneuron coupling to make predictions about the strength of stimulation required to overcome synchronizing effects of coupling. This methodology suggests a powerful alternative to pulsatile stimuli for deep brain stimulation as it uses less energy than pulsatile stimuli, and could eliminate the time consuming tuning process.

  4. 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.

  5. 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.

  6. Using brain stimulation to disentangle neural correlates of conscious vision.

    Science.gov (United States)

    de Graaf, Tom A; Sack, Alexander T

    2014-01-01

    Research into the neural correlates of consciousness (NCCs) has blossomed, due to the advent of new and increasingly sophisticated brain research tools. Neuroimaging has uncovered a variety of brain processes that relate to conscious perception, obtained in a range of experimental paradigms. But methods such as functional magnetic resonance imaging or electroencephalography do not always afford inference on the functional role these brain processes play in conscious vision. Such empirical NCCs could reflect neural prerequisites, neural consequences, or neural substrates of a conscious experience. Here, we take a closer look at the use of non-invasive brain stimulation (NIBS) techniques in this context. We discuss and review how NIBS methodology can enlighten our understanding of brain mechanisms underlying conscious vision by disentangling the empirical NCCs.

  7. Modeling of light absorption in tissue during infrared neural stimulation

    Science.gov (United States)

    Thompson, Alexander C.; Wade, Scott A.; Brown, William G. A.; Stoddart, Paul R.

    2012-07-01

    A Monte Carlo model has been developed to simulate light transport and absorption in neural tissue during infrared neural stimulation (INS). A range of fiber core sizes and numerical apertures are compared illustrating the advantages of using simulations when designing a light delivery system. A range of wavelengths, commonly used for INS, are also compared for stimulation of nerves in the cochlea, in terms of both the energy absorbed and the change in temperature due to a laser pulse. Modeling suggests that a fiber with core diameter of 200 μm and NA=0.22 is optimal for optical stimulation in the geometry used and that temperature rises in the spiral ganglion neurons are as low as 0.1°C. The results show a need for more careful experimentation to allow different proposed mechanisms of INS to be distinguished.

  8. Radiant energy during infrared neural stimulation at the target structure

    Science.gov (United States)

    Richter, Claus-Peter; Rajguru, Suhrud; Stafford, Ryan; Stock, Stuart R.

    2013-03-01

    Infrared neural stimulation (INS) describes a method, by which an infrared laser is used to stimulate neurons. The major benefit of INS over stimulating neurons with electrical current is its spatial selectivity. To translate the technique into a clinical application it is important to know the energy required to stimulate the neural structure. With this study we provide measurements of the radiant exposure, at the target structure that is required to stimulate the auditory neurons. Flat polished fibers were inserted into scala tympani so that the spiral ganglion was in front of the optical fiber. Angle polished fibers were inserted along scala tympani, and rotating the beveled surface of the fiber allowed the radiation beam to be directed perpendicular to the spiral ganglion. The radiant exposure for stimulation at the modiolus for flat and angle polished fibers averaged 6.78+/-2.15 mJ/cm2. With the angle polished fibers, a 90º change in the orientation of the optical beam from an orientation that resulted in an INS-evoked maximum response, resulted in a 50% drop in the response amplitude. When the orientation of the beam was changed by 180º, such that it was directed opposite to the orientation with the maxima, minimum response amplitude was observed.

  9. An improved genetic algorithm for designing optimal temporal patterns of neural stimulation

    Science.gov (United States)

    Cassar, Isaac R.; Titus, Nathan D.; Grill, Warren M.

    2017-12-01

    Objective. Electrical neuromodulation therapies typically apply constant frequency stimulation, but non-regular temporal patterns of stimulation may be more effective and more efficient. However, the design space for temporal patterns is exceedingly large, and model-based optimization is required for pattern design. We designed and implemented a modified genetic algorithm (GA) intended for design optimal temporal patterns of electrical neuromodulation. Approach. We tested and modified standard GA methods for application to designing temporal patterns of neural stimulation. We evaluated each modification individually and all modifications collectively by comparing performance to the standard GA across three test functions and two biophysically-based models of neural stimulation. Main results. The proposed modifications of the GA significantly improved performance across the test functions and performed best when all were used collectively. The standard GA found patterns that outperformed fixed-frequency, clinically-standard patterns in biophysically-based models of neural stimulation, but the modified GA, in many fewer iterations, consistently converged to higher-scoring, non-regular patterns of stimulation. Significance. The proposed improvements to standard GA methodology reduced the number of iterations required for convergence and identified superior solutions.

  10. Neural stimulators: A guide to imaging and postoperative appearances

    International Nuclear Information System (INIS)

    Adams, A.; Shand-Smith, J.; Watkins, L.; McEvoy, A.W.; Elneil, S.; Zrinzo, L.; Davagnanam, I.

    2014-01-01

    Implantable neural stimulators have been developed to aid patients with debilitating neurological conditions that are not amenable to other therapies. The aim of this article is to improve understanding of correct anatomical placement as well as the relevant imaging methods used to assess these devices. Potential complications following their insertion and an overview of the current indications and potential mechanism of action of these devices is provided

  11. A simple miniature device for wireless stimulation of neural circuits in small behaving animals.

    Science.gov (United States)

    Zhang, Yisi; Langford, Bruce; Kozhevnikov, Alexay

    2011-10-30

    The use of wireless neural stimulation devices offers significant advantages for neural stimulation experiments in behaving animals. We demonstrate a simple, low-cost and extremely lightweight wireless neural stimulation device which is made from off-the-shelf components. The device has low power consumption and does not require a high-power RF preamplifier. Neural stimulation can be carried out in either a voltage source mode or a current source mode. Using the device, we carry out wireless stimulation in the premotor brain area HVC of a songbird and demonstrate that such stimulation causes rapid perturbations of the acoustic structure of the song. Published by Elsevier B.V.

  12. Evidence of nonvagal neural stimulation of canine gastric acid secretion.

    Science.gov (United States)

    Tansy, M F; Probst, S J; Martin, J S

    1975-06-01

    In this study, we confirmed our original findings that central vagus stimulation is significantly associated with a subsequent increase in gastric mucus secretion. Central vagus stimulation following phenoxybenzamine hydrochloride administration was associated significantly with protracted elevations in secretory volume and titratable acid. We were unable to conclude that phenoxybenzamine itself in several pharmacologic dosages was associated with an increase in titratable acid. The acid secretory responses could be abolished by transection of the splanchnic nerves. Electrical stimulation of the peripheral part of the splanchnic nerve following administration of phenoxybenzamine was also associated with significant increases in secretory volume and titrable acidity. These secretory responses were not blocked by atropine but were diminished by burimamide. It is concluded that, in the dog, a largely heretofore unsuspected second neural pathway exists which is capable of influencing gastric acid secretion.

  13. Electric stimulation with sinusoids and white noise for neural prostheses

    Directory of Open Access Journals (Sweden)

    Daniel K Freeman

    2010-02-01

    Full Text Available We are investigating the use of novel stimulus waveforms in neural prostheses to determine whether they can provide more precise control over the temporal and spatial pattern of elicited activity as compared to conventional pulsatile stimulation. To study this, we measured the response of retinal ganglion cells to both sinusoidal and white noise waveforms. The use of cell-attached and whole cell patch clamp recordings allowed the responses to be observed without significant obstruction from the stimulus artifact. Electric stimulation with sinusoids elicited robust responses. White noise analysis was used to derive the linear kernel for the ganglion cell’s spiking response as well as for the underlying excitatory currents. These results suggest that in response to electric stimulation, presynaptic retinal neurons exhibit bandpass filtering characteristics with peak response that occur 25ms after onset. The experimental approach demonstrated here may be useful for studying the temporal response properties of other neurons in the CNS.

  14. 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.

  15. Waveform efficiency analysis of auditory nerve fiber stimulation for cochlear implants

    International Nuclear Information System (INIS)

    Navaii, Mehdi Lotfi; Sadhedi, Hamed; Jalali, Mohsen

    2013-01-01

    Evaluation of the electrical stimulation efficiency of various stimulating waveforms is an important issue for efficient neural stimulator design. Concerning the implantable micro devices design, it is also necessary to consider the feasibility of hardware implementation of the desired waveforms. In this paper, the charge, power and energy efficiency of four waveforms (i.e. square, rising ramp, triangular and rising ramp-decaying exponential) in various durations have been simulated and evaluated based on the computational model of the auditory nerve fibers. Moreover, for a fair comparison of their feasibility, a fully integrated current generator circuit has been developed so that the desired stimulating waveforms can be generated. The simulation results show that stimulation with the square waveforms is a proper choice in short and intermediate durations while the rising ramp-decaying exponential or triangular waveforms can be employed for long durations.

  16. 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

    a single spine, with two-photon uncaging) and in rapid, flexible spatial-temporal patterns [10-14]. Nevertheless, current technology generally requires damaging doses of UV or violet illumination and the continuous re-introduction of the caged compound, which, despite interest, makes for a difficult transition beyond in vitro preparations. Thus, the tremendous progress in the in vivo application of photo-stimulation tools over the past five years has been largely facilitated by two 'exciting' new photo-stimulation technologies: photo-biological stimulation of a rapidly increasing arsenal of light-sensitive ion channels and pumps ('optogenetic' probes[15-18]) and direct photo-thermal stimulation of neural tissue with an IR laser [19-21]. The Journal of Neural Engineering has dedicated a special section in this issue to highlight advances in optical stimulation technology, which includes original peer-reviewed contributions dealing with the design of modern optical systems for spatial-temporal control of optical excitation patterns and with the biophysics of neural-thermal interaction mediated by electromagnetic waves. The paper by Nikolenko, Peterka and Yuste [22] presents a compact design of a microscope-photo-stimulator based on a transmissive phase-modulating spatial-light modulator (SLM). Computer-generated holographic photo-stimulation using SLMs [12-14, 23] allows the efficient parallel projection of intense sparse patterns of light, and the welcome development of compact, user-friendly systems will likely reduce the barrier to its widespread adoption. The paper by Losavio et al [24] presents the design and functional characteristics of their acousto-optical deflector (AOD) systems for studying spatial-temporal dendritic integration in single neurons in vitro. Both single-photon (UV) and two-photon (femtosecond pulsed IR) AOD uncaging systems are described in detail. The paper presents an excellent overview of the current state of the art and limitations of

  17. Analysis of Oscillatory Neural Activity in Series Network Models of Parkinson's Disease During Deep Brain Stimulation.

    Science.gov (United States)

    Davidson, Clare M; de Paor, Annraoi M; Cagnan, Hayriye; Lowery, Madeleine M

    2016-01-01

    Parkinson's disease is a progressive, neurodegenerative disorder, characterized by hallmark motor symptoms. It is associated with pathological, oscillatory neural activity in the basal ganglia. Deep brain stimulation (DBS) is often successfully used to treat medically refractive Parkinson's disease. However, the selection of stimulation parameters is based on qualitative assessment of the patient, which can result in a lengthy tuning period and a suboptimal choice of parameters. This study explores fourth-order, control theory-based models of oscillatory activity in the basal ganglia. Describing function analysis is applied to examine possible mechanisms for the generation of oscillations in interacting nuclei and to investigate the suppression of oscillations with high-frequency stimulation. The theoretical results for the suppression of the oscillatory activity obtained using both the fourth-order model, and a previously described second-order model, are optimized to fit clinically recorded local field potential data obtained from Parkinsonian patients with implanted DBS. Close agreement between the power of oscillations recorded for a range of stimulation amplitudes is observed ( R(2)=0.69-0.99 ). The results suggest that the behavior of the system and the suppression of pathological neural oscillations with DBS is well described by the macroscopic models presented. The results also demonstrate that in this instance, a second-order model is sufficient to model the clinical data, without the need for added complexity. Describing the system behavior with computationally efficient models could aid in the identification of optimal stimulation parameters for patients in a clinical environment.

  18. Photovoltaic Pixels for Neural Stimulation: Circuit Models and Performance.

    Science.gov (United States)

    Boinagrov, David; Lei, Xin; Goetz, Georges; Kamins, Theodore I; Mathieson, Keith; Galambos, Ludwig; Harris, James S; Palanker, Daniel

    2016-02-01

    Photovoltaic conversion of pulsed light into pulsed electric current enables optically-activated neural stimulation with miniature wireless implants. In photovoltaic retinal prostheses, patterns of near-infrared light projected from video goggles onto subretinal arrays of photovoltaic pixels are converted into patterns of current to stimulate the inner retinal neurons. We describe a model of these devices and evaluate the performance of photovoltaic circuits, including the electrode-electrolyte interface. Characteristics of the electrodes measured in saline with various voltages, pulse durations, and polarities were modeled as voltage-dependent capacitances and Faradaic resistances. The resulting mathematical model of the circuit yielded dynamics of the electric current generated by the photovoltaic pixels illuminated by pulsed light. Voltages measured in saline with a pipette electrode above the pixel closely matched results of the model. Using the circuit model, our pixel design was optimized for maximum charge injection under various lighting conditions and for different stimulation thresholds. To speed discharge of the electrodes between the pulses of light, a shunt resistor was introduced and optimized for high frequency stimulation.

  19. Ultra-nanocrystalline diamond electrodes: optimization towards neural stimulation applications.

    Science.gov (United States)

    Garrett, David J; Ganesan, Kumaravelu; Stacey, Alastair; Fox, Kate; Meffin, Hamish; Prawer, Steven

    2012-02-01

    Diamond is well known to possess many favourable qualities for implantation into living tissue including biocompatibility, biostability, and for some applications hardness. However, conducting diamond has not, to date, been exploited in neural stimulation electrodes due to very low electrochemical double layer capacitance values that have been previously reported. Here we present electrochemical characterization of ultra-nanocrystalline diamond electrodes grown in the presence of nitrogen (N-UNCD) that exhibit charge injection capacity values as high as 163 µC cm(-2) indicating that N-UNCD is a viable material for microelectrode fabrication. Furthermore, we show that the maximum charge injection of N-UNCD can be increased by tailoring growth conditions and by subsequent electrochemical activation. For applications requiring yet higher charge injection, we show that N-UNCD electrodes can be readily metalized with platinum or iridium, further increasing charge injection capacity. Using such materials an implantable neural stimulation device fabricated from a single piece of bio-permanent material becomes feasible. This has significant advantages in terms of the physical stability and hermeticity of a long-term bionic implant.

  20. Electrical Neural Stimulation and Simultaneous in Vivo Monitoring with Transparent Graphene Electrode Arrays Implanted in GCaMP6f Mice.

    Science.gov (United States)

    Park, Dong-Wook; Ness, Jared P; Brodnick, Sarah K; Esquibel, Corinne; Novello, Joseph; Atry, Farid; Baek, Dong-Hyun; Kim, Hyungsoo; Bong, Jihye; Swanson, Kyle I; Suminski, Aaron J; Otto, Kevin J; Pashaie, Ramin; Williams, Justin C; Ma, Zhenqiang

    2018-01-23

    Electrical stimulation using implantable electrodes is widely used to treat various neuronal disorders such as Parkinson's disease and epilepsy and is a widely used research tool in neuroscience studies. However, to date, devices that help better understand the mechanisms of electrical stimulation in neural tissues have been limited to opaque neural electrodes. Imaging spatiotemporal neural responses to electrical stimulation with minimal artifact could allow for various studies that are impossible with existing opaque electrodes. Here, we demonstrate electrical brain stimulation and simultaneous optical monitoring of the underlying neural tissues using carbon-based, fully transparent graphene electrodes implanted in GCaMP6f mice. Fluorescence imaging of neural activity for varying electrical stimulation parameters was conducted with minimal image artifact through transparent graphene electrodes. In addition, full-field imaging of electrical stimulation verified more efficient neural activation with cathode leading stimulation compared to anode leading stimulation. We have characterized the charge density limitation of capacitive four-layer graphene electrodes as 116.07-174.10 μC/cm 2 based on electrochemical impedance spectroscopy, cyclic voltammetry, failure bench testing, and in vivo testing. This study demonstrates the transparent ability of graphene neural electrodes and provides a method to further increase understanding and potentially improve therapeutic electrical stimulation in the central and peripheral nervous systems.

  1. 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

  2. An energy-efficient, adiabatic electrode stimulator with inductive energy recycling and feedback current regulation.

    Science.gov (United States)

    Arfin, Scott K; Sarpeshkar, Rahul

    2012-02-01

    In this paper, we present a novel energy-efficient electrode stimulator. Our stimulator uses inductive storage and recycling of energy in a dynamic power supply. This supply drives an electrode in an adiabatic fashion such that energy consumption is minimized. It also utilizes a shunt current-sensor to monitor and regulate the current through the electrode via feedback, thus enabling flexible and safe stimulation. Since there are no explicit current sources or current limiters, wasteful energy dissipation across such elements is naturally avoided. The dynamic power supply allows efficient transfer of energy both to and from the electrode and is based on a DC-DC converter topology that we use in a bidirectional fashion in forward-buck or reverse-boost modes. In an exemplary electrode implementation intended for neural stimulation, we show how the stimulator combines the efficiency of voltage control and the safety and accuracy of current control in a single low-power integrated-circuit built in a standard .35 μm CMOS process. This stimulator achieves a 2x-3x reduction in energy consumption as compared to a conventional current-source-based stimulator operating from a fixed power supply. We perform a theoretical analysis of the energy efficiency that is in accord with experimental measurements. This theoretical analysis reveals that further improvements in energy efficiency may be achievable with better implementations in the future. Our electrode stimulator could be widely useful for neural, cardiac, retinal, cochlear, muscular and other biomedical implants where low power operation is important.

  3. 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

  4. Efficient Cancer Detection Using Multiple Neural Networks.

    Science.gov (United States)

    Shell, John; Gregory, William D

    2017-01-01

    The inspection of live excised tissue specimens to ascertain malignancy is a challenging task in dermatopathology and generally in histopathology. We introduce a portable desktop prototype device that provides highly accurate neural network classification of malignant and benign tissue. The handheld device collects 47 impedance data samples from 1 Hz to 32 MHz via tetrapolar blackened platinum electrodes. The data analysis was implemented with six different backpropagation neural networks (BNN). A data set consisting of 180 malignant and 180 benign breast tissue data files in an approved IRB study at the Aurora Medical Center, Milwaukee, WI, USA, were utilized as a neural network input. The BNN structure consisted of a multi-tiered consensus approach autonomously selecting four of six neural networks to determine a malignant or benign classification. The BNN analysis was then compared with the histology results with consistent sensitivity of 100% and a specificity of 100%. This implementation successfully relied solely on statistical variation between the benign and malignant impedance data and intricate neural network configuration. This device and BNN implementation provides a novel approach that could be a valuable tool to augment current medical practice assessment of the health of breast, squamous, and basal cell carcinoma and other excised tissue without requisite tissue specimen expertise. It has the potential to provide clinical management personnel with a fast non-invasive accurate assessment of biopsied or sectioned excised tissue in various clinical settings.

  5. A Programmable High-Voltage Compliance Neural Stimulator for Deep Brain Stimulation in Vivo

    Directory of Open Access Journals (Sweden)

    Cihun-Siyong Alex Gong

    2015-05-01

    Full Text Available Deep brain stimulation (DBS is one of the most effective therapies for movement and other disorders. The DBS neurosurgical procedure involves the implantation of a DBS device and a battery-operated neurotransmitter, which delivers electrical impulses to treatment targets through implanted electrodes. The DBS modulates the neuronal activities in the brain nucleus for improving physiological responses as long as an electric discharge above the stimulation threshold can be achieved. In an effort to improve the performance of an implanted DBS device, the device size, implementation cost, and power efficiency are among the most important DBS device design aspects. This study aims to present preliminary research results of an efficient stimulator, with emphasis on conversion efficiency. The prototype stimulator features high-voltage compliance, implemented with only a standard semiconductor process, without the use of extra masks in the foundry through our proposed circuit structure. The results of animal experiments, including evaluation of evoked responses induced by thalamic electrical stimuli with our fabricated chip, were shown to demonstrate the proof of concept of our design.

  6. Efficiency turns the table on neural encoding, decoding and noise.

    Science.gov (United States)

    Deneve, Sophie; Chalk, Matthew

    2016-04-01

    Sensory neurons are usually described with an encoding model, for example, a function that predicts their response from the sensory stimulus using a receptive field (RF) or a tuning curve. However, central to theories of sensory processing is the notion of 'efficient coding'. We argue here that efficient coding implies a completely different neural coding strategy. Instead of a fixed encoding model, neural populations would be described by a fixed decoding model (i.e. a model reconstructing the stimulus from the neural responses). Because the population solves a global optimization problem, individual neurons are variable, but not noisy, and have no truly invariant tuning curve or receptive field. We review recent experimental evidence and implications for neural noise correlations, robustness and adaptation. Copyright © 2016. Published by Elsevier Ltd.

  7. Computationally Efficient Neural Network Intrusion Security Awareness

    Energy Technology Data Exchange (ETDEWEB)

    Todd Vollmer; Milos Manic

    2009-08-01

    An enhanced version of an algorithm to provide anomaly based intrusion detection alerts for cyber security state awareness is detailed. A unique aspect is the training of an error back-propagation neural network with intrusion detection rule features to provide a recognition basis. Network packet details are subsequently provided to the trained network to produce a classification. This leverages rule knowledge sets to produce classifications for anomaly based systems. Several test cases executed on ICMP protocol revealed a 60% identification rate of true positives. This rate matched the previous work, but 70% less memory was used and the run time was reduced to less than 1 second from 37 seconds.

  8. Synaptic E-I Balance Underlies Efficient Neural Coding.

    Science.gov (United States)

    Zhou, Shanglin; Yu, Yuguo

    2018-01-01

    Both theoretical and experimental evidence indicate that synaptic excitation and inhibition in the cerebral cortex are well-balanced during the resting state and sensory processing. Here, we briefly summarize the evidence for how neural circuits are adjusted to achieve this balance. Then, we discuss how such excitatory and inhibitory balance shapes stimulus representation and information propagation, two basic functions of neural coding. We also point out the benefit of adopting such a balance during neural coding. We conclude that excitatory and inhibitory balance may be a fundamental mechanism underlying efficient coding.

  9. Computationally efficient model predictive control algorithms a neural network approach

    CERN Document Server

    Ławryńczuk, Maciej

    2014-01-01

    This book thoroughly discusses computationally efficient (suboptimal) Model Predictive Control (MPC) techniques based on neural models. The subjects treated include: ·         A few types of suboptimal MPC algorithms in which a linear approximation of the model or of the predicted trajectory is successively calculated on-line and used for prediction. ·         Implementation details of the MPC algorithms for feedforward perceptron neural models, neural Hammerstein models, neural Wiener models and state-space neural models. ·         The MPC algorithms based on neural multi-models (inspired by the idea of predictive control). ·         The MPC algorithms with neural approximation with no on-line linearization. ·         The MPC algorithms with guaranteed stability and robustness. ·         Cooperation between the MPC algorithms and set-point optimization. Thanks to linearization (or neural approximation), the presented suboptimal algorithms do not require d...

  10. Angiogenic factors stimulate growth of adult neural stem cells.

    Directory of Open Access Journals (Sweden)

    Andreas Androutsellis-Theotokis

    2010-02-01

    Full Text Available The ability to grow a uniform cell type from the adult central nervous system (CNS is valuable for developing cell therapies and new strategies for drug discovery. The adult mammalian brain is a source of neural stem cells (NSC found in both neurogenic and non-neurogenic zones but difficulties in culturing these hinders their use as research tools.Here we show that NSCs can be efficiently grown in adherent cell cultures when angiogenic signals are included in the medium. These signals include both anti-angiogenic factors (the soluble form of the Notch receptor ligand, Dll4 and pro-angiogenic factors (the Tie-2 receptor ligand, Angiopoietin 2. These treatments support the self renewal state of cultured NSCs and expression of the transcription factor Hes3, which also identifies the cancer stem cell population in human tumors. In an organotypic slice model, angiogenic factors maintain vascular structure and increase the density of dopamine neuron processes.We demonstrate new properties of adult NSCs and a method to generate efficient adult NSC cultures from various central nervous system areas. These findings will help establish cellular models relevant to cancer and regeneration.

  11. Towards a Switched-Capacitor Based Stimulator for Efficient Deep-Brain Stimulation

    Science.gov (United States)

    Vidal, Jose; Ghovanloo, Maysam

    2013-01-01

    We have developed a novel 4-channel prototype stimulation circuit for implantable neurological stimulators (INS). This Switched-Capacitor based Stimulator (SCS) aims to utilize charge storage and charge injection techniques to take advantage of both the efficiency of conventional voltage-controlled stimulators (VCS) and the safety and controllability of current-controlled stimulators (CCS). The discrete SCS prototype offers fine control over stimulation parameters such as voltage, current, pulse width, frequency, and active electrode channel via a LabVIEW graphical user interface (GUI) when connected to a PC through USB. Furthermore, the prototype utilizes a floating current sensor to provide charge-balanced biphasic stimulation and ensure safety. The stimulator was analyzed using an electrode-electrolyte interface (EEI) model as well as with a pair of pacing electrodes in saline. The primary motivation of this research is to test the feasibility and functionality of a safe, effective, and power-efficient switched-capacitor based stimulator for use in Deep Brain Stimulation. PMID:21095987

  12. Neural substrates underlying stimulation-enhanced motor skill learning after stroke.

    Science.gov (United States)

    Lefebvre, Stéphanie; Dricot, Laurence; Laloux, Patrice; Gradkowski, Wojciech; Desfontaines, Philippe; Evrard, Frédéric; Peeters, André; Jamart, Jacques; Vandermeeren, Yves

    2015-01-01

    Motor skill learning is one of the key components of motor function recovery after stroke, especially recovery driven by neurorehabilitation. Transcranial direct current stimulation can enhance neurorehabilitation and motor skill learning in stroke patients. However, the neural mechanisms underlying the retention of stimulation-enhanced motor skill learning involving a paretic upper limb have not been resolved. These neural substrates were explored by means of functional magnetic resonance imaging. Nineteen chronic hemiparetic stroke patients participated in a double-blind, cross-over randomized, sham-controlled experiment with two series. Each series consisted of two sessions: (i) an intervention session during which dual transcranial direct current stimulation or sham was applied during motor skill learning with the paretic upper limb; and (ii) an imaging session 1 week later, during which the patients performed the learned motor skill. The motor skill learning task, called the 'circuit game', involves a speed/accuracy trade-off and consists of moving a pointer controlled by a computer mouse along a complex circuit as quickly and accurately as possible. Relative to the sham series, dual transcranial direct current stimulation applied bilaterally over the primary motor cortex during motor skill learning with the paretic upper limb resulted in (i) enhanced online motor skill learning; (ii) enhanced 1-week retention; and (iii) superior transfer of performance improvement to an untrained task. The 1-week retention's enhancement driven by the intervention was associated with a trend towards normalization of the brain activation pattern during performance of the learned motor skill relative to the sham series. A similar trend towards normalization relative to sham was observed during performance of a simple, untrained task without a speed/accuracy constraint, despite a lack of behavioural difference between the dual transcranial direct current stimulation and sham

  13. Alteration of neural action potential patterns by axonal stimulation: the importance of stimulus location.

    Science.gov (United States)

    Crago, Patrick E; Makowski, Nathaniel S

    2014-10-01

    Stimulation of peripheral nerves is often superimposed on ongoing motor and sensory activity in the same axons, without a quantitative model of the net action potential train at the axon endpoint. We develop a model of action potential patterns elicited by superimposing constant frequency axonal stimulation on the action potentials arriving from a physiologically activated neural source. The model includes interactions due to collision block, resetting of the neural impulse generator, and the refractory period of the axon at the point of stimulation. Both the mean endpoint firing rate and the probability distribution of the action potential firing periods depend strongly on the relative firing rates of the two sources and the intersite conduction time between them. When the stimulus rate exceeds the neural rate, neural action potentials do not reach the endpoint and the rate of endpoint action potentials is the same as the stimulus rate, regardless of the intersite conduction time. However, when the stimulus rate is less than the neural rate, and the intersite conduction time is short, the two rates partially sum. Increases in stimulus rate produce non-monotonic increases in endpoint rate and continuously increasing block of neurally generated action potentials. Rate summation is reduced and more neural action potentials are blocked as the intersite conduction time increases. At long intersite conduction times, the endpoint rate simplifies to being the maximum of either the neural or the stimulus rate. This study highlights the potential of increasing the endpoint action potential rate and preserving neural information transmission by low rate stimulation with short intersite conduction times. Intersite conduction times can be decreased with proximal stimulation sites for muscles and distal stimulation sites for sensory endings. The model provides a basis for optimizing experiments and designing neuroprosthetic interventions involving motor or sensory stimulation.

  14. Evidence-Based Systematic Review: Effects of Neuromuscular Electrical Stimulation on Swallowing and Neural Activation

    Science.gov (United States)

    Clark, Heather; Lazarus, Cathy; Arvedson, Joan; Schooling, Tracy; Frymark, Tobi

    2009-01-01

    Purpose: To systematically review the literature examining the effects of neuromuscular electrical stimulation (NMES) on swallowing and neural activation. The review was conducted as part of a series examining the effects of oral motor exercises (OMEs) on speech, swallowing, and neural activation. Method: A systematic search was conducted to…

  15. Combining BMI stimulation and mathematical modeling for acute stroke recovery and neural repair

    Directory of Open Access Journals (Sweden)

    Sara L Gonzalez Andino

    2011-07-01

    Full Text Available Rehabilitation is a neural plasticity-exploiting approach that forces undamaged neural circuits to undertake the functionality of other circuits damaged by stroke. It aims to partial restoration of the neural functions by circuit remodeling rather than by the regeneration of damaged circuits. The core hypothesis of the present paper is that - in stroke - Brain Machine Interfaces can be designed to target neural repair instead of rehabilitation. To support this hypothesis we first review existing evidence on the role of endogenous or externally applied electric fields on all processes involved in CNS repair. We then describe our own results to illustrate the neuroprotective and neuroregenerative effects of BMI- electrical stimulation on sensory deprivation-related degenerative processes of the CNS. Finally, we discuss three of the crucial issues involved in the design of neural repair-oriented BMIs: when to stimulate, where to stimulate and - the particularly important but unsolved issue of - how to stimulate. We argue that optimal parameters for the electrical stimulation can be determined from studying and modeling the dynamics of the electric fields that naturally emerge at the central and peripheral nervous system during spontaneous healing in both, experimental animals and human patients. We conclude that a closed-loop BMI that defines the optimal stimulation parameters from a priori developed experimental models of the dynamics of spontaneous repair and the on-line monitoring of neural activity might place BMIs as an alternative or complement to stem-cell transplantation or pharmacological approaches, intensively pursued nowadays.

  16. The Codacs™ direct acoustic cochlear implant actuator: exploring alternative stimulation sites and their stimulation efficiency.

    Science.gov (United States)

    Grossöhmichen, Martin; Salcher, Rolf; Kreipe, Hans-Heinrich; Lenarz, Thomas; Maier, Hannes

    2015-01-01

    This work assesses the efficiency of the Codacs system actuator (Cochlear Ltd., Sydney Australia) in different inner ear stimulation modalities. Originally the actuator was intended for direct perilymph stimulation after stapedotomy using a piston prosthesis. A possible alternative application is the stimulation of middle ear structures or the round window (RW). Here the perilymph stimulation with a K-piston through a stapes footplate (SFP) fenestration (N = 10) as well as stimulation of the stapes head (SH) with a Bell prosthesis (N = 9), SFP stimulation with an Omega/Aerial prosthesis (N = 8) and reverse RW stimulation (N = 10) were performed in cadaveric human temporal bones (TBs). Codacs actuator output is expressed as equivalent sound pressure level (eq. SPL) using RW and SFP displacement responses, measured by Laser Doppler velocimetry as reference. The axial actuator coupling force in stimulation of stapes and RW was adjusted to ~5 mN. The Bell prosthesis and Omega/Aerial prosthesis stimulation generated similar mean eq. SPLs (Bell: 127.5-141.8 eq. dB SPL; Omega/Aerial: 123.6-143.9 eq. dB SPL), being significantly more efficient than K-piston perilymph stimulation (108.6-131.6 eq. dB SPL) and RW stimulation (108.3-128.2 eq. dB SPL). Our results demonstrate that SH, SFP and RW are adequate alternative stimulation sites for the Codacs actuator using coupling prostheses and an axial coupling force of ~5 mN. Based on the eq. SPLs, all investigated methods were adequate for in vivo hearing aid applications, provided that experimental conditions including constant coupling force will be implemented.

  17. The Codacs™ direct acoustic cochlear implant actuator: exploring alternative stimulation sites and their stimulation efficiency.

    Directory of Open Access Journals (Sweden)

    Martin Grossöhmichen

    Full Text Available This work assesses the efficiency of the Codacs system actuator (Cochlear Ltd., Sydney Australia in different inner ear stimulation modalities. Originally the actuator was intended for direct perilymph stimulation after stapedotomy using a piston prosthesis. A possible alternative application is the stimulation of middle ear structures or the round window (RW. Here the perilymph stimulation with a K-piston through a stapes footplate (SFP fenestration (N = 10 as well as stimulation of the stapes head (SH with a Bell prosthesis (N = 9, SFP stimulation with an Omega/Aerial prosthesis (N = 8 and reverse RW stimulation (N = 10 were performed in cadaveric human temporal bones (TBs. Codacs actuator output is expressed as equivalent sound pressure level (eq. SPL using RW and SFP displacement responses, measured by Laser Doppler velocimetry as reference. The axial actuator coupling force in stimulation of stapes and RW was adjusted to ~5 mN. The Bell prosthesis and Omega/Aerial prosthesis stimulation generated similar mean eq. SPLs (Bell: 127.5-141.8 eq. dB SPL; Omega/Aerial: 123.6-143.9 eq. dB SPL, being significantly more efficient than K-piston perilymph stimulation (108.6-131.6 eq. dB SPL and RW stimulation (108.3-128.2 eq. dB SPL. Our results demonstrate that SH, SFP and RW are adequate alternative stimulation sites for the Codacs actuator using coupling prostheses and an axial coupling force of ~5 mN. Based on the eq. SPLs, all investigated methods were adequate for in vivo hearing aid applications, provided that experimental conditions including constant coupling force will be implemented.

  18. Neural network fusion capabilities for efficient implementation of tracking algorithms

    Science.gov (United States)

    Sundareshan, Malur K.; Amoozegar, Farid

    1997-03-01

    The ability to efficiently fuse information of different forms to facilitate intelligent decision making is one of the major capabilities of trained multilayer neural networks that is now being recognized. While development of innovative adaptive control algorithms for nonlinear dynamical plants that attempt to exploit these capabilities seems to be more popular, a corresponding development of nonlinear estimation algorithms using these approaches, particularly for application in target surveillance and guidance operations, has not received similar attention. We describe the capabilities and functionality of neural network algorithms for data fusion and implementation of tracking filters. To discuss details and to serve as a vehicle for quantitative performance evaluations, the illustrative case of estimating the position and velocity of surveillance targets is considered. Efficient target- tracking algorithms that can utilize data from a host of sensing modalities and are capable of reliably tracking even uncooperative targets executing fast and complex maneuvers are of interest in a number of applications. The primary motivation for employing neural networks in these applications comes from the efficiency with which more features extracted from different sensor measurements can be utilized as inputs for estimating target maneuvers. A system architecture that efficiently integrates the fusion capabilities of a trained multilayer neural net with the tracking performance of a Kalman filter is described. The innovation lies in the way the fusion of multisensor data is accomplished to facilitate improved estimation without increasing the computational complexity of the dynamical state estimator itself.

  19. Transcranial Magnetic Stimulation and Connectivity Mapping: Tools for Studying the Neural Bases of Brain Disorders

    OpenAIRE

    Hampson, M.; Hoffman, R. E.

    2010-01-01

    There has been an increasing emphasis on characterizing pathophysiology underlying psychiatric and neurological disorders in terms of altered neural connectivity and network dynamics. Transcranial magnetic stimulation (TMS) provides a unique opportunity for investigating connectivity in the human brain. TMS allows researchers and clinicians to directly stimulate cortical regions accessible to electromagnetic coils positioned on the scalp. The induced activation can then propagate through...

  20. Algorithmic design of a noise-resistant and efficient closed-loop deep brain stimulation system: A computational approach.

    Directory of Open Access Journals (Sweden)

    Sofia D Karamintziou

    Full Text Available Advances in the field of closed-loop neuromodulation call for analysis and modeling approaches capable of confronting challenges related to the complex neuronal response to stimulation and the presence of strong internal and measurement noise in neural recordings. Here we elaborate on the algorithmic aspects of a noise-resistant closed-loop subthalamic nucleus deep brain stimulation system for advanced Parkinson's disease and treatment-refractory obsessive-compulsive disorder, ensuring remarkable performance in terms of both efficiency and selectivity of stimulation, as well as in terms of computational speed. First, we propose an efficient method drawn from dynamical systems theory, for the reliable assessment of significant nonlinear coupling between beta and high-frequency subthalamic neuronal activity, as a biomarker for feedback control. Further, we present a model-based strategy through which optimal parameters of stimulation for minimum energy desynchronizing control of neuronal activity are being identified. The strategy integrates stochastic modeling and derivative-free optimization of neural dynamics based on quadratic modeling. On the basis of numerical simulations, we demonstrate the potential of the presented modeling approach to identify, at a relatively low computational cost, stimulation settings potentially associated with a significantly higher degree of efficiency and selectivity compared with stimulation settings determined post-operatively. Our data reinforce the hypothesis that model-based control strategies are crucial for the design of novel stimulation protocols at the backstage of clinical applications.

  1. Algorithmic design of a noise-resistant and efficient closed-loop deep brain stimulation system: A computational approach.

    Science.gov (United States)

    Karamintziou, Sofia D; Custódio, Ana Luísa; Piallat, Brigitte; Polosan, Mircea; Chabardès, Stéphan; Stathis, Pantelis G; Tagaris, George A; Sakas, Damianos E; Polychronaki, Georgia E; Tsirogiannis, George L; David, Olivier; Nikita, Konstantina S

    2017-01-01

    Advances in the field of closed-loop neuromodulation call for analysis and modeling approaches capable of confronting challenges related to the complex neuronal response to stimulation and the presence of strong internal and measurement noise in neural recordings. Here we elaborate on the algorithmic aspects of a noise-resistant closed-loop subthalamic nucleus deep brain stimulation system for advanced Parkinson's disease and treatment-refractory obsessive-compulsive disorder, ensuring remarkable performance in terms of both efficiency and selectivity of stimulation, as well as in terms of computational speed. First, we propose an efficient method drawn from dynamical systems theory, for the reliable assessment of significant nonlinear coupling between beta and high-frequency subthalamic neuronal activity, as a biomarker for feedback control. Further, we present a model-based strategy through which optimal parameters of stimulation for minimum energy desynchronizing control of neuronal activity are being identified. The strategy integrates stochastic modeling and derivative-free optimization of neural dynamics based on quadratic modeling. On the basis of numerical simulations, we demonstrate the potential of the presented modeling approach to identify, at a relatively low computational cost, stimulation settings potentially associated with a significantly higher degree of efficiency and selectivity compared with stimulation settings determined post-operatively. Our data reinforce the hypothesis that model-based control strategies are crucial for the design of novel stimulation protocols at the backstage of clinical applications.

  2. Efficient Neural Network Modeling for Flight and Space Dynamics Simulation

    Directory of Open Access Journals (Sweden)

    Ayman Hamdy Kassem

    2011-01-01

    Full Text Available This paper represents an efficient technique for neural network modeling of flight and space dynamics simulation. The technique will free the neural network designer from guessing the size and structure for the required neural network model and will help to minimize the number of neurons. For linear flight/space dynamics systems, the technique can find the network weights and biases directly by solving a system of linear equations without the need for training. Nonlinear flight dynamic systems can be easily modeled by training its linearized models keeping the same network structure. The training is fast, as it uses the linear system knowledge to speed up the training process. The technique is tested on different flight/space dynamic models and showed promising results.

  3. Bayesian neural adjustment of inhibitory control predicts emergence of problem stimulant use.

    Science.gov (United States)

    Harlé, Katia M; Stewart, Jennifer L; Zhang, Shunan; Tapert, Susan F; Yu, Angela J; Paulus, Martin P

    2015-11-01

    Bayesian ideal observer models quantify individuals' context- and experience-dependent beliefs and expectations about their environment, which provides a powerful approach (i) to link basic behavioural mechanisms to neural processing; and (ii) to generate clinical predictors for patient populations. Here, we focus on (ii) and determine whether individual differences in the neural representation of the need to stop in an inhibitory task can predict the development of problem use (i.e. abuse or dependence) in individuals experimenting with stimulants. One hundred and fifty-seven non-dependent occasional stimulant users, aged 18-24, completed a stop-signal task while undergoing functional magnetic resonance imaging. These individuals were prospectively followed for 3 years and evaluated for stimulant use and abuse/dependence symptoms. At follow-up, 38 occasional stimulant users met criteria for a stimulant use disorder (problem stimulant users), while 50 had discontinued use (desisted stimulant users). We found that those individuals who showed greater neural responses associated with Bayesian prediction errors, i.e. the difference between actual and expected need to stop on a given trial, in right medial prefrontal cortex/anterior cingulate cortex, caudate, anterior insula, and thalamus were more likely to exhibit problem use 3 years later. Importantly, these computationally based neural predictors outperformed clinical measures and non-model based neural variables in predicting clinical status. In conclusion, young adults who show exaggerated brain processing underlying whether to 'stop' or to 'go' are more likely to develop stimulant abuse. Thus, Bayesian cognitive models provide both a computational explanation and potential predictive biomarkers of belief processing deficits in individuals at risk for stimulant addiction. © The Author (2015). Published by Oxford University Press on behalf of the Guarantors of Brain. All rights reserved. For Permissions, please

  4. An efficient automated parameter tuning framework for spiking neural networks.

    Science.gov (United States)

    Carlson, Kristofor D; Nageswaran, Jayram Moorkanikara; Dutt, Nikil; Krichmar, Jeffrey L

    2014-01-01

    As the desire for biologically realistic spiking neural networks (SNNs) increases, tuning the enormous number of open parameters in these models becomes a difficult challenge. SNNs have been used to successfully model complex neural circuits that explore various neural phenomena such as neural plasticity, vision systems, auditory systems, neural oscillations, and many other important topics of neural function. Additionally, SNNs are particularly well-adapted to run on neuromorphic hardware that will support biological brain-scale architectures. Although the inclusion of realistic plasticity equations, neural dynamics, and recurrent topologies has increased the descriptive power of SNNs, it has also made the task of tuning these biologically realistic SNNs difficult. To meet this challenge, we present an automated parameter tuning framework capable of tuning SNNs quickly and efficiently using evolutionary algorithms (EA) and inexpensive, readily accessible graphics processing units (GPUs). A sample SNN with 4104 neurons was tuned to give V1 simple cell-like tuning curve responses and produce self-organizing receptive fields (SORFs) when presented with a random sequence of counterphase sinusoidal grating stimuli. A performance analysis comparing the GPU-accelerated implementation to a single-threaded central processing unit (CPU) implementation was carried out and showed a speedup of 65× of the GPU implementation over the CPU implementation, or 0.35 h per generation for GPU vs. 23.5 h per generation for CPU. Additionally, the parameter value solutions found in the tuned SNN were studied and found to be stable and repeatable. The automated parameter tuning framework presented here will be of use to both the computational neuroscience and neuromorphic engineering communities, making the process of constructing and tuning large-scale SNNs much quicker and easier.

  5. Facilitating Access to Emotions: Neural Signature of EMDR Stimulation

    Science.gov (United States)

    Herkt, Deborah; Tumani, Visal; Grön, Georg; Kammer, Thomas; Hofmann, Arne; Abler, Birgit

    2014-01-01

    Background Eye Movement Desensitisation and Reprocessing (EMDR) is a method in psychotherapy effective in treating symptoms of posttraumatic stress disorder. The client attends to alternating bilateral visual, auditory or sensory stimulation while confronted with emotionally disturbing material. It is thought that the bilateral stimulation as a specific element of EMDR facilitates accessing and processing of negative material while presumably creating new associative links. We hypothesized that the putatively facilitated access should be reflected in increased activation of the amygdala upon bilateral EMDR stimulation even in healthy subjects. Methods We investigated 22 healthy female university students (mean 23.5 years) with fMRI. Subjects were scanned while confronted with blocks of disgusting and neutral picture stimuli. One third of the blocks was presented without any additional stimulation, one third with bilateral simultaneous auditory stimulation, and one third with bilateral alternating auditory stimulation as used in EMDR. Results Contrasting disgusting vs. neutral picture stimuli confirmed the expected robust effect of amygdala activation for all auditory stimulation conditions. The interaction analysis with the type of auditory stimulation revealed a specific increase in activation of the right amygdala for the bilateral alternating auditory stimulation. Activation of the left dorsolateral prefrontal cortex showed the opposite effect with decreased activation. Conclusions We demonstrate first time evidence for a putative neurobiological basis of the bilateral alternating stimulation as used in the EMDR method. The increase in limbic processing along with decreased frontal activation is in line with theoretical models of how bilateral alternating stimulation could help with therapeutic reintegration of information, and present findings may pave the way for future research on EMDR in the context of posttraumatic stress disorder. PMID:25165974

  6. COMMUNICATION Designing a somatosensory neural prosthesis: percepts evoked by different patterns of thalamic stimulation

    Science.gov (United States)

    Heming, Ethan; Sanden, Andrew; Kiss, Zelma H. T.

    2010-12-01

    Although major advances have been made in the development of motor prostheses, fine motor control requires intuitive somatosensory feedback. Here we explored whether a thalamic site for a somatosensory neural prosthetic could provide natural somatic sensation to humans. Different patterns of electrical stimulation (obtained from thalamic spike trains) were applied in patients undergoing deep brain stimulation surgery. Changes in pattern produced different sensations, while preserving somatotopic representation. While most percepts were reported as 'unnatural', some stimulations produced more 'natural' sensations than others. However, the additional patterns did not elicit more 'natural' percepts than high-frequency (333 Hz) electrical stimulation. These features suggest that despite some limitations, the thalamus may be a feasible site for a somatosensory neural prosthesis and different stimulation patterns may be useful in its development.

  7. Neural mechanisms underlying transcranial direct current stimulation in aphasia: A feasibility study.

    Directory of Open Access Journals (Sweden)

    Lena eUlm

    2015-10-01

    Full Text Available Little is known about the neural mechanisms by which transcranial direct current stimulation (tDCS impacts on language processing in post-stroke aphasia. This was addressed in a proof-of-principle study that explored the effects of tDCS application in aphasia during simultaneous functional magnetic resonance imaging (fMRI. We employed a single subject, cross-over, sham-tDCS controlled design and the stimulation was administered to an individualized perilesional stimulation site that was identified by a baseline fMRI scan and a picture naming task. Peak activity during the baseline scan was located in the spared left inferior frontal gyrus (IFG and this area was stimulated during a subsequent cross-over phase. tDCS was successfully administered to the target region and anodal- vs. sham-tDCS resulted in selectively increased activity at the stimulation site. Our results thus demonstrate that it is feasible to precisely target an individualized stimulation site in aphasia patients during simultaneous fMRI which allows assessing the neural mechanisms underlying tDCS application. The functional imaging results of this case report highlight one possible mechanism that may have contributed to beneficial behavioural stimulation effects in previous clinical tDCS trials in aphasia. In the future, this approach will allow identifying distinct patterns of stimulation effects on neural processing in larger cohorts of patients. This may ultimately yield information about the variability of tDCS-effects on brain functions in aphasia.

  8. 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.

  9. Using brain stimulation to disentangle neural correlates of conscious vision

    NARCIS (Netherlands)

    de Graaf, T.A.; Sack, A.T.

    2014-01-01

    Research into the neural correlates of consciousness (NCCs) has blossomed, due to the advent of new and increasingly sophisticated brain research tools. Neuroimaging has uncovered a variety of brain processes that relate to conscious perception, obtained in a range of experimental paradigms. But

  10. Contributions to muscle force and EMG by combined neural excitation and electrical stimulation

    Science.gov (United States)

    Crago, Patrick E.; Makowski, Nathaniel S.; Cole, Natalie M.

    2014-10-01

    Objective. Stimulation of muscle for research or clinical interventions is often superimposed on ongoing physiological activity without a quantitative understanding of the impact of the stimulation on the net muscle activity and the physiological response. Experimental studies show that total force during stimulation is less than the sum of the isolated voluntary and stimulated forces, but the occlusion mechanism is not understood. Approach. We develop a model of efferent motor activity elicited by superimposing stimulation during a physiologically activated contraction. The model combines action potential interactions due to collision block, source resetting, and refractory periods with previously published models of physiological motor unit recruitment, rate modulation, force production, and EMG generation in human first dorsal interosseous muscle to investigate the mechanisms and effectiveness of stimulation on the net muscle force and EMG. Main results. Stimulation during a physiological contraction demonstrates partial occlusion of force and the neural component of the EMG, due to action potential interactions in motor units activated by both sources. Depending on neural and stimulation firing rates as well as on force-frequency properties, individual motor unit forces can be greater, smaller, or unchanged by the stimulation. In contrast, voluntary motor unit EMG potentials in simultaneously stimulated motor units show progressive occlusion with increasing stimulus rate. The simulations predict that occlusion would be decreased by a reverse stimulation recruitment order. Significance. The results are consistent with and provide a mechanistic interpretation of previously published experimental evidence of force occlusion. The models also predict two effects that have not been reported previously—voluntary EMG occlusion and the advantages of a proximal stimulation site. This study provides a basis for the rational design of both future experiments and clinical

  11. Mathematical phenomenology of neural stimulation by periodic fields.

    Science.gov (United States)

    Balduzzo, M; Milone, F Ferro; Minelli, T A; Pittaro-Cadore, I; Turicchia, L

    2003-04-01

    Neuron synchronization has been hypothesized as the basic mechanism leading neurological phenomena like low electroencephalographic rhythm dimension or high coherence. Cognitive processes, such as associative memory, can also be explained in terms of neuron synchronization. Inspired by the analysis of an experiment on cortex periodic photostimulation, in resonance conditions, a simple network of integrate and fire (i and f) neurons, has been used to simulate cognitive perturbations by oscillatory and pulsate stimulation of the central nervous system (CNS). In view of realistic simulations of transcranial magnetic stimulation (TMS) phenomena, a discrete extension of the FitzHug-Nagumo nervous fiber model, endowed with regenerative nodes, has been developed too.

  12. Reactivating Neural Circuits with Clinically Accessible Stimulation to Restore Hand Function in Persons with Tetraplegia

    Science.gov (United States)

    2017-09-01

    AWARD NUMBER: W81XWH-16-1-0395 TITLE: Reactivating Neural Circuits with Clinically Accessible Stimulation to Restore Hand Function in...estimated to average 1 hour per response, including the time for reviewing instructions, searching existing data sources, gathering and maintaining the data...Clinically Accessible Stimulation to Restore Hand Function in Persons with Tetraplegia 5b. GRANT NUMBER 5c. PROGRAM ELEMENT NUMBER 6. AUTHOR(S

  13. Efficient universal computing architectures for decoding neural activity.

    Directory of Open Access Journals (Sweden)

    Benjamin I Rapoport

    Full Text Available The ability to decode neural activity into meaningful control signals for prosthetic devices is critical to the development of clinically useful brain- machine interfaces (BMIs. Such systems require input from tens to hundreds of brain-implanted recording electrodes in order to deliver robust and accurate performance; in serving that primary function they should also minimize power dissipation in order to avoid damaging neural tissue; and they should transmit data wirelessly in order to minimize the risk of infection associated with chronic, transcutaneous implants. Electronic architectures for brain- machine interfaces must therefore minimize size and power consumption, while maximizing the ability to compress data to be transmitted over limited-bandwidth wireless channels. Here we present a system of extremely low computational complexity, designed for real-time decoding of neural signals, and suited for highly scalable implantable systems. Our programmable architecture is an explicit implementation of a universal computing machine emulating the dynamics of a network of integrate-and-fire neurons; it requires no arithmetic operations except for counting, and decodes neural signals using only computationally inexpensive logic operations. The simplicity of this architecture does not compromise its ability to compress raw neural data by factors greater than [Formula: see text]. We describe a set of decoding algorithms based on this computational architecture, one designed to operate within an implanted system, minimizing its power consumption and data transmission bandwidth; and a complementary set of algorithms for learning, programming the decoder, and postprocessing the decoded output, designed to operate in an external, nonimplanted unit. The implementation of the implantable portion is estimated to require fewer than 5000 operations per second. A proof-of-concept, 32-channel field-programmable gate array (FPGA implementation of this portion

  14. Simulation of activation and propagation delay during tripolar neural stimulation

    NARCIS (Netherlands)

    Goodall, E.V.; Goodall, Eleanor V.; Kosterman, L. Martin; Struijk, Johannes J.; Struijk, J.J.; Holsheimer, J.

    1993-01-01

    Computer simulations were perfonned to investigate the influence of stimulus amplitude on cathodal activation delay, propagation delay and blocking during stimulation with a bipolar cuff electrode. Activation and propagation delays were combined in a total delay term which was minimized between the

  15. Attractor neural networks with resource-efficient synaptic connectivity

    Science.gov (United States)

    Pehlevan, Cengiz; Sengupta, Anirvan

    Memories are thought to be stored in the attractor states of recurrent neural networks. Here we explore how resource constraints interplay with memory storage function to shape synaptic connectivity of attractor networks. We propose that given a set of memories, in the form of population activity patterns, the neural circuit choses a synaptic connectivity configuration that minimizes a resource usage cost. We argue that the total synaptic weight (l1-norm) in the network measures the resource cost because synaptic weight is correlated with synaptic volume, which is a limited resource, and is proportional to neurotransmitter release and post-synaptic current, both of which cost energy. Using numerical simulations and replica theory, we characterize optimal connectivity profiles in resource-efficient attractor networks. Our theory explains several experimental observations on cortical connectivity profiles, 1) connectivity is sparse, because synapses are costly, 2) bidirectional connections are overrepresented and 3) are stronger, because attractor states need strong recurrence.

  16. Stochastic Nonlinear Evolutional Model of the Large-Scaled Neuronal Population and Dynamic Neural Coding Subject to Stimulation

    International Nuclear Information System (INIS)

    Wang Rubin; Yu Wei

    2005-01-01

    In this paper, we investigate how the population of neuronal oscillators deals with information and the dynamic evolution of neural coding when the external stimulation acts on it. Numerically computing method is used to describe the evolution process of neural coding in three-dimensioned space. The numerical result proves that only the suitable stimulation can change the coupling structure and plasticity of neurons

  17. A low-cost multichannel wireless neural stimulation system for freely roaming animals

    Science.gov (United States)

    Alam, Monzurul; Chen, Xi; Fernandez, Eduardo

    2013-12-01

    Objectives. Electrical stimulation of nerve tissue and recording of neural activity are the basis of many therapies and neural prostheses. Conventional stimulation systems have a number of practical limitations, especially in experiments involving freely roaming subjects. Our main objective was to develop a modular, versatile and inexpensive multichannel wireless system able to overcome some of these constraints. Approach. We have designed and implemented a new multichannel wireless neural stimulator based on commercial components. The system is small (2 cm × 4 cm × 0.5 cm) and light in weight (9 g) which allows it to be easily carried in a small backpack. To test and validate the performance and reliability of the whole system we conducted several bench tests and in vivo experiments. Main results. The performance and accuracy of the stimulator were comparable to commercial threaded systems. Stimulation sequences can be constructed on-the-fly with 251 selectable current levels (from 0 to 250 µA) with 1 µA step resolution. The pulse widths and intervals can be as long as 65 ms in 2 µs time resolution. The system covers approximately 10 m of transmission range in a regular laboratory environment and 100 m in free space (line of sight). Furthermore it provides great flexibility for experiments since it allows full control of the stimulator and the stimulation parameters in real time. When there is no stimulation, the device automatically goes into low-power sleep mode to preserve battery power. Significance. We introduce the design of a powerful multichannel wireless stimulator assembled from commercial components. Key features of the system are their reliability, robustness and small size. The system has a flexible design that can be modified straightforwardly to tailor it to any specific experimental need. Furthermore it can be effortlessly adapted for use with any kind of multielectrode arrays.

  18. Differential theory of learning for efficient neural network pattern recognition

    Science.gov (United States)

    Hampshire, John B., II; Vijaya Kumar, Bhagavatula

    1993-09-01

    We describe a new theory of differential learning by which a broad family of pattern classifiers (including many well-known neural network paradigms) can learn stochastic concepts efficiently. We describe the relationship between a classifier's ability to generate well to unseen test examples and the efficiency of the strategy by which it learns. We list a series of proofs that differential learning is efficient in its information and computational resource requirements, whereas traditional probabilistic learning strategies are not. The proofs are illustrated by a simple example that lends itself to closed-form analysis. We conclude with an optical character recognition task for which three different types of differentially generated classifiers generalize significantly better than their probabilistically generated counterparts.

  19. High Frequency Deep Brain Stimulation and Neural Rhythms in Parkinson's Disease.

    Science.gov (United States)

    Blumenfeld, Zack; Brontë-Stewart, Helen

    2015-12-01

    High frequency (HF) deep brain stimulation (DBS) is an established therapy for the treatment of Parkinson's disease (PD). It effectively treats the cardinal motor signs of PD, including tremor, bradykinesia, and rigidity. The most common neural target is the subthalamic nucleus, located within the basal ganglia, the region most acutely affected by PD pathology. Using chronically-implanted DBS electrodes, researchers have been able to record underlying neural rhythms from several nodes in the PD network as well as perturb it using DBS to measure the ensuing neural and behavioral effects, both acutely and over time. In this review, we provide an overview of the PD neural network, focusing on the pathophysiological signals that have been recorded from PD patients as well as the mechanisms underlying the therapeutic benefits of HF DBS. We then discuss evidence for the relationship between specific neural oscillations and symptoms of PD, including the aberrant relationships potentially underlying functional connectivity in PD as well as the use of different frequencies of stimulation to more specifically target certain symptoms. Finally, we briefly describe several current areas of investigation and how the ability to record neural data in ecologically-valid settings may allow researchers to explore the relationship between brain and behavior in an unprecedented manner, culminating in the future automation of neurostimulation therapy for the treatment of a variety of neuropsychiatric diseases.

  20. Thermodynamic efficiency of learning a rule in neural networks

    Science.gov (United States)

    Goldt, Sebastian; Seifert, Udo

    2017-11-01

    Biological systems have to build models from their sensory input data that allow them to efficiently process previously unseen inputs. Here, we study a neural network learning a binary classification rule for these inputs from examples provided by a teacher. We analyse the ability of the network to apply the rule to new inputs, that is to generalise from past experience. Using stochastic thermodynamics, we show that the thermodynamic costs of the learning process provide an upper bound on the amount of information that the network is able to learn from its teacher for both batch and online learning. This allows us to introduce a thermodynamic efficiency of learning. We analytically compute the dynamics and the efficiency of a noisy neural network performing online learning in the thermodynamic limit. In particular, we analyse three popular learning algorithms, namely Hebbian, Perceptron and AdaTron learning. Our work extends the methods of stochastic thermodynamics to a new type of learning problem and might form a suitable basis for investigating the thermodynamics of decision-making.

  1. An Efficient Supervised Training Algorithm for Multilayer Spiking Neural Networks.

    Science.gov (United States)

    Xie, Xiurui; Qu, Hong; Liu, Guisong; Zhang, Malu; Kurths, Jürgen

    2016-01-01

    The spiking neural networks (SNNs) are the third generation of neural networks and perform remarkably well in cognitive tasks such as pattern recognition. The spike emitting and information processing mechanisms found in biological cognitive systems motivate the application of the hierarchical structure and temporal encoding mechanism in spiking neural networks, which have exhibited strong computational capability. However, the hierarchical structure and temporal encoding approach require neurons to process information serially in space and time respectively, which reduce the training efficiency significantly. For training the hierarchical SNNs, most existing methods are based on the traditional back-propagation algorithm, inheriting its drawbacks of the gradient diffusion and the sensitivity on parameters. To keep the powerful computation capability of the hierarchical structure and temporal encoding mechanism, but to overcome the low efficiency of the existing algorithms, a new training algorithm, the Normalized Spiking Error Back Propagation (NSEBP) is proposed in this paper. In the feedforward calculation, the output spike times are calculated by solving the quadratic function in the spike response model instead of detecting postsynaptic voltage states at all time points in traditional algorithms. Besides, in the feedback weight modification, the computational error is propagated to previous layers by the presynaptic spike jitter instead of the gradient decent rule, which realizes the layer-wised training. Furthermore, our algorithm investigates the mathematical relation between the weight variation and voltage error change, which makes the normalization in the weight modification applicable. Adopting these strategies, our algorithm outperforms the traditional SNN multi-layer algorithms in terms of learning efficiency and parameter sensitivity, that are also demonstrated by the comprehensive experimental results in this paper.

  2. On supertaskers and the neural basis of efficient multitasking.

    Science.gov (United States)

    Medeiros-Ward, Nathan; Watson, Jason M; Strayer, David L

    2015-06-01

    The present study used brain imaging to determine the neural basis of individual differences in multitasking, the ability to successfully perform at least two attention-demanding tasks at once. Multitasking is mentally taxing and, therefore, should recruit the prefrontal cortex to maintain task goals when coordinating attentional control and managing the cognitive load. To investigate this possibility, we used functional neuroimaging to assess neural activity in both extraordinary multitaskers (Supertaskers) and control subjects who were matched on working memory capacity. Participants performed a challenging dual N-back task in which auditory and visual stimuli were presented simultaneously, requiring independent and continuous maintenance, updating, and verification of the contents of verbal and spatial working memory. With the task requirements and considerable cognitive load that accompanied increasing N-back, relative to the controls, the multitasking of Supertaskers was characterized by more efficient recruitment of anterior cingulate and posterior frontopolar prefrontal cortices. Results are interpreted using neuropsychological and evolutionary perspectives on individual differences in multitasking ability and the neural correlates of attentional control.

  3. How to build VLSI-efficient neural chips

    Energy Technology Data Exchange (ETDEWEB)

    Beiu, V.

    1998-02-01

    This paper presents several upper and lower bounds for the number-of-bits required for solving a classification problem, as well as ways in which these bounds can be used to efficiently build neural network chips. The focus will be on complexity aspects pertaining to neural networks: (1) size complexity and depth (size) tradeoffs, and (2) precision of weights and thresholds as well as limited interconnectivity. They show difficult problems-exponential growth in either space (precision and size) and/or time (learning and depth)-when using neural networks for solving general classes of problems (particular cases may enjoy better performances). The bounds for the number-of-bits required for solving a classification problem represent the first step of a general class of constructive algorithms, by showing how the quantization of the input space could be done in O (m{sup 2}n) steps. Here m is the number of examples, while n is the number of dimensions. The second step of the algorithm finds its roots in the implementation of a class of Boolean functions using threshold gates. It is substantiated by mathematical proofs for the size O (mn/{Delta}), and the depth O [log(mn)/log{Delta}] of the resulting network (here {Delta} is the maximum fan in). Using the fan in as a parameter, a full class of solutions can be designed. The third step of the algorithm represents a reduction of the size and an increase of its generalization capabilities. Extensions by using analogue COMPARISONs, allows for real inputs, and increase the generalization capabilities at the expense of longer training times. Finally, several solutions which can lower the size of the resulting neural network are detailed. The interesting aspect is that they are obtained for limited, or even constant, fan-ins. In support of these claims many simulations have been performed and are called upon.

  4. Oscillatory neural representations in the sensory thalamus predict neuropathic pain relief by deep brain stimulation.

    Science.gov (United States)

    Huang, Yongzhi; Green, Alexander L; Hyam, Jonathan; Fitzgerald, James; Aziz, Tipu Z; Wang, Shouyan

    2018-01-01

    Understanding the function of sensory thalamic neural activity is essential for developing and improving interventions for neuropathic pain. However, there is a lack of investigation of the relationship between sensory thalamic oscillations and pain relief in patients with neuropathic pain. This study aims to identify the oscillatory neural characteristics correlated with pain relief induced by deep brain stimulation (DBS), and develop a quantitative model to predict pain relief by integrating characteristic measures of the neural oscillations. Measures of sensory thalamic local field potentials (LFPs) in thirteen patients with neuropathic pain were screened in three dimensional feature space according to the rhythm, balancing, and coupling neural behaviours, and correlated with pain relief. An integrated approach based on principal component analysis (PCA) and multiple regression analysis is proposed to integrate the multiple measures and provide a predictive model. This study reveals distinct thalamic rhythms of theta, alpha, high beta and high gamma oscillations correlating with pain relief. The balancing and coupling measures between these neural oscillations were also significantly correlated with pain relief. The study enriches the series research on the function of thalamic neural oscillations in neuropathic pain and relief, and provides a quantitative approach for predicting pain relief by DBS using thalamic neural oscillations. Copyright © 2017 Elsevier Inc. All rights reserved.

  5. Vagal stimulation targets select populations of intrinsic cardiac neurons to control neurally induced atrial fibrillation.

    Science.gov (United States)

    Salavatian, Siamak; Beaumont, Eric; Longpré, Jean-Philippe; Armour, J Andrew; Vinet, Alain; Jacquemet, Vincent; Shivkumar, Kalyanam; Ardell, Jeffrey L

    2016-11-01

    Mediastinal nerve stimulation (MNS) reproducibly evokes atrial fibrillation (AF) by excessive and heterogeneous activation of intrinsic cardiac (IC) neurons. This study evaluated whether preemptive vagus nerve stimulation (VNS) impacts MNS-induced evoked changes in IC neural network activity to thereby alter susceptibility to AF. IC neuronal activity in the right atrial ganglionated plexus was directly recorded in anesthetized canines (n = 8) using a linear microelectrode array concomitant with right atrial electrical activity in response to: 1) epicardial touch or great vessel occlusion vs. 2) stellate or vagal stimulation. From these stressors, post hoc analysis (based on the Skellam distribution) defined IC neurons so recorded as afferent, efferent, or convergent (afferent and efferent inputs) local circuit neurons (LCN). The capacity of right-sided MNS to modify IC activity in the induction of AF was determined before and after preemptive right (RCV)- vs. left (LCV)-sided VNS (15 Hz, 500 μs; 1.2× bradycardia threshold). Neuronal (n = 89) activity at baseline (0.11 ± 0.29 Hz) increased during MNS-induced AF (0.51 ± 1.30 Hz; P neuronal synchrony increased during neurally induced AF, a local neural network response mitigated by preemptive VNS. These antiarrhythmic effects persisted post-VNS for, on average, 26 min. In conclusion, VNS preferentially targets convergent LCNs and their interactive coherence to mitigate the potential for neurally induced AF. The antiarrhythmic properties imposed by VNS exhibit memory. Copyright © 2016 the American Physiological Society.

  6. 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.

  7. Nanowire electrodes for high-density stimulation and measurement of neural circuits

    Directory of Open Access Journals (Sweden)

    Jacob T. Robinson

    2013-03-01

    Full Text Available Brain-machine interfaces (BMIs that can precisely monitor and control neural activity will likely require new hardware with improved resolution and specificity. New nanofabricated electrodes with feature sizes and densities comparable to neural circuits may lead to such improvements. In this perspective, we review the recent development of vertical nanowire (NW electrodes that could provide highly parallel single-cell recording and stimulation for future BMIs. We compare the advantages of these devices and discuss some of the technical challenges that must be overcome for this technology to become a platform for next-generation closed-loop BMIs.

  8. 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

  9. The development of neural stimulators: a review of preclinical safety and efficacy studies.

    Science.gov (United States)

    Shepherd, Robert K; Villalobos, Joel; Burns, Owen; Nayagam, David

    2018-05-14

    Given the rapid expansion of the field of neural stimulation and the rigorous regulatory approval requirements required before these devices can be applied clinically, it is important that there is clarity around conducting preclinical safety and efficacy studies required for the development of this technology. The present review examines basic design principles associated with the development of a safe neural stimulator and describes the suite of preclinical safety studies that need to be considered when taking a device to clinical trial. Neural stimulators are active implantable devices that provide therapeutic intervention, sensory feedback or improved motor control via electrical stimulation of neural or neuro-muscular tissue in response to trauma or disease. Because of their complexity, regulatory bodies classify these devices in the highest risk category (Class III), and they are therefore required to go through a rigorous regulatory approval process before progressing to market. The successful development of these devices is achieved through close collaboration across disciplines including engineers, scientists and a surgical/clinical team, and the adherence to clear design principles. Preclinical studies form one of several key components in the development pathway from concept to product release of neural stimulators. Importantly, these studies provide iterative feedback in order to optimise the final design of the device. Key components of any preclinical evaluation include: in vitro studies that are focussed on device reliability and include accelerated testing under highly controlled environments; in vivo studies using animal models of the disease or injury in order to assess safety and, given an appropriate animal model, the efficacy of the technology under both passive and electrically active conditions; and human cadaver and ex vivo studies designed to ensure the device's form factor conforms to human anatomy, to optimise the surgical approach and to

  10. Design and in vivo evaluation of more efficient and selective deep brain stimulation electrodes

    Science.gov (United States)

    Howell, Bryan; Huynh, Brian; Grill, Warren M.

    2015-08-01

    Objective. Deep brain stimulation (DBS) is an effective treatment for movement disorders and a promising therapy for treating epilepsy and psychiatric disorders. Despite its clinical success, the efficiency and selectivity of DBS can be improved. Our objective was to design electrode geometries that increased the efficiency and selectivity of DBS. Approach. We coupled computational models of electrodes in brain tissue with cable models of axons of passage (AOPs), terminating axons (TAs), and local neurons (LNs); we used engineering optimization to design electrodes for stimulating these neural elements; and the model predictions were tested in vivo. Main results. Compared with the standard electrode used in the Medtronic Model 3387 and 3389 arrays, model-optimized electrodes consumed 45-84% less power. Similar gains in selectivity were evident with the optimized electrodes: 50% of parallel AOPs could be activated while reducing activation of perpendicular AOPs from 44 to 48% with the standard electrode to 0-14% with bipolar designs; 50% of perpendicular AOPs could be activated while reducing activation of parallel AOPs from 53 to 55% with the standard electrode to 1-5% with an array of cathodes; and, 50% of TAs could be activated while reducing activation of AOPs from 43 to 100% with the standard electrode to 2-15% with a distal anode. In vivo, both the geometry and polarity of the electrode had a profound impact on the efficiency and selectivity of stimulation. Significance. Model-based design is a powerful tool that can be used to improve the efficiency and selectivity of DBS electrodes.

  11. Prolonged fasting impairs neural reactivity to visual stimulation.

    Science.gov (United States)

    Kohn, N; Wassenberg, A; Toygar, T; Kellermann, T; Weidenfeld, C; Berthold-Losleben, M; Chechko, N; Orfanos, S; Vocke, S; Laoutidis, Z G; Schneider, F; Karges, W; Habel, U

    2016-01-01

    Previous literature has shown that hypoglycemia influences the intensity of the BOLD signal. A similar but smaller effect may also be elicited by low normal blood glucose levels in healthy individuals. This may not only confound the BOLD signal measured in fMRI, but also more generally interact with cognitive processing, and thus indirectly influence fMRI results. Here we show in a placebo-controlled, crossover, double-blind study on 40 healthy subjects, that overnight fasting and low normal levels of glucose contrasted to an activated, elevated glucose condition have an impact on brain activation during basal visual stimulation. Additionally, functional connectivity of the visual cortex shows a strengthened association with higher-order attention-related brain areas in an elevated blood glucose condition compared to the fasting condition. In a fasting state visual brain areas show stronger coupling to the inferior temporal gyrus. Results demonstrate that prolonged overnight fasting leads to a diminished BOLD signal in higher-order occipital processing areas when compared to an elevated blood glucose condition. Additionally, functional connectivity patterns underscore the modulatory influence of fasting on visual brain networks. Patterns of brain activation and functional connectivity associated with a broad range of attentional processes are affected by maturation and aging and associated with psychiatric disease and intoxication. Thus, we conclude that prolonged fasting may decrease fMRI design sensitivity in any task involving attentional processes when fasting status or blood glucose is not controlled.

  12. Visible Light Neural Stimulation on graphitic-Carbon Nitride/Graphene Photocatalytic Fibers

    DEFF Research Database (Denmark)

    Zhang, Zhongyang; Xu, Ruodan; Wang, Zegao

    2017-01-01

    conversion, was for the first time investigated. Specifically, g-C3N4 was combined with graphene oxide (GO) in a 3D manner on the surfaces of electrospun polycaprolactone/gelatin (PG) fibers and functioned as a biocompatible interface for visible-light stimulating neuronal differentiation. The enhanced......Light stimulation allows remote and spatiotemporally accurate operation that has been applied as effective, non-invasive means of therapeutic interventions. Here, visible light neural stimulation of graphitic carbon nitride (g-C3N4), an emerging photocatalyst with visible-light optoelectronic...... was confirmed by the Lactate Dehydrogenase (LDH) assay, live dead staining and colorimetric cell viability assay CCK-8. Under a bidaily, monochromatic light stimulation at a wavelength of 450 nm at 10mW/cm2, a 18.5-fold increase of neurite outgrowth of PC12 was found on g-C3N4 coated fibers; while AA reduced GO...

  13. Selectively stimulating neural populations in the subthalamic region using a novel deep brain stimulation lead design

    NARCIS (Netherlands)

    van Dijk, Kees Joab; Verhagen, R.; Bour, L.J.; Heida, Tjitske

    2013-01-01

    Deep brain stimulation (DBS) of the Subthalamic Nucleus (STN) is widely used in advanced stages of Parkinson's disease(PD) and has proven to be an effective treatment of the various motor symptoms. The therapy involves implanting a lead consisting of multiple electrodes in the STN through which

  14. Neuromechanism study of insect-machine interface: flight control by neural electrical stimulation.

    Directory of Open Access Journals (Sweden)

    Huixia Zhao

    Full Text Available The insect-machine interface (IMI is a novel approach developed for man-made air vehicles, which directly controls insect flight by either neuromuscular or neural stimulation. In our previous study of IMI, we induced flight initiation and cessation reproducibly in restrained honeybees (Apis mellifera L. via electrical stimulation of the bilateral optic lobes. To explore the neuromechanism underlying IMI, we applied electrical stimulation to seven subregions of the honeybee brain with the aid of a new method for localizing brain regions. Results showed that the success rate for initiating honeybee flight decreased in the order: α-lobe (or β-lobe, ellipsoid body, lobula, medulla and antennal lobe. Based on a comparison with other neurobiological studies in honeybees, we propose that there is a cluster of descending neurons in the honeybee brain that transmits neural excitation from stimulated brain areas to the thoracic ganglia, leading to flight behavior. This neural circuit may involve the higher-order integration center, the primary visual processing center and the suboesophageal ganglion, which is also associated with a possible learning and memory pathway. By pharmacologically manipulating the electrically stimulated honeybee brain, we have shown that octopamine, rather than dopamine, serotonin and acetylcholine, plays a part in the circuit underlying electrically elicited honeybee flight. Our study presents a new brain stimulation protocol for the honeybee-machine interface and has solved one of the questions with regard to understanding which functional divisions of the insect brain participate in flight control. It will support further studies to uncover the involved neurons inside specific brain areas and to test the hypothesized involvement of a visual learning and memory pathway in IMI flight control.

  15. Attenuated Neural Processing of Risk in Young Adults at Risk for Stimulant Dependence.

    Directory of Open Access Journals (Sweden)

    Martina Reske

    Full Text Available Approximately 10% of young adults report non-medical use of stimulants (cocaine, amphetamine, methylphenidate, which puts them at risk for the development of dependence. This fMRI study investigates whether subjects at early stages of stimulant use show altered decision making processing.158 occasional stimulants users (OSU and 50 comparison subjects (CS performed a "risky gains" decision making task during which they could select safe options (cash in 20 cents or gamble them for double or nothing in two consecutive gambles (win or lose 40 or 80 cents, "risky decisions". The primary analysis focused on risky versus safe decisions. Three secondary analyses were conducted: First, a robust regression examined the effect of lifetime exposure to stimulants and marijuana; second, subgroups of OSU with >1000 (n = 42, or <50 lifetime marijuana uses (n = 32, were compared to CS with <50 lifetime uses (n = 46 to examine potential marijuana effects; third, brain activation associated with behavioral adjustment following monetary losses was probed.There were no behavioral differences between groups. OSU showed attenuated activation across risky and safe decisions in prefrontal cortex, insula, and dorsal striatum, exhibited lower anterior cingulate cortex (ACC and dorsal striatum activation for risky decisions and greater inferior frontal gyrus activation for safe decisions. Those OSU with relatively more stimulant use showed greater dorsal ACC and posterior insula attenuation. In comparison, greater lifetime marijuana use was associated with less neural differentiation between risky and safe decisions. OSU who chose more safe responses after losses exhibited similarities with CS relative to those preferring risky options.Individuals at risk for the development of stimulant use disorders presented less differentiated neural processing of risky and safe options. Specifically, OSU show attenuated brain response in regions critical for performance monitoring

  16. Neuromechanism study of insect-machine interface: flight control by neural electrical stimulation.

    Science.gov (United States)

    Zhao, Huixia; Zheng, Nenggan; Ribi, Willi A; Zheng, Huoqing; Xue, Lei; Gong, Fan; Zheng, Xiaoxiang; Hu, Fuliang

    2014-01-01

    The insect-machine interface (IMI) is a novel approach developed for man-made air vehicles, which directly controls insect flight by either neuromuscular or neural stimulation. In our previous study of IMI, we induced flight initiation and cessation reproducibly in restrained honeybees (Apis mellifera L.) via electrical stimulation of the bilateral optic lobes. To explore the neuromechanism underlying IMI, we applied electrical stimulation to seven subregions of the honeybee brain with the aid of a new method for localizing brain regions. Results showed that the success rate for initiating honeybee flight decreased in the order: α-lobe (or β-lobe), ellipsoid body, lobula, medulla and antennal lobe. Based on a comparison with other neurobiological studies in honeybees, we propose that there is a cluster of descending neurons in the honeybee brain that transmits neural excitation from stimulated brain areas to the thoracic ganglia, leading to flight behavior. This neural circuit may involve the higher-order integration center, the primary visual processing center and the suboesophageal ganglion, which is also associated with a possible learning and memory pathway. By pharmacologically manipulating the electrically stimulated honeybee brain, we have shown that octopamine, rather than dopamine, serotonin and acetylcholine, plays a part in the circuit underlying electrically elicited honeybee flight. Our study presents a new brain stimulation protocol for the honeybee-machine interface and has solved one of the questions with regard to understanding which functional divisions of the insect brain participate in flight control. It will support further studies to uncover the involved neurons inside specific brain areas and to test the hypothesized involvement of a visual learning and memory pathway in IMI flight control.

  17. Neuromechanism Study of Insect–Machine Interface: Flight Control by Neural Electrical Stimulation

    Science.gov (United States)

    Zhao, Huixia; Zheng, Nenggan; Ribi, Willi A.; Zheng, Huoqing; Xue, Lei; Gong, Fan; Zheng, Xiaoxiang; Hu, Fuliang

    2014-01-01

    The insect–machine interface (IMI) is a novel approach developed for man-made air vehicles, which directly controls insect flight by either neuromuscular or neural stimulation. In our previous study of IMI, we induced flight initiation and cessation reproducibly in restrained honeybees (Apis mellifera L.) via electrical stimulation of the bilateral optic lobes. To explore the neuromechanism underlying IMI, we applied electrical stimulation to seven subregions of the honeybee brain with the aid of a new method for localizing brain regions. Results showed that the success rate for initiating honeybee flight decreased in the order: α-lobe (or β-lobe), ellipsoid body, lobula, medulla and antennal lobe. Based on a comparison with other neurobiological studies in honeybees, we propose that there is a cluster of descending neurons in the honeybee brain that transmits neural excitation from stimulated brain areas to the thoracic ganglia, leading to flight behavior. This neural circuit may involve the higher-order integration center, the primary visual processing center and the suboesophageal ganglion, which is also associated with a possible learning and memory pathway. By pharmacologically manipulating the electrically stimulated honeybee brain, we have shown that octopamine, rather than dopamine, serotonin and acetylcholine, plays a part in the circuit underlying electrically elicited honeybee flight. Our study presents a new brain stimulation protocol for the honeybee–machine interface and has solved one of the questions with regard to understanding which functional divisions of the insect brain participate in flight control. It will support further studies to uncover the involved neurons inside specific brain areas and to test the hypothesized involvement of a visual learning and memory pathway in IMI flight control. PMID:25409523

  18. Evoked EMG-based torque prediction under muscle fatigue in implanted neural stimulation

    Science.gov (United States)

    Hayashibe, Mitsuhiro; Zhang, Qin; Guiraud, David; Fattal, Charles

    2011-10-01

    In patients with complete spinal cord injury, fatigue occurs rapidly and there is no proprioceptive feedback regarding the current muscle condition. Therefore, it is essential to monitor the muscle state and assess the expected muscle response to improve the current FES system toward adaptive force/torque control in the presence of muscle fatigue. Our team implanted neural and epimysial electrodes in a complete paraplegic patient in 1999. We carried out a case study, in the specific case of implanted stimulation, in order to verify the corresponding torque prediction based on stimulus evoked EMG (eEMG) when muscle fatigue is occurring during electrical stimulation. Indeed, in implanted stimulation, the relationship between stimulation parameters and output torques is more stable than external stimulation in which the electrode location strongly affects the quality of the recruitment. Thus, the assumption that changes in the stimulation-torque relationship would be mainly due to muscle fatigue can be made reasonably. The eEMG was proved to be correlated to the generated torque during the continuous stimulation while the frequency of eEMG also decreased during fatigue. The median frequency showed a similar variation trend to the mean absolute value of eEMG. Torque prediction during fatigue-inducing tests was performed based on eEMG in model cross-validation where the model was identified using recruitment test data. The torque prediction, apart from the potentiation period, showed acceptable tracking performances that would enable us to perform adaptive closed-loop control through implanted neural stimulation in the future.

  19. Can Intrinsic Fluctuations Increase Efficiency in Neural Information Processing?

    Science.gov (United States)

    Liljenström, Hans

    2003-05-01

    All natural processes are accompanied by fluctuations, characterized as noise or chaos. Biological systems, which have evolved during billions of years, are likely to have adapted, not only to cope with such fluctuations, but also to make use of them. We investigate how the complex dynamics of the brain, including oscillations, chaos and noise, can affect the efficiency of neural information processing. In particular, we consider the amplification and functional role of internal fluctuations. Using computer simulations of a neural network model of the olfactory cortex and hippocampus, we demonstrate how microscopic fluctuations can result in global effects at the network level. We show that the rate of information processing in associative memory tasks can be maximized for optimal noise levels, analogous to stochastic resonance phenomena. Noise can also induce transitions between different dynamical states, which could be of significance for learning and memory. A chaotic-like behavior, induced by noise or by an increase in neuronal excitability, can enhance system performance if it is transient and converges to a limit cycle memory state. We speculate whether this dynamical behavior perhaps could be related to (creative) thinking.

  20. Lifelong bilingualism maintains neural efficiency for cognitive control in aging.

    Science.gov (United States)

    Gold, Brian T; Kim, Chobok; Johnson, Nathan F; Kryscio, Richard J; Smith, Charles D

    2013-01-09

    Recent behavioral data have shown that lifelong bilingualism can maintain youthful cognitive control abilities in aging. Here, we provide the first direct evidence of a neural basis for the bilingual cognitive control boost in aging. Two experiments were conducted, using a perceptual task-switching paradigm, including a total of 110 participants. In Experiment 1, older adult bilinguals showed better perceptual switching performance than their monolingual peers. In Experiment 2, younger and older adult monolinguals and bilinguals completed the same perceptual task-switching experiment while functional magnetic resonance imaging (fMRI) was performed. Typical age-related performance reductions and fMRI activation increases were observed. However, like younger adults, bilingual older adults outperformed their monolingual peers while displaying decreased activation in left lateral frontal cortex and cingulate cortex. Critically, this attenuation of age-related over-recruitment associated with bilingualism was directly correlated with better task-switching performance. In addition, the lower blood oxygenation level-dependent response in frontal regions accounted for 82% of the variance in the bilingual task-switching reaction time advantage. These results suggest that lifelong bilingualism offsets age-related declines in the neural efficiency for cognitive control processes.

  1. Discovery of efficient stimulators for adult hippocampal neurogenesis based on scaffolds in dragon's blood.

    Science.gov (United States)

    Liang, Jian-Hua; Yang, Liang; Wu, Si; Liu, Si-Si; Cushman, Mark; Tian, Jing; Li, Nuo-Min; Yang, Qing-Hu; Zhang, He-Ao; Qiu, Yun-Jie; Xiang, Lin; Ma, Cong-Xuan; Li, Xue-Meng; Qing, Hong

    2017-08-18

    Reduction of hippocampal neurogenesis caused by aging and neurological disorders would impair neural circuits and result in memory loss. A new lead compound (N-trans-3',4'-methylenedioxystilben-4-yl acetamide 27) has been discovered to efficiently stimulate adult rats' neurogenesis. In-depth structure-activity relationship studies proved the necessity of a stilbene scaffold that is absent in highly cytotoxic analogs such as chalcones and heteroaryl rings and inactive analogs such as diphenyl acetylene and diphenyl ethane, and validated the importance of an NH in the carboxamide and a methylenedioxy substituent on the benzene ring. Immunohistochemical staining and biochemical analysis indicate, in contrast to previously reported neuroprotective chemicals, N-stilbenyl carboxamides have extra capacity for neuroproliferation-type neurogenesis, thereby providing a foundation for improving the plasticity of the adult mammalian brain. Copyright © 2017 Elsevier Masson SAS. All rights reserved.

  2. Masking of infrared neural stimulation (INS) in hearing and deaf guinea pigs

    Science.gov (United States)

    Kadakia, Sama; Young, Hunter; Richter, Claus-Peter

    2013-03-01

    Spatial selective infrared neural stimulation has potential to improve neural prostheses, including cochlear implants. The heating of a confined target volume depolarizes the cell membrane and results in an action potential. Tissue heating may also results in thermal damage or the generation of a stress relaxation wave. Stress relaxation waves may result in a direct mechanical stimulation of remaining hair cells in the cochlea, so called optophony. Data are presented that quantify the effect of an acoustical stimulus (noise masker) on the response obtained with INS in normal hearing, acutely deafened, and chronic deaf animals. While in normal hearing animals an acoustic masker can reduce the response to INS, in acutely deafened animals the masking effect is reduced, and in chronic deaf animals this effect has not been detected. The responses to INS remain stable following the different degrees of cochlear damage.

  3. Differentiation-Dependent Motility-Responses of Developing Neural Progenitors to Optogenetic Stimulation

    Directory of Open Access Journals (Sweden)

    Tímea Köhidi

    2017-12-01

    Full Text Available During neural tissue genesis, neural stem/progenitor cells are exposed to bioelectric stimuli well before synaptogenesis and neural circuit formation. Fluctuations in the electrochemical potential in the vicinity of developing cells influence the genesis, migration and maturation of neuronal precursors. The complexity of the in vivo environment and the coexistence of various progenitor populations hinder the understanding of the significance of ionic/bioelectric stimuli in the early phases of neuronal differentiation. Using optogenetic stimulation, we investigated the in vitro motility responses of radial glia-like neural stem/progenitor populations to ionic stimuli. Radial glia-like neural stem cells were isolated from CAGloxpStoploxpChR2(H134-eYFP transgenic mouse embryos. After transfection with Cre-recombinase, ChR2(channelrhodopsin-2-expressing and non-expressing cells were separated by eYFP fluorescence. Expression of light-gated ion channels were checked by patch clamp and fluorescence intensity assays. Neurogenesis by ChR2-expressing and non-expressing cells was induced by withdrawal of EGF from the medium. Cells in different (stem cell, migrating progenitor and maturing precursor stages of development were illuminated with laser light (λ = 488 nm; 1.3 mW/mm2; 300 ms in every 5 min for 12 h. The displacement of the cells was analyzed on images taken at the end of each light pulse. Results demonstrated that the migratory activity decreased with the advancement of neuronal differentiation regardless of stimulation. Light-sensitive cells, however, responded on a differentiation-dependent way. In non-differentiated ChR2-expressing stem cell populations, the motility did not change significantly in response to light-stimulation. The displacement activity of migrating progenitors was enhanced, while the motility of differentiating neuronal precursors was markedly reduced by illumination.

  4. Efficient Pruning Method for Ensemble Self-Generating Neural Networks

    Directory of Open Access Journals (Sweden)

    Hirotaka Inoue

    2003-12-01

    Full Text Available Recently, multiple classifier systems (MCS have been used for practical applications to improve classification accuracy. Self-generating neural networks (SGNN are one of the suitable base-classifiers for MCS because of their simple setting and fast learning. However, the computation cost of the MCS increases in proportion to the number of SGNN. In this paper, we propose an efficient pruning method for the structure of the SGNN in the MCS. We compare the pruned MCS with two sampling methods. Experiments have been conducted to compare the pruned MCS with an unpruned MCS, the MCS based on C4.5, and k-nearest neighbor method. The results show that the pruned MCS can improve its classification accuracy as well as reducing the computation cost.

  5. VEGF-mediated angiogenesis stimulates neural stem cell proliferation and differentiation in the premature brain

    International Nuclear Information System (INIS)

    Sun, Jinqiao; Sha, Bin; Zhou, Wenhao; Yang, Yi

    2010-01-01

    This study investigated the effects of angiogenesis on the proliferation and differentiation of neural stem cells in the premature brain. We observed the changes in neurogenesis that followed the stimulation and inhibition of angiogenesis by altering vascular endothelial growth factor (VEGF) expression in a 3-day-old rat model. VEGF expression was overexpressed by adenovirus transfection and down-regulated by siRNA interference. Using immunofluorescence assays, Western blot analysis, and real-time PCR methods, we observed angiogenesis and the proliferation and differentiation of neural stem cells. Immunofluorescence assays showed that the number of vWF-positive areas peaked at day 7, and they were highest in the VEGF up-regulation group and lowest in the VEGF down-regulation group at every time point. The number of neural stem cells, neurons, astrocytes, and oligodendrocytes in the subventricular zone gradually increased over time in the VEGF up-regulation group. Among the three groups, the number of these cells was highest in the VEGF up-regulation group and lowest in the VEGF down-regulation group at the same time point. Western blot analysis and real-time PCR confirmed these results. These data suggest that angiogenesis may stimulate the proliferation of neural stem cells and differentiation into neurons, astrocytes, and oligodendrocytes in the premature brain.

  6. Improved Selectivity From a Wavelength Addressable Device for Wireless Stimulation of Neural Tissue

    Directory of Open Access Journals (Sweden)

    Elif Ç. Seymour

    2014-02-01

    Full Text Available Electrical neural stimulation with micro electrodes is a promising technique for restoring lost functions in the central nervous system as a result of injury or disease. One of the problems related to current neural stimulators is the tissue response due to the connecting wires and the presence of a rigid electrode inside soft neural tissue. We have developed a novel, optically activated, microscale photovoltaic neurostimulator based on a custom layered compound semiconductor heterostructure that is both wireless and has a comparatively small volume. Optical activation provides a wireless means of energy transfer to the neurostimulator, eliminating wires and the associated complications. This neurostimulator was shown to evoke action potentials and a functional motor response in the rat spinal cord. In this work, we extend our design to include wavelength selectivity and thus allowing independent activation of devices. As a proof of concept, we fabricated two different microscale devices with different spectral responsivities in the near-infrared region. We assessed the improved addressability of individual devices via wavelength selectivity as compared to spatial selectivity alone through on-bench optical measurements of the devices in combination with an in vivo light intensity profile in the rat cortex obtained in a previous study. We show that wavelength selectivity improves the individual addressability of the floating stimulators, thus increasing the number of devices that can be implanted in close proximity to each other.

  7. Efficient computation in adaptive artificial spiking neural networks

    NARCIS (Netherlands)

    D. Zambrano (Davide); R.B.P. Nusselder (Roeland); H.S. Scholte; S.M. Bohte (Sander)

    2017-01-01

    textabstractArtificial Neural Networks (ANNs) are bio-inspired models of neural computation that have proven highly effective. Still, ANNs lack a natural notion of time, and neural units in ANNs exchange analog values in a frame-based manner, a computationally and energetically inefficient form of

  8. Canonical Wnt signaling transiently stimulates proliferation and enhances neurogenesis in neonatal neural progenitor cultures

    International Nuclear Information System (INIS)

    Hirsch, Cordula; Campano, Louise M.; Woehrle, Simon; Hecht, Andreas

    2007-01-01

    Canonical Wnt signaling triggers the formation of heterodimeric transcription factor complexes consisting of β-catenin and T cell factors, and thereby controls the execution of specific genetic programs. During the expansion and neurogenic phases of embryonic neural development canonical Wnt signaling initially controls proliferation of neural progenitor cells, and later neuronal differentiation. Whether Wnt growth factors affect neural progenitor cells postnatally is not known. Therefore, we have analyzed the impact of Wnt signaling on neural progenitors isolated from cerebral cortices of newborn mice. Expression profiling of pathway components revealed that these cells are fully equipped to respond to Wnt signals. However, Wnt pathway activation affected only a subset of neonatal progenitors and elicited a limited increase in proliferation and neuronal differentiation in distinct subsets of cells. Moreover, Wnt pathway activation only transiently stimulated S-phase entry but did not support long-term proliferation of progenitor cultures. The dampened nature of the Wnt response correlates with the predominant expression of inhibitory pathway components and the rapid actuation of negative feedback mechanisms. Interestingly, in differentiating cell cultures activation of canonical Wnt signaling reduced Hes1 and Hes5 expression suggesting that during postnatal neural development, Wnt/β-catenin signaling enhances neurogenesis from progenitor cells by interfering with Notch pathway activity

  9. 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.

  10. Vagal stimulation targets select populations of intrinsic cardiac neurons to control neurally induced atrial fibrillation

    Science.gov (United States)

    Salavatian, Siamak; Beaumont, Eric; Longpré, Jean-Philippe; Armour, J. Andrew; Vinet, Alain; Jacquemet, Vincent; Shivkumar, Kalyanam

    2016-01-01

    Mediastinal nerve stimulation (MNS) reproducibly evokes atrial fibrillation (AF) by excessive and heterogeneous activation of intrinsic cardiac (IC) neurons. This study evaluated whether preemptive vagus nerve stimulation (VNS) impacts MNS-induced evoked changes in IC neural network activity to thereby alter susceptibility to AF. IC neuronal activity in the right atrial ganglionated plexus was directly recorded in anesthetized canines (n = 8) using a linear microelectrode array concomitant with right atrial electrical activity in response to: 1) epicardial touch or great vessel occlusion vs. 2) stellate or vagal stimulation. From these stressors, post hoc analysis (based on the Skellam distribution) defined IC neurons so recorded as afferent, efferent, or convergent (afferent and efferent inputs) local circuit neurons (LCN). The capacity of right-sided MNS to modify IC activity in the induction of AF was determined before and after preemptive right (RCV)- vs. left (LCV)-sided VNS (15 Hz, 500 μs; 1.2× bradycardia threshold). Neuronal (n = 89) activity at baseline (0.11 ± 0.29 Hz) increased during MNS-induced AF (0.51 ± 1.30 Hz; P < 0.001). Convergent LCNs were preferentially activated by MNS. Preemptive RCV reduced MNS-induced changes in LCN activity (by 70%) while mitigating MNS-induced AF (by 75%). Preemptive LCV reduced LCN activity by 60% while mitigating AF potential by 40%. IC neuronal synchrony increased during neurally induced AF, a local neural network response mitigated by preemptive VNS. These antiarrhythmic effects persisted post-VNS for, on average, 26 min. In conclusion, VNS preferentially targets convergent LCNs and their interactive coherence to mitigate the potential for neurally induced AF. The antiarrhythmic properties imposed by VNS exhibit memory. PMID:27591222

  11. Transcranial magnetic stimulation and connectivity mapping: tools for studying the neural bases of brain disorders.

    Science.gov (United States)

    Hampson, M; Hoffman, R E

    2010-01-01

    There has been an increasing emphasis on characterizing pathophysiology underlying psychiatric and neurological disorders in terms of altered neural connectivity and network dynamics. Transcranial magnetic stimulation (TMS) provides a unique opportunity for investigating connectivity in the human brain. TMS allows researchers and clinicians to directly stimulate cortical regions accessible to electromagnetic coils positioned on the scalp. The induced activation can then propagate through long-range connections to other brain areas. Thus, by identifying distal regions activated during TMS, researchers can infer connectivity patterns in the healthy human brain and can examine how those patterns may be disrupted in patients with different brain disorders. Conversely, connectivity maps derived using neuroimaging methods can identify components of a dysfunctional network. Nodes in this dysfunctional network accessible as targets for TMS by virtue of their proximity to the scalp may then permit TMS-induced alterations of components of the network not directly accessible to TMS via propagated effects. Thus TMS can provide a portal for accessing and altering neural dynamics in networks that are widely distributed anatomically. Finally, when long-term modulation of network dynamics is induced by trains of repetitive TMS, changes in functional connectivity patterns can be studied in parallel with changes in patient symptoms. These correlational data can elucidate neural mechanisms underlying illness and recovery. In this review, we focus on the application of these approaches to the study of psychiatric and neurological illnesses.

  12. Transcranial magnetic stimulation and connectivity mapping: tools for studying the neural bases of brain disorders.

    Directory of Open Access Journals (Sweden)

    Michelle Hampson

    2010-08-01

    Full Text Available There has been an increasing emphasis on characterizing pathophysiology underlying psychiatric and neurological disorders in terms of altered neural connectivity and network dynamics. Transcranial magnetic stimulation (TMS provides a unique opportunity for investigating connectivity in the human brain. TMS allows researchers and clinicians to directly stimulate cortical regions accessible to electromagnetic coils positioned on the scalp. The induced activation can then propagate through long-range connections to other brain areas. Thus, by identifying distal regions activated during TMS, researchers can infer connectivity patterns in the healthy human brain and can examine how those patterns may be disrupted in patients with different brain disorders. Conversely, connectivity maps derived using neuroimaging methods can identify components of a dysfunctional network. Nodes in this dysfunctional network accessible as targets for TMS by virtue of their proximity to the scalp may then permit TMS-induced alterations of components of the network not directly accessible to TMS via propagated effects. Thus TMS can provide a portal for accessing and altering neural dynamics in networks that are widely distributed anatomically. Finally, when long-term modulation of network dynamics is induced by trains of repetitive TMS, changes in functional connectivity patterns can be studied in parallel with changes in patient symptoms. These correlational data can elucidate neural mechanisms underlying illness and recovery. In this review, we focus on the application of these approaches to the study of psychiatric and neurological illnesses.

  13. Learning by stimulation avoidance: A principle to control spiking neural networks dynamics.

    Science.gov (United States)

    Sinapayen, Lana; Masumori, Atsushi; Ikegami, Takashi

    2017-01-01

    Learning based on networks of real neurons, and learning based on biologically inspired models of neural networks, have yet to find general learning rules leading to widespread applications. In this paper, we argue for the existence of a principle allowing to steer the dynamics of a biologically inspired neural network. Using carefully timed external stimulation, the network can be driven towards a desired dynamical state. We term this principle "Learning by Stimulation Avoidance" (LSA). We demonstrate through simulation that the minimal sufficient conditions leading to LSA in artificial networks are also sufficient to reproduce learning results similar to those obtained in biological neurons by Shahaf and Marom, and in addition explains synaptic pruning. We examined the underlying mechanism by simulating a small network of 3 neurons, then scaled it up to a hundred neurons. We show that LSA has a higher explanatory power than existing hypotheses about the response of biological neural networks to external simulation, and can be used as a learning rule for an embodied application: learning of wall avoidance by a simulated robot. In other works, reinforcement learning with spiking networks can be obtained through global reward signals akin simulating the dopamine system; we believe that this is the first project demonstrating sensory-motor learning with random spiking networks through Hebbian learning relying on environmental conditions without a separate reward system.

  14. Neural correlates of erotic stimulation under different levels of female sexual hormones.

    Science.gov (United States)

    Abler, Birgit; Kumpfmüller, Daniela; Grön, Georg; Walter, Martin; Stingl, Julia; Seeringer, Angela

    2013-01-01

    Previous studies have demonstrated variable influences of sexual hormonal states on female brain activation and the necessity to control for these in neuroimaging studies. However, systematic investigations of these influences, particularly those of hormonal contraceptives as compared to the physiological menstrual cycle are scarce. In the present study, we investigated the hormonal modulation of neural correlates of erotic processing in a group of females under hormonal contraceptives (C group; N = 12), and a different group of females (nC group; N = 12) not taking contraceptives during their mid-follicular and mid-luteal phases of the cycle. We used functional magnetic resonance imaging to measure hemodynamic responses as an estimate of brain activation during three different experimental conditions of visual erotic stimulation: dynamic videos, static erotic pictures, and expectation of erotic pictures. Plasma estrogen and progesterone levels were assessed in all subjects. No strong hormonally modulating effect was detected upon more direct and explicit stimulation (viewing of videos or pictures) with significant activations in cortical and subcortical brain regions previously linked to erotic stimulation consistent across hormonal levels and stimulation type. Upon less direct and less explicit stimulation (expectation), activation patterns varied between the different hormonal conditions with various, predominantly frontal brain regions showing significant within- or between-group differences. Activation in the precentral gyrus during the follicular phase in the nC group was found elevated compared to the C group and positively correlated with estrogen levels. From the results we conclude that effects of hormonal influences on brain activation during erotic stimulation are weak if stimulation is direct and explicit but that female sexual hormones may modulate more subtle aspects of sexual arousal and behaviour as involved in sexual expectation. Results

  15. Neural correlates of erotic stimulation under different levels of female sexual hormones.

    Directory of Open Access Journals (Sweden)

    Birgit Abler

    Full Text Available Previous studies have demonstrated variable influences of sexual hormonal states on female brain activation and the necessity to control for these in neuroimaging studies. However, systematic investigations of these influences, particularly those of hormonal contraceptives as compared to the physiological menstrual cycle are scarce. In the present study, we investigated the hormonal modulation of neural correlates of erotic processing in a group of females under hormonal contraceptives (C group; N = 12, and a different group of females (nC group; N = 12 not taking contraceptives during their mid-follicular and mid-luteal phases of the cycle. We used functional magnetic resonance imaging to measure hemodynamic responses as an estimate of brain activation during three different experimental conditions of visual erotic stimulation: dynamic videos, static erotic pictures, and expectation of erotic pictures. Plasma estrogen and progesterone levels were assessed in all subjects. No strong hormonally modulating effect was detected upon more direct and explicit stimulation (viewing of videos or pictures with significant activations in cortical and subcortical brain regions previously linked to erotic stimulation consistent across hormonal levels and stimulation type. Upon less direct and less explicit stimulation (expectation, activation patterns varied between the different hormonal conditions with various, predominantly frontal brain regions showing significant within- or between-group differences. Activation in the precentral gyrus during the follicular phase in the nC group was found elevated compared to the C group and positively correlated with estrogen levels. From the results we conclude that effects of hormonal influences on brain activation during erotic stimulation are weak if stimulation is direct and explicit but that female sexual hormones may modulate more subtle aspects of sexual arousal and behaviour as involved in sexual

  16. Investigating neural efficiency of elite karate athletes during a mental arithmetic task using EEG.

    Science.gov (United States)

    Duru, Adil Deniz; Assem, Moataz

    2018-02-01

    Neural efficiency is proposed as one of the neural mechanisms underlying elite athletic performances. Previous sports studies examined neural efficiency using tasks that involve motor functions. In this study we investigate the extent of neural efficiency beyond motor tasks by using a mental subtraction task. A group of elite karate athletes are compared to a matched group of non-athletes. Electroencephalogram is used to measure cognitive dynamics during resting and increased mental workload periods. Mainly posterior alpha band power of the karate players was found to be higher than control subjects under both tasks. Moreover, event related synchronization/desynchronization has been computed to investigate the neural efficiency hypothesis among subjects. Finally, this study is the first study to examine neural efficiency related to a cognitive task, not a motor task, in elite karate players using ERD/ERS analysis. The results suggest that the effect of neural efficiency in the brain is global rather than local and thus might be contributing to the elite athletic performances. Also the results are in line with the neural efficiency hypothesis tested for motor performance studies.

  17. Effects of vibratory stimulation-induced kinesthetic illusions on the neural activities of patients with stroke.

    Science.gov (United States)

    Kodama, Takayuki; Nakano, Hideki; Ohsugi, Hironori; Murata, Shin

    2016-01-01

    [Purpose] This study evaluated the influence of vibratory stimulation-induced kinesthetic illusion on brain function after stroke. [Subjects] Twelve healthy individuals and 13 stroke patients without motor or sensory loss participated. [Methods] Electroencephalograms were taken at rest and during vibratory stimulation. As a neurophysiological index of brain function, we measured the μ-rhythm, which is present mainly in the kinesthetic cortex and is attenuated by movement or motor imagery and compared the data using source localization analyses in the Standardized Low Resolution Brain Electromagnetic Tomography (sLORETA) program. [Results] At rest, μ-rhythms appeared in the sensorimotor and supplementary motor cortices in both healthy controls and stroke patients. Under vibratory stimulation, no μ-rhythm appeared in the sensorimotor cortex of either group. Moreover, in the supplementary motor area, which stores the motor imagery required for kinesthetic illusions, the μ-rhythms of patients were significantly stronger than those of the controls, although the μ-rhythms of both groups were reduced. Thus, differences in neural activity in the supplementary motor area were apparent between the subject groups. [Conclusion] Kinesthetic illusions do occur in patients with motor deficits due to stroke. The neural basis of the supplementary motor area in stroke patients may be functionally different from that found in healthy controls.

  18. Targeting neural endophenotypes of eating disorders with non-invasive brain stimulation

    Directory of Open Access Journals (Sweden)

    Katharine A Dunlop

    2016-02-01

    Full Text Available The term eating disorders (ED encompasses a wide variety of disordered eating and compensatory behaviors, and so the term is associated with considerable clinical and phenotypic heterogeneity. This heterogeneity makes optimizing treatment techniques difficult. One class of treatments is non-invasive brain stimulation (NIBS. NIBS, including repetitive transcranial magnetic stimulation (rTMS and transcranial direct current stimulation (tDCS are accessible forms of neuromodulation that alter the cortical excitability of a target brain region. It is crucial for NIBS to be successful that the target is well selected for the patient population in question. Targets may best be selected by stepping back from conventional DSM-5 diagnostic criteria to identify neural substrates of more basic phenotypes, including behavior related rewards and punishment cognitive control, and social processes. These phenotypic dimensions have been recently laid out by the Research Domain Criteria (RDoC initiative. Consequently, this review is intended to identify potential dimensions as outlined by the RDoC and their underlying behavioral and neurobiological targets associated with ED as potential candidates for NIBS and review the available literature on rTMS and tDCS in ED. This review systematically reviews abnormal neural circuitry in ED within the RDoC framework, and also systematically reviews the available literature investigating NIBS as a treatment for ED.

  19. 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.

  20. Targeting Lumbar Spinal Neural Circuitry by Epidural Stimulation to Restore Motor Function After Spinal Cord Injury.

    Science.gov (United States)

    Minassian, Karen; McKay, W Barry; Binder, Heinrich; Hofstoetter, Ursula S

    2016-04-01

    Epidural spinal cord stimulation has a long history of application for improving motor control in spinal cord injury. This review focuses on its resurgence following the progress made in understanding the underlying neurophysiological mechanisms and on recent reports of its augmentative effects upon otherwise subfunctional volitional motor control. Early work revealed that the spinal circuitry involved in lower-limb motor control can be accessed by stimulating through electrodes placed epidurally over the posterior aspect of the lumbar spinal cord below a paralyzing injury. Current understanding is that such stimulation activates large-to-medium-diameter sensory fibers within the posterior roots. Those fibers then trans-synaptically activate various spinal reflex circuits and plurisegmentally organized interneuronal networks that control more complex contraction and relaxation patterns involving multiple muscles. The induced change in responsiveness of this spinal motor circuitry to any residual supraspinal input via clinically silent translesional neural connections that have survived the injury may be a likely explanation for rudimentary volitional control enabled by epidural stimulation in otherwise paralyzed muscles. Technological developments that allow dynamic control of stimulation parameters and the potential for activity-dependent beneficial plasticity may further unveil the remarkable capacity of spinal motor processing that remains even after severe spinal cord injuries.

  1. Neural Stimulation Has a Long-Term Effect on Foreign Vocabulary Acquisition.

    Science.gov (United States)

    Pasqualotto, Achille; Kobanbay, Begüm; Proulx, Michael J

    2015-01-01

    Acquisition of a foreign language is a challenging task that is becoming increasingly more important in the world nowadays. There is evidence suggesting that the frontal and temporal cortices are involved in language processing and comprehension, but it is still unknown whether foreign language acquisition recruits additional cortical areas in a causal manner. For the first time, we used transcranial random noise stimulation on the frontal and parietal brain areas, in order to compare its effect on the acquisition of unknown foreign words and a sham, or placebo, condition was also included. This type of noninvasive neural stimulation enhances cortical activity by boosting the spontaneous activity of neurons. Foreign vocabulary acquisition was tested both immediately and seven days after the stimulation. We found that stimulation on the posterior parietal, but not the dorsolateral prefrontal cortex or sham stimulation, significantly improved the memory performance in the long term. These results suggest that the posterior parietal cortex is directly involved in acquisition of foreign vocabulary, thus extending the "linguistic network" to this area.

  2. DANNP: an efficient artificial neural network pruning tool

    KAUST Repository

    Alshahrani, Mona

    2017-11-06

    Background Artificial neural networks (ANNs) are a robust class of machine learning models and are a frequent choice for solving classification problems. However, determining the structure of the ANNs is not trivial as a large number of weights (connection links) may lead to overfitting the training data. Although several ANN pruning algorithms have been proposed for the simplification of ANNs, these algorithms are not able to efficiently cope with intricate ANN structures required for complex classification problems. Methods We developed DANNP, a web-based tool, that implements parallelized versions of several ANN pruning algorithms. The DANNP tool uses a modified version of the Fast Compressed Neural Network software implemented in C++ to considerably enhance the running time of the ANN pruning algorithms we implemented. In addition to the performance evaluation of the pruned ANNs, we systematically compared the set of features that remained in the pruned ANN with those obtained by different state-of-the-art feature selection (FS) methods. Results Although the ANN pruning algorithms are not entirely parallelizable, DANNP was able to speed up the ANN pruning up to eight times on a 32-core machine, compared to the serial implementations. To assess the impact of the ANN pruning by DANNP tool, we used 16 datasets from different domains. In eight out of the 16 datasets, DANNP significantly reduced the number of weights by 70%–99%, while maintaining a competitive or better model performance compared to the unpruned ANN. Finally, we used a naïve Bayes classifier derived with the features selected as a byproduct of the ANN pruning and demonstrated that its accuracy is comparable to those obtained by the classifiers trained with the features selected by several state-of-the-art FS methods. The FS ranking methodology proposed in this study allows the users to identify the most discriminant features of the problem at hand. To the best of our knowledge, DANNP (publicly

  3. Visual awareness suppression by pre-stimulus brain stimulation; a neural effect.

    Science.gov (United States)

    Jacobs, Christianne; Goebel, Rainer; Sack, Alexander T

    2012-01-02

    Transcranial magnetic stimulation (TMS) has established the functional relevance of early visual cortex (EVC) for visual awareness with great temporal specificity non-invasively in conscious human volunteers. Many studies have found a suppressive effect when TMS was applied over EVC 80-100 ms after the onset of the visual stimulus (post-stimulus TMS time window). Yet, few studies found task performance to also suffer when TMS was applied even before visual stimulus presentation (pre-stimulus TMS time window). This pre-stimulus TMS effect, however, remains controversially debated and its origin had mainly been ascribed to TMS-induced eye-blinking artifacts. Here, we applied chronometric TMS over EVC during the execution of a visual discrimination task, covering an exhaustive range of visual stimulus-locked TMS time windows ranging from -80 pre-stimulus to 300 ms post-stimulus onset. Electrooculographical (EoG) recordings, sham TMS stimulation, and vertex TMS stimulation controlled for different types of non-neural TMS effects. Our findings clearly reveal TMS-induced masking effects for both pre- and post-stimulus time windows, and for both objective visual discrimination performance and subjective visibility. Importantly, all effects proved to be still present after post hoc removal of eye blink trials, suggesting a neural origin for the pre-stimulus TMS suppression effect on visual awareness. We speculate based on our data that TMS exerts its pre-stimulus effect via generation of a neural state which interacts with subsequent visual input. Copyright © 2011 Elsevier Inc. All rights reserved.

  4. Investigation of efficient features for image recognition by neural networks.

    Science.gov (United States)

    Goltsev, Alexander; Gritsenko, Vladimir

    2012-04-01

    In the paper, effective and simple features for image recognition (named LiRA-features) are investigated in the task of handwritten digit recognition. Two neural network classifiers are considered-a modified 3-layer perceptron LiRA and a modular assembly neural network. A method of feature selection is proposed that analyses connection weights formed in the preliminary learning process of a neural network classifier. In the experiments using the MNIST database of handwritten digits, the feature selection procedure allows reduction of feature number (from 60 000 to 7000) preserving comparable recognition capability while accelerating computations. Experimental comparison between the LiRA perceptron and the modular assembly neural network is accomplished, which shows that recognition capability of the modular assembly neural network is somewhat better. Copyright © 2011 Elsevier Ltd. All rights reserved.

  5. Electrical Stimulation Elicit Neural Stem Cells Activation:New Perspectives in CNS Repair

    Directory of Open Access Journals (Sweden)

    Ratrel eHuang

    2015-10-01

    Full Text Available Researchers are enthusiastically concerned about neural stem cell (NSC therapy in a wide array of diseases, including stroke, neurodegenerative disease, spinal cord injury (SCI and depression. Although enormous evidences have demonstrated that neurobehavioral improvement may benefit from NSC-supporting regeneration in animal models, approaches to endogenous and transplanted NSCs are blocked by hurdles of migration, proliferation, maturation and integration of NSCs. Electrical stimulation (ES may be a selective nondrug approach for mobilizing NSCs in the central nervous system (CNS. This technique is suitable for clinic application, because it is well established and its potential complications are manageable. Here, we provide a comprehensive review of the emerging positive role of different electrical cues in regulating NSC biology in vitro and in vivo, as well as biomaterial-based and chemical stimulation of NSCs. In the future, ES combined with stem cell therapy or other cues probably becomes an approach for promoting brain repair.

  6. Pilot acute study of feedback-controlled retrograde peristalsis invoked by neural gastric electrical stimulation

    International Nuclear Information System (INIS)

    Aelen, P; Jurkov, A; Aulanier, A; Mintchev, M P

    2009-01-01

    Neural gastric electrical stimulation (NGES) is a new method for invoking gastric contractions under microprocessor control. However, optimization of this technique using feedback mechanisms to minimize power consumption and maximize effectiveness has been lacking. The present pilot study proposes a prototype feedback-controlled neural gastric electric stimulator for the treatment of obesity. Both force-based and inter-electrode impedance-based feedback neurostimulators were implemented and tested. Four mongrel dogs (2 M, 2 F, weight 14.9 ± 2.3 kg) underwent subserosal implantation of two-channel, 1 cm, bipolar electrode leads and two force transducers in the distal antrum. Two of the dogs were stimulated with a force feedback system utilizing the force transducers, and the other two animals were stimulated utilizing an inter-electrode impedance-based feedback system utilizing the proximal electrode leads. Both feedback systems were able to recognize erythromycin-driven contractions of the stomach and were capable of overriding them with NGES-invoked retrograde contractions which exceeded the magnitudes of the erythromycin-driven contractions by an average of 100.6 ± 33.5% in all animals. The NGES-invoked contractions blocked the erythromycin-driven contractions past the proximal electrode pair and induced temporary gastroparesis in the vicinity of the distal force transducer despite the continuing erythromycin infusion. The amplitudes of the erythromycin-invoked contractions in the vicinity of the proximal force transducer decreased abruptly by an average of 47.9 ± 6.3% in all four dogs after triggering-invoked retrograde contractions, regardless of the specific feedback-controlled mechanism. The proposed technique could be helpful for retaining food longer in the stomach, thus inducing early satiety and diminishing food intake

  7. A wideband wireless neural stimulation platform for high-density microelectrode arrays.

    Science.gov (United States)

    Myers, Frank B; Simpson, Jim A; Ghovanloo, Maysam

    2006-01-01

    We describe a system that allows researchers to control an implantable neural microstimulator from a PC via a USB 2.0 interface and a novel dual-carrier wireless link, which provides separate data and power transmission. Our wireless stimulator, Interestim-2B (IS-2B), is a modular device capable of generating controlled-current stimulation pulse trains across 32 sites per module with support for a variety of stimulation schemes (biphasic/monophasic, bipolar/monopolar). We have developed software to generate multi-site stimulation commands for the IS-2B based on streaming data from artificial sensory devices such as cameras and microphones. For PC interfacing, we have developed a USB 2.0 microcontroller-based interface. Data is transmitted using frequency-shift keying (FSK) at 6/12 MHz to achieve a data rate of 3 Mb/s via a pair of rectangular coils. Power is generated using a class-E power amplifier operating at 1 MHz and transmitted via a separate pair of spiral planar coils which are oriented perpendicular to the data coils to minimize cross-coupling. We have successfully demonstrated the operation of the system by applying it as a visual prosthesis. Pulse-frequency modulated stimuli are generated in real-time based on a grayscale image from a webcam. These pulses are projected onto an 11x11 LED matrix that represents a 2D microelectrode array.

  8. A wireless integrated circuit for 100-channel charge-balanced neural stimulation.

    Science.gov (United States)

    Thurgood, B K; Warren, D J; Ledbetter, N M; Clark, G A; Harrison, R R

    2009-12-01

    The authors present the design of an integrated circuit for wireless neural stimulation, along with benchtop and in - vivo experimental results. The chip has the ability to drive 100 individual stimulation electrodes with constant-current pulses of varying amplitude, duration, interphasic delay, and repetition rate. The stimulation is performed by using a biphasic (cathodic and anodic) current source, injecting and retracting charge from the nervous system. Wireless communication and power are delivered over a 2.765-MHz inductive link. Only three off-chip components are needed to operate the stimulator: a 10-nF capacitor to aid in power-supply regulation, a small capacitor (power and command reception. The chip was fabricated in a commercially available 0.6- mum 2P3M BiCMOS process. The chip was able to activate motor fibers to produce muscle twitches via a Utah Slanted Electrode Array implanted in cat sciatic nerve, and to activate sensory fibers to recruit evoked potentials in somatosensory cortex.

  9. Excessive Sensory Stimulation during Development Alters Neural Plasticity and Vulnerability to Cocaine in Mice.

    Science.gov (United States)

    Ravinder, Shilpa; Donckels, Elizabeth A; Ramirez, Julian S B; Christakis, Dimitri A; Ramirez, Jan-Marino; Ferguson, Susan M

    2016-01-01

    Early life experiences affect the formation of neuronal networks, which can have a profound impact on brain function and behavior later in life. Previous work has shown that mice exposed to excessive sensory stimulation during development are hyperactive and novelty seeking, and display impaired cognition compared with controls. In this study, we addressed the issue of whether excessive sensory stimulation during development could alter behaviors related to addiction and underlying circuitry in CD-1 mice. We found that the reinforcing properties of cocaine were significantly enhanced in mice exposed to excessive sensory stimulation. Moreover, although these mice displayed hyperactivity that became more pronounced over time, they showed impaired persistence of cocaine-induced locomotor sensitization. These behavioral effects were associated with alterations in glutamatergic transmission in the nucleus accumbens and amygdala. Together, these findings suggest that excessive sensory stimulation in early life significantly alters drug reward and the neural circuits that regulate addiction and attention deficit hyperactivity. These observations highlight the consequences of early life experiences and may have important implications for children growing up in today's complex technological environment.

  10. DNA methyltransferase mediates dose-dependent stimulation of neural stem cell proliferation by folate.

    Science.gov (United States)

    Li, Wen; Yu, Min; Luo, Suhui; Liu, Huan; Gao, Yuxia; Wilson, John X; Huang, Guowei

    2013-07-01

    The proliferative response of neural stem cells (NSCs) to folate may play a critical role in the development, function and repair of the central nervous system. It is important to determine the dose-dependent effects of folate in NSC cultures that are potential sources of transplantable cells for therapies for neurodegenerative diseases. To determine the optimal concentration and mechanism of action of folate for stimulation of NSC proliferation in vitro, NSCs were exposed to folic acid or 5-methyltetrahydrofolate (5-MTHF) (0-200 μmol/L) for 24, 48 or 72 h. Immunocytochemistry and methyl thiazolyl tetrazolium assay showed that the optimal concentration of folic acid for NSC proliferation was 20-40 μmol/L. Stimulation of NSC proliferation by folic acid was associated with DNA methyltransferase (DNMT) activation and was attenuated by the DNMT inhibitor zebularine, which implies that folate dose-dependently stimulates NSC proliferation through a DNMT-dependent mechanism. Based on these new findings and previously published evidence, we have identified a mechanism by which folate stimulates NSC growth. Copyright © 2013 Elsevier Inc. All rights reserved.

  11. Modulating conscious movement intention by noninvasive brain stimulation and the underlying neural mechanisms.

    Science.gov (United States)

    Douglas, Zachary H; Maniscalco, Brian; Hallett, Mark; Wassermann, Eric M; He, Biyu J

    2015-05-06

    Conscious intention is a fundamental aspect of the human experience. Despite long-standing interest in the basis and implications of intention, its underlying neurobiological mechanisms remain poorly understood. Using high-definition transcranial DC stimulation (tDCS), we observed that enhancing spontaneous neuronal excitability in both the angular gyrus and the primary motor cortex caused the reported time of conscious movement intention to be ∼60-70 ms earlier. Slow brain waves recorded ∼2-3 s before movement onset, as well as hundreds of milliseconds after movement onset, independently correlated with the modulation of conscious intention by brain stimulation. These brain activities together accounted for 81% of interindividual variability in the modulation of movement intention by brain stimulation. A computational model using coupled leaky integrator units with biophysically plausible assumptions about the effect of tDCS captured the effects of stimulation on both neural activity and behavior. These results reveal a temporally extended brain process underlying conscious movement intention that spans seconds around movement commencement. Copyright © 2015 Douglas et al.

  12. Design, implementation and testing of an implantable impedance-based feedback-controlled neural gastric stimulator

    International Nuclear Information System (INIS)

    Arriagada, A J; Jurkov, A S; Mintchev, M P; Neshev, E; Andrews, C N; Muench, G

    2011-01-01

    Functional neural gastrointestinal electrical stimulation (NGES) is a methodology of gastric electrical stimulation that can be applied as a possible treatment for disorders such as obesity and gastroparesis. NGES is capable of generating strong lumen-occluding local contractions that can produce retrograde or antegrade movement of gastric content. A feedback-controlled implantable NGES system has been designed, implemented and tested both in laboratory conditions and in an acute animal setting. The feedback system, based on gastric tissue impedance change, is aimed at reducing battery energy requirements and managing the phenomenon of gastric tissue accommodation. Acute animal testing was undertaken in four mongrel dogs (2 M, 2 F, weight 25.53 ± 7.3 kg) that underwent subserosal two-channel electrode implantation. Three force transducers sutured serosally along the gastric axis and a wireless signal acquisition system were utilized to record stimulation-generated contractions and tissue impedance variations respectively. Mechanically induced contractions in the stomach were utilized to indirectly generate a tissue impedance change that was detected by the feedback system. Results showed that increasing or decreasing impedance changes were detected by the implantable stimulator and that therapy can be triggered as a result. The implantable feedback system brings NGES one step closer to long term treatment of burdening gastric motility disorders in humans

  13. Precision Scaling of Neural Networks for Efficient Audio Processing

    OpenAIRE

    Ko, Jong Hwan; Fromm, Josh; Philipose, Matthai; Tashev, Ivan; Zarar, Shuayb

    2017-01-01

    While deep neural networks have shown powerful performance in many audio applications, their large computation and memory demand has been a challenge for real-time processing. In this paper, we study the impact of scaling the precision of neural networks on the performance of two common audio processing tasks, namely, voice-activity detection and single-channel speech enhancement. We determine the optimal pair of weight/neuron bit precision by exploring its impact on both the performance and ...

  14. Efficient and Invariant Convolutional Neural Networks for Dense Prediction

    OpenAIRE

    Gao, Hongyang; Ji, Shuiwang

    2017-01-01

    Convolutional neural networks have shown great success on feature extraction from raw input data such as images. Although convolutional neural networks are invariant to translations on the inputs, they are not invariant to other transformations, including rotation and flip. Recent attempts have been made to incorporate more invariance in image recognition applications, but they are not applicable to dense prediction tasks, such as image segmentation. In this paper, we propose a set of methods...

  15. Fast and Efficient Asynchronous Neural Computation with Adapting Spiking Neural Networks

    NARCIS (Netherlands)

    D. Zambrano (Davide); S.M. Bohte (Sander)

    2016-01-01

    textabstractBiological neurons communicate with a sparing exchange of pulses - spikes. It is an open question how real spiking neurons produce the kind of powerful neural computation that is possible with deep artificial neural networks, using only so very few spikes to communicate. Building on

  16. Dissociation between neural and vascular responses to sympathetic stimulation : contribution of local adrenergic receptor function

    Science.gov (United States)

    Jacob, G.; Costa, F.; Shannon, J.; Robertson, D.; Biaggioni, I.

    2000-01-01

    Sympathetic activation produced by various stimuli, eg, mental stress or handgrip, evokes regional vascular responses that are often nonhomogeneous. This phenomenon is believed to be the consequence of the recruitment of differential central neural pathways or of a sympathetically mediated vasodilation. The purpose of this study was to determine whether a similar heterogeneous response occurs with cold pressor stimulation and to test the hypothesis that local differences in adrenergic receptor function could be in part responsible for this diversity. In 8 healthy subjects, local norepinephrine spillover and blood flow were measured in arms and legs at baseline and during sympathetic stimulation induced by baroreflex mechanisms (nitroprusside infusion) or cold pressor stimulation. At baseline, legs had higher vascular resistance (27+/-5 versus 17+/-2 U, P=0.05) despite lower norepinephrine spillover (0.28+/-0.04 versus 0.4+/-0.05 mg. min(-1). dL(-1), P=0.03). Norepinephrine spillover increased similarly in both arms and legs during nitroprusside infusion and cold pressor stimulation. On the other hand, during cold stimulation, vascular resistance increased in arms but not in legs (20+/-9% versus -7+/-4%, P=0.03). Increasing doses of isoproterenol and phenylephrine were infused intra-arterially in arms and legs to estimate beta-mediated vasodilation and alpha-induced vasoconstriction, respectively. beta-Mediated vasodilation was significantly lower in legs compared with arms. Thus, we report a dissociation between norepinephrine spillover and vascular responses to cold stress in lower limbs characterized by a paradoxical decrease in local resistance despite increases in sympathetic activity. The differences observed in adrenergic receptor responses cannot explain this phenomenon.

  17. When problem size matters: differential effects of brain stimulation on arithmetic problem solving and neural oscillations.

    Directory of Open Access Journals (Sweden)

    Bruno Rütsche

    Full Text Available The problem size effect is a well-established finding in arithmetic problem solving and is characterized by worse performance in problems with larger compared to smaller operand size. Solving small and large arithmetic problems has also been shown to involve different cognitive processes and distinct electroencephalography (EEG oscillations over the left posterior parietal cortex (LPPC. In this study, we aimed to provide further evidence for these dissociations by using transcranial direct current stimulation (tDCS. Participants underwent anodal (30min, 1.5 mA, LPPC and sham tDCS. After the stimulation, we recorded their neural activity using EEG while the participants solved small and large arithmetic problems. We found that the tDCS effects on performance and oscillatory activity critically depended on the problem size. While anodal tDCS improved response latencies in large arithmetic problems, it decreased solution rates in small arithmetic problems. Likewise, the lower-alpha desynchronization in large problems increased, whereas the theta synchronization in small problems decreased. These findings reveal that the LPPC is differentially involved in solving small and large arithmetic problems and demonstrate that the effects of brain stimulation strikingly differ depending on the involved neuro-cognitive processes.

  18. Acoustic stimulation can induce a selective neural network response mediated by piezoelectric nanoparticles

    Science.gov (United States)

    Rojas, Camilo; Tedesco, Mariateresa; Massobrio, Paolo; Marino, Attilio; Ciofani, Gianni; Martinoia, Sergio; Raiteri, Roberto

    2018-06-01

    Objective. We aim to develop a novel non-invasive or minimally invasive method for neural stimulation to be applied in the study and treatment of brain (dys)functions and neurological disorders. Approach. We investigate the electrophysiological response of in vitro neuronal networks when subjected to low-intensity pulsed acoustic stimulation, mediated by piezoelectric nanoparticles adsorbed on the neuronal membrane. Main results. We show that the presence of piezoelectric barium titanate nanoparticles induces, in a reproducible way, an increase in network activity when excited by stationary ultrasound waves in the MHz regime. Such a response can be fully recovered when switching the ultrasound pulse off, depending on the generated pressure field amplitude, whilst it is insensitive to the duration of the ultrasound pulse in the range 0.5 s–1.5 s. We demonstrate that the presence of piezoelectric nanoparticles is necessary, and when applying the same acoustic stimulation to neuronal cultures without nanoparticles or with non-piezoelectric nanoparticles with the same size distribution, no network response is observed. Significance. We believe that our results open up an extremely interesting approach when coupled with suitable functionalization strategies of the nanoparticles in order to address specific neurons and/or brain areas and applied in vivo, thus enabling remote, non-invasive, and highly selective modulation of the activity of neuronal subpopulations of the central nervous system of mammalians.

  19. Near infrared laser stimulation of human neural stem cells into neurons on graphene nanomesh semiconductors.

    Science.gov (United States)

    Akhavan, Omid; Ghaderi, Elham; Shirazian, Soheil A

    2015-02-01

    Reduced graphene oxide nanomeshes (rGONMs), as p-type semiconductors with band-gap energy of ∼ 1 eV, were developed and applied in near infrared (NIR) laser stimulation of human neural stem cells (hNSCs) into neurons. The biocompatibility of the rGONMs in growth of hNSCs was found similar to that of the graphene oxide (GO) sheets. Proliferation of the hNSCs on the GONMs was assigned to the excess oxygen functional groups formed on edge defects of the GONMs, resulting in superhydrophilicity of the surface. Under NIR laser stimulation, the graphene layers (especially the rGONMs) exhibited significant cell differentiations, including more elongations of the cells and higher differentiation of neurons than glia. The higher hNSC differentiation on the rGONM than the reduced GO (rGO) was assigned to the stimulation effects of the low-energy photoexcited electrons injected from the rGONM semiconductors into the cells, while the high-energy photoelectrons of the rGO (as a zero band-gap semiconductor) could suppress the cell proliferation and/or even cause cell damages. Using conventional heating of the culture media up to ∼ 43 °C (the temperature typically reached under the laser irradiation), no significant differentiation was observed in dark. This further confirmed the role of photoelectrons in the hNSC differentiation. Copyright © 2014 Elsevier B.V. All rights reserved.

  20. 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.

  1. Defining the neural fulcrum for chronic vagus nerve stimulation: implications for integrated cardiac control.

    Science.gov (United States)

    Ardell, Jeffrey L; Nier, Heath; Hammer, Matthew; Southerland, E Marie; Ardell, Christopher L; Beaumont, Eric; KenKnight, Bruce H; Armour, J Andrew

    2017-11-15

    The evoked cardiac response to bipolar cervical vagus nerve stimulation (VNS) reflects a dynamic interaction between afferent mediated decreases in central parasympathetic drive and suppressive effects evoked by direct stimulation of parasympathetic efferent axons to the heart. The neural fulcrum is defined as the operating point, based on frequency-amplitude-pulse width, where a null heart rate response is reproducibly evoked during the on-phase of VNS. Cardiac control, based on the principal of the neural fulcrum, can be elicited from either vagus. Beta-receptor blockade does not alter the tachycardia phase to low intensity VNS, but can increase the bradycardia to higher intensity VNS. While muscarinic cholinergic blockade prevented the VNS-induced bradycardia, clinically relevant doses of ACE inhibitors, beta-blockade and the funny channel blocker ivabradine did not alter the VNS chronotropic response. While there are qualitative differences in VNS heart control between awake and anaesthetized states, the physiological expression of the neural fulcrum is maintained. Vagus nerve stimulation (VNS) is an emerging therapy for treatment of chronic heart failure and remains a standard of therapy in patients with treatment-resistant epilepsy. The objective of this work was to characterize heart rate (HR) responses (HRRs) during the active phase of chronic VNS over a wide range of stimulation parameters in order to define optimal protocols for bidirectional bioelectronic control of the heart. In normal canines, bipolar electrodes were chronically implanted on the cervical vagosympathetic trunk bilaterally with anode cephalad to cathode (n = 8, 'cardiac' configuration) or with electrode positions reversed (n = 8, 'epilepsy' configuration). In awake state, HRRs were determined for each combination of pulse frequency (2-20 Hz), intensity (0-3.5 mA) and pulse widths (130-750 μs) over 14 months. At low intensities and higher frequency VNS, HR increased during the

  2. Pap-smear Classification Using Efficient Second Order Neural Network Training Algorithms

    DEFF Research Database (Denmark)

    Ampazis, Nikolaos; Dounias, George; Jantzen, Jan

    2004-01-01

    In this paper we make use of two highly efficient second order neural network training algorithms, namely the LMAM (Levenberg-Marquardt with Adaptive Momentum) and OLMAM (Optimized Levenberg-Marquardt with Adaptive Momentum), for the construction of an efficient pap-smear test classifier. The alg......In this paper we make use of two highly efficient second order neural network training algorithms, namely the LMAM (Levenberg-Marquardt with Adaptive Momentum) and OLMAM (Optimized Levenberg-Marquardt with Adaptive Momentum), for the construction of an efficient pap-smear test classifier...

  3. Energy efficiency optimisation for distillation column using artificial neural network models

    International Nuclear Information System (INIS)

    Osuolale, Funmilayo N.; Zhang, Jie

    2016-01-01

    This paper presents a neural network based strategy for the modelling and optimisation of energy efficiency in distillation columns incorporating the second law of thermodynamics. Real-time optimisation of distillation columns based on mechanistic models is often infeasible due to the effort in model development and the large computation effort associated with mechanistic model computation. This issue can be addressed by using neural network models which can be quickly developed from process operation data. The computation time in neural network model evaluation is very short making them ideal for real-time optimisation. Bootstrap aggregated neural networks are used in this study for enhanced model accuracy and reliability. Aspen HYSYS is used for the simulation of the distillation systems. Neural network models for exergy efficiency and product compositions are developed from simulated process operation data and are used to maximise exergy efficiency while satisfying products qualities constraints. Applications to binary systems of methanol-water and benzene-toluene separations culminate in a reduction of utility consumption of 8.2% and 28.2% respectively. Application to multi-component separation columns also demonstrate the effectiveness of the proposed method with a 32.4% improvement in the exergy efficiency. - Highlights: • Neural networks can accurately model exergy efficiency in distillation columns. • Bootstrap aggregated neural network offers improved model prediction accuracy. • Improved exergy efficiency is obtained through model based optimisation. • Reductions of utility consumption by 8.2% and 28.2% were achieved for binary systems. • The exergy efficiency for multi-component distillation is increased by 32.4%.

  4. 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.

  5. Functional electrical stimulation controlled by artificial neural networks: pilot experiments with simple movements are promising for rehabilitation applications.

    Science.gov (United States)

    Ferrante, Simona; Pedrocchi, Alessandra; Iannò, Marco; De Momi, Elena; Ferrarin, Maurizio; Ferrigno, Giancarlo

    2004-01-01

    This study falls within the ambit of research on functional electrical stimulation for the design of rehabilitation training for spinal cord injured patients. In this context, a crucial issue is the control of the stimulation parameters in order to optimize the patterns of muscle activation and to increase the duration of the exercises. An adaptive control system (NEURADAPT) based on artificial neural networks (ANNs) was developed to control the knee joint in accordance with desired trajectories by stimulating quadriceps muscles. This strategy includes an inverse neural model of the stimulated limb in the feedforward line and a neural network trained on-line in the feedback loop. NEURADAPT was compared with a linear closed-loop proportional integrative derivative (PID) controller and with a model-based neural controller (NEUROPID). Experiments on two subjects (one healthy and one paraplegic) show the good performance of NEURADAPT, which is able to reduce the time lag introduced by the PID controller. In addition, control systems based on ANN techniques do not require complicated calibration procedures at the beginning of each experimental session. After the initial learning phase, the ANN, thanks to its generalization capacity, is able to cope with a certain range of variability of skeletal muscle properties.

  6. Manipulation of food intake and weight dynamics using retrograde neural gastric electrical stimulation in a chronic canine model

    NARCIS (Netherlands)

    Aelen, P.; Neshev, E.; Cholette, M.; Crisanti, K.; Mitchell, P.; De bru, E.; Church, N.; Mintchev, M.P.

    2008-01-01

    Neural gastric electrical stimulation (NGES) could be a new technique for treating obesity. However, chronic animal experimentation exploring the efficacy of this therapy is lacking. In this study we investigated the utility of retrograde NGES in a chronic canine model. Nine mongrel dogs (26.8 ± 5.2

  7. Effective electric fields along realistic DTI-based neural trajectories for modelling the stimulation mechanisms of TMS

    NARCIS (Netherlands)

    De Geeter, N.; Crevecoeur, G.; Leemans, A.; Dupré, L.

    2015-01-01

    In transcranial magnetic stimulation (TMS), an applied alternating magnetic field induces an electric field in the brain that can interact with the neural system. It is generally assumed that this induced electric field is the crucial effect exciting a certain region of the brain. More specifically,

  8. Fatigue in multiple sclerosis: neural correlates and the role of non-invasive brain stimulation

    Directory of Open Access Journals (Sweden)

    Moussa A. Chalah

    2015-11-01

    Full Text Available Multiple sclerosis (MS is a chronic progressive inflammatory disease of the central nervous system and the major cause of non-traumatic disability in young adults. Fatigue is a frequent symptom reported by the majority of MS patients during their disease course and drastically af-fects their quality of life. Despite its significant prevalence and impact, the underlying patho-physiological mechanisms are not well elucidated. MS fatigue is still considered the result of multifactorial and complex constellations, and is commonly classified into primary fatigue related to the pathological changes of the disease itself, and secondary fatigue attributed to mimicking symptoms, comorbid sleep and mood disorders, and medications side effects. Data from neuroimaging, neurophysiology, neuroendocrine and neuroimmune studies have raised hypotheses regarding the origin of this symptom, some of which have succeeded in identifying an association between MS fatigue and structural or functional abnormalities within various brain networks. Hence, the aim of this work is to reappraise the neural correlates of MS fatigue and to discuss the rationale for the emergent use of noninvasive brain stimulation (NIBS techniques as potential treatments. This will include a presentation of the various NIBS modalities and a proposition of their potential mechanisms of action in this context. Specific issues related to the value of transcranial direct current stimulation will be addressed.

  9. Neural Activation during Anticipation of Near Pain-Threshold Stimulation Among the Pain-Fearful

    Directory of Open Access Journals (Sweden)

    Zhou Yang

    2016-07-01

    Full Text Available Fear of pain (FOP can increase risk for chronic pain and disability but little is known about corresponding neural responses in anticipation of potential pain. In this study, more (10 women, 6 men and less (7 women, 6 men pain-fearful groups underwent whole-brain functional magnetic resonance imaging (fMRI during anticipation of near pain-threshold stimulation. Groups did not differ in the proportion of stimuli judged to be painful but pain-fearful participants reported significantly more state fear prior to stimulus exposure. Within the entire sample, stronger activation was found in several pain regions (e.g., bilateral insula, midcingulate cortex (MCC, thalamus, superior frontal gyrus and visual areas linked to decoding stimulus valences (inferior orbital cortex during anticipation of painful stimuli. Between groups and correlation analyses indicated pain-fearful participants experienced comparatively more activity in regions implicated in evaluating potential threats and processing negative emotions during anticipation (i.e., MCC, mid occipital cortex, superior temporal pole, though group differences were not apparent in most so-called pain matrix regions. In sum, trait- and task-based FOP is associated with enhanced responsiveness in regions involved in threat processing and negative affect during anticipation of potentially painful stimulation.

  10. Neural Activation during Anticipation of Near Pain-Threshold Stimulation among the Pain-Fearful.

    Science.gov (United States)

    Yang, Zhou; Jackson, Todd; Huang, Chengzhi

    2016-01-01

    Fear of pain (FOP) can increase risk for chronic pain and disability but little is known about corresponding neural responses in anticipation of potential pain. In this study, more (10 women, 6 men) and less (7 women, 6 men) pain-fearful groups underwent whole-brain functional magnetic resonance imaging (fMRI) during anticipation of near pain-threshold stimulation. Groups did not differ in the proportion of stimuli judged to be painful but pain-fearful participants reported significantly more state fear prior to stimulus exposure. Within the entire sample, stronger activation was found in several pain perception regions (e.g., bilateral insula, midcingulate cortex (MCC), thalamus, superior frontal gyrus) and visual areas linked to decoding stimulus valences (inferior orbital cortex) during anticipation of "painful" stimuli. Between groups and correlation analyses indicated pain-fearful participants experienced comparatively more activity in regions implicated in evaluating potential threats and processing negative emotions during anticipation (i.e., MCC, mid occipital cortex, superior temporal pole), though group differences were not apparent in most so-called "pain matrix" regions. In sum, trait- and task-based FOP is associated with enhanced responsiveness in regions involved in threat processing and negative affect during anticipation of potentially painful stimulation.

  11. Targeted therapies using electrical and magnetic neural stimulation for the treatment of chronic pain in spinal cord injury.

    Science.gov (United States)

    Moreno-Duarte, Ingrid; Morse, Leslie R; Alam, Mahtab; Bikson, Marom; Zafonte, Ross; Fregni, Felipe

    2014-01-15

    Chronic neuropathic pain is one of the most common and disabling symptoms in individuals with spinal cord injury (SCI). Over two-thirds of subjects with SCI suffer from chronic pain influencing quality of life, rehabilitation, and recovery. Given the refractoriness of chronic pain to most pharmacological treatments, the majority of individuals with SCI report worsening of this condition over time. Moreover, only 4-6% of patients in this cohort report improvement. Novel treatments targeting mechanisms associated with pain-maladaptive plasticity, such as electromagnetic neural stimulation, may be desirable to improve outcomes. To date, few, small clinical trials have assessed the effects of invasive and noninvasive nervous system stimulation on pain after SCI. We aimed to review initial efficacy, safety and potential predictors of response by assessing the effects of neural stimulation techniques to treat SCI pain. A literature search was performed using the PubMed database including studies using the following targeted stimulation strategies: transcranial Direct Current Stimulation (tDCS), High Definition tDCS (HD-tDCS), repetitive Transcranial Magnetical Stimulation (rTMS), Cranial Electrotherapy Stimulation (CES), Transcutaneous Electrical Nerve Stimulation (TENS), Spinal Cord Stimulation (SCS) and Motor Cortex Stimulation (MCS), published prior to June of 2012. We included studies from 1998 to 2012. Eight clinical trials and one naturalistic observational study (nine studies in total) met the inclusion criteria. Among the clinical trials, three studies assessed the effects of tDCS, two of CES, two of rTMS and one of TENS. The naturalistic study investigated the analgesic effects of SCS. No clinical trials for epidural motor cortex stimulation (MCS) or HD-tDCS were found. Parameters of stimulation and also clinical characteristics varied significantly across studies. Three out of eight studies showed larger effects sizes (0.73, 0.88 and 1.86 respectively) for pain

  12. Stimulating Investments in Energy Efficiency Through Supply Chain Integration

    Directory of Open Access Journals (Sweden)

    Beatrice Marchi

    2018-04-01

    Full Text Available Attention to energy efficiency is recently experiencing substantial growth. To overcome the several barriers currently existing that represent an obstacle to the successful implementation of the wide set of energy efficiency measures available, the cooperation among members of a supply chain offers a huge potential. In supply chains, in addition to the traditional coordination of the operations, the members may also share financial resources or act jointly on the capital market. This study presents a two-stage supply chain model considering the opportunity to invest in new energy efficient technologies which are affected by learning effects: the member of the supply chain with better energy performance and/or better financial conditions may find it more profitable to invest in the development of the energy efficiency of its partner. The objective of the model is to determine the optimal investment for each supply chain member so as to maximize the Net Present Value of the supply chain. The impacts of the proposed joint decision-making are investigated through some numerical analysis and managerial insights are proposed: the joint decision-making process on the financial flows for the energy efficiency investments results are especially advantageous (up to a 20% increase of the supply chain Net Present Value when members have different access to capital, which could be the result of different economic conditions in companies’ countries, as well as different credit policies or different credit ratings.

  13. Efficient Healing Takes Some Nerve: Electrical Stimulation Enhances Innervation in Cutaneous Human Wounds.

    Science.gov (United States)

    Emmerson, Elaine

    2017-03-01

    Cutaneous nerves extend throughout the dermis and epidermis and control both the functional and reparative capacity of the skin. Denervation of the skin impairs cutaneous healing, presenting evidence that nerves provide cues essential for timely wound repair. Sebastian et al. demonstrate that electrical stimulation promotes reinnervation and neural differentiation in human acute wounds, thus accelerating wound repair. Copyright © 2016 The Author. Published by Elsevier Inc. All rights reserved.

  14. vDNN: Virtualized Deep Neural Networks for Scalable, Memory-Efficient Neural Network Design

    OpenAIRE

    Rhu, Minsoo; Gimelshein, Natalia; Clemons, Jason; Zulfiqar, Arslan; Keckler, Stephen W.

    2016-01-01

    The most widely used machine learning frameworks require users to carefully tune their memory usage so that the deep neural network (DNN) fits into the DRAM capacity of a GPU. This restriction hampers a researcher's flexibility to study different machine learning algorithms, forcing them to either use a less desirable network architecture or parallelize the processing across multiple GPUs. We propose a runtime memory manager that virtualizes the memory usage of DNNs such that both GPU and CPU...

  15. SiNC: Saliency-injected neural codes for representation and efficient retrieval of medical radiographs.

    Directory of Open Access Journals (Sweden)

    Jamil Ahmad

    Full Text Available Medical image collections contain a wealth of information which can assist radiologists and medical experts in diagnosis and disease detection for making well-informed decisions. However, this objective can only be realized if efficient access is provided to semantically relevant cases from the ever-growing medical image repositories. In this paper, we present an efficient method for representing medical images by incorporating visual saliency and deep features obtained from a fine-tuned convolutional neural network (CNN pre-trained on natural images. Saliency detector is employed to automatically identify regions of interest like tumors, fractures, and calcified spots in images prior to feature extraction. Neuronal activation features termed as neural codes from different CNN layers are comprehensively studied to identify most appropriate features for representing radiographs. This study revealed that neural codes from the last fully connected layer of the fine-tuned CNN are found to be the most suitable for representing medical images. The neural codes extracted from the entire image and salient part of the image are fused to obtain the saliency-injected neural codes (SiNC descriptor which is used for indexing and retrieval. Finally, locality sensitive hashing techniques are applied on the SiNC descriptor to acquire short binary codes for allowing efficient retrieval in large scale image collections. Comprehensive experimental evaluations on the radiology images dataset reveal that the proposed framework achieves high retrieval accuracy and efficiency for scalable image retrieval applications and compares favorably with existing approaches.

  16. Neural Control and Adaptive Neural Forward Models for Insect-like, Energy-Efficient, and Adaptable Locomotion of Walking Machines

    DEFF Research Database (Denmark)

    Manoonpong, Poramate; Parlitz, Ulrich; Wörgötter, Florentin

    2013-01-01

    such natural properties with artificial legged locomotion systems by using different approaches including machine learning algorithms, classical engineering control techniques, and biologically-inspired control mechanisms. However, their levels of performance are still far from the natural ones. By contrast...... on sensory feedback and adaptive neural forward models with efference copies. This neural closed-loop controller enables a walking machine to perform a multitude of different walking patterns including insect-like leg movements and gaits as well as energy-efficient locomotion. In addition, the forward models...... allow the machine to autonomously adapt its locomotion to deal with a change of terrain, losing of ground contact during stance phase, stepping on or hitting an obstacle during swing phase, leg damage, and even to promote cockroach-like climbing behavior. Thus, the results presented here show...

  17. Study Under AC Stimulation on Excitement Properties of Weighted Small-World Biological Neural Networks with Side-Restrain Mechanism

    International Nuclear Information System (INIS)

    Yuan Wujie; Luo Xiaoshu; Jiang Pinqun

    2007-01-01

    In this paper, we propose a new model of weighted small-world biological neural networks based on biophysical Hodgkin-Huxley neurons with side-restrain mechanism. Then we study excitement properties of the model under alternating current (AC) stimulation. The study shows that the excitement properties in the networks are preferably consistent with the behavior properties of a brain nervous system under different AC stimuli, such as refractory period and the brain neural excitement response induced by different intensities of noise and coupling. The results of the study have reference worthiness for the brain nerve electrophysiology and epistemological science.

  18. Neural Control and Adaptive Neural Forward Models for Insect-like, Energy-Efficient, and Adaptable Locomotion of Walking Machines

    Directory of Open Access Journals (Sweden)

    Poramate eManoonpong

    2013-02-01

    Full Text Available Living creatures, like walking animals, have found fascinating solutions for the problem of locomotion control. Their movements show the impression of elegance including versatile, energy-efficient, and adaptable locomotion. During the last few decades, roboticists have tried to imitate such natural properties with artificial legged locomotion systems by using different approaches including machine learning algorithms, classical engineering control techniques, and biologically-inspired control mechanisms. However, their levels of performance are still far from the natural ones. By contrast, animal locomotion mechanisms seem to largely depend not only on central mechanisms (central pattern generators, CPGs and sensory feedback (afferent-based control but also on internal forward models (efference copies. They are used to a different degree in different animals. Generally, CPGs organize basic rhythmic motions which are shaped by sensory feedback while internal models are used for sensory prediction and state estimations. According to this concept, we present here adaptive neural locomotion control consisting of a CPG mechanism with neuromodulation and local leg control mechanisms based on sensory feedback and adaptive neural forward models with efference copies. This neural closed-loop controller enables a walking machine to perform a multitude of different walking patterns including insect-like leg movements and gaits as well as energy-efficient locomotion. In addition, the forward models allow the machine to autonomously adapt its locomotion to deal with a change of terrain, losing of ground contact during stance phase, stepping on or hitting an obstacle during swing phase, leg damage, and even to promote cockroach-like climbing behavior. Thus, the results presented here show that the employed embodied neural closed-loop system can be a powerful way for developing robust and adaptable machines.

  19. Efficient decoding with steady-state Kalman filter in neural interface systems.

    Science.gov (United States)

    Malik, Wasim Q; Truccolo, Wilson; Brown, Emery N; Hochberg, Leigh R

    2011-02-01

    The Kalman filter is commonly used in neural interface systems to decode neural activity and estimate the desired movement kinematics. We analyze a low-complexity Kalman filter implementation in which the filter gain is approximated by its steady-state form, computed offline before real-time decoding commences. We evaluate its performance using human motor cortical spike train data obtained from an intracortical recording array as part of an ongoing pilot clinical trial. We demonstrate that the standard Kalman filter gain converges to within 95% of the steady-state filter gain in 1.5±0.5 s (mean ±s.d.). The difference in the intended movement velocity decoded by the two filters vanishes within 5 s, with a correlation coefficient of 0.99 between the two decoded velocities over the session length. We also find that the steady-state Kalman filter reduces the computational load (algorithm execution time) for decoding the firing rates of 25±3 single units by a factor of 7.0±0.9. We expect that the gain in computational efficiency will be much higher in systems with larger neural ensembles. The steady-state filter can thus provide substantial runtime efficiency at little cost in terms of estimation accuracy. This far more efficient neural decoding approach will facilitate the practical implementation of future large-dimensional, multisignal neural interface systems.

  20. Rhythmic entrainment source separation: Optimizing analyses of neural responses to rhythmic sensory stimulation.

    Science.gov (United States)

    Cohen, Michael X; Gulbinaite, Rasa

    2017-02-15

    Steady-state evoked potentials (SSEPs) are rhythmic brain responses to rhythmic sensory stimulation, and are often used to study perceptual and attentional processes. We present a data analysis method for maximizing the signal-to-noise ratio of the narrow-band steady-state response in the frequency and time-frequency domains. The method, termed rhythmic entrainment source separation (RESS), is based on denoising source separation approaches that take advantage of the simultaneous but differential projection of neural activity to multiple electrodes or sensors. Our approach is a combination and extension of existing multivariate source separation methods. We demonstrate that RESS performs well on both simulated and empirical data, and outperforms conventional SSEP analysis methods based on selecting electrodes with the strongest SSEP response, as well as several other linear spatial filters. We also discuss the potential confound of overfitting, whereby the filter captures noise in absence of a signal. Matlab scripts are available to replicate and extend our simulations and methods. We conclude with some practical advice for optimizing SSEP data analyses and interpreting the results. Copyright © 2016 Elsevier Inc. All rights reserved.

  1. Granulocyte-colony stimulating factor controls neural and behavioral plasticity in response to cocaine.

    Science.gov (United States)

    Calipari, Erin S; Godino, Arthur; Peck, Emily G; Salery, Marine; Mervosh, Nicholas L; Landry, Joseph A; Russo, Scott J; Hurd, Yasmin L; Nestler, Eric J; Kiraly, Drew D

    2018-01-16

    Cocaine addiction is characterized by dysfunction in reward-related brain circuits, leading to maladaptive motivation to seek and take the drug. There are currently no clinically available pharmacotherapies to treat cocaine addiction. Through a broad screen of innate immune mediators, we identify granulocyte-colony stimulating factor (G-CSF) as a potent mediator of cocaine-induced adaptations. Here we report that G-CSF potentiates cocaine-induced increases in neural activity in the nucleus accumbens (NAc) and prefrontal cortex. In addition, G-CSF injections potentiate cocaine place preference and enhance motivation to self-administer cocaine, while not affecting responses to natural rewards. Infusion of G-CSF neutralizing antibody into NAc blocks the ability of G-CSF to modulate cocaine's behavioral effects, providing a direct link between central G-CSF action in NAc and cocaine reward. These results demonstrate that manipulating G-CSF is sufficient to alter the motivation for cocaine, but not natural rewards, providing a pharmacotherapeutic avenue to manipulate addictive behaviors without abuse potential.

  2. Biphasic electrical currents stimulation promotes both proliferation and differentiation of fetal neural stem cells.

    Directory of Open Access Journals (Sweden)

    Keun-A Chang

    2011-04-01

    Full Text Available The use of non-chemical methods to differentiate stem cells has attracted researchers from multiple disciplines, including the engineering and the biomedical fields. No doubt, growth factor based methods are still the most dominant of achieving some level of proliferation and differentiation control--however, chemical based methods are still limited by the quality, source, and amount of the utilized reagents. Well-defined non-chemical methods to differentiate stem cells allow stem cell scientists to control stem cell biology by precisely administering the pre-defined parameters, whether they are structural cues, substrate stiffness, or in the form of current flow. We have developed a culture system that allows normal stem cell growth and the option of applying continuous and defined levels of electric current to alter the cell biology of growing cells. This biphasic current stimulator chip employing ITO electrodes generates both positive and negative currents in the same culture chamber without affecting surface chemistry. We found that biphasic electrical currents (BECs significantly increased the proliferation of fetal neural stem cells (NSCs. Furthermore, BECs also promoted the differentiation of fetal NSCs into neuronal cells, as assessed using immunocytochemistry. Our results clearly show that BECs promote both the proliferation and neuronal differentiation of fetal NSCs. It may apply to the development of strategies that employ NSCs in the treatment of various neurodegenerative diseases, such as Alzheimer's and Parkinson's diseases.

  3. Influence of attention focus on neural activity in the human spinal cord during thermal sensory stimulation.

    Science.gov (United States)

    Stroman, Patrick W; Coe, Brian C; Munoz, Doug P

    2011-01-01

    Perceptions of sensation and pain in healthy people are believed to be the net result of sensory input and descending modulation from brainstem and cortical regions depending on emotional and cognitive factors. Here, the influence of attention on neural activity in the spinal cord during thermal sensory stimulation of the hand was investigated with functional magnetic resonance imaging by systematically varying the participants' attention focus across and within repeated studies. Attention states included (1) attention to the stimulus by rating the sensation and (2) attention away from the stimulus by performing various mental tasks of watching a movie and identifying characters, detecting the direction of coherently moving dots within a randomly moving visual field and answering mentally-challenging questions. Functional MRI results spanning the cervical spinal cord and brainstem consistently demonstrated that the attention state had a significant influence on the activity detected in the cervical spinal cord, as well as in brainstem regions involved with the descending analgesia system. These findings have important implications for the detection and study of pain, and improved characterization of the effects of injury or disease. Copyright © 2011 Elsevier Inc. All rights reserved.

  4. Neural correlates of mirth and laughter: a direct electrical cortical stimulation study.

    Science.gov (United States)

    Yamao, Yukihiro; Matsumoto, Riki; Kunieda, Takeharu; Shibata, Sumiya; Shimotake, Akihiro; Kikuchi, Takayuki; Satow, Takeshi; Mikuni, Nobuhiro; Fukuyama, Hidenao; Ikeda, Akio; Miyamoto, Susumu

    2015-05-01

    Laughter consists of both motor and emotional aspects. The emotional component, known as mirth, is usually associated with the motor component, namely, bilateral facial movements. Previous electrical cortical stimulation (ES) studies revealed that mirth was associated with the basal temporal cortex, inferior frontal cortex, and medial frontal cortex. Functional neuroimaging implicated a role for the left inferior frontal and bilateral temporal cortices in humor processing. However, the neural origins and pathways linking mirth with facial movements are still unclear. We hereby report two cases with temporal lobe epilepsy undergoing subdural electrode implantation in whom ES of the left basal temporal cortex elicited both mirth and laughter-related facial muscle movements. In one case with normal hippocampus, high-frequency ES consistently caused contralateral facial movement, followed by bilateral facial movements with mirth. In contrast, in another case with hippocampal sclerosis (HS), ES elicited only mirth at low intensity and short duration, and eventually laughter at higher intensity and longer duration. In both cases, the basal temporal language area (BTLA) was located within or adjacent to the cortex where ES produced mirth. In conclusion, the present direct ES study demonstrated that 1) mirth had a close relationship with language function, 2) intact mesial temporal structures were actively engaged in the beginning of facial movements associated with mirth, and 3) these emotion-related facial movements had contralateral dominance. Copyright © 2014 Elsevier Ltd. All rights reserved.

  5. A new paradigm of electrical stimulation to enhance sensory neural function.

    Science.gov (United States)

    Breen, Paul P; ÓLaighin, Gearóid; McIntosh, Caroline; Dinneen, Sean F; Quinlan, Leo R; Serrador, Jorge M

    2014-08-01

    The ability to improve peripheral neural transmission would have significant therapeutic potential in medicine. A technology of this kind could be used to restore and/or enhance sensory function in individuals with depressed sensory function, such as older adults or patients with peripheral neuropathies. The goal of this study was to investigate if a new paradigm of subsensory electrical noise stimulation enhances somatosensory function. Vibration (50Hz) was applied with a Neurothesiometer to the plantar aspect of the foot in the presence or absence of subsensory electrical noise (1/f type). The noise was applied at a proximal site, on a defined region of the tibial nerve path above the ankle. Vibration perception thresholds (VPT) of younger adults were measured in control and experimental conditions, in the absence or presence of noise respectively. An improvement of ∼16% in VPT was found in the presence of noise. These are the first data to demonstrate that modulation of axonal transmission with externally applied electrical noise improves perception of tactile stimuli in humans. Copyright © 2014 IPEM. All rights reserved.

  6. Folic Acid supplementation stimulates notch signaling and cell proliferation in embryonic neural stem cells.

    Science.gov (United States)

    Liu, Huan; Huang, Guo-Wei; Zhang, Xu-Mei; Ren, Da-Lin; X Wilson, John

    2010-09-01

    The present study investigated the effect of folic acid supplementation on the Notch signaling pathway and cell proliferation in rat embryonic neural stem cells (NSCs). The NSCs were isolated from E14-16 rat brain and grown as neurospheres in serum-free suspension culture. Individual cultures were assigned to one of 3 treatment groups that differed according to the concentration of folic acid in the medium: Control (baseline folic acid concentration of 4 mg/l), low folic acid supplementation (4 mg/l above baseline, Folate-L) and high folic acid supplementation (40 mg/l above baseline, Folate-H). NSCs were identified by their expression of immunoreactive nestin and proliferating cells by incorporation of 5'bromo-2'deoxyuridine. Cell proliferation was also assessed by methyl thiazolyl tetrazolium assay. Notch signaling was analyzed by real-time PCR and western blot analyses of the expression of Notch1 and hairy and enhancer of split 5 (Hes5). Supplementation of NSCs with folic acid increased the mRNA and protein expression levels of Notch1 and Hes5. Folic acid supplementation also stimulated NSC proliferation dose-dependently. Embryonic NSCs respond to folic acid supplementation with increased Notch signaling and cell proliferation. This mechanism may mediate the effects of folic acid supplementation on neurogenesis in the embryonic nervous system.

  7. Shared Neural Mechanisms for the Evaluation of Intense Sensory Stimulation and Economic Reward, Dependent on Stimulation-Seeking Behavior.

    Science.gov (United States)

    Norbury, Agnes; Valton, Vincent; Rees, Geraint; Roiser, Jonathan P; Husain, Masud

    2016-09-28

    Why are some people strongly motivated by intense sensory experiences? Here we investigated how people encode the value of an intense sensory experience compared with economic reward, and how this varies according to stimulation-seeking preference. Specifically, we used a novel behavioral task in combination with computational modeling to derive the value individuals assigned to the opportunity to experience an intense tactile stimulus (mild electric shock). We then examined functional imaging data recorded during task performance to see how the opportunity to experience the sensory stimulus was encoded in stimulation-seekers versus stimulation-avoiders. We found that for individuals who positively sought out this kind of sensory stimulation, there was common encoding of anticipated economic and sensory rewards in the ventromedial prefrontal cortex. Conversely, there was robust encoding of the modeled probability of receiving such stimulation in the insula only in stimulation-avoidant individuals. Finally, we found preliminary evidence that sensory prediction error signals may be positively signed for stimulation-seekers, but negatively signed for stimulation-avoiders, in the posterior cingulate cortex. These findings may help explain why high intensity sensory experiences are appetitive for some individuals, but not for others, and may have relevance for the increased vulnerability for some psychopathologies, but perhaps increased resilience for others, in high sensation-seeking individuals. People vary in their preference for intense sensory experiences. Here, we investigated how different individuals evaluate the prospect of an unusual sensory experience (electric shock), compared with the opportunity to gain a more traditional reward (money). We found that in a subset of individuals who sought out such unusual sensory stimulation, anticipation of the sensory outcome was encoded in the same way as that of monetary gain, in the ventromedial prefrontal cortex

  8. 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.

  9. Energy-efficient neural information processing in individual neurons and neuronal networks.

    Science.gov (United States)

    Yu, Lianchun; Yu, Yuguo

    2017-11-01

    Brains are composed of networks of an enormous number of neurons interconnected with synapses. Neural information is carried by the electrical signals within neurons and the chemical signals among neurons. Generating these electrical and chemical signals is metabolically expensive. The fundamental issue raised here is whether brains have evolved efficient ways of developing an energy-efficient neural code from the molecular level to the circuit level. Here, we summarize the factors and biophysical mechanisms that could contribute to the energy-efficient neural code for processing input signals. The factors range from ion channel kinetics, body temperature, axonal propagation of action potentials, low-probability release of synaptic neurotransmitters, optimal input and noise, the size of neurons and neuronal clusters, excitation/inhibition balance, coding strategy, cortical wiring, and the organization of functional connectivity. Both experimental and computational evidence suggests that neural systems may use these factors to maximize the efficiency of energy consumption in processing neural signals. Studies indicate that efficient energy utilization may be universal in neuronal systems as an evolutionary consequence of the pressure of limited energy. As a result, neuronal connections may be wired in a highly economical manner to lower energy costs and space. Individual neurons within a network may encode independent stimulus components to allow a minimal number of neurons to represent whole stimulus characteristics efficiently. This basic principle may fundamentally change our view of how billions of neurons organize themselves into complex circuits to operate and generate the most powerful intelligent cognition in nature. © 2017 Wiley Periodicals, Inc. © 2017 Wiley Periodicals, Inc.

  10. Pap-smear Classification Using Efficient Second Order Neural Network Training Algorithms

    DEFF Research Database (Denmark)

    Ampazis, Nikolaos; Dounias, George; Jantzen, Jan

    2004-01-01

    In this paper we make use of two highly efficient second order neural network training algorithms, namely the LMAM (Levenberg-Marquardt with Adaptive Momentum) and OLMAM (Optimized Levenberg-Marquardt with Adaptive Momentum), for the construction of an efficient pap-smear test classifier. The alg......In this paper we make use of two highly efficient second order neural network training algorithms, namely the LMAM (Levenberg-Marquardt with Adaptive Momentum) and OLMAM (Optimized Levenberg-Marquardt with Adaptive Momentum), for the construction of an efficient pap-smear test classifier....... The algorithms are methodologically similar, and are based on iterations of the form employed in the Levenberg-Marquardt (LM) method for non-linear least squares problems with the inclusion of an additional adaptive momentum term arising from the formulation of the training task as a constrained optimization...

  11. Design of artificial neural networks using a genetic algorithm to predict collection efficiency in venturi scrubbers.

    Science.gov (United States)

    Taheri, Mahboobeh; Mohebbi, Ali

    2008-08-30

    In this study, a new approach for the auto-design of neural networks, based on a genetic algorithm (GA), has been used to predict collection efficiency in venturi scrubbers. The experimental input data, including particle diameter, throat gas velocity, liquid to gas flow rate ratio, throat hydraulic diameter, pressure drop across the venturi scrubber and collection efficiency as an output, have been used to create a GA-artificial neural network (ANN) model. The testing results from the model are in good agreement with the experimental data. Comparison of the results of the GA optimized ANN model with the results from the trial-and-error calibrated ANN model indicates that the GA-ANN model is more efficient. Finally, the effects of operating parameters such as liquid to gas flow rate ratio, throat gas velocity, and particle diameter on collection efficiency were determined.

  12. Effective electric fields along realistic DTI-based neural trajectories for modelling the stimulation mechanisms of TMS

    International Nuclear Information System (INIS)

    De Geeter, N; Crevecoeur, G; Dupré, L; Leemans, A

    2015-01-01

    In transcranial magnetic stimulation (TMS), an applied alternating magnetic field induces an electric field in the brain that can interact with the neural system. It is generally assumed that this induced electric field is the crucial effect exciting a certain region of the brain. More specifically, it is the component of this field parallel to the neuron’s local orientation, the so-called effective electric field, that can initiate neuronal stimulation. Deeper insights on the stimulation mechanisms can be acquired through extensive TMS modelling. Most models study simple representations of neurons with assumed geometries, whereas we embed realistic neural trajectories computed using tractography based on diffusion tensor images. This way of modelling ensures a more accurate spatial distribution of the effective electric field that is in addition patient and case specific. The case study of this paper focuses on the single pulse stimulation of the left primary motor cortex with a standard figure-of-eight coil. Including realistic neural geometry in the model demonstrates the strong and localized variations of the effective electric field between the tracts themselves and along them due to the interplay of factors such as the tract’s position and orientation in relation to the TMS coil, the neural trajectory and its course along the white and grey matter interface. Furthermore, the influence of changes in the coil orientation is studied. Investigating the impact of tissue anisotropy confirms that its contribution is not negligible. Moreover, assuming isotropic tissues lead to errors of the same size as rotating or tilting the coil with 10 degrees. In contrast, the model proves to be less sensitive towards the not well-known tissue conductivity values. (paper)

  13. Trait anxiety and the neural efficiency of manipulation in working memory

    NARCIS (Netherlands)

    Basten, U.; Stelzel, C.; Fiebach, C.J.

    2012-01-01

    The present study investigates the effects of trait anxiety on the neural efficiency of working memory component functions (manipulation vs. maintenance) in the absence of threat-related stimuli. For the manipulation of affectively neutral verbal information held in working memory, high- and

  14. Using repetitive transcranial magnetic stimulation to study the underlying neural mechanisms of human motor learning and memory.

    Science.gov (United States)

    Censor, Nitzan; Cohen, Leonardo G

    2011-01-01

    In the last two decades, there has been a rapid development in the research of the physiological brain mechanisms underlying human motor learning and memory. While conventional memory research performed on animal models uses intracellular recordings, microfusion of protein inhibitors to specific brain areas and direct induction of focal brain lesions, human research has so far utilized predominantly behavioural approaches and indirect measurements of neural activity. Repetitive transcranial magnetic stimulation (rTMS), a safe non-invasive brain stimulation technique, enables the study of the functional role of specific cortical areas by evaluating the behavioural consequences of selective modulation of activity (excitation or inhibition) on memory generation and consolidation, contributing to the understanding of the neural substrates of motor learning. Depending on the parameters of stimulation, rTMS can also facilitate learning processes, presumably through purposeful modulation of excitability in specific brain regions. rTMS has also been used to gain valuable knowledge regarding the timeline of motor memory formation, from initial encoding to stabilization and long-term retention. In this review, we summarize insights gained using rTMS on the physiological and neural mechanisms of human motor learning and memory. We conclude by suggesting possible future research directions, some with direct clinical implications.

  15. Efficient Online Learning Algorithms Based on LSTM Neural Networks.

    Science.gov (United States)

    Ergen, Tolga; Kozat, Suleyman Serdar

    2017-09-13

    We investigate online nonlinear regression and introduce novel regression structures based on the long short term memory (LSTM) networks. For the introduced structures, we also provide highly efficient and effective online training methods. To train these novel LSTM-based structures, we put the underlying architecture in a state space form and introduce highly efficient and effective particle filtering (PF)-based updates. We also provide stochastic gradient descent and extended Kalman filter-based updates. Our PF-based training method guarantees convergence to the optimal parameter estimation in the mean square error sense provided that we have a sufficient number of particles and satisfy certain technical conditions. More importantly, we achieve this performance with a computational complexity in the order of the first-order gradient-based methods by controlling the number of particles. Since our approach is generic, we also introduce a gated recurrent unit (GRU)-based approach by directly replacing the LSTM architecture with the GRU architecture, where we demonstrate the superiority of our LSTM-based approach in the sequential prediction task via different real life data sets. In addition, the experimental results illustrate significant performance improvements achieved by the introduced algorithms with respect to the conventional methods over several different benchmark real life data sets.

  16. Conductive nanogel-interfaced neural microelectrode arrays with electrically controlled in-situ delivery of manganese ions enabling high-resolution MEMRI for synchronous neural tracing with deep brain stimulation.

    Science.gov (United States)

    Huang, Wei-Chen; Lo, Yu-Chih; Chu, Chao-Yi; Lai, Hsin-Yi; Chen, You-Yin; Chen, San-Yuan

    2017-04-01

    Chronic brain stimulation has become a promising physical therapy with increased efficacy and efficiency in the treatment of neurodegenerative diseases. The application of deep brain electrical stimulation (DBS) combined with manganese-enhanced magnetic resonance imaging (MEMRI) provides an unbiased representation of the functional anatomy, which shows the communication between areas of the brain responding to the therapy. However, it is challenging for the current system to provide a real-time high-resolution image because the incorporated MnCl 2 solution through microinjection usually results in image blurring or toxicity due to the uncontrollable diffusion of Mn 2+ . In this study, we developed a new type of conductive nanogel-based neural interface composed of amphiphilic chitosan-modified poly(3,4 -ethylenedioxythiophene) (PMSDT) that can exhibit biomimic structural/mechanical properties and ionic/electrical conductivity comparable to that of Au. More importantly, the PMSDT enables metal-ligand bonding with Mn 2+ ions, so that the system can release Mn 2+ ions rather than MnCl 2 solution directly and precisely controlled by electrical stimulation (ES) to achieve real-time high-resolution MEMRI. With the integration of PMSDT nanogel-based coating in polyimide-based microelectrode arrays, the post-implantation DBS enables frequency-dependent MR imaging in vivo, as well as small focal imaging in response to channel site-specific stimulation on the implant. The MR imaging of the implanted brain treated with 5-min electrical stimulation showed a thalamocortical neuronal pathway after 36 h, confirming the effective activation of a downstream neuronal circuit following DBS. By eliminating the susceptibility to artifact and toxicity, this system, in combination with a MR-compatible implant and a bio-compliant neural interface, provides a harmless and synchronic functional anatomy for DBS. The study demonstrates a model of MEMRI-functionalized DBS based on functional

  17. The role of fluid intelligence and learning in analogical reasoning: How to become neurally efficient?

    Science.gov (United States)

    Dix, Annika; Wartenburger, Isabell; van der Meer, Elke

    2016-10-01

    This study on analogical reasoning evaluates the impact of fluid intelligence on adaptive changes in neural efficiency over the course of an experiment and specifies the underlying cognitive processes. Grade 10 students (N=80) solved unfamiliar geometric analogy tasks of varying difficulty. Neural efficiency was measured by the event-related desynchronization (ERD) in the alpha band, an indicator of cortical activity. Neural efficiency was defined as a low amount of cortical activity accompanying high performance during problem-solving. Students solved the tasks faster and more accurately the higher their FI was. Moreover, while high FI led to greater cortical activity in the first half of the experiment, high FI was associated with a neurally more efficient processing (i.e., better performance but same amount of cortical activity) in the second half of the experiment. Performance in difficult tasks improved over the course of the experiment for all students while neural efficiency increased for students with higher but decreased for students with lower fluid intelligence. Based on analyses of the alpha sub-bands, we argue that high fluid intelligence was associated with a stronger investment of attentional resource in the integration of information and the encoding of relations in this unfamiliar task in the first half of the experiment (lower-2 alpha band). Students with lower fluid intelligence seem to adapt their applied strategies over the course of the experiment (i.e., focusing on task-relevant information; lower-1 alpha band). Thus, the initially lower cortical activity and its increase in students with lower fluid intelligence might reflect the overcoming of mental overload that was present in the first half of the experiment. Copyright © 2016 Elsevier Inc. All rights reserved.

  18. DANoC: An Efficient Algorithm and Hardware Codesign of Deep Neural Networks on Chip.

    Science.gov (United States)

    Zhou, Xichuan; Li, Shengli; Tang, Fang; Hu, Shengdong; Lin, Zhi; Zhang, Lei

    2017-07-18

    Deep neural networks (NNs) are the state-of-the-art models for understanding the content of images and videos. However, implementing deep NNs in embedded systems is a challenging task, e.g., a typical deep belief network could exhaust gigabytes of memory and result in bandwidth and computational bottlenecks. To address this challenge, this paper presents an algorithm and hardware codesign for efficient deep neural computation. A hardware-oriented deep learning algorithm, named the deep adaptive network, is proposed to explore the sparsity of neural connections. By adaptively removing the majority of neural connections and robustly representing the reserved connections using binary integers, the proposed algorithm could save up to 99.9% memory utility and computational resources without undermining classification accuracy. An efficient sparse-mapping-memory-based hardware architecture is proposed to fully take advantage of the algorithmic optimization. Different from traditional Von Neumann architecture, the deep-adaptive network on chip (DANoC) brings communication and computation in close proximity to avoid power-hungry parameter transfers between on-board memory and on-chip computational units. Experiments over different image classification benchmarks show that the DANoC system achieves competitively high accuracy and efficiency comparing with the state-of-the-art approaches.

  19. A preferential design approach for energy-efficient and robust implantable neural signal processing hardware.

    Science.gov (United States)

    Narasimhan, Seetharam; Chiel, Hillel J; Bhunia, Swarup

    2009-01-01

    For implantable neural interface applications, it is important to compress data and analyze spike patterns across multiple channels in real time. Such a computational task for online neural data processing requires an innovative circuit-architecture level design approach for low-power, robust and area-efficient hardware implementation. Conventional microprocessor or Digital Signal Processing (DSP) chips would dissipate too much power and are too large in size for an implantable system. In this paper, we propose a novel hardware design approach, referred to as "Preferential Design" that exploits the nature of the neural signal processing algorithm to achieve a low-voltage, robust and area-efficient implementation using nanoscale process technology. The basic idea is to isolate the critical components with respect to system performance and design them more conservatively compared to the noncritical ones. This allows aggressive voltage scaling for low power operation while ensuring robustness and area efficiency. We have applied the proposed approach to a neural signal processing algorithm using the Discrete Wavelet Transform (DWT) and observed significant improvement in power and robustness over conventional design.

  20. Prediction of Protein Thermostability by an Efficient Neural Network Approach

    Directory of Open Access Journals (Sweden)

    Jalal Rezaeenour

    2016-10-01

    significantly improves the accuracy of ELM in prediction of thermostable enzymes. ELM tends to require more neurons in the hidden-layer than conventional tuning-based learning algorithms. To overcome these, the proposed approach uses a GA which optimizes the structure and the parameters of the ELM. In summary, optimization of ELM with GA results in an efficient prediction method; numerical experiments proved that our approach yields excellent results.

  1. Influence of stimulated Raman scattering on the conversion efficiency in four wave mixing

    International Nuclear Information System (INIS)

    Wunderlich, R.; Moore, M.A.; Garrett, W.R.; Payne, M.G.

    1988-01-01

    Secondary nonlinear optical effects following parametric four wave mixing in sodium vapor are investigated. The generated ultraviolet radiation induces stimulated Raman scattering and other four wave mixing process. Population transfer due to Raman transitions strongly influences the phase matching conditions for the primary mixing process. Pulse shortening and a reduction in conversion efficiency are observed. 8 refs., 3 figs

  2. Extended passaging increases the efficiency of neural differentiation from induced pluripotent stem cells

    Directory of Open Access Journals (Sweden)

    Koehler Karl R

    2011-08-01

    Full Text Available Abstract Background The use of induced pluripotent stem cells (iPSCs for the functional replacement of damaged neurons and in vitro disease modeling is of great clinical relevance. Unfortunately, the capacity of iPSC lines to differentiate into neurons is highly variable, prompting the need for a reliable means of assessing the differentiation capacity of newly derived iPSC cell lines. Extended passaging is emerging as a method of ensuring faithful reprogramming. We adapted an established and efficient embryonic stem cell (ESC neural induction protocol to test whether iPSCs (1 have the competence to give rise to functional neurons with similar efficiency as ESCs and (2 whether the extent of neural differentiation could be altered or enhanced by increased passaging. Results Our gene expression and morphological analyses revealed that neural conversion was temporally delayed in iPSC lines and some iPSC lines did not properly form embryoid bodies during the first stage of differentiation. Notably, these deficits were corrected by continual passaging in an iPSC clone. iPSCs with greater than 20 passages (late-passage iPSCs expressed higher expression levels of pluripotency markers and formed larger embryoid bodies than iPSCs with fewer than 10 passages (early-passage iPSCs. Moreover, late-passage iPSCs started to express neural marker genes sooner than early-passage iPSCs after the initiation of neural induction. Furthermore, late-passage iPSC-derived neurons exhibited notably greater excitability and larger voltage-gated currents than early-passage iPSC-derived neurons, although these cells were morphologically indistinguishable. Conclusions These findings strongly suggest that the efficiency neuronal conversion depends on the complete reprogramming of iPSCs via extensive passaging.

  3. Correlations between specific patterns of spontaneous activity and stimulation efficiency in degenerated retina.

    Directory of Open Access Journals (Sweden)

    Christine Haselier

    Full Text Available Retinal prostheses that are currently used to restore vision in patients suffering from retinal degeneration are not adjusted to the changes occurring during the remodeling process of the retina. Recent studies revealed abnormal rhythmic activity in the retina of genetic mouse models of retinitis pigmentosa. Here we describe this abnormal activity also in a pharmacologically-induced (MNU mouse model of retinal degeneration. To investigate how this abnormal activity affects the excitability of retinal ganglion cells, we recorded the electrical activity from whole mounted retinas of rd10 mice and MNU-treated mice using a microelectrode array system and applied biphasic current pulses of different amplitude and duration to stimulate ganglion cells electrically. We show that the electrical stimulation efficiency is strongly reduced in degenerated retinas, in particular when abnormal activity such as oscillations and rhythmic firing of bursts of action potentials can be observed. Using a prestimulus pulse sequence, we could abolish rhythmic retinal activity. Under these conditions, the stimulation efficiency was enhanced in a few cases but not in the majority of tested cells. Nevertheless, this approach supports the idea that modified stimulation protocols could help to improve the efficiency of retinal prostheses in the future.

  4. Efficient and Rapid Derivation of Primitive Neural Stem Cells and Generation of Brain Subtype Neurons From Human Pluripotent Stem Cells

    OpenAIRE

    Yan, Yiping; Shin, Soojung; Jha, Balendu Shekhar; Liu, Qiuyue; Sheng, Jianting; Li, Fuhai; Zhan, Ming; Davis, Janine; Bharti, Kapil; Zeng, Xianmin; Rao, Mahendra; Malik, Nasir; Vemuri, Mohan C.

    2013-01-01

    This study developed a highly efficient serum-free pluripotent stem cell (PSC) neural induction medium that can induce human PSCs into primitive neural stem cells (NSCs) in 7 days, obviating the need for time-consuming, laborious embryoid body generation or rosette picking. This method of primitive NSC derivation sets the stage for the scalable production of clinically relevant neural cells for cell therapy applications in good manufacturing practice conditions.

  5. Modeling of phytoextraction efficiency of microbially stimulated Salix dasyclados L. in the soils with different speciation of heavy metals.

    Science.gov (United States)

    Złoch, Michał; Kowalkowski, Tomasz; Tyburski, Jarosław; Hrynkiewicz, Katarzyna

    2017-12-02

    Bioaugmentation of soils with selected microorganisms during phytoextraction can be the key solution for successful bioremediation and should be accurately calculated for different physicochemical soil properties and heavy metal availability to guarantee the universality of this method. Equally important is the development of an accurate prediction tool to manage phytoremediation process. The main objective of this study was to evaluate the role of three metallotolerant siderophore-producing Streptomyces sp. B1-B3 strains in the phytoremediation of heavy metals with the use of S. dasyclados L. growing in four metalliferrous soils as well as modeling the efficiency of this process based on physicochemical and microbiological properties of the soils using artificial neural network (ANN) analysis. The bacterial inoculation of plants significantly stimulated plant biomass and reduced oxidative stress. Moreover, the bacteria affected the speciation of heavy metals and finally their mobility, thereby enhancing the uptake and bioaccumulation of Zn, Cd, and Pb in the biomass. The best capacity for phytoextraction was noted for strain B1, which had the highest siderophore secretion ability. Finally, ANN model permitted to predict efficiency of phytoextraction based on both the physicochemical properties of the soils and the activity of the soil microbiota with high precision.

  6. Tools and measures for stimulation the efficient energy consumption. Integrated resource planning in Romania

    International Nuclear Information System (INIS)

    Scripcariu, Daniela; Scripcariu, Mircea; Leca, Aureliu

    1996-01-01

    The integrated resource planning is based on analyses of the energy generation and energy consumption as a whole. Thus, increasing the energy efficiency appears to be the cheapest, the most available and the most cost-effective energy resource. In order to stimulate the increase of efficiency of energy consumption, besides economic efficiency criteria for selecting technical solutions, additional tools and measures are necessary. The paper presents the main tools and measures needed to foster an efficient energy consumption. Actions meant to stimulate DSM (Demand-Side Management) implementation in Romania are proposed. The paper contains 5 sections. In the introduction, the main aspects of the DSM are considered, namely, where the programs are implemented, who is the responsible, which are the objectives and finally, how the DSM programs are implemented. The following tools in management of energy use are examined: the energy prices, the regulation in the field of energy efficiency, standards and norms, energy labelling of the products and energy education. Among the measures for managing the energy use, the paper takes into consideration the institutions responsible for DSM, for instance, the Romanian Agency for Energy Conservation (ARCE), decentralization of decision making, the program approaches and financing the actions aiming at improving the energy efficiency. Finally, the paper analyses the criteria in choosing adequate solutions of improving the energy efficiency

  7. The Athlete’s Brain: Cross-Sectional Evidence for Neural Efficiency during Cycling Exercise

    Directory of Open Access Journals (Sweden)

    Sebastian Ludyga

    2016-01-01

    Full Text Available The “neural efficiency” hypothesis suggests that experts are characterized by a more efficient cortical function in cognitive tests. Although this hypothesis has been extended to a variety of movement-related tasks within the last years, it is unclear whether or not neural efficiency is present in cyclists performing endurance exercise. Therefore, this study examined brain cortical activity at rest and during exercise between cyclists of higher (HIGH; n=14; 55.6 ± 2.8 mL/min/kg and lower (LOW; n=15; 46.4 ± 4.1 mL/min/kg maximal oxygen consumption (VO2MAX. Male and female participants performed a graded exercise test with spirometry to assess VO2MAX. After 3 to 5 days, EEG was recorded at rest with eyes closed and during cycling at the individual anaerobic threshold over a 30 min period. Possible differences in alpha/beta ratio as well as alpha and beta power were investigated at frontal, central, and parietal sites. The statistical analysis revealed significant differences between groups (F=12.04; p=0.002, as the alpha/beta ratio was increased in HIGH compared to LOW in both the resting state (p≤0.018 and the exercise condition (p≤0.025. The present results indicate enhanced neural efficiency in subjects with high VO2MAX, possibly due to the inhibition of task-irrelevant cognitive processes.

  8. Event-driven processing for hardware-efficient neural spike sorting

    Science.gov (United States)

    Liu, Yan; Pereira, João L.; Constandinou, Timothy G.

    2018-02-01

    Objective. The prospect of real-time and on-node spike sorting provides a genuine opportunity to push the envelope of large-scale integrated neural recording systems. In such systems the hardware resources, power requirements and data bandwidth increase linearly with channel count. Event-based (or data-driven) processing can provide here a new efficient means for hardware implementation that is completely activity dependant. In this work, we investigate using continuous-time level-crossing sampling for efficient data representation and subsequent spike processing. Approach. (1) We first compare signals (synthetic neural datasets) encoded with this technique against conventional sampling. (2) We then show how such a representation can be directly exploited by extracting simple time domain features from the bitstream to perform neural spike sorting. (3) The proposed method is implemented in a low power FPGA platform to demonstrate its hardware viability. Main results. It is observed that considerably lower data rates are achievable when using 7 bits or less to represent the signals, whilst maintaining the signal fidelity. Results obtained using both MATLAB and reconfigurable logic hardware (FPGA) indicate that feature extraction and spike sorting accuracies can be achieved with comparable or better accuracy than reference methods whilst also requiring relatively low hardware resources. Significance. By effectively exploiting continuous-time data representation, neural signal processing can be achieved in a completely event-driven manner, reducing both the required resources (memory, complexity) and computations (operations). This will see future large-scale neural systems integrating on-node processing in real-time hardware.

  9. Common neural structures activated by epidural and transcutaneous lumbar spinal cord stimulation: Elicitation of posterior root-muscle reflexes.

    Directory of Open Access Journals (Sweden)

    Ursula S Hofstoetter

    Full Text Available Epidural electrical stimulation of the lumbar spinal cord is currently regaining momentum as a neuromodulation intervention in spinal cord injury (SCI to modify dysregulated sensorimotor functions and augment residual motor capacity. There is ample evidence that it engages spinal circuits through the electrical stimulation of large-to-medium diameter afferent fibers within lumbar and upper sacral posterior roots. Recent pilot studies suggested that the surface electrode-based method of transcutaneous spinal cord stimulation (SCS may produce similar neuromodulatory effects as caused by epidural SCS. Neurophysiological and computer modeling studies proposed that this noninvasive technique stimulates posterior-root fibers as well, likely activating similar input structures to the spinal cord as epidural stimulation. Here, we add a yet missing piece of evidence substantiating this assumption. We conducted in-depth analyses and direct comparisons of the electromyographic (EMG characteristics of short-latency responses in multiple leg muscles to both stimulation techniques derived from ten individuals with SCI each. Post-activation depression of responses evoked by paired pulses applied either epidurally or transcutaneously confirmed the reflex nature of the responses. The muscle responses to both techniques had the same latencies, EMG peak-to-peak amplitudes, and waveforms, except for smaller responses with shorter onset latencies in the triceps surae muscle group and shorter offsets of the responses in the biceps femoris muscle during epidural stimulation. Responses obtained in three subjects tested with both methods at different time points had near-identical waveforms per muscle group as well as same onset latencies. The present results strongly corroborate the activation of common neural input structures to the lumbar spinal cord-predominantly primary afferent fibers within multiple posterior roots-by both techniques and add to unraveling the

  10. Efficient probabilistic inference in generic neural networks trained with non-probabilistic feedback.

    Science.gov (United States)

    Orhan, A Emin; Ma, Wei Ji

    2017-07-26

    Animals perform near-optimal probabilistic inference in a wide range of psychophysical tasks. Probabilistic inference requires trial-to-trial representation of the uncertainties associated with task variables and subsequent use of this representation. Previous work has implemented such computations using neural networks with hand-crafted and task-dependent operations. We show that generic neural networks trained with a simple error-based learning rule perform near-optimal probabilistic inference in nine common psychophysical tasks. In a probabilistic categorization task, error-based learning in a generic network simultaneously explains a monkey's learning curve and the evolution of qualitative aspects of its choice behavior. In all tasks, the number of neurons required for a given level of performance grows sublinearly with the input population size, a substantial improvement on previous implementations of probabilistic inference. The trained networks develop a novel sparsity-based probabilistic population code. Our results suggest that probabilistic inference emerges naturally in generic neural networks trained with error-based learning rules.Behavioural tasks often require probability distributions to be inferred about task specific variables. Here, the authors demonstrate that generic neural networks can be trained using a simple error-based learning rule to perform such probabilistic computations efficiently without any need for task specific operations.

  11. Efficient and reliable characterization of the corticospinal system using transcranial magnetic stimulation.

    Science.gov (United States)

    Kukke, Sahana N; Paine, Rainer W; Chao, Chi-Chao; de Campos, Ana C; Hallett, Mark

    2014-06-01

    The purpose of this study is to develop a method to reliably characterize multiple features of the corticospinal system in a more efficient manner than typically done in transcranial magnetic stimulation studies. Forty transcranial magnetic stimulation pulses of varying intensity were given over the first dorsal interosseous motor hot spot in 10 healthy adults. The first dorsal interosseous motor-evoked potential size was recorded during rest and activation to create recruitment curves. The Boltzmann sigmoidal function was fit to the data, and parameters relating to maximal motor-evoked potential size, curve slope, and stimulus intensity leading to half-maximal motor-evoked potential size were computed from the curve fit. Good to excellent test-retest reliability was found for all corticospinal parameters at rest and during activation with 40 transcranial magnetic stimulation pulses. Through the use of curve fitting, important features of the corticospinal system can be determined with fewer stimuli than typically used for the same information. Determining the recruitment curve provides a basis to understand the state of the corticospinal system and select subject-specific parameters for transcranial magnetic stimulation testing quickly and without unnecessary exposure to magnetic stimulation. This method can be useful in individuals who have difficulty in maintaining stillness, including children and patients with motor disorders.

  12. Enhancement of multitasking performance and neural oscillations by transcranial alternating current stimulation

    NARCIS (Netherlands)

    Hsu, W.Y.; Zanto, T.P.; van Schouwenburg, M.R.; Gazzaley, A.

    2017-01-01

    Multitasking is associated with the generation of stimulus-locked theta (4–7 Hz) oscillations arising from prefrontal cortex (PFC). Transcranial alternating current stimulation (tACS) is a non-invasive brain stimulation technique that influences endogenous brain oscillations. Here, we investigate

  13. Neural Signatures of Cognitive Flexibility and Reward Sensitivity Following Nicotinic Receptor Stimulation in Dependent Smokers: A Randomized Trial.

    Science.gov (United States)

    Lesage, Elise; Aronson, Sarah E; Sutherland, Matthew T; Ross, Thomas J; Salmeron, Betty Jo; Stein, Elliot A

    2017-06-01

    Withdrawal from nicotine is an important contributor to smoking relapse. Understanding how reward-based decision making is affected by abstinence and by pharmacotherapies such as nicotine replacement therapy and varenicline tartrate may aid cessation treatment. To independently assess the effects of nicotine dependence and stimulation of the nicotinic acetylcholine receptor on the ability to interpret valence information (reward sensitivity) and subsequently alter behavior as reward contingencies change (cognitive flexibility) in a probabilistic reversal learning task. Nicotine-dependent smokers and nonsmokers completed a probabilistic reversal learning task during acquisition of functional magnetic resonance imaging (fMRI) in a 2-drug, double-blind placebo-controlled crossover design conducted from January 21, 2009, to September 29, 2011. Smokers were abstinent from cigarette smoking for 12 hours for all sessions. In a fully Latin square fashion, participants in both groups underwent MRI twice while receiving varenicline and twice while receiving a placebo pill, wearing either a nicotine or a placebo patch. Imaging analysis was performed from June 15, 2015, to August 10, 2016. A well-established computational model captured effects of smoking status and administration of nicotine and varenicline on probabilistic reversal learning choice behavior. Neural effects of smoking status, nicotine, and varenicline were tested for on MRI contrasts that captured reward sensitivity and cognitive flexibility. The study included 24 nicotine-dependent smokers (12 women and 12 men; mean [SD] age, 35.8 [9.9] years) and 20 nonsmokers (10 women and 10 men; mean [SD] age, 30.4 [7.2] years). Computational modeling indicated that abstinent smokers were biased toward response shifting and that their decisions were less sensitive to the available evidence, suggesting increased impulsivity during withdrawal. These behavioral impairments were mitigated with nicotine and varenicline

  14. Stimulating R and D of industrial energy-efficient technology. Policy lessons--impulse technology

    International Nuclear Information System (INIS)

    Luiten, Esther; Blok, Kornelis

    2004-01-01

    Stimulating research and development (R and D) of innovative energy-efficient technologies for industry is an attractive option for reducing greenhouse gas emissions. Impulse technology, an innovative papermaking technology, is always included in studies assessing the long-term potential of industrial energy efficiency. Aim of this article is to analyse the R and D trajectory of impulse technology in order to explore how government can stimulate the development of industrial energy-efficient technology. The concept of 'momentum' is used to characterise the network of actors and to understand the effect of government R and D support in this particular case study. The network analysis convincingly shows that although marketed as an energy-efficient technology, other benefits were in fact driving forces. Researchers at various national pulp and paper research institutes were successful in attracting government R and D support by claiming an improved energy efficiency. The momentum of the technology network was modest between 1980 and 1990. Therefore, government R and D support accelerated the development of impulse technology in this period. However, when the perspectives of the technology deteriorated--momentum decreased--researchers at national research institutes continued to attract government R and D support successfully. But 25 years of R and D--and over 15 years government R and D support--have not yet resulted in a proven technology. The case study illustrates the risk of continuing R and D support too long without taking into account actors' drivers to invest in R and D. Once momentum decreased, government should have been more circumspect in evaluating the (energy efficiency) promise of impulse technology. The major policy lesson is that government has to look beyond claimed energy efficiencies; government has to value (qualitative) information on (changing) technology networks in deciding upon starting, continuing or pulling out financial R and D support to

  15. Tissue heterogeneity as a mechanism for localized neural stimulation by applied electric fields

    International Nuclear Information System (INIS)

    Miranda, P C; Correia, L; Salvador, R; Basser, P J

    2007-01-01

    We investigate the heterogeneity of electrical conductivity as a new mechanism to stimulate excitable tissues via applied electric fields. In particular, we show that stimulation of axons crossing internal boundaries can occur at boundaries where the electric conductivity of the volume conductor changes abruptly. The effectiveness of this and other stimulation mechanisms was compared by means of models and computer simulations in the context of transcranial magnetic stimulation. While, for a given stimulation intensity, the largest membrane depolarization occurred where an axon terminates or bends sharply in a high electric field region, a slightly smaller membrane depolarization, still sufficient to generate action potentials, also occurred at an internal boundary where the conductivity jumped from 0.143 S m -1 to 0.333 S m -1 , simulating a white-matter-grey-matter interface. Tissue heterogeneity can also give rise to local electric field gradients that are considerably stronger and more focal than those impressed by the stimulation coil and that can affect the membrane potential, albeit to a lesser extent than the two mechanisms mentioned above. Tissue heterogeneity may play an important role in electric and magnetic 'far-field' stimulation

  16. Tissue heterogeneity as a mechanism for localized neural stimulation by applied electric fields

    Energy Technology Data Exchange (ETDEWEB)

    Miranda, P C [Institute of Biophysics and Biomedical Engineering, Faculty of Sciences, University of Lisbon, 1749-016 Lisbon (Portugal); Correia, L [Institute of Biophysics and Biomedical Engineering, Faculty of Sciences, University of Lisbon, 1749-016 Lisbon (Portugal); Salvador, R [Institute of Biophysics and Biomedical Engineering, Faculty of Sciences, University of Lisbon, 1749-016 Lisbon (Portugal); Basser, P J [Section on Tissue Biophysics and Biomimetics, NICHD, National Institutes of Health, Bethesda, MD 20892-1428 (United States)

    2007-09-21

    We investigate the heterogeneity of electrical conductivity as a new mechanism to stimulate excitable tissues via applied electric fields. In particular, we show that stimulation of axons crossing internal boundaries can occur at boundaries where the electric conductivity of the volume conductor changes abruptly. The effectiveness of this and other stimulation mechanisms was compared by means of models and computer simulations in the context of transcranial magnetic stimulation. While, for a given stimulation intensity, the largest membrane depolarization occurred where an axon terminates or bends sharply in a high electric field region, a slightly smaller membrane depolarization, still sufficient to generate action potentials, also occurred at an internal boundary where the conductivity jumped from 0.143 S m{sup -1} to 0.333 S m{sup -1}, simulating a white-matter-grey-matter interface. Tissue heterogeneity can also give rise to local electric field gradients that are considerably stronger and more focal than those impressed by the stimulation coil and that can affect the membrane potential, albeit to a lesser extent than the two mechanisms mentioned above. Tissue heterogeneity may play an important role in electric and magnetic 'far-field' stimulation.

  17. Body Position Influences Which Neural Structures Are Recruited by Lumbar Transcutaneous Spinal Cord Stimulation.

    Directory of Open Access Journals (Sweden)

    Simon M Danner

    Full Text Available Transcutaneous stimulation of the human lumbosacral spinal cord is used to evoke spinal reflexes and to neuromodulate altered sensorimotor function following spinal cord injury. Both applications require the reliable stimulation of afferent posterior root fibers. Yet under certain circumstances, efferent anterior root fibers can be co-activated. We hypothesized that body position influences the preferential stimulation of sensory or motor fibers. Stimulus-triggered responses to transcutaneous spinal cord stimulation were recorded using surface-electromyography from quadriceps, hamstrings, tibialis anterior, and triceps surae muscles in 10 individuals with intact nervous systems in the supine, standing and prone positions. Single and paired (30-ms inter-stimulus intervals biphasic stimulation pulses were applied through surface electrodes placed on the skin between the T11 and T12 inter-spinous processes referenced to electrodes on the abdomen. The paired stimulation was applied to evaluate the origin of the evoked electromyographic response; trans-synaptic responses would be suppressed whereas direct efferent responses would almost retain their amplitude. We found that responses to the second stimulus were decreased to 14%±5% of the amplitude of the response to the initial pulse in the supine position across muscles, to 30%±5% in the standing, and to only 80%±5% in the prone position. Response thresholds were lowest during standing and highest in the prone position and response amplitudes were largest in the supine and smallest in the prone position. The responses obtained in the supine and standing positions likely resulted from selective stimulation of sensory fibers while concomitant motor-fiber stimulation occurred in the prone position. We assume that changes of root-fiber paths within the generated electric field when in the prone position increase the stimulation thresholds of posterior above those of anterior root fibers. Thus, we

  18. Targeting Lumbar Spinal Neural Circuitry by Epidural Stimulation to Restore Motor Function After Spinal Cord Injury

    OpenAIRE

    Minassian, Karen; McKay, W. Barry; Binder, Heinrich; Hofstoetter, Ursula S.

    2016-01-01

    Epidural spinal cord stimulation has a long history of application for improving motor control in spinal cord injury. This review focuses on its resurgence following the progress made in understanding the underlying neurophysiological mechanisms and on recent reports of its augmentative effects upon otherwise subfunctional volitional motor control. Early work revealed that the spinal circuitry involved in lower-limb motor control can be accessed by stimulating through electrodes placed epidur...

  19. Wearable Neural Prostheses - Restoration of Sensory-Motor Function by Transcutaneous Electrical Stimulation

    OpenAIRE

    Micera, Silvestro; Keller, Thierry; Lawrence, Marc; Morari, Manfred; Popovic, Dejan B.

    2010-01-01

    In this article, we focus on the least invasive interface: transcutaneous ES (TES), i.e., the use of surface electrodes as an interface between the stimulator and sensory-motor systems. TES is delivered by a burst of short electrical charge pulses applied between pairs of electrodes positioned on the skin. Monophasic or charge-balanced biphasic (symmetric or asymmetric) stimulation pulses can be delivered. The latter ones have the advantage to provide contraction force while minimizing tissue...

  20. Wearable neural prostheses. Restoration of sensory-motor function by transcutaneous electrical stimulation.

    Science.gov (United States)

    Micera, Silvestro; Keller, Thierry; Lawrence, Marc; Morari, Manfred; Popović, Dejan B

    2010-01-01

    In this article, we focus on the least invasive interface: transcutaneous ES (TES), i.e., the use of surface electrodes as an interface between the stimulator and sensory-motor systems. TES is delivered by a burst of short electrical charge pulses applied between pairs of electrodes positioned on the skin. Monophasic or charge-balanced biphasic (symmetric or asymmetric) stimulation pulses can be delivered. The latter ones have the advantage to provide contraction force while minimizing tissue damage.

  1. Neural network configuration and efficiency underlies individual differences in spatial orientation ability.

    Science.gov (United States)

    Arnold, Aiden E G F; Protzner, Andrea B; Bray, Signe; Levy, Richard M; Iaria, Giuseppe

    2014-02-01

    Spatial orientation is a complex cognitive process requiring the integration of information processed in a distributed system of brain regions. Current models on the neural basis of spatial orientation are based primarily on the functional role of single brain regions, with limited understanding of how interaction among these brain regions relates to behavior. In this study, we investigated two sources of variability in the neural networks that support spatial orientation--network configuration and efficiency--and assessed whether variability in these topological properties relates to individual differences in orientation accuracy. Participants with higher accuracy were shown to express greater activity in the right supramarginal gyrus, the right precentral cortex, and the left hippocampus, over and above a core network engaged by the whole group. Additionally, high-performing individuals had increased levels of global efficiency within a resting-state network composed of brain regions engaged during orientation and increased levels of node centrality in the right supramarginal gyrus, the right primary motor cortex, and the left hippocampus. These results indicate that individual differences in the configuration of task-related networks and their efficiency measured at rest relate to the ability to spatially orient. Our findings advance systems neuroscience models of orientation and navigation by providing insight into the role of functional integration in shaping orientation behavior.

  2. Energy efficiency : an economic stimulator; Efficacite energetique : un moteur economique vert

    Energy Technology Data Exchange (ETDEWEB)

    Contant, A.

    2009-04-01

    In an effort to meet Quebec's energy requirements projected for 2015, Hydro-Quebec along with its partners and clients will invest $3 billion in energy efficiency. Quebec's Energy Efficiency Agency, Canada's Office of Energy Efficiency and the Federation of Canadian Municipalities (FCM) green municipal fund have all contributed to energy efficiency projects to stimulate the economy. These measures are expected to create nearly 4000 jobs in Quebec for electricians, heating contractors, plumbers and building professionals. This investment will also benefit the suppliers and distributors of electrical materials as well as the forestry industry, cement manufacturers, and specialized engineers. Since the benefits of energy efficiency upgrades are already well established, projects can get underway without further studies. The proposed energy efficiency projects can be applied anywhere in the province of Quebec and are not intended for any specific region. To name a few, the projects have included energy upgrades in an arena in Riviere du Loup, the Montreal Health Institute's head office building, and traffic light upgrades in Levis, Quebec. The article noted that energy efficiency upgrades made in the office buildings of Alcan, IBM, Molson and Bombardier have all resulted in at least a 5 per cent reduction in electricity use. All these changes have been good for the environment, even though Quebec's electricity is generated almost entirely from renewable energy sources. 6 figs.

  3. Dual small-molecule targeting of SMAD signaling stimulates human induced pluripotent stem cells toward neural lineages.

    Directory of Open Access Journals (Sweden)

    Methichit Wattanapanitch

    Full Text Available Incurable neurological disorders such as Parkinson's disease (PD, Huntington's disease (HD, and Alzheimer's disease (AD are very common and can be life-threatening because of their progressive disease symptoms with limited treatment options. To provide an alternative renewable cell source for cell-based transplantation and as study models for neurological diseases, we generated induced pluripotent stem cells (iPSCs from human dermal fibroblasts (HDFs and then differentiated them into neural progenitor cells (NPCs and mature neurons by dual SMAD signaling inhibitors. Reprogramming efficiency was improved by supplementing the histone deacethylase inhibitor, valproic acid (VPA, and inhibitor of p160-Rho associated coiled-coil kinase (ROCK, Y-27632, after retroviral transduction. We obtained a number of iPS colonies that shared similar characteristics with human embryonic stem cells in terms of their morphology, cell surface antigens, pluripotency-associated gene and protein expressions as well as their in vitro and in vivo differentiation potentials. After treatment with Noggin and SB431542, inhibitors of the SMAD signaling pathway, HDF-iPSCs demonstrated rapid and efficient differentiation into neural lineages. Six days after neural induction, neuroepithelial cells (NEPCs were observed in the adherent monolayer culture, which had the ability to differentiate further into NPCs and neurons, as characterized by their morphology and the expression of neuron-specific transcripts and proteins. We propose that our study may be applied to generate neurological disease patient-specific iPSCs allowing better understanding of disease pathogenesis and drug sensitivity assays.

  4. The reliability of nonlinear least-squares algorithm for data analysis of neural response activity during sinusoidal rotational stimulation in semicircular canal neurons.

    Science.gov (United States)

    Ren, Pengyu; Li, Bowen; Dong, Shiyao; Chen, Lin; Zhang, Yuelin

    2018-01-01

    Although many mathematical methods were used to analyze the neural activity under sinusoidal stimulation within linear response range in vestibular system, the reliabilities of these methods are still not reported, especially in nonlinear response range. Here we chose nonlinear least-squares algorithm (NLSA) with sinusoidal model to analyze the neural response of semicircular canal neurons (SCNs) during sinusoidal rotational stimulation (SRS) over a nonlinear response range. Our aim was to acquire a reliable mathematical method for data analysis under SRS in vestibular system. Our data indicated that the reliability of this method in an entire SCNs population was quite satisfactory. However, the reliability was strongly negatively depended on the neural discharge regularity. In addition, stimulation parameters were the vital impact factors influencing the reliability. The frequency had a significant negative effect but the amplitude had a conspicuous positive effect on the reliability. Thus, NLSA with sinusoidal model resulted a reliable mathematical tool for data analysis of neural response activity under SRS in vestibular system and more suitable for those under the stimulation with low frequency but high amplitude, suggesting that this method can be used in nonlinear response range. This method broke out of the restriction of neural activity analysis under nonlinear response range and provided a solid foundation for future study in nonlinear response range in vestibular system.

  5. Recording of the Neural Activity Induced by the Electrical Subthalamic Stimulation Using Ca2+ Imaging

    Science.gov (United States)

    Tamura, Atsushi; Yagi, Tetsuya; Osanai, Makoto

    The basal ganglia (BG) have important roles in some kind of motor control and learning. Parkinson's disease is one of the motor impairment disease. Recently, to recover a motor severity in patients of Parkinsonism, the stimulus electrode is implanted to the subthalamic nucleus, which is a part of the basal ganglia, and the deep brain stimulation (DBS) is often conducted. However, the effects of the DBS on the subthalamic neurons have not been elucidated. Thus, to analyze the effects of the electrical stimulation on the subthalamic neurons, we conducted the calcium imaging at the mouse subthalamic nucleus. When the single stimulus was applied to the subthalamic nucleus, the intracellular calcium ([Ca2+]i) transients were observed. In the case of application of the single electrical stimulation, the [Ca2+]i arose near the stimulus position. When 100 Hz 10-100 times tetanic stimulations were applied, the responded area and the amplitudes of [Ca2+]i transients were increased. The [Ca2+]i transients were disappeared almost completely on the action potential blockade, but blockade of the excitatory and the inhibitory synaptic transmission had little effects on the responded area and the amplitudes of the [Ca2+]i transients. These results suggested that the electrical stimulation to the subthalamic neurons led to activate the subthalamic neurons directly but not via synaptic transmissions. Thus, DBS may change the activity of the subthalamic neurons, hence, may alter the input-output relationship of the subthalamic neurons

  6. Design of a Closed-Loop, Bidirectional Brain Machine Interface System With Energy Efficient Neural Feature Extraction and PID Control.

    Science.gov (United States)

    Liu, Xilin; Zhang, Milin; Richardson, Andrew G; Lucas, Timothy H; Van der Spiegel, Jan

    2017-08-01

    This paper presents a bidirectional brain machine interface (BMI) microsystem designed for closed-loop neuroscience research, especially experiments in freely behaving animals. The system-on-chip (SoC) consists of 16-channel neural recording front-ends, neural feature extraction units, 16-channel programmable neural stimulator back-ends, in-channel programmable closed-loop controllers, global analog-digital converters (ADC), and peripheral circuits. The proposed neural feature extraction units includes 1) an ultra low-power neural energy extraction unit enabling a 64-step natural logarithmic domain frequency tuning, and 2) a current-mode action potential (AP) detection unit with time-amplitude window discriminator. A programmable proportional-integral-derivative (PID) controller has been integrated in each channel enabling a various of closed-loop operations. The implemented ADCs include a 10-bit voltage-mode successive approximation register (SAR) ADC for the digitization of the neural feature outputs and/or local field potential (LFP) outputs, and an 8-bit current-mode SAR ADC for the digitization of the action potential outputs. The multi-mode stimulator can be programmed to perform monopolar or bipolar, symmetrical or asymmetrical charge balanced stimulation with a maximum current of 4 mA in an arbitrary channel configuration. The chip has been fabricated in 0.18 μ m CMOS technology, occupying a silicon area of 3.7 mm 2 . The chip dissipates 56 μW/ch on average. General purpose low-power microcontroller with Bluetooth module are integrated in the system to provide wireless link and SoC configuration. Methods, circuit techniques and system topology proposed in this work can be used in a wide range of relevant neurophysiology research, especially closed-loop BMI experiments.

  7. Functional Magnetic Resonance Imaging Evaluation of Auricular Percutaneous Electrical Neural Field Stimulation for Fibromyalgia: Protocol for a Feasibility Study.

    Science.gov (United States)

    Gebre, Melat; Woodbury, Anna; Napadow, Vitaly; Krishnamurthy, Venkatagiri; Krishnamurthy, Lisa C; Sniecinski, Roman; Crosson, Bruce

    2018-02-06

    Fibromyalgia is a chronic pain state that includes widespread musculoskeletal pain, fatigue, psychiatric symptoms, cognitive and sleep disturbances, and multiple somatic symptoms. Current therapies are often insufficient or come with significant risks, and while there is an increasing demand for non-pharmacologic and especially non-opioid pain management such as that offered through complementary and alternative medicine therapies, there is currently insufficient evidence to recommend these therapies. Percutaneous electrical neural stimulation (PENS) is an evidence-based treatment option for pain conditions that involves electrical current stimulation through needles inserted into the skin. Percutaneous electrical neural field stimulation (PENFS) of the auricle is similar to PENS, but instead of targeting a single neurovascular bundle, PENFS stimulates the entire ear, covering all auricular branches of the cranial nerves, including the vagus nerve. The neural mechanisms of PENFS for fibromyalgia symptom relief are unknown. We hypothesize that PENFS treatment will decrease functional brain connectivity between the default mode network (DMN) and right posterior insula in fibromyalgia patients. We expect that the decrease in functional connectivity between the DMN and insula will correlate with patient-reported analgesic improvements as indicated by the Defense and Veterans Pain Rating Scale (DVPRS) and will be anti-correlated with patient-reported analgesic medication consumption. Exploratory analyses will be performed for further hypothesis generation. A total of 20 adults from the Atlanta Veterans Affairs Medical Center diagnosed with fibromyalgia will be randomized into 2 groups: 10 subjects to a control (standard therapy) group and 10 subjects to a PENFS treatment group. The pragmatic, standard therapy group will include pharmacologic treatments such as anticonvulsants, non-steroidal anti-inflammatory drugs, topical agents and physical therapy individualized to

  8. Evaluation and statistical judgement of neural responses to sinusoidal stimulation in cases with superimposed drift and noise.

    Science.gov (United States)

    Jastreboff, P W

    1979-06-01

    Time histograms of neural responses evoked by sinuosidal stimulation often contain a slow drifting and an irregular noise which disturb Fourier analysis of these responses. Section 2 of this paper evaluates the extent to which a linear drift influences the Fourier analysis, and develops a combined Fourier and linear regression analysis for detecting and correcting for such a linear drift. Usefulness of this correcting method is demonstrated for the time histograms of actual eye movements and Purkinje cell discharges evoked by sinusoidal rotation of rabbits in the horizontal plane. In Sect. 3, the analysis of variance is adopted for estimating the probability of the random occurrence of the response curve extracted by Fourier analysis from noise. This method proved to be useful for avoiding false judgements as to whether the response curve was meaningful, particularly when the response was small relative to the contaminating noise.

  9. Rhythmic entrainment source separation: Optimizing analyses of neural responses to rhythmic sensory stimulation

    NARCIS (Netherlands)

    Cohen, M.S.; Gulbinaite, R.

    2017-01-01

    Steady-state evoked potentials (SSEPs) are rhythmic brain responses to rhythmic sensory stimulation, and are often used to study perceptual and attentional processes. We present a data analysis method for maximizing the signal-to-noise ratio of the narrow-band steady-state response in the frequency

  10. A novel lead design enables selective deep brain stimulation of neural populations in the subthalamic region

    NARCIS (Netherlands)

    van Dijk, Kees J.; Verhagen, Rens; Chaturvedi, Ashutosh; McIntyre, Cameron C.; Bour, Lo J.; Heida, Ciska; Veltink, Peter H.

    2015-01-01

    The clinical effects of deep brain stimulation (DBS) of the subthalamic nucleus (STN-DBS) as a treatment for Parkinson's disease are sensitive to the location of the DBS lead within the STN. New high density (HD) lead designs have been created which are hypothesized to provide additional degrees of

  11. A novel lead design enables selective deep brain stimulation of neural populations in the subthalamic region

    NARCIS (Netherlands)

    van Dijk, Kees J.; Verhagen, Rens; Chaturvedi, Ashutosh; McIntyre, Cameron C.; Bour, Lo J.; Heida, Tjitske; Veltink, Peter H.

    2015-01-01

    Objective. The clinical effects of deep brain stimulation (DBS) of the subthalamic nucleus (STN-DBS) as a treatment for Parkinson's disease are sensitive to the location of the DBS lead within the STN. New high density (HD) lead designs have been created which are hypothesized to provide additional

  12. Enhancement of multitasking performance and neural oscillations by transcranial alternating current stimulation.

    Science.gov (United States)

    Hsu, Wan-Yu; Zanto, Theodore P; van Schouwenburg, Martine R; Gazzaley, Adam

    2017-01-01

    Multitasking is associated with the generation of stimulus-locked theta (4-7 Hz) oscillations arising from prefrontal cortex (PFC). Transcranial alternating current stimulation (tACS) is a non-invasive brain stimulation technique that influences endogenous brain oscillations. Here, we investigate whether applying alternating current stimulation within the theta frequency band would affect multitasking performance, and explore tACS effects on neurophysiological measures. Brief runs of bilateral PFC theta-tACS were applied while participants were engaged in a multitasking paradigm accompanied by electroencephalography (EEG) data collection. Unlike an active control group, a tACS stimulation group showed enhancement of multitasking performance after a 90-minute session (F1,35 = 6.63, p = 0.01, ηp2 = 0.16; effect size = 0.96), coupled with significant modulation of posterior beta (13-30 Hz) activities (F1,32 = 7.66, p = 0.009, ηp2 = 0.19; effect size = 0.96). Across participant regression analyses indicated that those participants with greater increases in frontal theta, alpha and beta oscillations exhibited greater multitasking performance improvements. These results indicate frontal theta-tACS generates benefits on multitasking performance accompanied by widespread neuronal oscillatory changes, and suggests that future tACS studies with extended treatments are worth exploring as promising tools for cognitive enhancement.

  13. Enhancement of multitasking performance and neural oscillations by transcranial alternating current stimulation.

    Directory of Open Access Journals (Sweden)

    Wan-Yu Hsu

    Full Text Available Multitasking is associated with the generation of stimulus-locked theta (4-7 Hz oscillations arising from prefrontal cortex (PFC. Transcranial alternating current stimulation (tACS is a non-invasive brain stimulation technique that influences endogenous brain oscillations. Here, we investigate whether applying alternating current stimulation within the theta frequency band would affect multitasking performance, and explore tACS effects on neurophysiological measures. Brief runs of bilateral PFC theta-tACS were applied while participants were engaged in a multitasking paradigm accompanied by electroencephalography (EEG data collection. Unlike an active control group, a tACS stimulation group showed enhancement of multitasking performance after a 90-minute session (F1,35 = 6.63, p = 0.01, ηp2 = 0.16; effect size = 0.96, coupled with significant modulation of posterior beta (13-30 Hz activities (F1,32 = 7.66, p = 0.009, ηp2 = 0.19; effect size = 0.96. Across participant regression analyses indicated that those participants with greater increases in frontal theta, alpha and beta oscillations exhibited greater multitasking performance improvements. These results indicate frontal theta-tACS generates benefits on multitasking performance accompanied by widespread neuronal oscillatory changes, and suggests that future tACS studies with extended treatments are worth exploring as promising tools for cognitive enhancement.

  14. Improved efficiency of stimulated Raman adiabatic passage in photoassociation of a Bose-Einstein condensate

    International Nuclear Information System (INIS)

    Mackie, Matt; Suominen, Kalle-Antti; Haerkoenen, Kari; Collin, Anssi; Javanainen, Juha

    2004-01-01

    We theoretically examine Raman photoassociation of a Bose-Einstein condensate, revisiting stimulated Raman adiabatic passage (STIRAP). Due to collisional mean-field shifts, efficient molecular conversion requires strong coupling and low density, either of which can bring about rogue photodissociation to noncondensate modes. We demonstrate explicitly that rogue transitions are negligible for low excited-state fractions and photodissociation that is slower than the STIRAP time scale. Moreover, we derive a reduced-parameter model of collisions, and thereby find that a gain in the molecular conversion efficiency can be obtained by adjusting the atom-atom scattering length with off-resonant magnetoassociation. This gain saturates when the atom-atom scattering length is tuned to a specific fraction of either the molecule-molecule or atom-molecule scattering length. We conclude that a fully optimized STIRAP scheme may offer the best chance for achieving coherent conversion from an atomic to a molecular condensate with photoassociation

  15. Consequences of Converting Graded to Action Potentials upon Neural Information Coding and Energy Efficiency

    Science.gov (United States)

    Sengupta, Biswa; Laughlin, Simon Barry; Niven, Jeremy Edward

    2014-01-01

    Information is encoded in neural circuits using both graded and action potentials, converting between them within single neurons and successive processing layers. This conversion is accompanied by information loss and a drop in energy efficiency. We investigate the biophysical causes of this loss of information and efficiency by comparing spiking neuron models, containing stochastic voltage-gated Na+ and K+ channels, with generator potential and graded potential models lacking voltage-gated Na+ channels. We identify three causes of information loss in the generator potential that are the by-product of action potential generation: (1) the voltage-gated Na+ channels necessary for action potential generation increase intrinsic noise and (2) introduce non-linearities, and (3) the finite duration of the action potential creates a ‘footprint’ in the generator potential that obscures incoming signals. These three processes reduce information rates by ∼50% in generator potentials, to ∼3 times that of spike trains. Both generator potentials and graded potentials consume almost an order of magnitude less energy per second than spike trains. Because of the lower information rates of generator potentials they are substantially less energy efficient than graded potentials. However, both are an order of magnitude more efficient than spike trains due to the higher energy costs and low information content of spikes, emphasizing that there is a two-fold cost of converting analogue to digital; information loss and cost inflation. PMID:24465197

  16. Rhythmic entrainment source separation: Optimizing analyses of neural responses to rhythmic sensory stimulation

    OpenAIRE

    Cohen, M.S.; Gulbinaite, R.

    2017-01-01

    Steady-state evoked potentials (SSEPs) are rhythmic brain responses to rhythmic sensory stimulation, and are often used to study perceptual and attentional processes. We present a data analysis method for maximizing the signal-to-noise ratio of the narrow-band steady-state response in the frequency and time-frequency domains. The method, termed rhythmic entrainment source separation (RESS), is based on denoising source separation approaches that take advantage of the simultaneous but differen...

  17. Modulating Conscious Movement Intention by Noninvasive Brain Stimulation and the Underlying Neural Mechanisms

    OpenAIRE

    Douglas, Zachary H.; Maniscalco, Brian; Hallett, Mark; Wassermann, Eric M.; He, Biyu J.

    2015-01-01

    Conscious intention is a fundamental aspect of the human experience. Despite long-standing interest in the basis and implications of intention, its underlying neurobiological mechanisms remain poorly understood. Using high-definition transcranial DC stimulation (tDCS), we observed that enhancing spontaneous neuronal excitability in both the angular gyrus and the primary motor cortex caused the reported time of conscious movement intention to be ∼60–70 ms earlier. Slow brain waves recorded ∼2–...

  18. Combining neural networks and signed particles to simulate quantum systems more efficiently

    Science.gov (United States)

    Sellier, Jean Michel

    2018-04-01

    Recently a new formulation of quantum mechanics has been suggested which describes systems by means of ensembles of classical particles provided with a sign. This novel approach mainly consists of two steps: the computation of the Wigner kernel, a multi-dimensional function describing the effects of the potential over the system, and the field-less evolution of the particles which eventually create new signed particles in the process. Although this method has proved to be extremely advantageous in terms of computational resources - as a matter of fact it is able to simulate in a time-dependent fashion many-body systems on relatively small machines - the Wigner kernel can represent the bottleneck of simulations of certain systems. Moreover, storing the kernel can be another issue as the amount of memory needed is cursed by the dimensionality of the system. In this work, we introduce a new technique which drastically reduces the computation time and memory requirement to simulate time-dependent quantum systems which is based on the use of an appropriately tailored neural network combined with the signed particle formalism. In particular, the suggested neural network is able to compute efficiently and reliably the Wigner kernel without any training as its entire set of weights and biases is specified by analytical formulas. As a consequence, the amount of memory for quantum simulations radically drops since the kernel does not need to be stored anymore as it is now computed by the neural network itself, only on the cells of the (discretized) phase-space which are occupied by particles. As its is clearly shown in the final part of this paper, not only this novel approach drastically reduces the computational time, it also remains accurate. The author believes this work opens the way towards effective design of quantum devices, with incredible practical implications.

  19. Central-peripheral neural network interactions evoked by vagus nerve stimulation: functional consequences on control of cardiac function.

    Science.gov (United States)

    Ardell, Jeffrey L; Rajendran, Pradeep S; Nier, Heath A; KenKnight, Bruce H; Armour, J Andrew

    2015-11-15

    Using vagus nerve stimulation (VNS), we sought to determine the contribution of vagal afferents to efferent control of cardiac function. In anesthetized dogs, the right and left cervical vagosympathetic trunks were stimulated in the intact state, following ipsilateral or contralateral vagus nerve transection (VNTx), and then following bilateral VNTx. Stimulations were performed at currents from 0.25 to 4.0 mA, frequencies from 2 to 30 Hz, and a 500-μs pulse width. Right or left VNS evoked significantly greater current- and frequency-dependent suppression of chronotropic, inotropic, and lusitropic function subsequent to sequential VNTx. Bradycardia threshold was defined as the current first required for a 5% decrease in heart rate. The threshold for the right vs. left vagus-induced bradycardia in the intact state (2.91 ± 0.18 and 3.47 ± 0.20 mA, respectively) decreased significantly with right VNTx (1.69 ± 0.17 mA for right and 3.04 ± 0.27 mA for left) and decreased further following bilateral VNTx (1.29 ± 0.16 mA for right and 1.74 ± 0.19 mA for left). Similar effects were observed following left VNTx. The thresholds for afferent-mediated effects on cardiac parameters were 0.62 ± 0.04 and 0.65 ± 0.06 mA with right and left VNS, respectively, and were reflected primarily as augmentation. Afferent-mediated tachycardias were maintained following β-blockade but were eliminated by VNTx. The increased effectiveness and decrease in bradycardia threshold with sequential VNTx suggest that 1) vagal afferents inhibit centrally mediated parasympathetic efferent outflow and 2) the ipsilateral and contralateral vagi exert a substantial buffering capacity. The intact threshold reflects the interaction between multiple levels of the cardiac neural hierarchy. Copyright © 2015 the American Physiological Society.

  20. The Synapse Project: Engagement in mentally challenging activities enhances neural efficiency.

    Science.gov (United States)

    McDonough, Ian M; Haber, Sara; Bischof, Gérard N; Park, Denise C

    2015-01-01

    Correlational and limited experimental evidence suggests that an engaged lifestyle is associated with the maintenance of cognitive vitality in old age. However, the mechanisms underlying these engagement effects are poorly understood. We hypothesized that mental effort underlies engagement effects and used fMRI to examine the impact of high-challenge activities (digital photography and quilting) compared with low-challenge activities (socializing or performing low-challenge cognitive tasks) on neural function at pretest, posttest, and one year after the engagement program. In the scanner, participants performed a semantic-classification task with two levels of difficulty to assess the modulation of brain activity in response to task demands. The High-Challenge group, but not the Low-Challenge group, showed increased modulation of brain activity in medial frontal, lateral temporal, and parietal cortex-regions associated with attention and semantic processing-some of which were maintained a year later. This increased modulation stemmed from decreases in brain activity during the easy condition for the High-Challenge group and was associated with time committed to the program, age, and cognition. Sustained engagement in cognitively demanding activities facilitated cognition by increasing neural efficiency. Mentally-challenging activities may be neuroprotective and an important element to maintaining a healthy brain into late adulthood.

  1. GABAA receptors in visual and auditory cortex and neural activity changes during basic visual stimulation

    Directory of Open Access Journals (Sweden)

    Pengmin eQin

    2012-12-01

    Full Text Available Recent imaging studies have demonstrated that levels of resting GABA in the visual cortex predict the degree of stimulus-induced activity in the same region. These studies have used the presentation of discrete visual stimulus; the change from closed eyes to open also represents a simple visual stimulus, however, and has been shown to induce changes in local brain activity and in functional connectivity between regions. We thus aimed to investigate the role of the GABA system, specifically GABAA receptors, in the changes in brain activity between the eyes closed (EC and eyes open (EO state in order to provide detail at the receptor level to complement previous studies of GABA concentrations. We conducted an fMRI study involving two different modes of the change from EC to EO: An EO and EC block design, allowing the modelling of the haemodynamic response, followed by longer periods of EC and EO to allow the measuring of functional connectivity. The same subjects also underwent [18F]Flumazenil PET measure GABAA receptor binding potentials. It was demonstrated that the local-to-global ratio of GABAA receptor binding potential in the visual cortex predicted the degree of changes in neural activity from EC to EO. This same relationship was also shown in the auditory cortex. Furthermore, the local-to-global ratio of GABAA receptor binding potential in the visual cortex also predicts the change of functional connectivity between visual and auditory cortex from EC to EO. These findings contribute to our understanding of the role of GABAA receptors in stimulus-induced neural activity in local regions and in inter-regional functional connectivity.

  2. FPGA IMPLEMENTATION OF ADAPTIVE INTEGRATED SPIKING NEURAL NETWORK FOR EFFICIENT IMAGE RECOGNITION SYSTEM

    Directory of Open Access Journals (Sweden)

    T. Pasupathi

    2014-05-01

    Full Text Available Image recognition is a technology which can be used in various applications such as medical image recognition systems, security, defense video tracking, and factory automation. In this paper we present a novel pipelined architecture of an adaptive integrated Artificial Neural Network for image recognition. In our proposed work we have combined the feature of spiking neuron concept with ANN to achieve the efficient architecture for image recognition. The set of training images are trained by ANN and target output has been identified. Real time videos are captured and then converted into frames for testing purpose and the image were recognized. The machine can operate at up to 40 frames/sec using images acquired from the camera. The system has been implemented on XC3S400 SPARTAN-3 Field Programmable Gate Arrays.

  3. Efficient organ localization using multi-label convolutional neural networks in thorax-abdomen CT scans

    Science.gov (United States)

    Efrain Humpire-Mamani, Gabriel; Arindra Adiyoso Setio, Arnaud; van Ginneken, Bram; Jacobs, Colin

    2018-04-01

    Automatic localization of organs and other structures in medical images is an important preprocessing step that can improve and speed up other algorithms such as organ segmentation, lesion detection, and registration. This work presents an efficient method for simultaneous localization of multiple structures in 3D thorax-abdomen CT scans. Our approach predicts the location of multiple structures using a single multi-label convolutional neural network for each orthogonal view. Each network takes extra slices around the current slice as input to provide extra context. A sigmoid layer is used to perform multi-label classification. The output of the three networks is subsequently combined to compute a 3D bounding box for each structure. We used our approach to locate 11 structures of interest. The neural network was trained and evaluated on a large set of 1884 thorax-abdomen CT scans from patients undergoing oncological workup. Reference bounding boxes were annotated by human observers. The performance of our method was evaluated by computing the wall distance to the reference bounding boxes. The bounding boxes annotated by the first human observer were used as the reference standard for the test set. Using the best configuration, we obtained an average wall distance of 3.20~+/-~7.33 mm in the test set. The second human observer achieved 1.23~+/-~3.39 mm. For all structures, the results were better than those reported in previously published studies. In conclusion, we proposed an efficient method for the accurate localization of multiple organs. Our method uses multiple slices as input to provide more context around the slice under analysis, and we have shown that this improves performance. This method can easily be adapted to handle more organs.

  4. Elimination of the geomagnetic field stimulates the proliferation of mouse neural progenitor and stem cells

    Directory of Open Access Journals (Sweden)

    Jing-Peng Fu

    2016-08-01

    Full Text Available Abstract Living organisms are exposed to the geomagnetic field (GMF throughout their lifespan. Elimination of the GMF, resulting in a hypogeomagnetic field (HMF, leads to central nervous system dysfunction and abnormal development in animals. However, the cellular mechanisms underlying these effects have not been identified so far. Here, we show that exposure to an HMF (<200 nT, produced by a magnetic field shielding chamber, promotes the proliferation of neural progenitor/stem cells (NPCs/NSCs from C57BL/6 mice. Following seven-day HMF-exposure, the primary neurospheres (NSs were significantly larger in size, and twice more NPCs/NSCs were harvested from neonatal NSs, when compared to the GMF controls. The self-renewal capacity and multipotency of the NSs were maintained, as HMF-exposed NSs were positive for NSC markers (Nestin and Sox2, and could differentiate into neurons and astrocyte/glial cells and be passaged continuously. In addition, adult mice exposed to the HMF for one month were observed to have a greater number of proliferative cells in the subventricular zone. These findings indicate that continuous HMF-exposure increases the proliferation of NPCs/NSCs, in vitro and in vivo. HMF-disturbed NPCs/NSCs production probably affects brain development and function, which provides a novel clue for elucidating the cellular mechanisms of the bio-HMF response.

  5. Effects of Electromagnetic Stimulation on Cell Density and Neural Markers in Murine Enteric Cell Cultures

    International Nuclear Information System (INIS)

    Carreon-Rodriguez, A.; Belkind-Gerson, J.; Serrano-Luna, G.; Canedo-Dorantes, L.

    2008-01-01

    Availability of adult stem cells from several organs like bone marrow, umbilical cord blood or peripheral blood has become a powerful therapeutic tool for many chronic diseases. Potential of adult stem cells for regeneration extents to other tissues among them the nervous system. However two obstacles should be resolved before such cells could be currently applied in clinical practice: a) slow growth rate and b) ability to form enough dense colonies in order to populate a specific injury or cellular deficiency. Many approaches have been explored as genetic differentiation programs, growth factors, and supplemented culture media, among others. Electromagnetic field stimulation of differentiation, proliferation, migration, and particularly on neurogenesis is little known. Since the biological effects of ELF-EMF are well documented, we hypothesize ELF-EMF could affect growth and maturation of stem cells derived of enteric tissue

  6. 1 mm3-sized optical neural stimulator based on CMOS integrated photovoltaic power receiver

    Science.gov (United States)

    Tokuda, Takashi; Ishizu, Takaaki; Nattakarn, Wuthibenjaphonchai; Haruta, Makito; Noda, Toshihiko; Sasagawa, Kiyotaka; Sawan, Mohamad; Ohta, Jun

    2018-04-01

    In this work, we present a simple complementary metal-oxide semiconductor (CMOS)-controlled photovoltaic power-transfer platform that is suitable for very small (less than or equal to 1-2 mm) electronic devices such as implantable health-care devices or distributed nodes for the Internet of Things. We designed a 1.25 mm × 1.25 mm CMOS power receiver chip that contains integrated photovoltaic cells. We characterized the CMOS-integrated power receiver and successfully demonstrated blue light-emitting diode (LED) operation powered by infrared light. Then, we integrated the CMOS chip and a few off-chip components into a 1-mm3 implantable optogenetic stimulator, and demonstrated the operation of the device.

  7. Enhanced control of electrochemical response in metallic materials in neural stimulation electrode applications

    Energy Technology Data Exchange (ETDEWEB)

    Watkins, K.G.; Steen, W.M.; Manna, I. [Univ. of Liverpool (United Kingdom)] [and others

    1996-12-31

    New means have been investigated for the production of electrode devices (stimulation electrodes) which could be implanted in the human body in order to control pain, activate paralysed limbs or provide electrode arrays for cochlear implants for the deaf or for the relief of tinitus. To achieve this ion implantation and laser materials processing techniques were employed. Ir was ion implanted in Ti-6Al-4V alloy and the surface subsequently enriched in the noble metal by dissolution in sulphuric acid. For laser materials processing techniques, investigation has been carried out on the laser cladding and laser alloying of Ir in Ti wire. A particular aim has been the determination of conditions required for the formation of a two phase Ir, Ir-rich, and Ti-rich microstructure which would enable subsequent removal of the non-noble phase to leave a highly porous noble metal with large real surface area and hence improved charge carrying capacity compared with conventional non porous electrodes. Evaluation of the materials produced has been carried out using repetitive cyclic voltammetry, amongst other techniques. For laser alloyed Ir on Ti wire, it has been found that differences in the melting point and density of the materials makes control of the cladding or alloying process difficult. Investigation of laser process parameters for the control of alloying and cladding in this system was carried out and a set of conditions for the successful production of two phase Ir-rich and Ti-rich components in a coating layer with strong metallurgical bonding to the Ti alloy substrate was derived. The laser processed material displays excellent potential for further development in providing stimulation electrodes with the current carrying capacity of Ir but in a form which is malleable and hence capable of formation into smaller electrodes with improved spatial resolution compared with presently employed electrodes.

  8. Artificial neural networks: an efficient tool for modelling and optimization of biofuel production (a mini review)

    International Nuclear Information System (INIS)

    Sewsynker-Sukai, Yeshona; Faloye, Funmilayo; Kana, Evariste Bosco Gueguim

    2016-01-01

    In view of the looming energy crisis as a result of depleting fossil fuel resources and environmental concerns from greenhouse gas emissions, the need for sustainable energy sources has secured global attention. Research is currently focused towards renewable sources of energy due to their availability and environmental friendliness. Biofuel production like other bioprocesses is controlled by several process parameters including pH, temperature and substrate concentration; however, the improvement of biofuel production requires a robust process model that accurately relates the effect of input variables to the process output. Artificial neural networks (ANNs) have emerged as a tool for modelling complex, non-linear processes. ANNs are applied in the prediction of various processes; they are useful for virtual experimentations and can potentially enhance bioprocess research and development. In this study, recent findings on the application of ANN for the modelling and optimization of biohydrogen, biogas, biodiesel, microbial fuel cell technology and bioethanol are reviewed. In addition, comparative studies on the modelling efficiency of ANN and other techniques such as the response surface methodology are briefly discussed. The review highlights the efficiency of ANNs as a modelling and optimization tool in biofuel process development

  9. Probing neural mechanisms underlying auditory stream segregation in humans by transcranial direct current stimulation (tDCS).

    Science.gov (United States)

    Deike, Susann; Deliano, Matthias; Brechmann, André

    2016-10-01

    One hypothesis concerning the neural underpinnings of auditory streaming states that frequency tuning of tonotopically organized neurons in primary auditory fields in combination with physiological forward suppression is necessary for the separation of representations of high-frequency A and low-frequency B tones. The extent of spatial overlap between the tonotopic activations of A and B tones is thought to underlie the perceptual organization of streaming sequences into one coherent or two separate streams. The present study attempts to interfere with these mechanisms by transcranial direct current stimulation (tDCS) and to probe behavioral outcomes reflecting the perception of ABAB streaming sequences. We hypothesized that tDCS by modulating cortical excitability causes a change in the separateness of the representations of A and B tones, which leads to a change in the proportions of one-stream and two-stream percepts. To test this, 22 subjects were presented with ambiguous ABAB sequences of three different frequency separations (∆F) and had to decide on their current percept after receiving sham, anodal, or cathodal tDCS over the left auditory cortex. We could confirm our hypothesis at the most ambiguous ∆F condition of 6 semitones. For anodal compared with sham and cathodal stimulation, we found a significant decrease in the proportion of two-stream perception and an increase in the proportion of one-stream perception. The results demonstrate the feasibility of using tDCS to probe mechanisms underlying auditory streaming through the use of various behavioral measures. Moreover, this approach allows one to probe the functions of auditory regions and their interactions with other processing stages. Copyright © 2016 The Authors. Published by Elsevier Ltd.. All rights reserved.

  10. Neural regulation of duodenal alkali secretion: Effects of electrical field stimulation

    International Nuclear Information System (INIS)

    Crampton, J.R.; Gibbons, L.G.; Rees, W.D.W.

    1988-01-01

    The role of transmitters released from enteric neurons in regulating bicarbonate secretion by the proximal duodenum has been studied using electrical field stimulation (EFS). Stripped duodenal mucosa from Rana catesbeiana was mounted as an intact tube over circular platinum electrode,s and luminal alkalinization was measured by pH stat titration before, during, and after EFS. Transmucosal potential difference (PD) was simultaneously measured before and after EFS by paired electrodes. Square-wave pulses 50 V, 2 ms in duration, at 10 Hz were delivered in trains of 0.5 s at 1 Hz for periods of 15 min after stable basal secretion. This resulted in a 63 ± 27% increase in alkalinization that returned to basal values after cessation of the stimulus, without change in transmucosal PD. Serosal-to-lumen [ 3 H]mannitol flux was not affected. Repetition of the stimulus resulted in a similar responses for as long as the tissue remained viable. The response to EFS was abolished by tetrodotoxin and veratrine indicating that intrinsic neurons were responsible for mediating the effect. In addition, the effect was blocked by serosal dinitrophenol, indicating that the secretory response occurred by a metabolically dependent process. These results indicate that alkalinization by proximal duodenum may be controlled by neurotransmitter release from local enteric neurons

  11. The dynamic efficiency of instruments for stimulating the dissemination of renewable energy technologies

    Energy Technology Data Exchange (ETDEWEB)

    Lamy, M.L.; Menanteau, Ph.; Finon, D.

    2002-06-01

    In this paper the authors examine the efficiency of the different incentive schemes for the development of renewable energy sources, both from a theoretical point of view by comparing price-based approaches with quantity-based approaches, and from a practical point of view by looking at concrete examples of how these different instruments have been implemented. The main focus is on the dynamic efficiency of the different instruments taking as an illustration the recent experience of stimulating wind power development in European countries. Theoretically, price-based or quantity-based approaches should be comparable methods for achieving renewable energy targets but uncertainty and implementing conditions may modify the symmetry of the two approaches. Accordingly, fixed feed in tariffs have clearly been superior to competitive bidding as far as installed capacity or industrial development are concerned. Finally the paper also examines the possibility that the price versus quantity issue could be reactivated with the emergence of the green certificate markets which present theoretical advantages of quota-based approaches without the limitations of competitive bidding systems. (author)

  12. Fluvoxamine stimulates oligodendrogenesis of cultured neural stem cells and attenuates inflammation and demyelination in an animal model of multiple sclerosis.

    Science.gov (United States)

    Ghareghani, Majid; Zibara, Kazem; Sadeghi, Heibatollah; Dokoohaki, Shima; Sadeghi, Hossein; Aryanpour, Roya; Ghanbari, Amir

    2017-07-07

    Multiple Sclerosis (MS) require medications controlling severity of the pathology and depression, affecting more than half of the patients. In this study, the effect of antidepressant drug fluvoxamine, a selective serotonin reuptake inhibitor, was investigated in vitro and in vivo. Nanomolar concentrations of fluvoxamine significantly increased cell viability and proliferation of neural stem cells (NSCs) through increasing mRNA expression of Notch1, Hes1 and Ki-67, and protein levels of NICD. Also, physiological concentrations of fluvoxamine were optimal for NSC differentiation toward oligodendrocytes, astrocytes and neurons. In addition, fluvoxamine attenuated experimental autoimmune encephalomyelitis (EAE) severity, a rat MS model, by significantly decreasing its clinical scores. Moreover, fluvoxamine treated EAE rats showed a decrease in IFN-γ serum levels and an increase in IL-4, pro- and anti-inflammatory cytokines respectively, compared to untreated EAE rats. Furthermore, immune cell infiltration and demyelination plaque significantly decreased in spinal cords of fluvoxamine-treated rats, which was accompanied by an increase in protein expression of MBP and GFAP positive cells and a decrease in lactate serum levels, a new biomarker of MS progression. In summary, besides its antidepressant activity, fluvoxamine stimulates proliferation and differentiation of NSCs particularly toward oligodendrocytes, a producer of CNS myelin.

  13. Emotion recognition impairment and apathy after subthalamic nucleus stimulation in Parkinson's disease have separate neural substrates.

    Science.gov (United States)

    Drapier, D; Péron, J; Leray, E; Sauleau, P; Biseul, I; Drapier, S; Le Jeune, F; Travers, D; Bourguignon, A; Haegelen, C; Millet, B; Vérin, M

    2008-09-01

    To test the hypothesis that emotion recognition and apathy share the same functional circuit involving the subthalamic nucleus (STN). A consecutive series of 17 patients with advanced Parkinson's disease (PD) was assessed 3 months before (M-3) and 3 months (M+3) after STN deep brain stimulation (DBS). Mean (+/-S.D.) age at surgery was 56.9 (8.7) years. Mean disease duration at surgery was 11.8 (2.6) years. Apathy was measured using the Apathy Evaluation Scale (AES) at both M-3 and M3. Patients were also assessed using a computerised paradigm of facial emotion recognition [Ekman, P., & Friesen, W. V. (1976). Pictures of facial affect. Palo Alto: Consulting Psychologist Press] before and after STN DBS. Prior to this, the Benton Facial Recognition Test was used to check that the ability to perceive faces was intact. Apathy had significantly worsened at M3 (42.5+/-8.9, p=0.006) after STN-DBS, in relation to the preoperative assessment (37.2+/-5.5). There was also a significant reduction in recognition percentages for facial expressions of fear (43.1%+/-22.9 vs. 61.6%+/-21.4, p=0.022) and sadness (52.7%+/-19.1 vs. 67.6%+/-22.8, p=0.031) after STN DBS. However, the postoperative worsening of apathy and emotion recognition impairment were not correlated. Our results confirm that the STN is involved in both the apathy and emotion recognition networks. However, the absence of any correlation between apathy and emotion recognition impairment suggests that the worsening of apathy following surgery could not be explained by a lack of facial emotion recognition and that its behavioural and cognitive components should therefore also be taken into consideration.

  14. Vertical electric field stimulated neural cell functionality on porous amorphous carbon electrodes.

    Science.gov (United States)

    Jain, Shilpee; Sharma, Ashutosh; Basu, Bikramjit

    2013-12-01

    We demonstrate the efficacy of amorphous macroporous carbon substrates as electrodes to support neuronal cell proliferation and differentiation in electric field mediated culture conditions. The electric field was applied perpendicular to carbon substrate electrode, while growing mouse neuroblastoma (N2a) cells in vitro. The placement of the second electrode outside of the cell culture medium allows the investigation of cell response to electric field without the concurrent complexities of submerged electrodes such as potentially toxic electrode reactions, electro-kinetic flows and charge transfer (electrical current) in the cell medium. The macroporous carbon electrodes are uniquely characterized by a higher specific charge storage capacity (0.2 mC/cm(2)) and low impedance (3.3 kΩ at 1 kHz). The optimal window of electric field stimulation for better cell viability and neurite outgrowth is established. When a uniform or a gradient electric field was applied perpendicular to the amorphous carbon substrate, it was found that the N2a cell viability and neurite length were higher at low electric field strengths (≤ 2.5 V/cm) compared to that measured without an applied field (0 V/cm). While the cell viability was assessed by two complementary biochemical assays (MTT and LDH), the differentiation was studied by indirect immunostaining. Overall, the results of the present study unambiguously establish the uniform/gradient vertical electric field based culture protocol to either enhance or to restrict neurite outgrowth respectively at lower or higher field strengths, when neuroblastoma cells are cultured on porous glassy carbon electrodes having a desired combination of electrochemical properties. Copyright © 2013 Elsevier Ltd. All rights reserved.

  15. Feed Forward Artificial Neural Network Model to Estimate the TPH Removal Efficiency in Soil Washing Process

    Directory of Open Access Journals (Sweden)

    Hossein Jafari Mansoorian

    2017-01-01

    Full Text Available Background & Aims of the Study: A feed forward artificial neural network (FFANN was developed to predict the efficiency of total petroleum hydrocarbon (TPH removal from a contaminated soil, using soil washing process with Tween 80. The main objective of this study was to assess the performance of developed FFANN model for the estimation of   TPH removal. Materials and Methods: Several independent repressors including pH, shaking speed, surfactant concentration and contact time were used to describe the removal of TPH as a dependent variable in a FFANN model. 85% of data set observations were used for training the model and remaining 15% were used for model testing, approximately. The performance of the model was compared with linear regression and assessed, using Root of Mean Square Error (RMSE as goodness-of-fit measure Results: For the prediction of TPH removal efficiency, a FANN model with a three-hidden-layer structure of 4-3-1 and a learning rate of 0.01 showed the best predictive results. The RMSE and R2 for the training and testing steps of the model were obtained to be 2.596, 0.966, 10.70 and 0.78, respectively. Conclusion: For about 80% of the TPH removal efficiency can be described by the assessed regressors the developed model. Thus, focusing on the optimization of soil washing process regarding to shaking speed, contact time, surfactant concentration and pH can improve the TPH removal performance from polluted soils. The results of this study could be the basis for the application of FANN for the assessment of soil washing process and the control of petroleum hydrocarbon emission into the environments.

  16. Exponential current pulse generation for efficient very high-impedance multisite stimulation.

    Science.gov (United States)

    Ethier, S; Sawan, M

    2011-02-01

    We describe in this paper an intracortical current-pulse generator for high-impedance microstimulation. This dual-chip system features a stimuli generator and a high-voltage electrode driver. The stimuli generator produces flexible rising exponential pulses in addition to standard rectangular stimuli. This novel stimulation waveform is expected to provide superior energy efficiency for action potential triggering while releasing less toxic reduced ions in the cortical tissues. The proposed fully integrated electrode driver is used as the output stage where high-voltage supplies are generated on-chip to significantly increase the voltage compliance for stimulation through high-impedance electrode-tissue interfaces. The stimuli generator has been implemented in 0.18-μm CMOS technology while a 0.8-μm CMOS/DMOS process has been used to integrate the high-voltage output stage. Experimental results show that the rectangular pulses cover a range of 1.6 to 167.2 μA with a DNL and an INL of 0.098 and 0.163 least-significant bit, respectively. The maximal dynamic range of the generated exponential reaches 34.36 dB at full scale within an error of ± 0.5 dB while all of its parameters (amplitude, duration, and time constant) are independently programmable over wide ranges. This chip consumes a maximum of 88.3 μ W in the exponential mode. High-voltage supplies of 8.95 and -8.46 V are generated by the output stage, boosting the voltage swing up to 13.6 V for a load as high as 100 kΩ.

  17. Noise exposure alters long-term neural firing rates and synchrony in primary auditory and rostral belt cortices following bimodal stimulation.

    Science.gov (United States)

    Takacs, Joseph D; Forrest, Taylor J; Basura, Gregory J

    2017-12-01

    We previously demonstrated that bimodal stimulation (spinal trigeminal nucleus [Sp5] paired with best frequency tone) altered neural tone-evoked and spontaneous firing rates (SFRs) in primary auditory cortex (A1) 15 min after pairing in guinea pigs with and without noise-induced tinnitus. Neural responses were enhanced (+10 ms) or suppressed (0 ms) based on the bimodal pairing interval. Here we investigated whether bimodal stimulation leads to long-term (up to 2 h) changes in tone-evoked and SFRs and neural synchrony (correlate of tinnitus) and if the long-term bimodal effects are altered following noise exposure. To obviate the effects of permanent hearing loss on the results, firing rates and neural synchrony were measured three weeks following unilateral (left ear) noise exposure and a temporary threshold shift. Simultaneous extra-cellular single-unit recordings were made from contralateral (to noise) A1 and dorsal rostral belt (RB); an associative auditory cortical region thought to influence A1, before and after bimodal stimulation (pairing intervals of 0 ms; simultaneous Sp5-tone and +10 ms; Sp5 precedes tone). Sixty and 120 min after 0 ms pairing tone-evoked and SFRs were suppressed in sham A1; an effect only preserved 120 min following pairing in noise. Stimulation at +10 ms only affected SFRs 120 min after pairing in sham and noise-exposed A1. Within sham RB, pairing at 0 and +10 ms persistently suppressed tone-evoked and SFRs, while 0 ms pairing in noise markedly enhanced tone-evoked and SFRs up to 2 h. Together, these findings suggest that bimodal stimulation has long-lasting effects in A1 that also extend to the associative RB that is altered by noise and may have persistent implications for how noise damaged brains process multi-sensory information. Moreover, prior to bimodal stimulation, noise damage increased neural synchrony in A1, RB and between A1 and RB neurons. Bimodal stimulation led to persistent changes in neural synchrony in

  18. Stimulation of marketing channels of innovations participants as the way of increasing its management efficiency

    OpenAIRE

    L.О. Syhyda

    2012-01-01

    In article participants of distribution marketing channel are defined. Variants of manufacturer stimulation carrying out are separated. Stages of stimulation process in marketing channel are offered. Methods of stimulation carrying out in marketing channels of traditional and innovative production are defined.

  19. EDITORIAL: Deep brain stimulation, deontology and duty: the moral obligation of non-abandonment at the neural interface Deep brain stimulation, deontology and duty: the moral obligation of non-abandonment at the neural interface

    Science.gov (United States)

    Fins, Joseph J.; MD; FACP

    2009-10-01

    intrusions on their bodies and their selves. Previously, I suggested that stimulation parameters for the treatment of neuropsychiatric disorders might be manipulated by patients one day. I envisioned a degree of patient discretion, within a pre-set safe range determined by physicians, much like patient-controlled analgesia (PCA) pumps give patients control over the dosing of opioid analgesia [3]. I am glad that such an advance is evolving as a means to preserve batteries in the treatment of motor disorders [16]. I would encourage the neural engineers to embrace the ethical mandate to develop additional platforms that might enhance patient self-determination and foster a greater degree of functional independence. While the neuromodulation community has every reason to celebrate its accomplishments, it would be better served by appreciating that the insertion of a device into the human brain comes with, if not the penumbra of sacrilege, a moral obligation to step out of the shadows and remain clearly available to patients and families over the long haul. Although neuromodulation has liberated many patients from the shackles of disease, we need to appreciate that the hardware that has made this possible can remain tethering. The challenge for the next generation of innovators is to minimize these burdens at this neural interface. By reducing barriers to care that exist in an unprepared health care system and developing more user-friendly technology, the neuromodulation community can expand its reach and broaden the relief provided by these neuro-palliative interventions [17]. Acknowledgements and Disclosures Dr Fins is the recipient of an Investigator Award in Health Policy Research (Minds Apart: Severe Brain Injury and Health Policy) from The Robert Wood Johnson Foundation. He also gratefully acknowledges grant support from the Buster Foundation (Neuroethics and Disorders of Consciousness). He is an unfunded co-investigator of a study of deep brain stimulation in the minimally

  20. Spinal Cord Stimulation (SCS) with Anatomically Guided (3D) Neural Targeting Shows Superior Chronic Axial Low Back Pain Relief Compared to Traditional SCS-LUMINA Study.

    Science.gov (United States)

    Veizi, Elias; Hayek, Salim M; North, James; Brent Chafin, T; Yearwood, Thomas L; Raso, Louis; Frey, Robert; Cairns, Kevin; Berg, Anthony; Brendel, John; Haider, Nameer; McCarty, Matthew; Vucetic, Henry; Sherman, Alden; Chen, Lilly; Mekel-Bobrov, Nitzan

    2017-08-01

    The aim of this study was to determine whether spinal cord stimulation (SCS) using 3D neural targeting provided sustained overall and low back pain relief in a broad routine clinical practice population. This was a multicenter, open-label observational study with an observational arm and retrospective analysis of a matched cohort. After IPG implantation, programming was done using a patient-specific, model-based algorithm to adjust for lead position (3D neural targeting) or previous generation software (traditional). Demographics, medical histories, SCS parameters, pain locations, pain intensities, disabilities, and safety data were collected for all patients. A total of 213 patients using 3D neural targeting were included, with a trial-to-implant ratio of 86%. Patients used seven different lead configurations, with 62% receiving 24 to 32 contacts, and a broad range of stimulation parameters utilizing a mean of 14.3 (±6.1) contacts. At 24 months postimplant, pain intensity decreased significantly from baseline (ΔNRS = 4.2, N = 169, P  pain subgroup (ΔNRS = 5.3, N = 91, P  low back pain also decreased significantly from baseline to 24 months (ΔNRS = 4.1, N = 70, P  pain responder rates of 51% (traditional SCS) and 74% (neural targeting SCS) and axial low back pain responder rates of 41% and 71% in the traditional SCS and neural targeting SCS cohorts, respectively. Lastly, complications occurred in a total of 33 of the 213 patients, with a 1.6% lead replacement rate and a 1.6% explant rate. Our results suggest that 3D neural targeting SCS and its associated hardware flexibility provide effective treatment for both chronic leg and chronic axial low back pain that is significantly superior to traditional SCS. © 2017 American Academy of Pain Medicine. All rights reserved. For permissions, please e-mail: journals.permissions@oup.com

  1. PreSMA stimulation changes task-free functional connectivity in the fronto-basal-ganglia that correlates with response inhibition efficiency.

    Science.gov (United States)

    Xu, Benjamin; Sandrini, Marco; Wang, Wen-Tung; Smith, Jason F; Sarlls, Joelle E; Awosika, Oluwole; Butman, John A; Horwitz, Barry; Cohen, Leonardo G

    2016-09-01

    Previous work using transcranial magnetic stimulation (TMS) demonstrated that the right presupplementary motor area (preSMA), a node in the fronto-basal-ganglia network, is critical for response inhibition. However, TMS influences interconnected regions, raising the possibility of a link between the preSMA activity and the functional connectivity within the network. To understand this relationship, we applied single-pulse TMS to the right preSMA during functional magnetic resonance imaging when the subjects were at rest to examine changes in neural activity and functional connectivity within the network in relation to the efficiency of response inhibition evaluated with a stop-signal task. The results showed that preSMA-TMS increased activation in the right inferior-frontal cortex (rIFC) and basal ganglia and modulated their task-free functional connectivity. Both the TMS-induced changes in the basal-ganglia activation and the functional connectivity between rIFC and left striatum, and of the overall network correlated with the efficiency of response inhibition and with the white-matter microstructure along the preSMA-rIFC pathway. These results suggest that the task-free functional and structural connectivity between the rIFCop and basal ganglia are critical to the efficiency of response inhibition. Hum Brain Mapp 37:3236-3249, 2016. © 2016 Wiley Periodicals, Inc. © 2016 Wiley Periodicals, Inc.

  2. Encoding neural and synaptic functionalities in electron spin: A pathway to efficient neuromorphic computing

    Science.gov (United States)

    Sengupta, Abhronil; Roy, Kaushik

    2017-12-01

    Present day computers expend orders of magnitude more computational resources to perform various cognitive and perception related tasks that humans routinely perform every day. This has recently resulted in a seismic shift in the field of computation where research efforts are being directed to develop a neurocomputer that attempts to mimic the human brain by nanoelectronic components and thereby harness its efficiency in recognition problems. Bridging the gap between neuroscience and nanoelectronics, this paper attempts to provide a review of the recent developments in the field of spintronic device based neuromorphic computing. Description of various spin-transfer torque mechanisms that can be potentially utilized for realizing device structures mimicking neural and synaptic functionalities is provided. A cross-layer perspective extending from the device to the circuit and system level is presented to envision the design of an All-Spin neuromorphic processor enabled with on-chip learning functionalities. Device-circuit-algorithm co-simulation framework calibrated to experimental results suggest that such All-Spin neuromorphic systems can potentially achieve almost two orders of magnitude energy improvement in comparison to state-of-the-art CMOS implementations.

  3. Effects of transcranial direct current stimulation on hemichannel pannexin-1 and neural plasticity in rat model of cerebral infarction.

    Science.gov (United States)

    Jiang, T; Xu, R X; Zhang, A W; Di, W; Xiao, Z J; Miao, J Y; Luo, N; Fang, Y N

    2012-12-13

    The aim of this study was to investigate the effects of transcranial direct current stimulation (TDCS) on hemichannel pannexin-1 (PX1) in cortical neurons and neural plasticity, and explore the optimal time window of TDCS therapy after stroke. Adult male Sprague-Dawley rats (n=90) were randomly assigned to sham operation, middle cerebral artery occlusion (MCAO), and TDCS groups, and underwent sham operation, unilateral middle cerebral artery (MCA) electrocoagulation, and unilateral MCA electrocoagulation plus TDCS (daily anodal and cathodal 10 Hz, 0.1 mA TDCS for 30 min beginning day 1 after stroke), respectively. Motor function was assessed using the beam walking test (BWT), and density of dendritic spines (DS) and PX1 mRNA expression were compared among groups on days 3, 7, and 14 after stroke. Effects of PX1 blockage on DS in hippocampal neurons after hypoxia-ischemia were observed. TDCS significantly improved motor function on days 7 and 14 after stroke as indicated by reduced BWT scores compared with the MCAO group. The density of DS was decreased after stroke; the TDCS group had increased DS density compared with the MCAO group on days 3, 7, and 14 (all P<0.0001). Cerebral infarction induced increased PX1 mRNA expression on days 3, 7, and 14 (P<0.0001), and the peak PX1 mRNA expression was observed on day 7. TDCS did not decrease the up-regulated PX1 mRNA expression after stroke on day 3, but did reduce the increased post-stroke PX1 mRNA expression on days 7 and 14 (P<0.0001). TDCS increased the DS density after stroke, indicating that it may promote neural plasticity after stroke. TDCS intervention from day 7 to day 14 after stroke demonstrated motor function improvement and can down-regulate the elevated PX1 mRNA expression after stroke. Copyright © 2012 IBRO. Published by Elsevier Ltd. All rights reserved.

  4. 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

  5. Efficient and rapid derivation of primitive neural stem cells and generation of brain subtype neurons from human pluripotent stem cells.

    Science.gov (United States)

    Yan, Yiping; Shin, Soojung; Jha, Balendu Shekhar; Liu, Qiuyue; Sheng, Jianting; Li, Fuhai; Zhan, Ming; Davis, Janine; Bharti, Kapil; Zeng, Xianmin; Rao, Mahendra; Malik, Nasir; Vemuri, Mohan C

    2013-11-01

    Human pluripotent stem cells (hPSCs), including human embryonic stem cells and human induced pluripotent stem cells, are unique cell sources for disease modeling, drug discovery screens, and cell therapy applications. The first step in producing neural lineages from hPSCs is the generation of neural stem cells (NSCs). Current methods of NSC derivation involve the time-consuming, labor-intensive steps of an embryoid body generation or coculture with stromal cell lines that result in low-efficiency derivation of NSCs. In this study, we report a highly efficient serum-free pluripotent stem cell neural induction medium that can induce hPSCs into primitive NSCs (pNSCs) in 7 days, obviating the need for time-consuming, laborious embryoid body generation or rosette picking. The pNSCs expressed the neural stem cell markers Pax6, Sox1, Sox2, and Nestin; were negative for Oct4; could be expanded for multiple passages; and could be differentiated into neurons, astrocytes, and oligodendrocytes, in addition to the brain region-specific neuronal subtypes GABAergic, dopaminergic, and motor neurons. Global gene expression of the transcripts of pNSCs was comparable to that of rosette-derived and human fetal-derived NSCs. This work demonstrates an efficient method to generate expandable pNSCs, which can be further differentiated into central nervous system neurons and glia with temporal, spatial, and positional cues of brain regional heterogeneity. This method of pNSC derivation sets the stage for the scalable production of clinically relevant neural cells for cell therapy applications in good manufacturing practice conditions.

  6. Stronger efferent suppression of cochlear neural potentials by contralateral acoustic stimulation in awake than in anesthetized chinchilla

    Directory of Open Access Journals (Sweden)

    Cristian eAedo

    2015-03-01

    Full Text Available There are two types of sensory cells in the mammalian cochlea, inner hair cells, which make synaptic contact with auditory-nerve afferent fibers, and outer hair cells that are innervated by crossed and uncrossed medial olivocochlear (MOC efferent fibers. Contralateral acoustic stimulation activates the uncrossed efferent MOC fibers reducing cochlear neural responses, thus modifying the input to the central auditory system. The chinchilla, among all studied mammals, displays the lowest percentage of uncrossed MOC fibers raising questions about the strength and frequency distribution of the contralateral-sound effect in this species. On the other hand, MOC effects on cochlear sensitivity have been mainly studied in anesthetized animals and since the MOC-neuron activity depends on the level of anesthesia, it is important to assess the influence of anesthesia in the strength of efferent effects. Seven adult chinchillas (Chinchilla laniger were chronically implanted with round-window electrodes in both cochleae. We compared the effect of contralateral sound in awake and anesthetized condition. Compound action potentials (CAP and cochlear microphonics (CM were measured in the ipsilateral cochlea in response to tones in absence and presence of contralateral sound. Control measurements performed after middle-ear muscles section in one animal discarded any possible middle-ear reflex activation. Contralateral sound produced CAP amplitude reductions in all chinchillas, with suppression effects greater by about 1-3 dB in awake than in anesthetized animals. In contrast, CM amplitude increases of up to 1.9 dB were found in only three awake chinchillas. In both conditions the strongest efferent effects were produced by contralateral tones at frequencies equal or close to those of ipsilateral tones. Contralateral CAP suppressions for 1-6 kHz ipsilateral tones corresponded to a span of uncrossed MOC fiber innervation reaching at least the central third of the

  7. Stronger efferent suppression of cochlear neural potentials by contralateral acoustic stimulation in awake than in anesthetized chinchilla.

    Science.gov (United States)

    Aedo, Cristian; Tapia, Eduardo; Pavez, Elizabeth; Elgueda, Diego; Delano, Paul H; Robles, Luis

    2015-01-01

    There are two types of sensory cells in the mammalian cochlea, inner hair cells, which make synaptic contact with auditory-nerve afferent fibers, and outer hair cells that are innervated by crossed and uncrossed medial olivocochlear (MOC) efferent fibers. Contralateral acoustic stimulation activates the uncrossed efferent MOC fibers reducing cochlear neural responses, thus modifying the input to the central auditory system. The chinchilla, among all studied mammals, displays the lowest percentage of uncrossed MOC fibers raising questions about the strength and frequency distribution of the contralateral-sound effect in this species. On the other hand, MOC effects on cochlear sensitivity have been mainly studied in anesthetized animals and since the MOC-neuron activity depends on the level of anesthesia, it is important to assess the influence of anesthesia in the strength of efferent effects. Seven adult chinchillas (Chinchilla laniger) were chronically implanted with round-window electrodes in both cochleae. We compared the effect of contralateral sound in awake and anesthetized condition. Compound action potentials (CAP) and cochlear microphonics (CM) were measured in the ipsilateral cochlea in response to tones in absence and presence of contralateral sound. Control measurements performed after middle-ear muscles section in one animal discarded any possible middle-ear reflex activation. Contralateral sound produced CAP amplitude reductions in all chinchillas, with suppression effects greater by about 1-3 dB in awake than in anesthetized animals. In contrast, CM amplitude increases of up to 1.9 dB were found in only three awake chinchillas. In both conditions the strongest efferent effects were produced by contralateral tones at frequencies equal or close to those of ipsilateral tones. Contralateral CAP suppressions for 1-6 kHz ipsilateral tones corresponded to a span of uncrossed MOC fiber innervation reaching at least the central third of the chinchilla cochlea.

  8. Hybrid feedback feedforward: An efficient design of adaptive neural network control.

    Science.gov (United States)

    Pan, Yongping; Liu, Yiqi; Xu, Bin; Yu, Haoyong

    2016-04-01

    This paper presents an efficient hybrid feedback feedforward (HFF) adaptive approximation-based control (AAC) strategy for a class of uncertain Euler-Lagrange systems. The control structure includes a proportional-derivative (PD) control term in the feedback loop and a radial-basis-function (RBF) neural network (NN) in the feedforward loop, which mimics the human motor learning control mechanism. At the presence of discontinuous friction, a sigmoid-jump-function NN is incorporated to improve control performance. The major difference of the proposed HFF-AAC design from the traditional feedback AAC (FB-AAC) design is that only desired outputs, rather than both tracking errors and desired outputs, are applied as RBF-NN inputs. Yet, such a slight modification leads to several attractive properties of HFF-AAC, including the convenient choice of an approximation domain, the decrease of the number of RBF-NN inputs, and semiglobal practical asymptotic stability dominated by control gains. Compared with previous HFF-AAC approaches, the proposed approach possesses the following two distinctive features: (i) all above attractive properties are achieved by a much simpler control scheme; (ii) the bounds of plant uncertainties are not required to be known. Consequently, the proposed approach guarantees a minimum configuration of the control structure and a minimum requirement of plant knowledge for the AAC design, which leads to a sharp decrease of implementation cost in terms of hardware selection, algorithm realization and system debugging. Simulation results have demonstrated that the proposed HFF-AAC can perform as good as or even better than the traditional FB-AAC under much simpler control synthesis and much lower computational cost. Copyright © 2015 Elsevier Ltd. All rights reserved.

  9. Efficient Transfer Entropy Analysis of Non-Stationary Neural Time Series

    Science.gov (United States)

    Vicente, Raul; Díaz-Pernas, Francisco J.; Wibral, Michael

    2014-01-01

    Information theory allows us to investigate information processing in neural systems in terms of information transfer, storage and modification. Especially the measure of information transfer, transfer entropy, has seen a dramatic surge of interest in neuroscience. Estimating transfer entropy from two processes requires the observation of multiple realizations of these processes to estimate associated probability density functions. To obtain these necessary observations, available estimators typically assume stationarity of processes to allow pooling of observations over time. This assumption however, is a major obstacle to the application of these estimators in neuroscience as observed processes are often non-stationary. As a solution, Gomez-Herrero and colleagues theoretically showed that the stationarity assumption may be avoided by estimating transfer entropy from an ensemble of realizations. Such an ensemble of realizations is often readily available in neuroscience experiments in the form of experimental trials. Thus, in this work we combine the ensemble method with a recently proposed transfer entropy estimator to make transfer entropy estimation applicable to non-stationary time series. We present an efficient implementation of the approach that is suitable for the increased computational demand of the ensemble method's practical application. In particular, we use a massively parallel implementation for a graphics processing unit to handle the computationally most heavy aspects of the ensemble method for transfer entropy estimation. We test the performance and robustness of our implementation on data from numerical simulations of stochastic processes. We also demonstrate the applicability of the ensemble method to magnetoencephalographic data. While we mainly evaluate the proposed method for neuroscience data, we expect it to be applicable in a variety of fields that are concerned with the analysis of information transfer in complex biological, social, and

  10. Towards an Efficient Artificial Neural Network Pruning and Feature Ranking Tool

    KAUST Repository

    AlShahrani, Mona

    2015-01-01

    Artificial Neural Networks (ANNs) are known to be among the most effective and expressive machine learning models. Their impressive abilities to learn have been reflected in many broad application domains such as image recognition, medical diagnosis, online banking, robotics, dynamic systems, and many others. ANNs with multiple layers of complex non-linear transformations (a.k.a Deep ANNs) have shown recently successful results in the area of computer vision and speech recognition. ANNs are parametric models that approximate unknown functions in which parameter values (weights) are adapted during training. ANN’s weights can be large in number and thus render the trained model more complex with chances for “overfitting” training data. In this study, we explore the effects of network pruning on performance of ANNs and ranking of features that describe the data. Simplified ANN model results in fewer parameters, less computation and faster training. We investigate the use of Hessian-based pruning algorithms as well as simpler ones (i.e. non Hessian-based) on nine datasets with varying number of input features and ANN parameters. The Hessian-based Optimal Brain Surgeon algorithm (OBS) is robust but slow. Therefore a faster parallel Hessian- approximation is provided. An additional speedup is provided using a variant we name ‘Simple n Optimal Brain Surgeon’ (SNOBS), which represents a good compromise between robustness and time efficiency. For some of the datasets, the ANN pruning experiments show on average 91% reduction in the number of ANN parameters and about 60% - 90% in the number of ANN input features, while maintaining comparable or better accuracy to the case when no pruning is applied. Finally, we show through a comprehensive comparison with seven state-of-the art feature filtering methods that the feature selection and ranking obtained as a byproduct of the ANN pruning is comparable in accuracy to these methods.

  11. Towards an Efficient Artificial Neural Network Pruning and Feature Ranking Tool

    KAUST Repository

    AlShahrani, Mona

    2015-05-24

    Artificial Neural Networks (ANNs) are known to be among the most effective and expressive machine learning models. Their impressive abilities to learn have been reflected in many broad application domains such as image recognition, medical diagnosis, online banking, robotics, dynamic systems, and many others. ANNs with multiple layers of complex non-linear transformations (a.k.a Deep ANNs) have shown recently successful results in the area of computer vision and speech recognition. ANNs are parametric models that approximate unknown functions in which parameter values (weights) are adapted during training. ANN’s weights can be large in number and thus render the trained model more complex with chances for “overfitting” training data. In this study, we explore the effects of network pruning on performance of ANNs and ranking of features that describe the data. Simplified ANN model results in fewer parameters, less computation and faster training. We investigate the use of Hessian-based pruning algorithms as well as simpler ones (i.e. non Hessian-based) on nine datasets with varying number of input features and ANN parameters. The Hessian-based Optimal Brain Surgeon algorithm (OBS) is robust but slow. Therefore a faster parallel Hessian- approximation is provided. An additional speedup is provided using a variant we name ‘Simple n Optimal Brain Surgeon’ (SNOBS), which represents a good compromise between robustness and time efficiency. For some of the datasets, the ANN pruning experiments show on average 91% reduction in the number of ANN parameters and about 60% - 90% in the number of ANN input features, while maintaining comparable or better accuracy to the case when no pruning is applied. Finally, we show through a comprehensive comparison with seven state-of-the art feature filtering methods that the feature selection and ranking obtained as a byproduct of the ANN pruning is comparable in accuracy to these methods.

  12. Wavelet based artificial neural network applied for energy efficiency enhancement of decoupled HVAC system

    International Nuclear Information System (INIS)

    Jahedi, G.; Ardehali, M.M.

    2012-01-01

    Highlights: ► In HVAC systems, temperature and relative humidity are coupled and dynamic mathematical models are non-linear. ► A wavelet-based ANN is used in series with an infinite impulse response filter for self tuning of PD controller. ► Energy consumption is evaluated for a decoupled bi-linear HVAC system with variable air volume and variable water flow. ► Substantial enhancement in energy efficiency is realized, when the gain coefficients of PD controllers are tuned adaptively. - Abstract: Control methodologies could lower energy demand and consumption of heating, ventilating and air conditioning (HVAC) systems and, simultaneously, achieve better comfort conditions. However, the application of classical controllers is unsatisfactory as HVAC systems are non-linear and the control variables such as temperature and relative humidity (RH) inside the thermal zone are coupled. The objective of this study is to develop and simulate a wavelet-based artificial neural network (WNN) for self tuning of a proportional-derivative (PD) controller for a decoupled bi-linear HVAC system with variable air volume and variable water flow responsible for controlling temperature and RH of a thermal zone, where thermal comfort and energy consumption of the system are evaluated. To achieve the objective, a WNN is used in series with an infinite impulse response (IIR) filter for faster and more accurate identification of system dynamics, as needed for on-line use and off-line batch mode training. The WNN-IIR algorithm is used for self-tuning of two PD controllers for temperature and RH. The simulation results show that the WNN-IIR controller performance is superior, as compared with classical PD controller. The enhancement in efficiency of the HVAC system is accomplished due to substantially lower consumption of energy during the transient operation, when the gain coefficients of PD controllers are tuned in an adaptive manner, as the steady state setpoints for temperature and

  13. Vitamin E isomer δ-tocopherol enhances the efficiency of neural stem cell differentiation via L-type calcium channel.

    Science.gov (United States)

    Deng, Sihao; Hou, Guoqiang; Xue, Zhiqin; Zhang, Longmei; Zhou, Yuye; Liu, Chao; Liu, Yanqing; Li, Zhiyuan

    2015-01-12

    The effects of the vitamin E isomer δ-tocopherol on neural stem cell (NSC) differentiation have not been investigated until now. Here we investigated the effects of δ-tocopherol on NSC neural differentiation, maturation and its possible mechanisms. Neonatal rat NSCs were grown in suspended neurosphere cultures, and were identified by their expression of nestin protein and their capacity for self-renewal. Treatment with a low concentration of δ-tocopherol induced a significant increase in the percentage of β-III-tubulin-positive cells. δ-Tocopherol also stimulated morphological maturation of neurons in culture. We further observed that δ-tocopherol stimulation increased the expression of voltage-dependent Ca(2+) channels. Moreover, a L-type specific Ca(2+) channel blocker verapamil reduced the percentage of differentiated neurons after δ-tocopherol treatment, and blocked the effects of δ-tocopherol on NSC differentiation into neurons. Together, our study demonstrates that δ-tocopherol may act through elevation of L-type calcium channel activity to increase neuronal differentiation. Copyright © 2014 Elsevier Ireland Ltd. All rights reserved.

  14. A Design Methodology for Efficient Implementation of Deconvolutional Neural Networks on an FPGA

    OpenAIRE

    Zhang, Xinyu; Das, Srinjoy; Neopane, Ojash; Kreutz-Delgado, Ken

    2017-01-01

    In recent years deep learning algorithms have shown extremely high performance on machine learning tasks such as image classification and speech recognition. In support of such applications, various FPGA accelerator architectures have been proposed for convolutional neural networks (CNNs) that enable high performance for classification tasks at lower power than CPU and GPU processors. However, to date, there has been little research on the use of FPGA implementations of deconvolutional neural...

  15. Efficiency test of filtering methods for the removal of transcranial magnetic stimulation artifacts on human electroencephalography with artificially transcranial magnetic stimulation-corrupted signals

    Science.gov (United States)

    Zilber, Nicolas A.; Katayama, Yoshinori; Iramina, Keiji; Erich, Wintermantel

    2010-05-01

    A new approach is proposed to test the efficiency of methods, such as the Kalman filter and the independent component analysis (ICA), when applied to remove the artifacts induced by transcranial magnetic stimulation (TMS) from electroencephalography (EEG). By using EEG recordings corrupted by TMS induction, the shape of the artifacts is approximately described with a model based on an equivalent circuit simulation. These modeled artifacts are subsequently added to other EEG signals—this time not influenced by TMS. The resulting signals prove of interest since we also know their form without the pseudo-TMS artifacts. Therefore, they enable us to use a fit test to compare the signals we obtain after removing the artifacts with the original signals. This efficiency test turned out very useful in comparing the methods between them, as well as in determining the parameters of the filtering that give satisfactory results with the automatic ICA.

  16. Effects of Electrical and Optogenetic Deep Brain Stimulation on Synchronized Oscillatory Activity in Parkinsonian Basal Ganglia.

    Science.gov (United States)

    Ratnadurai-Giridharan, Shivakeshavan; Cheung, Chung C; Rubchinsky, Leonid L

    2017-11-01

    Conventional deep brain stimulation of basal ganglia uses high-frequency regular electrical pulses to treat Parkinsonian motor symptoms but has a series of limitations. Relatively new and not yet clinically tested, optogenetic stimulation is an effective experimental stimulation technique to affect pathological network dynamics. We compared the effects of electrical and optogenetic stimulation of the basal gangliaon the pathologicalParkinsonian rhythmic neural activity. We studied the network response to electrical stimulation and excitatory and inhibitory optogenetic stimulations. Different stimulations exhibit different interactions with pathological activity in the network. We studied these interactions for different network and stimulation parameter values. Optogenetic stimulation was found to be more efficient than electrical stimulation in suppressing pathological rhythmicity. Our findings indicate that optogenetic control of neural synchrony may be more efficacious than electrical control because of the different ways of how stimulations interact with network dynamics.

  17. Orphan nuclear receptor TLX activates Wnt/β-catenin signalling to stimulate neural stem cell proliferation and self-renewal

    Science.gov (United States)

    Qu, Qiuhao; Sun, Guoqiang; Li, Wenwu; Yang, Su; Ye, Peng; Zhao, Chunnian; Yu, Ruth T.; Gage, Fred H.; Evans, Ronald M.; Shi, Yanhong

    2010-01-01

    The nuclear receptor TLX (also known as NR2E1) is essential for adult neural stem cell self-renewal; however, the molecular mechanisms involved remain elusive. Here we show that TLX activates the canonical Wnt/β-catenin pathway in adult mouse neural stem cells. Furthermore, we demonstrate that Wnt/β-catenin signalling is important in the proliferation and self-renewal of adult neural stem cells in the presence of epidermal growth factor and fibroblast growth factor. Wnt7a and active β-catenin promote neural stem cell self-renewal, whereas the deletion of Wnt7a or the lentiviral transduction of axin, a β-catenin inhibitor, led to decreased cell proliferation in adult neurogenic areas. Lentiviral transduction of active β-catenin led to increased numbers of type B neural stem cells in the subventricular zone of adult brains, whereas deletion of Wnt7a or TLX resulted in decreased numbers of neural stem cells retaining bromodeoxyuridine label in the adult brain. Both Wnt7a and active β-catenin significantly rescued a TLX (also known as Nr2e1) short interfering RNA-induced deficiency in neural stem cell proliferation. Lentiviral transduction of an active β-catenin increased cell proliferation in neurogenic areas of TLX-null adult brains markedly. These results strongly support the hypothesis that TLX acts through the Wnt/β-catenin pathway to regulate neural stem cell proliferation and self-renewal. Moreover, this study suggests that neural stem cells can promote their own self-renewal by secreting signalling molecules that act in an autocrine/paracrine mode. PMID:20010817

  18. Orphan nuclear receptor TLX activates Wnt/beta-catenin signalling to stimulate neural stem cell proliferation and self-renewal.

    Science.gov (United States)

    Qu, Qiuhao; Sun, Guoqiang; Li, Wenwu; Yang, Su; Ye, Peng; Zhao, Chunnian; Yu, Ruth T; Gage, Fred H; Evans, Ronald M; Shi, Yanhong

    2010-01-01

    The nuclear receptor TLX (also known as NR2E1) is essential for adult neural stem cell self-renewal; however, the molecular mechanisms involved remain elusive. Here we show that TLX activates the canonical Wnt/beta-catenin pathway in adult mouse neural stem cells. Furthermore, we demonstrate that Wnt/beta-catenin signalling is important in the proliferation and self-renewal of adult neural stem cells in the presence of epidermal growth factor and fibroblast growth factor. Wnt7a and active beta-catenin promote neural stem cell self-renewal, whereas the deletion of Wnt7a or the lentiviral transduction of axin, a beta-catenin inhibitor, led to decreased cell proliferation in adult neurogenic areas. Lentiviral transduction of active beta-catenin led to increased numbers of type B neural stem cells in the subventricular zone of adult brains, whereas deletion of Wnt7a or TLX resulted in decreased numbers of neural stem cells retaining bromodeoxyuridine label in the adult brain. Both Wnt7a and active beta-catenin significantly rescued a TLX (also known as Nr2e1) short interfering RNA-induced deficiency in neural stem cell proliferation. Lentiviral transduction of an active beta-catenin increased cell proliferation in neurogenic areas of TLX-null adult brains markedly. These results strongly support the hypothesis that TLX acts through the Wnt/beta-catenin pathway to regulate neural stem cell proliferation and self-renewal. Moreover, this study suggests that neural stem cells can promote their own self-renewal by secreting signalling molecules that act in an autocrine/paracrine mode.

  19. An Efficient Neural-Network-Based Microseismic Monitoring Platform for Hydraulic Fracture on an Edge Computing Architecture.

    Science.gov (United States)

    Zhang, Xiaopu; Lin, Jun; Chen, Zubin; Sun, Feng; Zhu, Xi; Fang, Gengfa

    2018-06-05

    Microseismic monitoring is one of the most critical technologies for hydraulic fracturing in oil and gas production. To detect events in an accurate and efficient way, there are two major challenges. One challenge is how to achieve high accuracy due to a poor signal-to-noise ratio (SNR). The other one is concerned with real-time data transmission. Taking these challenges into consideration, an edge-computing-based platform, namely Edge-to-Center LearnReduce, is presented in this work. The platform consists of a data center with many edge components. At the data center, a neural network model combined with convolutional neural network (CNN) and long short-term memory (LSTM) is designed and this model is trained by using previously obtained data. Once the model is fully trained, it is sent to edge components for events detection and data reduction. At each edge component, a probabilistic inference is added to the neural network model to improve its accuracy. Finally, the reduced data is delivered to the data center. Based on experiment results, a high detection accuracy (over 96%) with less transmitted data (about 90%) was achieved by using the proposed approach on a microseismic monitoring system. These results show that the platform can simultaneously improve the accuracy and efficiency of microseismic monitoring.

  20. An Efficient Neural-Network-Based Microseismic Monitoring Platform for Hydraulic Fracture on an Edge Computing Architecture

    Directory of Open Access Journals (Sweden)

    Xiaopu Zhang

    2018-06-01

    Full Text Available Microseismic monitoring is one of the most critical technologies for hydraulic fracturing in oil and gas production. To detect events in an accurate and efficient way, there are two major challenges. One challenge is how to achieve high accuracy due to a poor signal-to-noise ratio (SNR. The other one is concerned with real-time data transmission. Taking these challenges into consideration, an edge-computing-based platform, namely Edge-to-Center LearnReduce, is presented in this work. The platform consists of a data center with many edge components. At the data center, a neural network model combined with convolutional neural network (CNN and long short-term memory (LSTM is designed and this model is trained by using previously obtained data. Once the model is fully trained, it is sent to edge components for events detection and data reduction. At each edge component, a probabilistic inference is added to the neural network model to improve its accuracy. Finally, the reduced data is delivered to the data center. Based on experiment results, a high detection accuracy (over 96% with less transmitted data (about 90% was achieved by using the proposed approach on a microseismic monitoring system. These results show that the platform can simultaneously improve the accuracy and efficiency of microseismic monitoring.

  1. Modulation of neural activity in the temporoparietal junction with transcranial direct current stimulation changes the role of beliefs in moral judgment

    Directory of Open Access Journals (Sweden)

    Hang eYe

    2015-12-01

    Full Text Available Judgments about whether an action is morally right or wrong typically depend on our capacity to infer the actor’s beliefs and the outcomes of the action. Prior neuroimaging studies have found that mental state (e.g., beliefs, intentions attribution for moral judgment involves a complex neural network that includes the temporoparietal junction (TPJ. However, neuroimaging studies cannot demonstrate a direct causal relationship between the activity of this brain region and mental state attribution for moral judgment. In the current study, we used transcranial direct current stimulation (tDCS to transiently alter neural activity in the TPJ. The participants were randomly assigned to one of three stimulation treatments (right anodal/left cathodal tDCS, left anodal/right cathodal tDCS, or sham stimulation. Each participant was required to complete two similar tasks of moral judgment before receiving tDCS and after receiving tDCS. We studied whether tDCS to the TPJ altered mental state attribution for moral judgment. The results indicated that restraining the activity of the right temporoparietal junction (RTPJ or the left the temporoparietal junction (LTPJ decreased the role of beliefs in moral judgments and led to an increase in the dependence of the participants’ moral judgments on the action’s consequences. We also found that the participants exhibited reduced reaction times both in the cases of intentional harms and attempted harms after receiving right cathodal/left anodal tDCS to the TPJ. These findings inform and extend the current neural models of moral judgment and moral development in typically developing people and in individuals with neurodevelopmental disorders such as autism.

  2. Gold nanoparticles functionalized with a fragment of the neural cell adhesion molecule L1 stimulate L1-mediated functions

    Science.gov (United States)

    Schulz, Florian; Lutz, David; Rusche, Norman; Bastús, Neus G.; Stieben, Martin; Höltig, Michael; Grüner, Florian; Weller, Horst; Schachner, Melitta; Vossmeyer, Tobias; Loers, Gabriele

    2013-10-01

    The neural cell adhesion molecule L1 is involved in nervous system development and promotes regeneration in animal models of acute and chronic injury of the adult nervous system. To translate these conducive functions into therapeutic approaches, a 22-mer peptide that encompasses a minimal and functional L1 sequence of the third fibronectin type III domain of murine L1 was identified and conjugated to gold nanoparticles (AuNPs) to obtain constructs that interact homophilically with the extracellular domain of L1 and trigger the cognate beneficial L1-mediated functions. Covalent conjugation was achieved by reacting mixtures of two cysteine-terminated forms of this L1 peptide and thiolated poly(ethylene) glycol (PEG) ligands (~2.1 kDa) with citrate stabilized AuNPs of two different sizes (~14 and 40 nm in diameter). By varying the ratio of the L1 peptide-PEG mixtures, an optimized layer composition was achieved that resulted in the expected homophilic interaction of the AuNPs. These AuNPs were stable as tested over a time period of 30 days in artificial cerebrospinal fluid and interacted with the extracellular domain of L1 on neurons and Schwann cells, as could be shown by using cells from wild-type and L1-deficient mice. In vitro, the L1-derivatized particles promoted neurite outgrowth and survival of neurons from the central and peripheral nervous system and stimulated Schwann cell process formation and proliferation. These observations raise the hope that, in combination with other therapeutic approaches, L1 peptide-functionalized AuNPs may become a useful tool to ameliorate the deficits resulting from acute and chronic injuries of the mammalian nervous system.The neural cell adhesion molecule L1 is involved in nervous system development and promotes regeneration in animal models of acute and chronic injury of the adult nervous system. To translate these conducive functions into therapeutic approaches, a 22-mer peptide that encompasses a minimal and functional L1

  3. Neural and hybrid modeling: an alternative route to efficiently predict the behavior of biotechnological processes aimed at biofuels obtainment.

    Science.gov (United States)

    Curcio, Stefano; Saraceno, Alessandra; Calabrò, Vincenza; Iorio, Gabriele

    2014-01-01

    The present paper was aimed at showing that advanced modeling techniques, based either on artificial neural networks or on hybrid systems, might efficiently predict the behavior of two biotechnological processes designed for the obtainment of second-generation biofuels from waste biomasses. In particular, the enzymatic transesterification of waste-oil glycerides, the key step for the obtainment of biodiesel, and the anaerobic digestion of agroindustry wastes to produce biogas were modeled. It was proved that the proposed modeling approaches provided very accurate predictions of systems behavior. Both neural network and hybrid modeling definitely represented a valid alternative to traditional theoretical models, especially when comprehensive knowledge of the metabolic pathways, of the true kinetic mechanisms, and of the transport phenomena involved in biotechnological processes was difficult to be achieved.

  4. Neural and Hybrid Modeling: An Alternative Route to Efficiently Predict the Behavior of Biotechnological Processes Aimed at Biofuels Obtainment

    Directory of Open Access Journals (Sweden)

    Stefano Curcio

    2014-01-01

    Full Text Available The present paper was aimed at showing that advanced modeling techniques, based either on artificial neural networks or on hybrid systems, might efficiently predict the behavior of two biotechnological processes designed for the obtainment of second-generation biofuels from waste biomasses. In particular, the enzymatic transesterification of waste-oil glycerides, the key step for the obtainment of biodiesel, and the anaerobic digestion of agroindustry wastes to produce biogas were modeled. It was proved that the proposed modeling approaches provided very accurate predictions of systems behavior. Both neural network and hybrid modeling definitely represented a valid alternative to traditional theoretical models, especially when comprehensive knowledge of the metabolic pathways, of the true kinetic mechanisms, and of the transport phenomena involved in biotechnological processes was difficult to be achieved.

  5. Decision-making conflict and the neural efficiency hypothesis of intelligence: a functional near-infrared spectroscopy investigation.

    Science.gov (United States)

    Di Domenico, Stefano I; Rodrigo, Achala H; Ayaz, Hasan; Fournier, Marc A; Ruocco, Anthony C

    2015-04-01

    Research on the neural efficiency hypothesis of intelligence (NEH) has revealed that the brains of more intelligent individuals consume less energy when performing easy cognitive tasks but more energy when engaged in difficult mental operations. However, previous studies testing the NEH have relied on cognitive tasks that closely resemble psychometric tests of intelligence, potentially confounding efficiency during intelligence-test performance with neural efficiency per se. The present study sought to provide a novel test of the NEH by examining patterns of prefrontal activity while participants completed an experimental paradigm that is qualitatively distinct from the contents of psychometric tests of intelligence. Specifically, participants completed a personal decision-making task (e.g., which occupation would you prefer, dancer or chemist?) in which they made a series of forced choices according to their subjective preferences. The degree of decisional conflict (i.e., choice difficulty) between the available response options was manipulated on the basis of participants' unique preference ratings for the target stimuli, which were obtained prior to scanning. Evoked oxygenation of the prefrontal cortex was measured using 16-channel continuous-wave functional near-infrared spectroscopy. Consistent with the NEH, intelligence predicted decreased activation of the right inferior frontal gyrus (IFG) during low-conflict situations and increased activation of the right-IFG during high-conflict situations. This pattern of right-IFG activity among more intelligent individuals was complemented by faster reaction times in high-conflict situations. These results provide new support for the NEH and suggest that the neural efficiency of more intelligent individuals generalizes to the performance of cognitive tasks that are distinct from intelligence tests. Copyright © 2015 Elsevier Inc. All rights reserved.

  6. Application of Artificial Neural Networks for Efficient High-Resolution 2D DOA Estimation

    Directory of Open Access Journals (Sweden)

    M. Agatonović

    2012-12-01

    Full Text Available A novel method to provide high-resolution Two-Dimensional Direction of Arrival (2D DOA estimation employing Artificial Neural Networks (ANNs is presented in this paper. The observed space is divided into azimuth and elevation sectors. Multilayer Perceptron (MLP neural networks are employed to detect the presence of a source in a sector while Radial Basis Function (RBF neural networks are utilized for DOA estimation. It is shown that a number of appropriately trained neural networks can be successfully used for the high-resolution DOA estimation of narrowband sources in both azimuth and elevation. The training time of each smaller network is significantly re¬duced as different training sets are used for networks in detection and estimation stage. By avoiding the spectral search, the proposed method is suitable for real-time ap¬plications as it provides DOA estimates in a matter of seconds. At the same time, it demonstrates the accuracy comparable to that of the super-resolution 2D MUSIC algorithm.

  7. Efficient forward propagation of time-sequences in convolutional neural networks using Deep Shifting

    NARCIS (Netherlands)

    K.L. Groenland (Koen); S.M. Bohte (Sander)

    2016-01-01

    textabstractWhen a Convolutional Neural Network is used for on-the-fly evaluation of continuously updating time-sequences, many redundant convolution operations are performed. We propose the method of Deep Shifting, which remembers previously calculated results of convolution operations in order

  8. Effects of reinforcement-blocking doses of pimozide on neural systems driven by rewarding stimulation of the MFB: a /sup 14/C-2-deoxyglucose analysis

    Energy Technology Data Exchange (ETDEWEB)

    Gomita, Y.; Gallistel, C.R.

    1982-10-01

    An analysis by means of /sup 14/C-2-deoxyglucose autoradiography of the neural systems unilaterally activated by the reinforcing stimulation used in the two accompanying papers revealed strong and reliable effects in the nucleus of the diagonal band of Broca, in the medial forebrain bundle (MFB) and/or the fornix throughout the diencephalon, and in the part of the anterior ventral tegmentum where the dopaminergic projection to the lateral habenula originates. The terminal fields of the dopaminergic forebrain projections were not affected, but there was bilateral suppression of lateral habenular activity. A second experiment found that the same systems are still activated by (automatically administered) reinforcing stimulation in rats treated with reinforcement blocking doses of pimozide. The only clear effect of pimozide was to reverse the bilateral suppressive effect of the stimulation on lateral habenular activity. Animals treated with pimozide show greatly elevated activity in the lateral habenula, whether or not they receive reinforcing stimulation. The results suggest that pimozide's effect on reinforcement is mediated by the circuitry interconnecting the lateral habenula with the nucleus of the diagonal band of Broca and/or the anterior ventral tegmentum.

  9. A Simple fMRI Compatible Robotic Stimulator to Study the Neural Mechanisms of Touch and Pain.

    Science.gov (United States)

    Riillo, F; Bagnato, C; Allievi, A G; Takagi, A; Fabrizi, L; Saggio, G; Arichi, T; Burdet, E

    2016-08-01

    This paper presents a simple device for the investigation of the human somatosensory system with functional magnetic imaging (fMRI). PC-controlled pneumatic actuation is employed to produce innocuous or noxious mechanical stimulation of the skin. Stimulation patterns are synchronized with fMRI and other relevant physiological measurements like electroencephalographic activity and vital physiological parameters. The system allows adjustable regulation of stimulation parameters and provides consistent patterns of stimulation. A validation experiment demonstrates that the system safely and reliably identifies clusters of functional activity in brain regions involved in the processing of pain. This new device is inexpensive, portable, easy-to-assemble and customizable to suit different experimental requirements. It provides robust and consistent somatosensory stimulation, which is of crucial importance to investigating the mechanisms of pain and its strong connection with the sense of touch.

  10. Application of neural network technology to nuclear plant thermal efficiency improvement

    International Nuclear Information System (INIS)

    Doremus, Rick; Allen Ho, S.; Bailey, James V.; Roman, Harry

    2004-01-01

    Due to the tremendous cost of building new nuclear power plants, it has become increasingly attractive to increase the power output from the existing operating power plants. There are two options that may be available to accomplish this goal. One option is to uprate the plant through licensing modification for a comfortably achievable goal of 4% to 6%. However, the licensing efforts required are no small task, vary from plant to plant, and may take years to accomplish. Some nuclear power plants may not have this option because of design, environmental, political, or geographical limitations. A second option exists that is simpler and more immediate. It focuses on improving the plant operating conditions using adaptive software that could increase the total plant output by approximately one-half percent by adjusting certain key operating parameters. No design basis analyses, hardware modifications, or licensing changes are required. In fact, this technique can be used on a plant that has already obtained licensing modification to obtain an additional one-half percent on top of the 4% to 6% increase. Public Service Electric and Gas and ARD Corporation are jointly investigating the creation of a Plant Optimization System, called POSITIVE. POSITIVE is an adaptive software tool that enables a user to analyze current plant data to identify potential problem areas and to obtain recommendations for increasing the plant's electric output. POSITIVE uses a combination of expert systems and adaptive software to analyze the thermal performance of a nuclear power plant. Historical data, obtained while the plant was above 93% power, is used to train neural networks to determine the current electric output of the plant. Once sufficiently trained, new data can be processed through the neural network. The neural network first determines the electric output associated with the current data. If the actual power matches the power predicted by the network, the neural network can be used

  11. EGF–FGF{sub 2} stimulates the proliferation and improves the neuronal commitment of mouse epidermal neural crest stem cells (EPI-NCSCs)

    Energy Technology Data Exchange (ETDEWEB)

    Bressan, Raul Bardini; Melo, Fernanda Rosene; Almeida, Patricia Alves; Bittencourt, Denise Avani; Visoni, Silvia; Jeremias, Talita Silva [Departamento de Biologia Celular, Embriologia e Genética, Centro de Ciências Biológicas, Universidade Federal de Santa Catarina, Campus Universitário – Trindade, 88040-900 Florianópolis SC (Brazil); Costa, Ana Paula; Leal, Rodrigo Bainy [Departamento de Bioquímica, Centro de Ciências Biológicas, Universidade Federal de Santa Catarina, Campus Universitário – Trindade, 88040-900 Florianópolis SC (Brazil); Trentin, Andrea Gonçalves, E-mail: andrea.trentin@ufsc.br [Departamento de Biologia Celular, Embriologia e Genética, Centro de Ciências Biológicas, Universidade Federal de Santa Catarina, Campus Universitário – Trindade, 88040-900 Florianópolis SC (Brazil)

    2014-09-10

    Epidermal neural crest stem cells (EPI-NCSCs), which reside in the bulge of hair follicles, are attractive candidates for several applications in cell therapy, drug screening and tissue engineering. As suggested remnants of the embryonic neural crest (NC) in an adult location, EPI-NCSCs are able to generate a wide variety of cell types and are readily accessible by a minimally invasive procedure. Since the combination of epidermal growth factor (EGF) and fibroblast growth factor type 2 (FGF{sub 2}) is mitogenic and promotes the neuronal commitment of various stem cell populations, we examined its effects in the proliferation and neuronal potential of mouse EPI-NCSCs. By using a recognized culture protocol of bulge whiskers follicles, we were able to isolate a population of EPI-NCSCs, characterized by the migratory potential, cell morphology and expression of phenotypic markers of NC cells. EPI-NCSCs expressed neuronal, glial and smooth muscle markers and exhibited the NC-like fibroblastic morphology. The treatment with the combination EGF and FGF{sub 2}, however, increased their proliferation rate and promoted the acquisition of a neuronal-like morphology accompanied by reorganization of neural cytoskeletal proteins βIII-tubulin and nestin, as well as upregulation of the pan neuronal marker βIII-tubulin and down regulation of the undifferentiated NC, glial and smooth muscle cell markers. Moreover, the treatment enhanced the response of EPI-NCSCs to neurogenic stimulation, as evidenced by induction of GAP43, and increased expression of Mash-1 in neuron-like cell, both neuronal-specific proteins. Together, the results suggest that the combination of EGF–FGF2 stimulates the proliferation and improves the neuronal potential of EPI-NCSCs similarly to embryonic NC cells, ES cells and neural progenitor/stem cells of the central nervous system and highlights the advantage of using EGF–FGF{sub 2} in neuronal differentiation protocols. - Highlights: • EPI

  12. EGF–FGF2 stimulates the proliferation and improves the neuronal commitment of mouse epidermal neural crest stem cells (EPI-NCSCs)

    International Nuclear Information System (INIS)

    Bressan, Raul Bardini; Melo, Fernanda Rosene; Almeida, Patricia Alves; Bittencourt, Denise Avani; Visoni, Silvia; Jeremias, Talita Silva; Costa, Ana Paula; Leal, Rodrigo Bainy; Trentin, Andrea Gonçalves

    2014-01-01

    Epidermal neural crest stem cells (EPI-NCSCs), which reside in the bulge of hair follicles, are attractive candidates for several applications in cell therapy, drug screening and tissue engineering. As suggested remnants of the embryonic neural crest (NC) in an adult location, EPI-NCSCs are able to generate a wide variety of cell types and are readily accessible by a minimally invasive procedure. Since the combination of epidermal growth factor (EGF) and fibroblast growth factor type 2 (FGF 2 ) is mitogenic and promotes the neuronal commitment of various stem cell populations, we examined its effects in the proliferation and neuronal potential of mouse EPI-NCSCs. By using a recognized culture protocol of bulge whiskers follicles, we were able to isolate a population of EPI-NCSCs, characterized by the migratory potential, cell morphology and expression of phenotypic markers of NC cells. EPI-NCSCs expressed neuronal, glial and smooth muscle markers and exhibited the NC-like fibroblastic morphology. The treatment with the combination EGF and FGF 2 , however, increased their proliferation rate and promoted the acquisition of a neuronal-like morphology accompanied by reorganization of neural cytoskeletal proteins βIII-tubulin and nestin, as well as upregulation of the pan neuronal marker βIII-tubulin and down regulation of the undifferentiated NC, glial and smooth muscle cell markers. Moreover, the treatment enhanced the response of EPI-NCSCs to neurogenic stimulation, as evidenced by induction of GAP43, and increased expression of Mash-1 in neuron-like cell, both neuronal-specific proteins. Together, the results suggest that the combination of EGF–FGF2 stimulates the proliferation and improves the neuronal potential of EPI-NCSCs similarly to embryonic NC cells, ES cells and neural progenitor/stem cells of the central nervous system and highlights the advantage of using EGF–FGF 2 in neuronal differentiation protocols. - Highlights: • EPI-NCSCs express

  13. 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.

  14. Thymidine Kinase-Negative Herpes Simplex Virus 1 Can Efficiently Establish Persistent Infection in Neural Tissues of Nude Mice.

    Science.gov (United States)

    Huang, Chih-Yu; Yao, Hui-Wen; Wang, Li-Chiu; Shen, Fang-Hsiu; Hsu, Sheng-Min; Chen, Shun-Hua

    2017-02-15

    patients with persistent infection. However, answers to the questions as to whether TK-negative (TK - ) HSV-1 can establish persistent infection in brains of immunocompromised hosts and whether neurons in vivo are permissive for TK - HSV-1 remain elusive. Using three genetically engineered HSV-1 TK - mutants and two strains of nude mice deficient in T cells, we found that all three HSV-1 TK - mutants can efficiently establish persistent infection in the brain stem and trigeminal ganglion and detected glycoprotein C, a true late viral antigen, in brainstem neurons. Our study provides evidence that TK - HSV-1 can persist in neural tissues and replicate in brain neurons of immunocompromised hosts. Copyright © 2017 American Society for Microbiology.

  15. Efficient Embedded Decoding of Neural Network Language Models in a Machine Translation System.

    Science.gov (United States)

    Zamora-Martinez, Francisco; Castro-Bleda, Maria Jose

    2018-02-22

    Neural Network Language Models (NNLMs) are a successful approach to Natural Language Processing tasks, such as Machine Translation. We introduce in this work a Statistical Machine Translation (SMT) system which fully integrates NNLMs in the decoding stage, breaking the traditional approach based on [Formula: see text]-best list rescoring. The neural net models (both language models (LMs) and translation models) are fully coupled in the decoding stage, allowing to more strongly influence the translation quality. Computational issues were solved by using a novel idea based on memorization and smoothing of the softmax constants to avoid their computation, which introduces a trade-off between LM quality and computational cost. These ideas were studied in a machine translation task with different combinations of neural networks used both as translation models and as target LMs, comparing phrase-based and [Formula: see text]-gram-based systems, showing that the integrated approach seems more promising for [Formula: see text]-gram-based systems, even with nonfull-quality NNLMs.

  16. Stimulation of Efficient Employee Performance through Human Resource Management Practices: A Study on the Health Care Sector of Bangladesh

    Directory of Open Access Journals (Sweden)

    Fatema Nusrat

    2018-01-01

    Full Text Available As the world is becoming more competitive and unstable than ever before; health care sector, especially in a developing country like Bangladesh, is seeking to gain competitive advantage through the performance of its employees and is turning to be more innovative in this perspective through human resource management (HRM practices. Experts view HRM practices as a set of internally consistent policies and practices designed and implemented to ensure that the human capital of the organization contributes to the achievement of its objectives. This paper examined the effects of human resource management (HRM practices on stimulating or enhancing efficient employee performance in the health care sector of Bangladesh. Ten dimensions and 43 item statements of human resource management (HRM practices and efficient employee performance have been adopted to undertake this study. Data have been gathered following a quantitative survey by a structured questionnaire conducted among a diverse group of employees (N = 240 working in 20 different health care service providing organizations of Bangladesh following simple random sampling method. Several statistical techniques consisting of descriptive analysis, Pearson correlations, ANOVA, Coefficient and regression analysis have been applied using SPSS software to analyze the collected data for taking decisions regarding the hypotheses. The results of the statistical analysis reveal that human resource management (HRM practices positively stimulates efficient employee performance. This study therefore recommends among others: enhancement of motivation among employees, improvement in the reward system, establishment of strong organizational culture, training and re-training of employees,  and employees participation in decision making.

  17. Effects of oral stimulation with capsaicin on salivary secretion and neural activities in the autonomic system and the brain

    Directory of Open Access Journals (Sweden)

    Yoko Kono

    2018-06-01

    Conclusion: These results suggest that oral stimulation with capsaicin may be effective in improving oral conditions by increasing salivary flow and SIgA secretion, and in enhancing physical and mental conditions as indicated by sympathetic nerve and EEG changes.

  18. Effect of task complexity on intelligence and neural efficiency in children: an event-related potential study.

    Science.gov (United States)

    Zhang, Qiong; Shi, Jiannong; Luo, Yuejia; Liu, Sainan; Yang, Jie; Shen, Mowei

    2007-10-08

    The present study investigates the effects of task complexity, intelligence and neural efficiency on children's performance on an Elementary Cognitive Task. Twenty-three children were divided into two groups on the basis of their Raven Progressive Matrix scores and were then asked to complete a choice reaction task with two test conditions. We recorded the electroencephalogram and calculated the peak latencies and amplitudes for anteriorly distributed P225, N380 and late positive component. Our results suggested shorter late positive component latencies in brighter children, possibly reflecting a higher processing speed in these individuals. Increased P225 amplitude and increased N380 amplitudes for brighter children may indicate a more efficient allocation of attention for brighter children. No moderating effect of task complexity on brain-intelligence relationship was found.

  19. An Efficient Feature Extraction Method with Pseudo-Zernike Moment in RBF Neural Network-Based Human Face Recognition System

    Directory of Open Access Journals (Sweden)

    Ahmadi Majid

    2003-01-01

    Full Text Available This paper introduces a novel method for the recognition of human faces in digital images using a new feature extraction method that combines the global and local information in frontal view of facial images. Radial basis function (RBF neural network with a hybrid learning algorithm (HLA has been used as a classifier. The proposed feature extraction method includes human face localization derived from the shape information. An efficient distance measure as facial candidate threshold (FCT is defined to distinguish between face and nonface images. Pseudo-Zernike moment invariant (PZMI with an efficient method for selecting moment order has been used. A newly defined parameter named axis correction ratio (ACR of images for disregarding irrelevant information of face images is introduced. In this paper, the effect of these parameters in disregarding irrelevant information in recognition rate improvement is studied. Also we evaluate the effect of orders of PZMI in recognition rate of the proposed technique as well as RBF neural network learning speed. Simulation results on the face database of Olivetti Research Laboratory (ORL indicate that the proposed method for human face recognition yielded a recognition rate of 99.3%.

  20. Development of efficiency module of organization of Arctic sea cargo transportation with application of neural network technologies

    Science.gov (United States)

    Sobolevskaya, E. Yu; Glushkov, S. V.; Levchenko, N. G.; Orlov, A. P.

    2018-05-01

    The analysis of software intended for organizing and managing the processes of sea cargo transportation has been carried out. The shortcomings of information resources are presented, for the organization of work in the Arctic and Subarctic regions of the Far East: the lack of decision support systems, the lack of factor analysis to calculate the time and cost of delivery. The architecture of the module for calculating the effectiveness of the organization of sea cargo transportation has been developed. The simulation process has been considered, which is based on the neural network. The main classification factors with their weighting coefficients have been identified. The architecture of the neural network has been developed to calculate the efficiency of the organization of sea cargo transportation in Arctic conditions. The architecture of the intellectual system of organization of sea cargo transportation has been developed, taking into account the difficult navigation conditions in the Arctic. Its implementation will allow one to provide the management of the shipping company with predictive analytics; to support decision-making; to calculate the most efficient delivery route; to provide on demand online transportation forecast, to minimize the shipping cost, delays in transit, and risks to cargo safety.

  1. Applying a supervised ANN (artificial neural network) approach to the prognostication of driven wheel energy efficiency indices

    International Nuclear Information System (INIS)

    Taghavifar, Hamid; Mardani, Aref

    2014-01-01

    This paper examines the prediction of energy efficiency indices of driven wheels (i.e. traction coefficient and tractive power efficiency) as affected by wheel load, slippage and forward velocity at three different levels with three replicates to form a total of 162 data points. The pertinent experiments were carried out in the soil bin testing facility. A feed-forward ANN (artificial neural network) with standard BP (back propagation) algorithm was practiced to construct a supervised representation to predict the energy efficiency indices of driven wheels. It was deduced, in view of the statistical performance criteria (i.e. MSE (mean squared error) and R 2 ), that a supervised ANN with 3-8-10-2 topology and Levenberg–Marquardt training algorithm represented the optimal model. Modeling implementations indicated that ANN is a powerful technique to prognosticate the stochastic energy efficiency indices as affected by soil-wheel interactions with MSE of 0.001194 and R 2 of 0.987 and 0.9772 for traction coefficient and tractive power efficiency. It was found that traction coefficient and tractive power efficiency increase with increased slippage. A similar trend is valid for the influence of wheel load on the objective parameters. Wherein increase of velocity led to an increment of tractive power efficiency, velocity had no significant effect on traction coefficient. - Highlights: • Energy efficiency indexes were assessed as affected by tire parameters. • ANN was applied for prognostication of the objective parameters. • A 3-8-10-2 ANN with MSE of 0.001194 and R 2 of 0.987 and 0.9772 was designated as optimal model. • Optimal values of learning rate and momentum were found 0.9 and 0.5, respectively

  2. Opposing Effects of α2- and β-Adrenergic Receptor Stimulation on Quiescent Neural Precursor Cell Activity and Adult Hippocampal Neurogenesis

    Science.gov (United States)

    Prosper, Boris W.; Marathe, Swanand; Husain, Basma F. A.; Kernie, Steven G.; Bartlett, Perry F.; Vaidya, Vidita A.

    2014-01-01

    Norepinephrine regulates latent neural stem cell activity and adult hippocampal neurogenesis, and has an important role in modulating hippocampal functions such as learning, memory and mood. Adult hippocampal neurogenesis is a multi-stage process, spanning from the activation and proliferation of hippocampal stem cells, to their differentiation into neurons. However, the stage-specific effects of noradrenergic receptors in regulating adult hippocampal neurogenesis remain poorly understood. In this study, we used transgenic Nestin-GFP mice and neurosphere assays to show that modulation of α2- and β-adrenergic receptor activity directly affects Nestin-GFP/GFAP-positive precursor cell population albeit in an opposing fashion. While selective stimulation of α2-adrenergic receptors decreases precursor cell activation, proliferation and immature neuron number, stimulation of β-adrenergic receptors activates the quiescent precursor pool and enhances their proliferation in the adult hippocampus. Furthermore, our data indicate no major role for α1-adrenergic receptors, as we did not observe any change in either the activation and proliferation of hippocampal precursors following selective stimulation or blockade of α1-adrenergic receptors. Taken together, our data suggest that under physiological as well as under conditions that lead to enhanced norepinephrine release, the balance between α2- and β-adrenergic receptor activity regulates precursor cell activity and hippocampal neurogenesis. PMID:24922313

  3. Effective deep brain stimulation suppresses low frequency network oscillations in the basal ganglia by regularizing neural firing patterns

    Science.gov (United States)

    McConnell, George C.; So, Rosa Q.; Hilliard, Justin D; Lopomo, Paola; Grill, Warren M.

    2012-01-01

    Deep brain stimulation (DBS) of the subthalamic nucleus (STN) is an effective treatment for the motor symptoms of Parkinson’s disease (PD). The effects of DBS depend strongly on stimulation frequency: high frequencies (>90Hz) improve motor symptoms, while low frequencies (basal ganglia were studied in the unilateral 6-hydroxydopamine lesioned rat model of PD. Only high frequency DBS reversed motor symptoms and the effectiveness of DBS depended strongly on stimulation frequency in a manner reminiscent of its clinical effects in persons with PD. Quantification of single-unit activity in the globus pallidus externa (GPe) and substantia nigra reticulata (SNr) revealed that high frequency DBS, but not low frequency DBS, reduced pathological low frequency oscillations (~9Hz) and entrained neurons to fire at the stimulation frequency. Similarly, the coherence between simultaneously recorded pairs of neurons within and across GPe and SNr shifted from the pathological low frequency band to the stimulation frequency during high frequency DBS, but not during low frequency DBS. The changes in firing patterns in basal ganglia neurons were not correlated with changes in firing rate. These results indicate that high frequency DBS is more effective than low frequency DBS, not as a result of changes in firing rate, but rather due to its ability to replace pathological low frequency network oscillations with a regularized pattern of neuronal firing. PMID:23136407

  4. Effective deep brain stimulation suppresses low-frequency network oscillations in the basal ganglia by regularizing neural firing patterns.

    Science.gov (United States)

    McConnell, George C; So, Rosa Q; Hilliard, Justin D; Lopomo, Paola; Grill, Warren M

    2012-11-07

    Deep brain stimulation (DBS) of the subthalamic nucleus (STN) is an effective treatment for the motor symptoms of Parkinson's disease (PD). The effects of DBS depend strongly on stimulation frequency: high frequencies (>90 Hz) improve motor symptoms, while low frequencies (basal ganglia were studied in the unilateral 6-hydroxydopamine lesioned rat model of PD. Only high-frequency DBS reversed motor symptoms, and the effectiveness of DBS depended strongly on stimulation frequency in a manner reminiscent of its clinical effects in persons with PD. Quantification of single-unit activity in the globus pallidus externa (GPe) and substantia nigra reticulata (SNr) revealed that high-frequency DBS, but not low-frequency DBS, reduced pathological low-frequency oscillations (∼9 Hz) and entrained neurons to fire at the stimulation frequency. Similarly, the coherence between simultaneously recorded pairs of neurons within and across GPe and SNr shifted from the pathological low-frequency band to the stimulation frequency during high-frequency DBS, but not during low-frequency DBS. The changes in firing patterns in basal ganglia neurons were not correlated with changes in firing rate. These results indicate that high-frequency DBS is more effective than low-frequency DBS, not as a result of changes in firing rate, but rather due to its ability to replace pathological low-frequency network oscillations with a regularized pattern of neuronal firing.

  5. Highly Efficient Optical Pumping of Spin Defects in Silicon Carbide for Stimulated Microwave Emission

    Science.gov (United States)

    Fischer, M.; Sperlich, A.; Kraus, H.; Ohshima, T.; Astakhov, G. V.; Dyakonov, V.

    2018-05-01

    We investigate the pump efficiency of silicon-vacancy-related spins in silicon carbide. For a crystal inserted into a microwave cavity with a resonance frequency of 9.4 GHz, the spin population inversion factor of 75 with the saturation optical pump power of about 350 mW is achieved at room temperature. At cryogenic temperature, the pump efficiency drastically increases, owing to an exceptionally long spin-lattice relaxation time exceeding one minute. Based on the experimental results, we find realistic conditions under which a silicon carbide maser can operate in continuous-wave mode and serve as a quantum microwave amplifier.

  6. Effect of electrical stimulation on neural regeneration via the p38-RhoA and ERK1/2-Bcl-2 pathways in spinal cord-injured rats.

    Science.gov (United States)

    Joo, Min Cheol; Jang, Chul Hwan; Park, Jong Tae; Choi, Seung Won; Ro, Seungil; Kim, Min Seob; Lee, Moon Young

    2018-02-01

    Although electrical stimulation is therapeutically applied for neural regeneration in patients, it remains unclear how electrical stimulation exerts its effects at the molecular level on spinal cord injury (SCI). To identify the signaling pathway involved in electrical stimulation improving the function of injured spinal cord, 21 female Sprague-Dawley rats were randomly assigned to three groups: control (no surgical intervention, n = 6), SCI (SCI only, n = 5), and electrical simulation (ES; SCI induction followed by ES treatment, n = 10). A complete spinal cord transection was performed at the 10 th thoracic level. Electrical stimulation of the injured spinal cord region was applied for 4 hours per day for 7 days. On days 2 and 7 post SCI, the Touch-Test Sensory Evaluators and the Basso-Beattie-Bresnahan locomotor scale were used to evaluate rat sensory and motor function. Somatosensory-evoked potentials of the tibial nerve of a hind paw of the rat were measured to evaluate the electrophysiological function of injured spinal cord. Western blot analysis was performed to measure p38-RhoA and ERK1/2-Bcl-2 pathways related protein levels in the injured spinal cord. Rat sensory and motor functions were similar between SCI and ES groups. Compared with the SCI group, in the ES group, the latencies of the somatosensory-evoked potential of the tibial nerve of rats were significantly shortened, the amplitudes were significantly increased, RhoA protein level was significantly decreased, protein gene product 9.5 expression, ERK1/2, p38, and Bcl-2 protein levels in the spinal cord were significantly increased. These data suggest that ES can promote the recovery of electrophysiological function of the injured spinal cord through regulating p38-RhoA and ERK1/2-Bcl-2 pathway-related protein levels in the injured spinal cord.

  7. Effect of electrical stimulation on neural regeneration via the p38-RhoA and ERK1/2-Bcl-2 pathways in spinal cord-injured rats

    Science.gov (United States)

    Joo, Min Cheol; Jang, Chul Hwan; Park, Jong Tae; Choi, Seung Won; Ro, Seungil; Kim, Min Seob; Lee, Moon Young

    2018-01-01

    Although electrical stimulation is therapeutically applied for neural regeneration in patients, it remains unclear how electrical stimulation exerts its effects at the molecular level on spinal cord injury (SCI). To identify the signaling pathway involved in electrical stimulation improving the function of injured spinal cord, 21 female Sprague-Dawley rats were randomly assigned to three groups: control (no surgical intervention, n = 6), SCI (SCI only, n = 5), and electrical simulation (ES; SCI induction followed by ES treatment, n = 10). A complete spinal cord transection was performed at the 10th thoracic level. Electrical stimulation of the injured spinal cord region was applied for 4 hours per day for 7 days. On days 2 and 7 post SCI, the Touch-Test Sensory Evaluators and the Basso-Beattie-Bresnahan locomotor scale were used to evaluate rat sensory and motor function. Somatosensory-evoked potentials of the tibial nerve of a hind paw of the rat were measured to evaluate the electrophysiological function of injured spinal cord. Western blot analysis was performed to measure p38-RhoA and ERK1/2-Bcl-2 pathways related protein levels in the injured spinal cord. Rat sensory and motor functions were similar between SCI and ES groups. Compared with the SCI group, in the ES group, the latencies of the somatosensory-evoked potential of the tibial nerve of rats were significantly shortened, the amplitudes were significantly increased, RhoA protein level was significantly decreased, protein gene product 9.5 expression, ERK1/2, p38, and Bcl-2 protein levels in the spinal cord were significantly increased. These data suggest that ES can promote the recovery of electrophysiological function of the injured spinal cord through regulating p38-RhoA and ERK1/2-Bcl-2 pathway-related protein levels in the injured spinal cord. PMID:29557386

  8. Motor sequence learning-induced neural efficiency in functional brain connectivity.

    Science.gov (United States)

    Karim, Helmet T; Huppert, Theodore J; Erickson, Kirk I; Wollam, Mariegold E; Sparto, Patrick J; Sejdić, Ervin; VanSwearingen, Jessie M

    2017-02-15

    Previous studies have shown the functional neural circuitry differences before and after an explicitly learned motor sequence task, but have not assessed these changes during the process of motor skill learning. Functional magnetic resonance imaging activity was measured while participants (n=13) were asked to tap their fingers to visually presented sequences in blocks that were either the same sequence repeated (learning block) or random sequences (control block). Motor learning was associated with a decrease in brain activity during learning compared to control. Lower brain activation was noted in the posterior parietal association area and bilateral thalamus during the later periods of learning (not during the control). Compared to the control condition, we found the task-related motor learning was associated with decreased connectivity between the putamen and left inferior frontal gyrus and left middle cingulate brain regions. Motor learning was associated with changes in network activity, spatial extent, and connectivity. Copyright © 2016 Elsevier B.V. All rights reserved.

  9. Efficient airport detection using region-based fully convolutional neural networks

    Science.gov (United States)

    Xin, Peng; Xu, Yuelei; Zhang, Xulei; Ma, Shiping; Li, Shuai; Lv, Chao

    2018-04-01

    This paper presents a model for airport detection using region-based fully convolutional neural networks. To achieve fast detection with high accuracy, we shared the conv layers between the region proposal procedure and the airport detection procedure and used graphics processing units (GPUs) to speed up the training and testing time. For lack of labeled data, we transferred the convolutional layers of ZF net pretrained by ImageNet to initialize the shared convolutional layers, then we retrained the model using the alternating optimization training strategy. The proposed model has been tested on an airport dataset consisting of 600 images. Experiments show that the proposed method can distinguish airports in our dataset from similar background scenes almost real-time with high accuracy, which is much better than traditional methods.

  10. Efficient second order Algorithms for Function Approximation with Neural Networks. Application to Sextic Potentials

    International Nuclear Information System (INIS)

    Gougam, L.A.; Taibi, H.; Chikhi, A.; Mekideche-Chafa, F.

    2009-01-01

    The problem of determining the analytical description for a set of data arises in numerous sciences and applications and can be referred to as data modeling or system identification. Neural networks are a convenient means of representation because they are known to be universal approximates that can learn data. The desired task is usually obtained by a learning procedure which consists in adjusting the s ynaptic weights . For this purpose, many learning algorithms have been proposed to update these weights. The convergence for these learning algorithms is a crucial criterion for neural networks to be useful in different applications. The aim of the present contribution is to use a training algorithm for feed forward wavelet networks used for function approximation. The training is based on the minimization of the least-square cost function. The minimization is performed by iterative second order gradient-based methods. We make use of the Levenberg-Marquardt algorithm to train the architecture of the chosen network and, then, the training procedure starts with a simple gradient method which is followed by a BFGS (Broyden, Fletcher, Glodfarb et Shanno) algorithm. The performances of the two algorithms are then compared. Our method is then applied to determine the energy of the ground state associated to a sextic potential. In fact, the Schrodinger equation does not always admit an exact solution and one has, generally, to solve it numerically. To this end, the sextic potential is, firstly, approximated with the above outlined wavelet network and, secondly, implemented into a numerical scheme. Our results are in good agreement with the ones found in the literature.

  11. Architecture and performance of neural networks for efficient A/C control in buildings

    International Nuclear Information System (INIS)

    Mahmoud, Mohamed A.; Ben-Nakhi, Abdullatif E.

    2003-01-01

    The feasibility of using neural networks (NNs) for optimizing air conditioning (AC) setback scheduling in public buildings was investigated. The main focus is on optimizing the network architecture in order to achieve best performance. To save energy, the temperature inside public buildings is allowed to rise after business hours by setting back the thermostat. The objective is to predict the time of the end of thermostat setback (EoS) such that the design temperature inside the building is restored in time for the start of business hours. State of the art building simulation software, ESP-r, was used to generate a database that covered the years 1995-1999. The software was used to calculate the EoS for two office buildings using the climate records in Kuwait. The EoS data for 1995 and 1996 were used for training and testing the NNs. The robustness of the trained NN was tested by applying them to a 'production' data set (1997-1999), which the networks have never 'seen' before. For each of the six different NN architectures evaluated, parametric studies were performed to determine the network parameters that best predict the EoS. External hourly temperature readings were used as network inputs, and the thermostat end of setback (EoS) is the output. The NN predictions were improved by developing a neural control scheme (NC). This scheme is based on using the temperature readings as they become available. For each NN architecture considered, six NNs were designed and trained for this purpose. The performance of the NN analysis was evaluated using a statistical indicator (the coefficient of multiple determination) and by statistical analysis of the error patterns, including ANOVA (analysis of variance). The results show that the NC, when used with a properly designed NN, is a powerful instrument for optimizing AC setback scheduling based only on external temperature records

  12. Astrocyte glycogen metabolism is required for neural activity during aglycemia or intense stimulation in mouse white matter

    DEFF Research Database (Denmark)

    Brown, Angus M; Sickmann, Helle M; Fosgerau, Keld

    2005-01-01

    We tested the hypothesis that inhibiting glycogen degradation accelerates compound action potential (CAP) failure in mouse optic nerve (MON) during aglycemia or high-intensity stimulation. Axon function was assessed as the evoked CAP, and glycogen content was measured biochemically. Isofagomine, ...

  13. Distinct Neural-Functional Effects of Treatments With Selective Serotonin Reuptake Inhibitors, Electroconvulsive Therapy, and Transcranial Magnetic Stimulation and Their Relations to Regional Brain Function in Major Depression: A Meta-analysis.

    Science.gov (United States)

    Chau, David T; Fogelman, Phoebe; Nordanskog, Pia; Drevets, Wayne C; Hamilton, J Paul

    2017-05-01

    Functional neuroimaging studies have examined the neural substrates of treatments for major depressive disorder (MDD). Low sample size and methodological heterogeneity, however, undermine the generalizability of findings from individual studies. We conducted a meta-analysis to identify reliable neural changes resulting from different modes of treatment for MDD and compared them with each other and with reliable neural functional abnormalities observed in depressed versus control samples. We conducted a meta-analysis of studies reporting changes in brain activity (e.g., as indexed by positron emission tomography) following treatments with selective serotonin reuptake inhibitors (SSRIs), electroconvulsive therapy (ECT), or transcranial magnetic stimulation. Additionally, we examined the statistical reliability of overlap among thresholded meta-analytic SSRI, ECT, and transcranial magnetic stimulation maps as well as a map of abnormal neural function in MDD. Our meta-analysis revealed that 1) SSRIs decrease activity in the anterior insula, 2) ECT decreases activity in central nodes of the default mode network, 3) transcranial magnetic stimulation does not result in reliable neural changes, and 4) regional effects of these modes of treatment do not significantly overlap with each other or with regions showing reliable functional abnormality in MDD. SSRIs and ECT produce neurally distinct effects relative to each other and to the functional abnormalities implicated in depression. These treatments therefore may exert antidepressant effects by diminishing neural functions not implicated in depression but that nonetheless impact mood. We discuss how the distinct neural changes resulting from SSRIs and ECT can account for both treatment effects and side effects from these therapies as well as how to individualize these treatments. Copyright © 2017 Society of Biological Psychiatry. Published by Elsevier Inc. All rights reserved.

  14. Direct and efficient transfection of mouse neural stem cells and mature neurons by in vivo mRNA electroporation.

    Science.gov (United States)

    Bugeon, Stéphane; de Chevigny, Antoine; Boutin, Camille; Coré, Nathalie; Wild, Stefan; Bosio, Andreas; Cremer, Harold; Beclin, Christophe

    2017-11-01

    In vivo brain electroporation of DNA expression vectors is a widely used method for lineage and gene function studies in the developing and postnatal brain. However, transfection efficiency of DNA is limited and adult brain tissue is refractory to electroporation. Here, we present a systematic study of mRNA as a vector for acute genetic manipulation in the developing and adult brain. We demonstrate that mRNA electroporation is far more efficient than DNA electroporation, and leads to faster and more homogeneous protein expression in vivo Importantly, mRNA electroporation allows the manipulation of neural stem cells and postmitotic neurons in the adult brain using minimally invasive procedures. Finally, we show that this approach can be efficiently used for functional studies, as exemplified by transient overexpression of the neurogenic factor Myt1l and by stably inactivating Dicer nuclease in vivo in adult born olfactory bulb interneurons and in fully integrated cortical projection neurons. © 2017. Published by The Company of Biologists Ltd.

  15. Playing the electric light orchestra--how electrical stimulation of visual cortex elucidates the neural basis of perception.

    Science.gov (United States)

    Cicmil, Nela; Krug, Kristine

    2015-09-19

    Vision research has the potential to reveal fundamental mechanisms underlying sensory experience. Causal experimental approaches, such as electrical microstimulation, provide a unique opportunity to test the direct contributions of visual cortical neurons to perception and behaviour. But in spite of their importance, causal methods constitute a minority of the experiments used to investigate the visual cortex to date. We reconsider the function and organization of visual cortex according to results obtained from stimulation techniques, with a special emphasis on electrical stimulation of small groups of cells in awake subjects who can report their visual experience. We compare findings from humans and monkeys, striate and extrastriate cortex, and superficial versus deep cortical layers, and identify a number of revealing gaps in the 'causal map' of visual cortex. Integrating results from different methods and species, we provide a critical overview of the ways in which causal approaches have been used to further our understanding of circuitry, plasticity and information integration in visual cortex. Electrical stimulation not only elucidates the contributions of different visual areas to perception, but also contributes to our understanding of neuronal mechanisms underlying memory, attention and decision-making.

  16. Playing the electric light orchestra—how electrical stimulation of visual cortex elucidates the neural basis of perception

    Science.gov (United States)

    Cicmil, Nela; Krug, Kristine

    2015-01-01

    Vision research has the potential to reveal fundamental mechanisms underlying sensory experience. Causal experimental approaches, such as electrical microstimulation, provide a unique opportunity to test the direct contributions of visual cortical neurons to perception and behaviour. But in spite of their importance, causal methods constitute a minority of the experiments used to investigate the visual cortex to date. We reconsider the function and organization of visual cortex according to results obtained from stimulation techniques, with a special emphasis on electrical stimulation of small groups of cells in awake subjects who can report their visual experience. We compare findings from humans and monkeys, striate and extrastriate cortex, and superficial versus deep cortical layers, and identify a number of revealing gaps in the ‘causal map′ of visual cortex. Integrating results from different methods and species, we provide a critical overview of the ways in which causal approaches have been used to further our understanding of circuitry, plasticity and information integration in visual cortex. Electrical stimulation not only elucidates the contributions of different visual areas to perception, but also contributes to our understanding of neuronal mechanisms underlying memory, attention and decision-making. PMID:26240421

  17. An Efficient Implementation of Deep Convolutional Neural Networks for MRI Segmentation.

    Science.gov (United States)

    Hoseini, Farnaz; Shahbahrami, Asadollah; Bayat, Peyman

    2018-02-27

    Image segmentation is one of the most common steps in digital image processing, classifying a digital image into different segments. The main goal of this paper is to segment brain tumors in magnetic resonance images (MRI) using deep learning. Tumors having different shapes, sizes, brightness and textures can appear anywhere in the brain. These complexities are the reasons to choose a high-capacity Deep Convolutional Neural Network (DCNN) containing more than one layer. The proposed DCNN contains two parts: architecture and learning algorithms. The architecture and the learning algorithms are used to design a network model and to optimize parameters for the network training phase, respectively. The architecture contains five convolutional layers, all using 3 × 3 kernels, and one fully connected layer. Due to the advantage of using small kernels with fold, it allows making the effect of larger kernels with smaller number of parameters and fewer computations. Using the Dice Similarity Coefficient metric, we report accuracy results on the BRATS 2016, brain tumor segmentation challenge dataset, for the complete, core, and enhancing regions as 0.90, 0.85, and 0.84 respectively. The learning algorithm includes the task-level parallelism. All the pixels of an MR image are classified using a patch-based approach for segmentation. We attain a good performance and the experimental results show that the proposed DCNN increases the segmentation accuracy compared to previous techniques.

  18. Investigating the Neural Bases for Intra-Subject Cognitive Efficiency Using Functional Magnetic Resonance Imaging

    Directory of Open Access Journals (Sweden)

    Neena K. Rao

    2014-10-01

    Full Text Available Several fMRI studies have examined brain regions mediating inter-subject variability in cognitive efficiency, but none have examined regions mediating intra-subject variability in efficiency. Thus, the present study was designed to identify brain regions involved in intra-subject variability in cognitive efficiency via participant-level correlations between trial-level reaction time (RT and trial-level fMRI BOLD percent signal change on a processing speed task. On each trial, participants indicated whether a digit-symbol probe-pair was present or absent in an array of nine digit-symbol probe-pairs while fMRI data were collected. Deconvolution analyses, using RT time-series models (derived from the proportional scaling of an event-related hemodynamic response function model by trial-level RT, were used to evaluate relationships between trial-level RTs and BOLD percent signal change. Although task-related patterns of activation and deactivation were observed in regions including bilateral occipital, bilateral parietal, portions of the medial wall such as the precuneus, default mode network regions including anterior cingulate, posterior cingulate, bilateral temporal, right cerebellum, and right cuneus, RT-BOLD correlations were observed in a more circumscribed set of regions. Positive RT-related patterns, or RT-BOLD correlations where fast RTs were associated with lower BOLD percent signal change, were observed in regions including bilateral occipital, bilateral parietal, and the precuneus. RT-BOLD correlations were not observed in the default mode network indicating a smaller set of regions associated with intra-subject variability in cognitive efficiency. The results are discussed in terms of a distributed area of regions that mediate variability in the cognitive efficiency that might underlie processing speed differences between individuals.

  19. Efficient spiking neural network model of pattern motion selectivity in visual cortex.

    Science.gov (United States)

    Beyeler, Michael; Richert, Micah; Dutt, Nikil D; Krichmar, Jeffrey L

    2014-07-01

    Simulating large-scale models of biological motion perception is challenging, due to the required memory to store the network structure and the computational power needed to quickly solve the neuronal dynamics. A low-cost yet high-performance approach to simulating large-scale neural network models in real-time is to leverage the parallel processing capability of graphics processing units (GPUs). Based on this approach, we present a two-stage model of visual area MT that we believe to be the first large-scale spiking network to demonstrate pattern direction selectivity. In this model, component-direction-selective (CDS) cells in MT linearly combine inputs from V1 cells that have spatiotemporal receptive fields according to the motion energy model of Simoncelli and Heeger. Pattern-direction-selective (PDS) cells in MT are constructed by pooling over MT CDS cells with a wide range of preferred directions. Responses of our model neurons are comparable to electrophysiological results for grating and plaid stimuli as well as speed tuning. The behavioral response of the network in a motion discrimination task is in agreement with psychophysical data. Moreover, our implementation outperforms a previous implementation of the motion energy model by orders of magnitude in terms of computational speed and memory usage. The full network, which comprises 153,216 neurons and approximately 40 million synapses, processes 20 frames per second of a 40 × 40 input video in real-time using a single off-the-shelf GPU. To promote the use of this algorithm among neuroscientists and computer vision researchers, the source code for the simulator, the network, and analysis scripts are publicly available.

  20. GABA(A) receptors in visual and auditory cortex and neural activity changes during basic visual stimulation.

    Science.gov (United States)

    Qin, Pengmin; Duncan, Niall W; Wiebking, Christine; Gravel, Paul; Lyttelton, Oliver; Hayes, Dave J; Verhaeghe, Jeroen; Kostikov, Alexey; Schirrmacher, Ralf; Reader, Andrew J; Northoff, Georg

    2012-01-01

    Recent imaging studies have demonstrated that levels of resting γ-aminobutyric acid (GABA) in the visual cortex predict the degree of stimulus-induced activity in the same region. These studies have used the presentation of discrete visual stimulus; the change from closed eyes to open also represents a simple visual stimulus, however, and has been shown to induce changes in local brain activity and in functional connectivity between regions. We thus aimed to investigate the role of the GABA system, specifically GABA(A) receptors, in the changes in brain activity between the eyes closed (EC) and eyes open (EO) state in order to provide detail at the receptor level to complement previous studies of GABA concentrations. We conducted an fMRI study involving two different modes of the change from EC to EO: an EO and EC block design, allowing the modeling of the haemodynamic response, followed by longer periods of EC and EO to allow the measuring of functional connectivity. The same subjects also underwent [(18)F]Flumazenil PET to measure GABA(A) receptor binding potentials. It was demonstrated that the local-to-global ratio of GABA(A) receptor binding potential in the visual cortex predicted the degree of changes in neural activity from EC to EO. This same relationship was also shown in the auditory cortex. Furthermore, the local-to-global ratio of GABA(A) receptor binding potential in the visual cortex also predicted the change in functional connectivity between the visual and auditory cortex from EC to EO. These findings contribute to our understanding of the role of GABA(A) receptors in stimulus-induced neural activity in local regions and in inter-regional functional connectivity.

  1. Fish and chips: implementation of a neural network model into computer chips to maximize swimming efficiency in autonomous underwater vehicles.

    Science.gov (United States)

    Blake, R W; Ng, H; Chan, K H S; Li, J

    2008-09-01

    Recent developments in the design and propulsion of biomimetic autonomous underwater vehicles (AUVs) have focused on boxfish as models (e.g. Deng and Avadhanula 2005 Biomimetic micro underwater vehicle with oscillating fin propulsion: system design and force measurement Proc. 2005 IEEE Int. Conf. Robot. Auto. (Barcelona, Spain) pp 3312-7). Whilst such vehicles have many potential advantages in operating in complex environments (e.g. high manoeuvrability and stability), limited battery life and payload capacity are likely functional disadvantages. Boxfish employ undulatory median and paired fins during routine swimming which are characterized by high hydromechanical Froude efficiencies (approximately 0.9) at low forward speeds. Current boxfish-inspired vehicles are propelled by a low aspect ratio, 'plate-like' caudal fin (ostraciiform tail) which can be shown to operate at a relatively low maximum Froude efficiency (approximately 0.5) and is mainly employed as a rudder for steering and in rapid swimming bouts (e.g. escape responses). Given this and the fact that bioinspired engineering designs are not obligated to wholly duplicate a biological model, computer chips were developed using a multilayer perception neural network model of undulatory fin propulsion in the knifefish Xenomystus nigri that would potentially allow an AUV to achieve high optimum values of propulsive efficiency at any given forward velocity, giving a minimum energy drain on the battery. We envisage that externally monitored information on flow velocity (sensory system) would be conveyed to the chips residing in the vehicle's control unit, which in turn would signal the locomotor unit to adopt kinematics (e.g. fin frequency, amplitude) associated with optimal propulsion efficiency. Power savings could protract vehicle operational life and/or provide more power to other functions (e.g. communications).

  2. 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.

  3. Brain changes following four weeks of unimanual motor training: Evidence from behavior, neural stimulation, cortical thickness, and functional MRI.

    Science.gov (United States)

    Sale, Martin V; Reid, Lee B; Cocchi, Luca; Pagnozzi, Alex M; Rose, Stephen E; Mattingley, Jason B

    2017-09-01

    Although different aspects of neuroplasticity can be quantified with behavioral probes, brain stimulation, and brain imaging assessments, no study to date has combined all these approaches into one comprehensive assessment of brain plasticity. Here, 24 healthy right-handed participants practiced a sequence of finger-thumb opposition movements for 10 min each day with their left hand. After 4 weeks, performance for the practiced sequence improved significantly (P left (mean increase: 53.0% practiced, 6.5% control) and right (21.0%; 15.8%) hands. Training also induced significant (cluster p-FWE right hemisphere, 301 voxel cluster; left hemisphere 700 voxel cluster), and sensorimotor cortices and superior parietal lobules (right hemisphere 864 voxel cluster; left hemisphere, 1947 voxel cluster). Transcranial magnetic stimulation over the right ("trained") primary motor cortex yielded a 58.6% mean increase in a measure of motor evoked potential amplitude, as recorded at the left abductor pollicis brevis muscle. Cortical thickness analyses based on structural MRI suggested changes in the right precentral gyrus, right post central gyrus, right dorsolateral prefrontal cortex, and potentially the right supplementary motor area. Such findings are consistent with LTP-like neuroplastic changes in areas that were already responsible for finger sequence execution, rather than improved recruitment of previously nonutilized tissue. Hum Brain Mapp 38:4773-4787, 2017. © 2017 Wiley Periodicals, Inc. © 2017 Wiley Periodicals, Inc.

  4. Efficient derivation of multipotent neural stem/progenitor cells from non-human primate embryonic stem cells.

    Directory of Open Access Journals (Sweden)

    Hiroko Shimada

    Full Text Available The common marmoset (Callithrix jacchus is a small New World primate that has been used as a non-human primate model for various biomedical studies. We previously demonstrated that transplantation of neural stem/progenitor cells (NS/PCs derived from mouse and human embryonic stem cells (ESCs and induced pluripotent stem cells (iPSCs promote functional locomotor recovery of mouse spinal cord injury models. However, for the clinical application of such a therapeutic approach, we need to evaluate the efficacy and safety of pluripotent stem cell-derived NS/PCs not only by xenotransplantation, but also allotransplantation using non-human primate models to assess immunological rejection and tumorigenicity. In the present study, we established a culture method to efficiently derive NS/PCs as neurospheres from common marmoset ESCs. Marmoset ESC-derived neurospheres could be passaged repeatedly and showed sequential generation of neurons and astrocytes, similar to that of mouse ESC-derived NS/PCs, and gave rise to functional neurons as indicated by calcium imaging. Although marmoset ESC-derived NS/PCs could not differentiate into oligodendrocytes under default culture conditions, these cells could abundantly generate oligodendrocytes by incorporating additional signals that recapitulate in vivo neural development. Moreover, principal component analysis of microarray data demonstrated that marmoset ESC-derived NS/PCs acquired similar gene expression profiles to those of fetal brain-derived NS/PCs by repeated passaging. Therefore, marmoset ESC-derived NS/PCs may be useful not only for accurate evaluation by allotransplantation of NS/PCs into non-human primate models, but are also applicable to analysis of iPSCs established from transgenic disease model marmosets.

  5. An efficient 3-D eddy-current solver using an independent impedance method for transcranial magnetic stimulation.

    Science.gov (United States)

    De Geeter, Nele; Crevecoeur, Guillaume; Dupre, Luc

    2011-02-01

    In many important bioelectromagnetic problem settings, eddy-current simulations are required. Examples are the reduction of eddy-current artifacts in magnetic resonance imaging and techniques, whereby the eddy currents interact with the biological system, like the alteration of the neurophysiology due to transcranial magnetic stimulation (TMS). TMS has become an important tool for the diagnosis and treatment of neurological diseases and psychiatric disorders. A widely applied method for simulating the eddy currents is the impedance method (IM). However, this method has to contend with an ill conditioned problem and consequently a long convergence time. When dealing with optimal design problems and sensitivity control, the convergence rate becomes even more crucial since the eddy-current solver needs to be evaluated in an iterative loop. Therefore, we introduce an independent IM (IIM), which improves the conditionality and speeds up the numerical convergence. This paper shows how IIM is based on IM and what are the advantages. Moreover, the method is applied to the efficient simulation of TMS. The proposed IIM achieves superior convergence properties with high time efficiency, compared to the traditional IM and is therefore a useful tool for accurate and fast TMS simulations.

  6. Continuous theta burst stimulation facilitates the clearance efficiency of the glymphatic pathway in a mouse model of sleep deprivation.

    Science.gov (United States)

    Liu, Dong-Xu; He, Xia; Wu, Dan; Zhang, Qun; Yang, Chao; Liang, Feng-Yin; He, Xiao-Fei; Dai, Guang-Yan; Pei, Zhong; Lan, Yue; Xu, Guang-Qing

    2017-07-13

    Sleep deprivation (SD) is a common condition associated with a variety of nervous system diseases, and has a negative impact on emotional and cognitive function. Continuous theta burst stimulation (cTBS) is known to improve cognition and emotion function in normal situations as well as in various types of dysfunction, but the mechanism remains unknown. We used two-photon in vivo imaging to explore the effect of cTBS on glymphatic pathway clearance in normal and SD C57BL/6J mice. Aquaporin-4 (AQP4) polarization was detected by immunofluorescence. Anxiety-like behaviors was measured using open field tests. We found that SD reduced influx efficiency along the peri-vascular space (PVS), disturbed AQP4 polarization and induced anxiety-like behaviors. CTBS significantly attenuated the decrease in efficiency of solute clearance usually incurred with SD, restored the loss of AQP4 polarization and improved anxiety-like behavior in SD animals. Our results implied that cTBS had the potential to protect against neuronal dysfunction induced by sleep disorders. Copyright © 2017 Elsevier B.V. All rights reserved.

  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. Nanoparticle-neural stem cells for targeted ovarian cancer treatment: optimization of silica nanoparticles for efficient drug loading

    Science.gov (United States)

    Patel, Z.; Berlin, J.; Abidi, W.

    2018-02-01

    One of the drugs used to treat ovarian cancer is cisplatin. However, cisplatin kills normal surrounding tissue in addition to cancer cells. To improve tumor targeting efficiency, our lab uses neural stem cells (NSCs), which migrate directly to ovarian tumors. If free cisplatin is loaded into NSCs for targeted drug delivery, it will kill the NSCs. To prevent the drug cisplatin from killing both the NSCs and normal surrounding tissue, our lab synthesizes silica nanoparticles (SiNPs) that act as a protective carrier. The big picture here is to maximize efficiency of tumor targeting using NSCs and minimize toxicity to these NSCs using SiNPs. The goal of this project is to optimize the stability of SiNPs, which is important for efficient drug loading. To do this, the concentration of tetraethyl orthosilicate (TEOS), one of the main components of SiNPs, was varied. We hypothesized that more TEOS equates to more stable SiNPs because TEOS contributes carbon to SiNPs, and thus a tightly-packed chemical structure results in a stable particle. Then, the stability of the SiNPs were checked in cell media and phosphate buffered saline (PBS). Lastly, the SiNPs were analyzed for their porosity using the transmission electron microscope (TEM). TEM imaging showed white spots in the 200-800 μL TEOS batches and no white spots in the 1000-1800 μL TEOS batches. The white spots were pores, which indicate instability. We concluded that the ultimate factor that determines the stability of SiNPs (100 nm) is the concentration of organic substance.

  9. Insights on the neural basis of motor plasticity induced by theta burst stimulation from TMS-EEG

    Science.gov (United States)

    VERNET, Marine; BASHIR, Shahid; YOO, Woo-Kyoung; PEREZ, Jennifer M.; NAJIB, Umer; PASCUAL-LEONE, Alvaro

    2014-01-01

    Transcranial magnetic stimulation (TMS) is a useful tool to induce and measure plasticity in the human brain. However, the cortical effects are generally indirectly evaluated with motor-evoked potentials (MEPs) reflective of modulation of cortico-spinal excitability. In this study, we aim to provide direct measures of cortical plasticity by combining TMS with electroencephalography (EEG). Continuous theta-burst stimulation (cTBS) was applied over the primary motor cortex (M1) of young healthy adults; and we measured modulation of (i) motor evoked-potentials (MEPs), (ii) TMS-induced EEG evoked potentials (TEPs), (iii) TMS-induced EEG synchronization and (iv) eyes-closed resting EEG. Our results show the expected cTBS-induced decrease in MEPs size, which we found to be paralleled by a modulation of a combination of TEPs. Furthermore, we found that cTBS increased the power in the theta band of eyes-closed resting EEG, whereas it decreased single-pulse TMS-induced power in the theta and alpha bands. In addition, cTBS decreased the power in the beta band of eyes-closed resting EEG, whereas it increased single-pulse TMS-induced power in the beta band. We suggest that cTBS acts by modulating the phase alignment between already active oscillators; it synchronizes low frequency (theta and/or alpha) oscillators and desynchronizes high frequency (beta) oscillators. These results provide novel insights into the cortical effects of cTBS and could be useful for exploring cTBS-induced plasticity outside of the motor cortex. PMID:23190020

  10. Stimulating at the right time: phase-specific deep brain stimulation.

    Science.gov (United States)

    Cagnan, Hayriye; Pedrosa, David; Little, Simon; Pogosyan, Alek; Cheeran, Binith; Aziz, Tipu; Green, Alexander; Fitzgerald, James; Foltynie, Thomas; Limousin, Patricia; Zrinzo, Ludvic; Hariz, Marwan; Friston, Karl J; Denison, Timothy; Brown, Peter

    2017-01-01

    SEE MOLL AND ENGEL DOI101093/AWW308 FOR A SCIENTIFIC COMMENTARY ON THIS ARTICLE: Brain regions dynamically engage and disengage with one another to execute everyday actions from movement to decision making. Pathologies such as Parkinson's disease and tremor emerge when brain regions controlling movement cannot readily decouple, compromising motor function. Here, we propose a novel stimulation strategy that selectively regulates neural synchrony through phase-specific stimulation. We demonstrate for the first time the therapeutic potential of such a stimulation strategy for the treatment of patients with pathological tremor. Symptom suppression is achieved by delivering stimulation to the ventrolateral thalamus, timed according to the patient's tremor rhythm. Sustained locking of deep brain stimulation to a particular phase of tremor afforded clinically significant tremor relief (up to 87% tremor suppression) in selected patients with essential tremor despite delivering less than half the energy of conventional high frequency stimulation. Phase-specific stimulation efficacy depended on the resonant characteristics of the underlying tremor network. Selective regulation of neural synchrony through phase-locked stimulation has the potential to both increase the efficiency of therapy and to minimize stimulation-induced side effects. © The Author (2016). Published by Oxford University Press on behalf of the Guarantors of Brain.

  11. A stem cell medium containing neural stimulating factor induces a pancreatic cancer stem-like cell-enriched population

    Science.gov (United States)

    WATANABE, YUSAKU; YOSHIMURA, KIYOSHI; YOSHIKAWA, KOICHI; TSUNEDOMI, RYOICHI; SHINDO, YOSHITARO; MATSUKUMA, SOU; MAEDA, NORIKO; KANEKIYO, SHINSUKE; SUZUKI, NOBUAKI; KURAMASU, ATSUO; SONODA, KOUHEI; TAMADA, KOJI; KOBAYASHI, SEI; SAYA, HIDEYUKI; HAZAMA, SHOICHI; OKA, MASAAKI

    2014-01-01

    Cancer stem cells (CSCs) have been studied for their self-renewal capacity and pluripotency, as well as their resistance to anticancer therapy and their ability to metastasize to distant organs. CSCs are difficult to study because their population is quite low in tumor specimens. To overcome this problem, we established a culture method to induce a pancreatic cancer stem-like cell (P-CSLC)-enriched population from human pancreatic cancer cell lines. Human pancreatic cancer cell lines established at our department were cultured in CSC-inducing media containing epidermal growth factor (EGF), basic fibroblast growth factor (bFGF), leukemia inhibitory factor (LIF), neural cell survivor factor-1 (NSF-1), and N-acetylcysteine. Sphere cells were obtained and then transferred to a laminin-coated dish and cultured for approximately two months. The surface markers, gene expression, aldehyde dehydrogenase (ALDH) activity, cell cycle, and tumorigenicity of these induced cells were examined for their stem cell-like characteristics. The population of these induced cells expanded within a few months. The ratio of CD24high, CD44high, epithelial specific antigen (ESA) high, and CD44variant (CD44v) high cells in the induced cells was greatly enriched. The induced cells stayed in the G0/G1 phase and demonstrated mesenchymal and stemness properties. The induced cells had high tumorigenic potential. Thus, we established a culture method to induce a P-CSLCenriched population from human pancreatic cancer cell lines. The CSLC population was enriched approximately 100-fold with this method. Our culture method may contribute to the precise analysis of CSCs and thus support the establishment of CSC-targeting therapy. PMID:25118635

  12. Stimulating neural plasticity with real-time fMRI neurofeedback in Huntington's disease: A proof of concept study.

    Science.gov (United States)

    Papoutsi, Marina; Weiskopf, Nikolaus; Langbehn, Douglas; Reilmann, Ralf; Rees, Geraint; Tabrizi, Sarah J

    2018-03-01

    Novel methods that stimulate neuroplasticity are increasingly being studied to treat neurological and psychiatric conditions. We sought to determine whether real-time fMRI neurofeedback training is feasible in Huntington's disease (HD), and assess any factors that contribute to its effectiveness. In this proof-of-concept study, we used this technique to train 10 patients with HD to volitionally regulate the activity of their supplementary motor area (SMA). We collected detailed behavioral and neuroimaging data before and after training to examine changes of brain function and structure, and cognitive and motor performance. We found that patients overall learned to increase activity of the target region during training with variable effects on cognitive and motor behavior. Improved cognitive and motor performance after training predicted increases in pre-SMA grey matter volume, fMRI activity in the left putamen, and increased SMA-left putamen functional connectivity. Although we did not directly target the putamen and corticostriatal connectivity during neurofeedback training, our results suggest that training the SMA can lead to regulation of associated networks with beneficial effects in behavior. We conclude that neurofeedback training can induce plasticity in patients with Huntington's disease despite the presence of neurodegeneration, and the effects of training a single region may engage other regions and circuits implicated in disease pathology. © 2017 The Authors. Human Brain Mapping Published by Wiley Periodicals, Inc.

  13. Diffusion Tensor Imaging Evaluation of Neural Network Development in Patients Undergoing Therapeutic Repetitive Transcranial Magnetic Stimulation following Stroke

    Directory of Open Access Journals (Sweden)

    Naoki Yamada

    2018-01-01

    Full Text Available We aimed to investigate plastic changes in cerebral white matter structures using diffusion tensor imaging following a 15-day stroke rehabilitation program. We compared the detection of cerebral plasticity between generalized fractional anisotropy (GFA, a novel tool for investigating white matter structures, and fractional anisotropy (FA. Low-frequency repetitive transcranial magnetic stimulation (LF-rTMS of 2400 pulses applied to the nonlesional hemisphere and 240 min intensive occupation therapy (OT daily over 15 days. Motor function was evaluated using the Fugl-Meyer assessment (FMA and Wolf Motor Function Test (WMFT. Patients underwent diffusion tensor magnetic resonance imaging (MRI on admission and discharge, from which bilateral FA and GFA values in Brodmann area (BA 4 and BA6 were calculated. Motor function improved following treatment (p<0.001. Treatment increased GFA values for both the lesioned and nonlesioned BA4 (p<0.05, p<0.001, resp.. Changes in GFA value for BA4 of the lesioned hemisphere were significantly inversely correlated with changes in WMFT scores (R2=0.363, p<0.05. Our findings indicate that the GFA may have a potentially more useful ability than FA to detect changes in white matter structures in areas of fiber intersection for any such future investigations.

  14. Biomarkers and Stimulation Algorithms for Adaptive Brain Stimulation

    Directory of Open Access Journals (Sweden)

    Kimberly B. Hoang

    2017-10-01

    Full Text Available The goal of this review is to describe in what ways feedback or adaptive stimulation may be delivered and adjusted based on relevant biomarkers. Specific treatment mechanisms underlying therapeutic brain stimulation remain unclear, in spite of the demonstrated efficacy in a number of nervous system diseases. Brain stimulation appears to exert widespread influence over specific neural networks that are relevant to specific disease entities. In awake patients, activation or suppression of these neural networks can be assessed by either symptom alleviation (i.e., tremor, rigidity, seizures or physiological criteria, which may be predictive of expected symptomatic treatment. Secondary verification of network activation through specific biomarkers that are linked to symptomatic disease improvement may be useful for several reasons. For example, these biomarkers could aid optimal intraoperative localization, possibly improve efficacy or efficiency (i.e., reduced power needs, and provide long-term adaptive automatic adjustment of stimulation parameters. Possible biomarkers for use in portable or implanted devices span from ongoing physiological brain activity, evoked local field potentials (LFPs, and intermittent pathological activity, to wearable devices, biochemical, blood flow, optical, or magnetic resonance imaging (MRI changes, temperature changes, or optogenetic signals. First, however, potential biomarkers must be correlated directly with symptom or disease treatment and network activation. Although numerous biomarkers are under consideration for a variety of stimulation indications the feasibility of these approaches has yet to be fully determined. Particularly, there are critical questions whether the use of adaptive systems can improve efficacy over continuous stimulation, facilitate adjustment of stimulation interventions and improve our understanding of the role of abnormal network function in disease mechanisms.

  15. A novel system of artificial antigen-presenting cells efficiently stimulates Flu peptide-specific cytotoxic T cells in vitro

    International Nuclear Information System (INIS)

    Han, Hui; Peng, Ji-Run; Chen, Peng-Cheng; Gong, Lei; Qiao, Shi-Shi; Wang, Wen-Zhen; Cui, Zhu-Qingqing; Yu, Xin; Wei, Yu-Hua; Leng, Xi-Sheng

    2011-01-01

    Highlights: → Adoptive immunotherapy depends on relevant numbers of cytolytic T lymphocytes. → An ideal artificial APCs system was successfully prepared in vivo. → Controlled release of IL-2 leads to much more T-cell expansion. → This system is better than general cellular APCs on T-cell expansion. -- Abstract: Therapeutic numbers of antigen-specific cytotoxic T lymphocytes (CTLs) are key effectors in successful adoptive immunotherapy. However, efficient and reproducible methods to meet the qualification remain poor. To address this issue, we designed the artificial antigen-presenting cell (aAPC) system based on poly(lactic-co-glycolic acid) (PLGA). A modified emulsion method was used for the preparation of PLGA particles encapsulating interleukin-2 (IL-2). Biotinylated molecular ligands for recognition and co-stimulation of T cells were attached to the particle surface through the binding of avidin-biotin. These formed the aAPC system. The function of aAPCs in the proliferation of specific CTLs against human Flu antigen was detected by enzyme-linked immunospot assay (ELISPOT) and MTT staining methods. Finally, we successfully prepared this suitable aAPC system. The results show that IL-2 is released from aAPCs in a sustained manner over 30 days. This dramatically improves the stimulatory capacity of this system as compared to the effect of exogenous addition of cytokine. In addition, our aAPCs promote the proliferation of Flu antigen-specific CTLs more effectively than the autologous cellular APCs. Here, this aAPC platform is proved to be suitable for expansion of human antigen-specific T cells.

  16. A novel system of artificial antigen-presenting cells efficiently stimulates Flu peptide-specific cytotoxic T cells in vitro

    Energy Technology Data Exchange (ETDEWEB)

    Han, Hui [Department of Hepatobiliary Surgery, Peking University People' s Hospital, Beijing 100044 (China); Peng, Ji-Run, E-mail: pengjr@medmail.com.cn [Department of Hepatobiliary Surgery, Peking University People' s Hospital, Beijing 100044 (China); Chen, Peng-Cheng; Gong, Lei [Department of Hepatobiliary Surgery, Peking University People' s Hospital, Beijing 100044 (China); Qiao, Shi-Shi [Department of Hepatobiliary Surgery, The First Affiliated Hospital, Zhengzhou University, Zhengzhou 450052 (China); Wang, Wen-Zhen; Cui, Zhu-Qingqing; Yu, Xin; Wei, Yu-Hua [Department of Hepatobiliary Surgery, Peking University People' s Hospital, Beijing 100044 (China); Leng, Xi-Sheng, E-mail: lengxs2003@yahoo.com.cn [Department of Hepatobiliary Surgery, Peking University People' s Hospital, Beijing 100044 (China)

    2011-08-05

    Highlights: {yields} Adoptive immunotherapy depends on relevant numbers of cytolytic T lymphocytes. {yields} An ideal artificial APCs system was successfully prepared in vivo. {yields} Controlled release of IL-2 leads to much more T-cell expansion. {yields} This system is better than general cellular APCs on T-cell expansion. -- Abstract: Therapeutic numbers of antigen-specific cytotoxic T lymphocytes (CTLs) are key effectors in successful adoptive immunotherapy. However, efficient and reproducible methods to meet the qualification remain poor. To address this issue, we designed the artificial antigen-presenting cell (aAPC) system based on poly(lactic-co-glycolic acid) (PLGA). A modified emulsion method was used for the preparation of PLGA particles encapsulating interleukin-2 (IL-2). Biotinylated molecular ligands for recognition and co-stimulation of T cells were attached to the particle surface through the binding of avidin-biotin. These formed the aAPC system. The function of aAPCs in the proliferation of specific CTLs against human Flu antigen was detected by enzyme-linked immunospot assay (ELISPOT) and MTT staining methods. Finally, we successfully prepared this suitable aAPC system. The results show that IL-2 is released from aAPCs in a sustained manner over 30 days. This dramatically improves the stimulatory capacity of this system as compared to the effect of exogenous addition of cytokine. In addition, our aAPCs promote the proliferation of Flu antigen-specific CTLs more effectively than the autologous cellular APCs. Here, this aAPC platform is proved to be suitable for expansion of human antigen-specific T cells.

  17. Adrenaline administration promotes the efficiency of granulocyte colony stimulating factor-mediated hematopoietic stem and progenitor cell mobilization in mice.

    Science.gov (United States)

    Chen, Chong; Cao, Jiang; Song, Xuguang; Zeng, Lingyu; Li, Zhenyu; Li, Yong; Xu, Kailin

    2013-01-01

    A high dose of granulocyte colony stimulating factor (G-CSF) is widely used to mobilize hematopoietic stem and progenitor cells (HSPC), but G-CSF is relatively inefficient and may cause adverse effects. Recently, adrenaline has been found to play important roles in HSPC mobilization. In this study, we explored whether adrenaline combined with G-CSF could induce HSPC mobilization in a mouse model. Mice were treated with adrenaline and either a high or low dose of G-CSF alone or in combination. Peripheral blood HSPC counts were evaluated by flow cytometry. Levels of bone marrow SDF-1 were measured by ELISA, the transcription of CXCR4 and SDF-1 was measured by real-time RT-PCR, and CXCR4 protein was detected by Western blot. Our results showed that adrenaline alone fails to mobilize HSPCs into the peripheral blood; however, when G-CSF and adrenaline are combined, the WBC counts and percentages of HSPCs are significantly higher compared to those in mice that received G-CSF alone. The combined use of adrenaline and G-CSF not only accelerated HSPC mobilization, but also enabled the efficient mobilization of HSPCs into the peripheral blood at lower doses of G-CSF. Adrenaline/G-CSF treatment also extensively downregulated levels of SDF-1 and CXCR4 in mouse bone marrow. These results demonstrated that adrenaline combined with G-CSF can induce HSPC mobilization by down-regulating the CXCR4/SDF-1 axis, indicating that the use of adrenaline may enable the use of reduced dosages or durations of G-CSF treatment, minimizing G-CSF-associated complications.

  18. Effects of Electroacupuncture Combined with Repetitive Transcranial Magnetic Stimulation on the Expression of Nestin in Neural Stem Cell after Focal Cerebral Ischemia in Adult Rats

    Institute of Scientific and Technical Information of China (English)

    HUANG Guofu; HUANG Xiaolin; CHEN Hong; HAY Xiaohua

    2009-01-01

    Objective: To investigate the influence of electroacupuncture (EA) combined with repetitive transeranial magnetic stimulation(rTMS) on the temporal profile of nestin expression after induction of focal cerebral isehemia in adult rats and to explore the mechanism of EA combined with rTMS in treating ischemic brain injury. Method: The model of transient focal ischemia was produced by occlusion of middle cerebral artery. Seventy-five Wistar rats were randomly divided into normal group, model group, EA group, rTMS group and EA +rTMS group. The neurologic impairment rating and ability of learning and memory were observed at the 7th、14th and 28th d after infarction respectively. Meanwhile, Western blotting was used to observe the number of nestin expression positive cells. Result: Nestin-positive cells were found in cortex, subgranular zone (SGZ), subventricular zone (SVZ) of the ipsilateral side at different time points after cerebral isehemia. The number of nestin-positive cells peaked at the 7th d, began to decrease at the 14th d and was significantly higher in EA+rTMS group than that in model group (P<0.05), then almost reached normal at the 28th d. The improvement of neural motor function deficits as well as the indexes of learning and memory were more obvious in EA+rTMS group compared with model group (P<0.01, P<0.05). These effects were most obvious in EA+rTMS group compared with the EA and rTMS group (P<0.05). Conclusion: EA and rTMS possess the potency of building up and can increase the number of nestin-positive cells in some brain regions after focal cerebral ischemia, which might be one of the important mechanisms of EA combined with rTMS in treating ischemia brain injury.

  19. The ectodomain of cadherin-11 binds to erbB2 and stimulates Akt phosphorylation to promote cranial neural crest cell migration.

    Directory of Open Access Journals (Sweden)

    Ketan Mathavan

    Full Text Available During development, a multi-potent group of cells known as the cranial neural crest (CNC migrate to form craniofacial structures. Proper migration of these cells requires proteolysis of cell adhesion molecules, such as cadherins. In Xenopus laevis, preventing extracellular cleavage of cadherin-11 impairs CNC migration. However, overexpression of the soluble cleavage product (EC1-3 is capable of rescuing this phenotype. The mechanism by which EC1-3 promotes CNC migration has not been investigated until now. Here we show that EC1-3 stimulates phosphorylation of Akt, a target of PI3K, in X.laevis CNC. Through immunoprecipitation experiments, we determined that EC1-3 interacts with all ErbB receptors, PDGFRα, and FGFR1. Of these receptors, only ErbB2 was able to produce an increase in Akt phosphorylation upon treatment with a recombinant EC1-3. This increase was abrogated by mubritinib, an inhibitor of ErbB2. We were able to recapitulate this decrease in Akt phosphorylation in vivo by knocking down ErbB2 in CNC cells. Knockdown of the receptor also significantly reduced CNC migration in vivo. We confirmed the importance of ErbB2 and ErbB receptor signaling in CNC migration using mubritinib and canertinib, respectively. Mubritinib and the PI3K inhibitor LY294002 significantly decreased cell migration while canertinib nearly prevented it altogether. These data show that ErbB2 and Akt are important for CNC migration and implicate other ErbB receptors and Akt-independent signaling pathways. Our findings provide the first example of a functional interaction between the extracellular domain of a type II classical cadherin and growth factor receptors.

  20. Long-term CO2 rise has increased photosynthetic efficiency and water use efficiency but did not stimulate diameter growth of tropical trees

    Science.gov (United States)

    Groenendijk, P.; Zuidema, P.; Sleen, P. V. D.; Vlam, M.; Ehlers, I.; Schleucher, J.

    2014-12-01

    Tropical forests are a crucial component of the global carbon cycle, and their responses to atmospheric changes may shift carbon cycling and climate systems. Dynamic Global Vegetation Models (DGVMs) are the major tools to simulate tropical forest responses to climate change. One of the main determinants of these simulated responses is the effect of CO2 on tropical tree physiology and growth, the 'CO2 fertilization effect'. The paucity of CO2 enrichment experiments in the tropics importantly limits insights into the CO2 fertilization effect as well as the validation of DGVMs. However, use can be made of the 40% rise in atmospheric CO2 concentration since the onset of the Industrial Revolution. The effects of the historical CO2 rise on tree physiology and growth can be obtained from stable isotopes, isotopomers and tree diameter increments obtained in tree-ring studies. We studied the physiological and growth responses of 12 tree species in Bolivia, Cameroon and Thailand to 150 years of CO2 enrichment. Analyses of 13C of wood cellulose revealed strong, long-term increases in leaf intercellular CO2 concentrations for all study species and a marked improvement of intrinsic water use efficiency (iWUE). For a subset of one species per site, we studied the Deuterium isotopomers (isomers with isotopic atoms) of glucose in wood to obtain a direct estimate of the photorespiration-to-photosynthesis ratio. We found that this ratio consistently and strongly decreased over the past century, thus increasing the effeciency and rate of photosynthesis. In spite of these strong physiological responses to increased CO2levels, we did not find evidence for increased tree diameter growth for any of the sites, or for sites combined. Possible reasons for the lack of a growth stimulation include increased (leaf) temperature, insufficient availability of nutrients or a shift in biomass investment in trees. Our results suggest that the strong CO2 fertilization of tropical tree growth often

  1. DNA topoisomerase IIβ stimulates neurite outgrowth in neural differentiated human mesenchymal stem cells through regulation of Rho-GTPases (RhoA/Rock2 pathway) and Nurr1 expression.

    Science.gov (United States)

    Zaim, Merve; Isik, Sevim

    2018-04-25

    DNA topoisomerase IIβ (topo IIβ) is known to regulate neural differentiation by inducing the neuronal genes responsible for critical neural differentiation events such as neurite outgrowth and axon guidance. However, the pathways of axon growth controlled by topo IIβ have not been clarified yet. Microarray results of our previous study have shown that topo IIβ silencing in neural differentiated primary human mesenchymal stem cells (hMSCs) significantly alters the expression pattern of genes involved in neural polarity, axonal growth, and guidance, including Rho-GTPases. This study aims to further analyze the regulatory role of topo IIβ on the process of axon growth via regulation of Rho-GTPases. For this purpose, topo IIβ was silenced in neurally differentiated hMSCs. Cells lost their morphology because of topo IIβ deficiency, becoming enlarged and flattened. Additionally, a reduction in both neural differentiation efficiency and neurite length, upregulation in RhoA and Rock2, downregulation in Cdc42 gene expression were detected. On the other hand, cells were transfected with topo IIβ gene to elucidate the possible neuroprotective effect of topo IIβ overexpression on neural-induced hMSCs. Topo IIβ overexpression prompted all the cells to exhibit neural cell morphology as characterized by longer neurites. RhoA and Rock2 expressions were downregulated, whereas Cdc42 expression was upregulated. Nurr1 expression level correlated with topo IIβ in both topo IIβ-overexpressed and -silenced cells. Furthermore, differential translocation of Rho-GTPases was detected by immunostaining in response to topo IIβ. Our results suggest that topo IIβ deficiency could give rise to neurodegeneration through dysregulation of Rho-GTPases. However, further in-vivo research is needed to demonstrate if re-regulation of Rho GTPases by topo IIβ overexpression could be a neuroprotective treatment in the case of neurodegenerative diseases.

  2. Designing an artificial neural network using radial basis function to model exergetic efficiency of nanofluids in mini double pipe heat exchanger

    Science.gov (United States)

    Ghasemi, Nahid; Aghayari, Reza; Maddah, Heydar

    2018-06-01

    The present study aims at predicting and optimizing exergetic efficiency of TiO2-Al2O3/water nanofluid at different Reynolds numbers, volume fractions and twisted ratios using Artificial Neural Networks (ANN) and experimental data. Central Composite Design (CCD) and cascade Radial Basis Function (RBF) were used to display the significant levels of the analyzed factors on the exergetic efficiency. The size of TiO2-Al2O3/water nanocomposite was 20-70 nm. The parameters of ANN model were adapted by a training algorithm of radial basis function (RBF) with a wide range of experimental data set. Total mean square error and correlation coefficient were used to evaluate the results which the best result was obtained from double layer perceptron neural network with 30 neurons in which total Mean Square Error(MSE) and correlation coefficient (R2) were equal to 0.002 and 0.999, respectively. This indicated successful prediction of the network. Moreover, the proposed equation for predicting exergetic efficiency was extremely successful. According to the optimal curves, the optimum designing parameters of double pipe heat exchanger with inner twisted tape and nanofluid under the constrains of exergetic efficiency 0.937 are found to be Reynolds number 2500, twisted ratio 2.5 and volume fraction( v/v%) 0.05.

  3. Study of the efficiency of transplantation of human neural stem cells to rats with spinal trauma: the use of functional load tests and BBB test.

    Science.gov (United States)

    Lebedev, S V; Karasev, A V; Chekhonin, V P; Savchenko, E A; Viktorov, I V; Chelyshev, Yu A; Shaimardanova, G F

    2010-09-01

    Human ensheating neural stem cells of the olfactory epithelium were transplanted to adult male rats immediately after contusion trauma of the spinal cord at T9 level rostrally and caudally to the injury. Voluntary movements (by a 21-point BBB scale), rota-rod performance, and walking along a narrowing beam were monitored weekly over 60 days. In rats receiving cell transplantation, the mean BBB score significantly increased by 11% by the end of the experiment. The mean parameters of load tests also regularly surpassed the corresponding parameters in controls. The efficiency of transplantation (percent of animals with motor function recovery parameters surpassing the corresponding mean values in the control groups) was 62% by the state of voluntary motions, 37% by the rota-rod test, and 32% by the narrowing beam test. Morphometry revealed considerable shrinking of the zone of traumatic damage in the spinal cord and activation of posttraumatic remyelination in animals receiving transplantation of human neural stem cells.

  4. The efficiency of simultaneous binaural ocular vestibular evoked myogenic potentials: a comparative study with monaural acoustic stimulation in healthy subjects.

    Science.gov (United States)

    Kim, Min-Beom; Ban, Jae Ho

    2012-12-01

    To evaluate the test-retest reliability and convenience of simultaneous binaural acoustic-evoked ocular vestibular evoked myogenic potentials (oVEMP). Thirteen healthy subjects with no history of ear diseases participated in this study. All subjects underwent oVEMP test with both separated monaural acoustic stimulation and simultaneous binaural acoustic stimulation. For evaluating test-retest reliability, three repetitive sessions were performed in each ear for calculating the intraclass correlation coefficient (ICC) for both monaural and binaural tests. We analyzed data from the biphasic n1-p1 complex, such as latency of peak, inter-peak amplitude, and asymmetric ratio of amplitude in both ears. Finally, we checked the total time required to complete each test for evaluating test convenience. No significant difference was observed in amplitude and asymmetric ratio in comparison between monaural and binaural oVEMP. However, latency was slightly delayed in binaural oVEMP. In test-retest reliability analysis, binaural oVEMP showed excellent ICC values ranging from 0.68 to 0.98 in latency, asymmetric ratio, and inter-peak amplitude. Additionally, the test time was shorter in binaural than monaural oVEMP. oVEMP elicited from binaural acoustic stimulation yields similar satisfactory results as monaural stimulation. Further, excellent test-retest reliability and shorter test time were achieved in binaural than in monaural oVEMP.

  5. Highly efficient methods to obtain homogeneous dorsal neural progenitor cells from human and mouse embryonic stem cells and induced pluripotent stem cells.

    Science.gov (United States)

    Zhang, Meixiang; Ngo, Justine; Pirozzi, Filomena; Sun, Ying-Pu; Wynshaw-Boris, Anthony

    2018-03-15

    Embryonic stem cells (ESCs) and induced pluripotent stem cells (iPSCs) have been widely used to generate cellular models harboring specific disease-related genotypes. Of particular importance are ESC and iPSC applications capable of producing dorsal telencephalic neural progenitor cells (NPCs) that are representative of the cerebral cortex and overcome the challenges of maintaining a homogeneous population of cortical progenitors over several passages in vitro. While previous studies were able to derive NPCs from pluripotent cell types, the fraction of dorsal NPCs in this population is small and decreases over several passages. Here, we present three protocols that are highly efficient in differentiating mouse and human ESCs, as well as human iPSCs, into a homogeneous and stable population of dorsal NPCs. These protocols will be useful for modeling cerebral cortical neurological and neurodegenerative disorders in both mouse and human as well as for high-throughput drug screening for therapeutic development. We optimized three different strategies for generating dorsal telencephalic NPCs from mouse and human pluripotent cell types through single or double inhibition of bone morphogenetic protein (BMP) and/or SMAD pathways. Mouse and human pluripotent cells were aggregated to form embryoid bodies in suspension and were treated with dorsomorphin alone (BMP inhibition) or combined with SB431542 (double BMP/SMAD inhibition) during neural induction. Neural rosettes were then selected from plated embryoid bodies to purify the population of dorsal NPCs. We tested the expression of key dorsal NPC markers as well as nonectodermal markers to confirm the efficiency of our three methods in comparison to published and commercial protocols. Single and double inhibition of BMP and/or SMAD during neural induction led to the efficient differentiation of dorsal NPCs, based on the high percentage of PAX6-positive cells and the NPC gene expression profile. There were no statistically

  6. Improving efficiency of two-type maximum power point tracking methods of tip-speed ratio and optimum torque in wind turbine system using a quantum neural network

    International Nuclear Information System (INIS)

    Ganjefar, Soheil; Ghassemi, Ali Akbar; Ahmadi, Mohamad Mehdi

    2014-01-01

    In this paper, a quantum neural network (QNN) is used as controller in the adaptive control structures to improve efficiency of the maximum power point tracking (MPPT) methods in the wind turbine system. For this purpose, direct and indirect adaptive control structures equipped with QNN are used in tip-speed ratio (TSR) and optimum torque (OT) MPPT methods. The proposed control schemes are evaluated through a battery-charging windmill system equipped with PMSG (permanent magnet synchronous generator) at a random wind speed to demonstrate transcendence of their effectiveness as compared to PID controller and conventional neural network controller (CNNC). - Highlights: • Using a new control method to harvest the maximum power from wind energy system. • Using an adaptive control scheme based on quantum neural network (QNN). • Improving of MPPT-TSR method by direct adaptive control scheme based on QNN. • Improving of MPPT-OT method by indirect adaptive control scheme based on QNN. • Using a windmill system based on PMSG to evaluate proposed control schemes

  7. Strategies for 2nd generation biofuels in EU - Co-firing to stimulate feedstock supply development and process integration to improve energy efficiency and economic competitiveness

    International Nuclear Information System (INIS)

    Berndes, Goeran; Hansson, Julia; Egeskog, Andrea; Johnsson, Filip

    2010-01-01

    The present biofuel policies in the European Union primarily stimulate 1st generation biofuels that are produced based on conventional food crops. They may be a distraction from lignocellulose based 2nd generation biofuels - and also from biomass use for heat and electricity - by keeping farmers' attention and significant investments focusing on first generation biofuels and the cultivation of conventional food crops as feedstocks. This article presents two strategies that can contribute to the development of 2nd generation biofuels based on lignocellulosic feedstocks. The integration of gasification-based biofuel plants in district heating systems is one option for increasing the energy efficiency and improving the economic competitiveness of such biofuels. Another option, biomass co-firing with coal, generates high-efficiency biomass electricity and reduces CO 2 emissions by replacing coal. It also offers a near-term market for lignocellulosic biomass, which can stimulate development of supply systems for biomass also suitable as feedstock for 2nd generation biofuels. Regardless of the long-term priorities of biomass use for energy, the stimulation of lignocellulosic biomass production by development of near term and cost-effective markets is judged to be a no-regrets strategy for Europe. Strategies that induce a relevant development and exploit existing energy infrastructures in order to reduce risk and reach lower costs, are proposed an attractive complement the present and prospective biofuel policies. (author)

  8. Prediction of geomagnetic storm using neural networks: Comparison of the efficiency of the Satellite and ground-based input parameters

    International Nuclear Information System (INIS)

    Stepanova, Marina; Antonova, Elizavieta; Munos-Uribe, F A; Gordo, S L Gomez; Torres-Sanchez, M V

    2008-01-01

    Different kinds of neural networks have established themselves as an effective tool in the prediction of different geomagnetic indices, including the Dst being the most important constituent for determination of the impact of Space Weather on the human life. Feed-forward networks with one hidden layer are used to forecast the Dst variation, using separately the solar wind paramenters, polar cap index, and auroral electrojet index as input parameters. It was found that in all three cases the storm-time intervals were predicted much more precisely as quite time intervals. The majority of cross-correlation coefficients between predicted and observed Dst of strong geomagnetic storms are situated between 0.8 and 0.9. Changes in the neural network architecture, including the number of nodes in the input and hidden layers and the transfer functions between them lead to an improvement of a network performance up to 10%.

  9. Efficient 1.9 μm emission in H2-filled hollow core fiber by pure stimulated vibrational Raman scattering

    International Nuclear Information System (INIS)

    Wang, Zefeng; Yu, Fei; Wadsworth, William J; Knight, Jonathan C

    2014-01-01

    We report here efficient 1.9 μm emission by pure stimulated vibrational Raman scattering in a hydrogen-filled anti-resonant hollow-core fiber pumped with a 1064 nm microchip laser. A maximum quantum conversion efficiency ∼48% was achieved by using a 6.5 m length of fiber filled with 23 bar hydrogen, with a maximum peak output power >2 kW. By properly designing the transmission bands of the fiber, selecting alternative pump sources and active gases, the emission wavelength could be extended into the mid-infrared. This provides a potential route for generating efficient, compact, broadly tunable, high power, and narrow linewidth mid-infrared fiber gas lasers with broad application in defense, environmental, and medical monitoring. (letter)

  10. Efficient and Fast Differentiation of Human Neural Stem Cells from Human Embryonic Stem Cells for Cell Therapy

    Directory of Open Access Journals (Sweden)

    Xinxin Han

    2017-01-01

    Full Text Available Stem cell-based therapies have been used for repairing damaged brain tissue and helping functional recovery after brain injury. Aberrance neurogenesis is related with brain injury, and multipotential neural stem cells from human embryonic stem (hES cells provide a great promise for cell replacement therapies. Optimized protocols for neural differentiation are necessary to produce functional human neural stem cells (hNSCs for cell therapy. However, the qualified procedure is scarce and detailed features of hNSCs originated from hES cells are still unclear. In this study, we developed a method to obtain hNSCs from hES cells, by which we could harvest abundant hNSCs in a relatively short time. Then, we examined the expression of pluripotent and multipotent marker genes through immunostaining and confirmed differentiation potential of the differentiated hNSCs. Furthermore, we analyzed the mitotic activity of these hNSCs. In this report, we provided comprehensive features of hNSCs and delivered the knowledge about how to obtain more high-quality hNSCs from hES cells which may help to accelerate the NSC-based therapies in brain injury treatment.

  11. Metabonomic Analysis Reveals Efficient Ameliorating Effects of Acupoint Stimulations on the Menopause-caused Alterations in Mammalian Metabolism

    Science.gov (United States)

    Zhang, Limin; Wang, Yulan; Xu, Yunxiang; Lei, Hehua; Zhao, Ying; Li, Huihui; Lin, Xiaosheng; Chen, Guizhen; Tang, Huiru

    2014-01-01

    Acupoint stimulations are effective in ameliorating symptoms of menopause which is an unavoidable ageing consequence for women. To understand the mechanistic aspects of such treatments, we systematically analyzed the effects of acupoint laser-irradiation and catgut-embedding on the ovariectomy-induced rat metabolic changes using NMR and GC-FID/MS methods. Results showed that ovariectomization (OVX) caused comprehensive metabolic changes in lipid peroxidation, glycolysis, TCA cycle, choline and amino acid metabolisms. Both acupoint laser-irradiation and catgut-embedding ameliorated the OVX-caused metabonomic changes more effectively than hormone replacement therapy (HRT) with nilestriol. Such effects of acupoint stimulations were highlighted in alleviating lipid peroxidation, restoring glucose homeostasis and partial reversion of the OVX-altered amino acid metabolism. These findings provided new insights into the menopause effects on mammalian biochemistry and beneficial effects of acupoint stimulations in comparison with HRT, demonstrating metabonomics as a powerful approach for potential applications in disease prognosis and developments of effective therapies.

  12. Evalutation of efficiency of dynamic laser magnetic stimulation of eye drainage system of patients with open angle glaucomatosis

    Directory of Open Access Journals (Sweden)

    Sidelnikova V.S.

    2014-06-01

    Full Text Available The purpose of the study is to develop a comprehensive treatment aimed at improving uveoscleral outflow in the application of dynamic laser magnetic stimulation of the drainage system of the eye and evaluation of its effectiveness in treating patients with primary open-angle glaucoma (POAG. Material. 106 patients diagnosed POAG I, II, III stages were examined. Group 1 consisted of 62 patients treated with medical therapy and dynamic laser magnetic stimulation of the drainage system of the eye using the "AMO-ATOS-ICL", produced by JSC "TRIMA", Saratov. Group 2 consisted of 64 patients who received only medical therapy. Comprehensive survey including standard eye examination, static perimetry, visual evoked potentials study, the study of intraocular blood flow was conducted to all patients. Analysis of the results of the complex therapeutic effects showed that as the result of treatment 73% of patients had a decrease of intraocular pressure and the ease factor outflow increase. 52% of patients had a decrease in the number and area of relative. 63% of patients had activation of intraocular blood flow. These indices remained stable for three months. Conclusion. The treatment with the technique of dynamic laser magnetic stimulation of the drainage system of the eye of patients with primary open-angle glaucoma leads to lower intraocular pressure, and to the improvement of dopple-rographic and perimetric indications.

  13. Does regulation stimulate productivity? The effect of air quality policies on the efficiency of US power plants

    International Nuclear Information System (INIS)

    Fleishman, Rachel; Alexander, Rob; Bretschneider, Stuart; Popp, David

    2009-01-01

    This research examines the effect of air quality regulations on the productivity of US power plants based on both economic and environmental outputs. Using data envelopment analysis (DEA) to estimate an efficiency measure incorporating both economic and environmental outcomes, we look at changes in efficiency in US power plants over an eleven-year time period (1994-2004) during which several different regulations were implemented for the control of nitrogen oxides (NO x ) and sulfur dioxide (SO 2 ). The paper then models how estimated efficiency behaves over time as a function of regulatory changes. Findings suggest mixed effects of regulations on power plant efficiency when pollution abatement and electricity generation are both included as outputs.

  14. Stimulation of neural differentiation in human bone marrow mesenchymal stem cells by extremely low-frequency electromagnetic fields incorporated with MNPs.

    Science.gov (United States)

    Choi, Yun-Kyong; Lee, Dong Heon; Seo, Young-Kwon; Jung, Hyun; Park, Jung-Keug; Cho, Hyunjin

    2014-10-01

    Human bone marrow-derived mesenchymal stem cells (hBM-MSCs) have been investigated as a new cell-therapeutic solution due to their capacity that could differentiate into neural-like cells. Extremely low-frequency electromagnetic fields (ELF-EMFs) therapy has emerged as a novel technique, using mechanical stimulus to differentiate hBM-MSCs and significantly enhance neuronal differentiation to affect cellular and molecular reactions. Magnetic iron oxide (Fe3O4) nanoparticles (MNPs) have recently achieved widespread use for biomedical applications and polyethylene glycol (PEG)-labeled nanoparticles are used to increase their circulation time, aqueous solubility, biocompatibility, and nonspecific cellular uptake as well as to decrease immunogenicity. Many studies have used MNP-labeled cells for differentiation, but there have been no reports of MNP-labeled neural differentiation combined with EMFs. In this study, synthesized PEG-phospholipid encapsulated magnetite (Fe3O4) nanoparticles are used on hBM-MSCs to improve their intracellular uptake. The PEGylated nanoparticles were exposed to the cells under 50 Hz of EMFs to improve neural differentiation. First, we measured cell viability and intracellular iron content in hBM-MSCs after treatment with MNPs. Analysis was conducted by RT-PCR, and immunohistological analysis using neural cell type-specific genes and antibodies after exposure to 50 Hz electromagnetic fields. These results suggest that electromagnetic fields enhance neural differentiation in hBM-MSCs incorporated with MNPs and would be an effective method for differentiating neural cells.

  15. Fuel cell-based CHP system modelling using Artificial Neural Networks aimed at developing techno-economic efficiency maximization control systems

    International Nuclear Information System (INIS)

    Asensio, F.J.; San Martín, J.I.; Zamora, I.; Garcia-Villalobos, J.

    2017-01-01

    This paper focuses on the modelling of the performance of a Polymer Electrolyte Membrane Fuel Cell (PEMFC)-based cogeneration system to integrate it in hybrid and/or connected to grid systems and enable the optimization of the techno-economic efficiency of the system in which it is integrated. To this end, experimental tests on a PEMFC-based cogeneration system of 600 W of electrical power have been performed to train an Artificial Neural Network (ANN). Once the learning of the ANN, it has been able to emulate real operating conditions, such as the cooling water out temperature and the hydrogen consumption of the PEMFC depending on several variables, such as the electric power demanded, temperature of the inlet water flow to the cooling circuit, cooling water flow and the heat demanded to the CHP system. After analysing the results, it is concluded that the presented model reproduces with enough accuracy and precision the performance of the experimented PEMFC, thus enabling the use of the model and the ANN learning methodology to model other PEMFC-based cogeneration systems and integrate them in techno-economic efficiency optimization control systems. - Highlights: • The effect of the energy demand variation on the PEMFC's efficiency is predicted. • The model relies on experimental data obtained from a 600 W PEMFC. • It provides the temperature and the hydrogen consumption with good accuracy. • The range in which the global energy efficiency could be improved is provided.

  16. Differential Contribution of the Guanylyl Cyclase-Cyclic GMP-Protein Kinase G Pathway to the Proliferation of Neural Stem Cells Stimulated by Nitric Oxide

    Directory of Open Access Journals (Sweden)

    Bruno P. Carreira

    2012-02-01

    Full Text Available Nitric oxide (NO is an important inflammatory mediator involved in the initial boost in the proliferation of neural stem cells following brain injury. However, the mechanisms underlying the proliferative effect of NO are still unclear. The aim of this work was to investigate whether cyclic GMP (cGMP and the cGMP-dependent kinase (PKG are involved in the proliferative effect triggered by NO in neural stem cells. For this purpose, cultures of neural stem cells isolated from the mouse subventricular zone (SVZ were used. We observed that long-term exposure to the NO donor (24 h, NOC-18, increased the proliferation of SVZ cells in a cGMP-dependent manner, since the guanylate cyclase inhibitor, ODQ, prevented cell proliferation. Similarly to NOC-18, the cGMP analogue, 8-Br-cGMP, also increased cell proliferation. Interestingly, shorter exposures to NO (6 h increased cell proliferation in a cGMP-independent manner via the ERK/MAP kinase pathway. The selective inhibitor of PKG, KT5823, prevented the proliferative effect induced by NO at 24 h but not at 6 h. In conclusion, the proliferative effect of NO is initially mediated by the ERK/MAPK pathway, and at later stages by the GC/cGMP/PKG pathway. Thus, our work shows that NO induces neural stem cell proliferation by targeting these two pathways in a biphasic manner.

  17. Efficient trigger signal generation from wasted backward amplified stimulated emission at optical amplifiers for optical coherence tomography

    Directory of Open Access Journals (Sweden)

    Kim Seung Taek

    2015-01-01

    Full Text Available This paper propose an optical structure to generate trigger signals for optical coherence tomography (OCT using backward light which is usually disposed. The backward light is called backward amplified stimulated emission generated from semiconductor optical amplifier (SOA when using swept wavelength tunable laser (SWTL. A circulator is applied to block undesirable lights in the SWTL instead of an isolator in common SWTL. The circulator also diverts backward amplified spontaneous lights, which finally bring out trigger signals for a high speed digitizer. The spectra of the forward lights at SOA and the waveform of the backward lights were measured to check the procedure of the trigger formation in the experiment. The results showed that the trigger signals from the proposed SWTL with the circulator was quite usable in OCT.

  18. 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.

  19. Efficient Monte Carlo sampling of inverse problems using a neural network-based forward—applied to GPR crosshole traveltime inversion

    Science.gov (United States)

    Hansen, T. M.; Cordua, K. S.

    2017-12-01

    Probabilistically formulated inverse problems can be solved using Monte Carlo-based sampling methods. In principle, both advanced prior information, based on for example, complex geostatistical models and non-linear forward models can be considered using such methods. However, Monte Carlo methods may be associated with huge computational costs that, in practice, limit their application. This is not least due to the computational requirements related to solving the forward problem, where the physical forward response of some earth model has to be evaluated. Here, it is suggested to replace a numerical complex evaluation of the forward problem, with a trained neural network that can be evaluated very fast. This will introduce a modeling error that is quantified probabilistically such that it can be accounted for during inversion. This allows a very fast and efficient Monte Carlo sampling of the solution to an inverse problem. We demonstrate the methodology for first arrival traveltime inversion of crosshole ground penetrating radar data. An accurate forward model, based on 2-D full-waveform modeling followed by automatic traveltime picking, is replaced by a fast neural network. This provides a sampling algorithm three orders of magnitude faster than using the accurate and computationally expensive forward model, and also considerably faster and more accurate (i.e. with better resolution), than commonly used approximate forward models. The methodology has the potential to dramatically change the complexity of non-linear and non-Gaussian inverse problems that have to be solved using Monte Carlo sampling techniques.

  20. From neuro-pigments to neural efficiency: The relationship between retinal carotenoids and behavioral and neuroelectric indices of cognitive control in childhood.

    Science.gov (United States)

    Walk, Anne M; Khan, Naiman A; Barnett, Sasha M; Raine, Lauren B; Kramer, Arthur F; Cohen, Neal J; Moulton, Christopher J; Renzi-Hammond, Lisa M; Hammond, Billy R; Hillman, Charles H

    2017-08-01

    Lutein and zeaxanthin are plant pigments known to preferentially accumulate in neural tissue. Macular Pigment Optical Density (MPOD), a non-invasive measure of retinal carotenoids and surrogate measure of brain carotenoid concentration, has been associated with disease prevention and cognitive health. Superior MPOD status in later adulthood has been shown to provide neuroprotective effects on cognition. Given that childhood signifies a critical period for carotenoid accumulation in brain, it is likely that the beneficial impact would be evident during development, though this relationship has not been directly investigated. The present study investigated the relationship between MPOD and the behavioral and neuroelectric indices elicited during a cognitive control task in preadolescent children. 49 participants completed a modified flanker task while event-related potentials (ERPs) were recorded to assess the P3 component of the ERP waveform. MPOD was associated with both behavioral performance and P3 amplitude such that children with higher MPOD had more accurate performance and lower P3 amplitudes. These relationships were more pronounced for trials requiring greater amounts of cognitive control. These results indicate that children with higher MPOD may respond to cognitive tasks more efficiently, maintaining high performance while displaying neural indices indicative of lower cognitive load. These findings provide novel support for the neuroprotective influence of retinal carotenoids during preadolescence. Copyright © 2017 Elsevier B.V. All rights reserved.

  1. Safe and efficient method for cryopreservation of human induced pluripotent stem cell-derived neural stem and progenitor cells by a programmed freezer with a magnetic field.

    Science.gov (United States)

    Nishiyama, Yuichiro; Iwanami, Akio; Kohyama, Jun; Itakura, Go; Kawabata, Soya; Sugai, Keiko; Nishimura, Soraya; Kashiwagi, Rei; Yasutake, Kaori; Isoda, Miho; Matsumoto, Morio; Nakamura, Masaya; Okano, Hideyuki

    2016-06-01

    Stem cells represent a potential cellular resource in the development of regenerative medicine approaches to the treatment of pathologies in which specific cells are degenerated or damaged by genetic abnormality, disease, or injury. Securing sufficient supplies of cells suited to the demands of cell transplantation, however, remains challenging, and the establishment of safe and efficient cell banking procedures is an important goal. Cryopreservation allows the storage of stem cells for prolonged time periods while maintaining them in adequate condition for use in clinical settings. Conventional cryopreservation systems include slow-freezing and vitrification both have advantages and disadvantages in terms of cell viability and/or scalability. In the present study, we developed an advanced slow-freezing technique using a programmed freezer with a magnetic field called Cells Alive System (CAS) and examined its effectiveness on human induced pluripotent stem cell-derived neural stem/progenitor cells (hiPSC-NS/PCs). This system significantly increased cell viability after thawing and had less impact on cellular proliferation and differentiation. We further found that frozen-thawed hiPSC-NS/PCs were comparable with non-frozen ones at the transcriptome level. Given these findings, we suggest that the CAS is useful for hiPSC-NS/PCs banking for clinical uses involving neural disorders and may open new avenues for future regenerative medicine. Copyright © 2015 The Authors. Published by Elsevier Ireland Ltd.. All rights reserved.

  2. Enhancement of the grafting efficiency of transplanted marrow cells by preincubation with interleukin-3 and granulocyte-macrophage colony-stimulating factor

    Energy Technology Data Exchange (ETDEWEB)

    Tavassoli, M.; Konno, M.; Shiota, Y.; Omoto, E.; Minguell, J.J.; Zanjani, E.D.

    1991-04-01

    To improve the grafting efficiency of transplanted murine hematopoietic progenitors, we briefly preincubated mouse bone marrow cells with interleukin-3 (IL-3) or granulocyte-macrophage colony-stimulating factor (GM-CSF) ex vivo before their transplantation into irradiated recipients. This treatment was translated into an increase in the seeding efficiency of colony-forming unit-spleen (CFU-S) and CFU-GM after transplantation. Not only was the concentration of CFU-S in the tibia increased 2 and 24 hours after transplantation, but the total cell number and CFU-S and CFU-GM concentrations were persistently higher in IL-3- and GM-CSF-treated groups 1 to 3 weeks after transplantation. In addition, the survival of animals as a function of transplanted cell number was persistently higher in IL-3- and GM-CSF-treated groups compared with controls. The data indicate that the pretreatment of marrow cells with IL-3 and GM-CSF before transplantation increases the seeding efficiency of hematopoietic stem cells and probably other progenitor cells after transplantation. This increased efficiency may be mediated by upward modulation of homing receptors. Therefore, ex vivo preincubation of donor marrow cells with IL-3 and GM-CSF may be a useful tactic in bone marrow transplantation.

  3. Structural Reliability: An Assessment Using a New and Efficient Two-Phase Method Based on Artificial Neural Network and a Harmony Search Algorithm

    Directory of Open Access Journals (Sweden)

    Naser Kazemi Elaki

    2016-06-01

    Full Text Available In this research, a two-phase algorithm based on the artificial neural network (ANN and a harmony search (HS algorithm has been developed with the aim of assessing the reliability of structures with implicit limit state functions. The proposed method involves the generation of datasets to be used specifically for training by Finite Element analysis, to establish an ANN model using a proven ANN model in the reliability assessment process as an analyzer for structures, and finally estimate the reliability index and failure probability by using the HS algorithm, without any requirements for the explicit form of limit state function. The proposed algorithm is investigated here, and its accuracy and efficiency are demonstrated by using several numerical examples. The results obtained show that the proposed algorithm gives an appropriate estimate for the assessment of reliability of structures.

  4. Stimulating energy-efficient innovations in the Dutch building sector: Empirical evidence from patent counts and policy lessons

    International Nuclear Information System (INIS)

    Noailly, Joelle; Batrakova, Svetlana

    2010-01-01

    In the Netherlands where the building sector accounts for 33% of carbon emissions, the government aims to halve the total energy use from buildings by 2030 compared to 1990 levels. To this end, the Dutch government has set specific goals in order to foster technological innovation related to energy efficiency in buildings. The objective of this paper is to explore the links between technological innovation and public policies in this sector over the last 30 years. The paper aims (1) to measure the evolution of innovations related to energy efficiency in buildings in the Netherlands using patent counts and (2) to provide a historical overview of the policy framework. Descriptive data on patenting activities show that the Netherlands have a clear comparative advantage in the field of energy-saving lighting technologies, mainly due to intensive patenting activities by Philips. High-efficiency boilers also represent a substantial share of Dutch innovation activities in this domain over the last decades. In many other fields (such as insulation, heat-pumps and cogeneration, solar boilers, etc.), however, Germany, Austria and Scandinavian countries rank much higher than the Netherlands. The descriptive analysis of Dutch energy policy shows an intensification of energy policy in the mid-1990s, followed by a slight decline after 2001. Overall, the simultaneous introduction of policy instruments makes it difficult to evaluate the effectiveness of policies. Also, the policy framework is characterized by the introduction of a large number of short-lived policy instruments and frequent policy changes. The lack of stability and continuity of energy policy may be damaging for innovation. - Research Highlights: →The Netherlands are a top innovative country in the field of energy-efficient innovations for buildings, mainly due to high patenting activities by Philips in energy-saving lighting technologies. →In many other fields (insulation, heat-pumps, etc) Germany, Austria and

  5. Histopathological examination of nerve samples from pure neural leprosy patients: obtaining maximum information to improve diagnostic efficiency

    Directory of Open Access Journals (Sweden)

    Sérgio Luiz Gomes Antunes

    2012-03-01

    Full Text Available Nerve biopsy examination is an important auxiliary procedure for diagnosing pure neural leprosy (PNL. When acid-fast bacilli (AFB are not detected in the nerve sample, the value of other nonspecific histological alterations should be considered along with pertinent clinical, electroneuromyographical and laboratory data (the detection of Mycobacterium leprae DNA with polymerase chain reaction and the detection of serum anti-phenolic glycolipid 1 antibodies to support a possible or probable PNL diagnosis. Three hundred forty nerve samples [144 from PNL patients and 196 from patients with non-leprosy peripheral neuropathies (NLN] were examined. Both AFB-negative and AFB-positive PNL samples had more frequent histopathological alterations (epithelioid granulomas, mononuclear infiltrates, fibrosis, perineurial and subperineurial oedema and decreased numbers of myelinated fibres than the NLN group. Multivariate analysis revealed that independently, mononuclear infiltrate and perineurial fibrosis were more common in the PNL group and were able to correctly classify AFB-negative PNL samples. These results indicate that even in the absence of AFB, these histopathological nerve alterations may justify a PNL diagnosis when observed in conjunction with pertinent clinical, epidemiological and laboratory data.

  6. Histopathological examination of nerve samples from pure neural leprosy patients: obtaining maximum information to improve diagnostic efficiency.

    Science.gov (United States)

    Antunes, Sérgio Luiz Gomes; Chimelli, Leila; Jardim, Márcia Rodrigues; Vital, Robson Teixeira; Nery, José Augusto da Costa; Corte-Real, Suzana; Hacker, Mariana Andréa Vilas Boas; Sarno, Euzenir Nunes

    2012-03-01

    Nerve biopsy examination is an important auxiliary procedure for diagnosing pure neural leprosy (PNL). When acid-fast bacilli (AFB) are not detected in the nerve sample, the value of other nonspecific histological alterations should be considered along with pertinent clinical, electroneuromyographical and laboratory data (the detection of Mycobacterium leprae DNA with polymerase chain reaction and the detection of serum anti-phenolic glycolipid 1 antibodies) to support a possible or probable PNL diagnosis. Three hundred forty nerve samples [144 from PNL patients and 196 from patients with non-leprosy peripheral neuropathies (NLN)] were examined. Both AFB-negative and AFB-positive PNL samples had more frequent histopathological alterations (epithelioid granulomas, mononuclear infiltrates, fibrosis, perineurial and subperineurial oedema and decreased numbers of myelinated fibres) than the NLN group. Multivariate analysis revealed that independently, mononuclear infiltrate and perineurial fibrosis were more common in the PNL group and were able to correctly classify AFB-negative PNL samples. These results indicate that even in the absence of AFB, these histopathological nerve alterations may justify a PNL diagnosis when observed in conjunction with pertinent clinical, epidemiological and laboratory data.

  7. Stimulating R and D of industrial energy-efficient technology; the effect of government intervention on the development of strip casting technology

    International Nuclear Information System (INIS)

    Luiten, E.E.M.; Blok, Kornelis

    2003-01-01

    Strip casting technology in steel-making is known as an innovative energy-efficient technology. Stimulating the development (R and D) of such industrial process technologies is an appealing government intervention strategy for reducing greenhouse gas emissions. In this article, we analyse (a) the R and D trajectory of strip casting technology and (b) the effect of government intervention on the development of this particular energy-efficient technology. For this purpose we made a detailed investigation of the networks within which the technology was developed. The huge capital cost advantages of strip casting technology were already notified back in the 19th century. However, only after 1975 a robust technology network emerged. There is no single, simple determinant explaining the slow emergence of the technology network: the innovative technology had to become a more incremental improvement to the conventional production facilities before R and D was seriously pursued. Once the technology network emerged, it proved to have a strong momentum of itself. Steel firms maintained their confidence in the strategic cost advantages of the technology and persistently invested in up-scaling the technology. The effect of government intervention was minimal, because the technology network had its own strong momentum. All in all, R and D was only loosely influenced by energy-efficiency considerations or by government intervention. The major policy lesson is that information on technology networks and its momentum--in addition to classic information on energy-efficiency improvements and investments costs--is required to improve the effect of government intervention in the field of industrial energy-efficiency R and D and innovation

  8. Motor cortex stimulation: role of computer modeling

    NARCIS (Netherlands)

    Manola, L.; Holsheimer, J.; Sakas, D.E.; Simpson, B.A

    Motor cortex stimulation (MCS) is a promising clinical technique used to treat chronic, otherwise intractable pain. However, the mechanisms by which the neural elements that are stimulated during MCS induce pain relief are not understood. Neither is it known which neural elements (fibers (parallel

  9. A Lipid Based Antigen Delivery System Efficiently Facilitates MHC Class-I Antigen Presentation in Dendritic Cells to Stimulate CD8+ T Cells

    Science.gov (United States)

    Maji, Mithun; Mazumder, Saumyabrata; Bhattacharya, Souparno; Choudhury, Somsubhra Thakur; Sabur, Abdus; Shadab, Md.; Bhattacharya, Pradyot; Ali, Nahid

    2016-06-01

    The most effective strategy for protection against intracellular infections such as Leishmania is vaccination with live parasites. Use of recombinant proteins avoids the risks associated with live vaccines. However, due to low immunogenicity, they fail to trigger T cell responses particularly of CD8+ cells requisite for persistent immunity. Previously we showed the importance of protein entrapment in cationic liposomes and MPL as adjuvant for elicitation of CD4+ and CD8+ T cell responses for long-term protection. In this study we investigated the role of cationic liposomes on maturation and antigen presentation capacity of dendritic cells (DCs). We observed that cationic liposomes were taken up very efficiently by DCs and transported to different cellular sites. DCs activated with liposomal rgp63 led to efficient presentation of antigen to specific CD4+ and CD8+ T cells. Furthermore, lymphoid CD8+ T cells from liposomal rgp63 immunized mice demonstrated better proliferative ability when co-cultured ex vivo with stimulated DCs. Addition of MPL to vaccine enhanced the antigen presentation by DCs and induced more efficient antigen specific CD8+ T cell responses when compared to free and liposomal antigen. These liposomal formulations presented to CD8+ T cells through TAP-dependent MHC-I pathway offer new possibilities for a safe subunit vaccine.

  10. Kilohertz and Low-Frequency Electrical Stimulation With the Same Pulse Duration Have Similar Efficiency for Inducing Isometric Knee Extension Torque and Discomfort.

    Science.gov (United States)

    Medeiros, Flávia Vanessa; Bottaro, Martim; Vieira, Amilton; Lucas, Tiago Pires; Modesto, Karenina Arrais; Bo, Antonio Padilha L; Cipriano, Gerson; Babault, Nicolas; Durigan, João Luiz Quagliotti

    2017-06-01

    To test the hypotheses that, as compared with pulsed current with the same pulse duration, kilohertz frequency alternating current would not differ in terms of evoked-torque production and perceived discomfort, and as a result, it would show the same current efficiency. A repeated-measures design with 4 stimuli presented in random order was used to test 25 women: (1) 500-microsecond pulse duration, (2) 250-microsecond pulse duration, (3) 500-microsecond pulse duration and low carrier frequency (1 kHz), (4) 250-microsecond pulse duration and high carrier frequency (4 kHz). Isometric peak torque of quadriceps muscle was measured using an isokinetic dynamometer. Discomfort was measured using a visual analog scale. Currents with long pulse durations induced approximately 21% higher evoked torque than short pulse durations. In addition, currents with 500 microseconds delivered greater amounts of charge than stimulation patterns using 250-microsecond pulse durations (P torque and discomfort. However, neuromuscular electrical stimulation (NMES) with longer pulse duration induces higher NMES-evoked torque, regardless of the carrier frequency. Pulse duration is an important variable that should receive more attention for an optimal application of NMES in clinical settings.

  11. Stimulating utilities to promote energy efficiency: Process evaluation of Madison Gas and Electric's Competition Pilot Program

    Energy Technology Data Exchange (ETDEWEB)

    Vine, E.; De Buen, O.; Goldfman, C.

    1990-12-01

    This report describes the process evaluation of the design and implementation of the Energy Conservation Competition Pilot (hereafter referred to as the Competition), ordered by the Public Service Commission of Wisconsin (PSCW) with a conceptual framework defined by PSCW staff for the Madison Gas and Electric (MGE) Company. This process evaluation documents the history of the Competition, describing the marketing strategies adopted by MGE and its competitors, customer service and satisfaction, administrative issues, the distribution of installed measures, free riders, and the impact of the Competition on MGE, its competitors, and other Wisconsin utilities. We also suggest recommendations for a future Competition, compare the Competition with other approaches that public utility commissions (PUCs) have used to motivate utilities to promote energy efficiency, and discuss its transferability to other utilities. 48 refs., 8 figs., 40 tabs.

  12. Medial forebrain bundle lesions fail to structurally and functionally disconnect the ventral tegmental area from many ipsilateral forebrain nuclei: implications for the neural substrate of brain stimulation reward.

    Science.gov (United States)

    Simmons, J M; Ackermann, R F; Gallistel, C R

    1998-10-15

    Lesions in the medial forebrain bundle rostral to a stimulating electrode have variable effects on the rewarding efficacy of self-stimulation. We attempted to account for this variability by measuring the anatomical and functional effects of electrolytic lesions at the level of the lateral hypothalamus (LH) and by correlating these effects to postlesion changes in threshold pulse frequency (pps) for self-stimulation in the ventral tegmental area (VTA). We implanted True Blue in the VTA and compared cell labeling patterns in forebrain regions of intact and lesioned animals. We also compared stimulation-induced regional [14C]deoxyglucose (DG) accumulation patterns in the forebrains of intact and lesioned animals. As expected, postlesion threshold shifts varied: threshold pps remained the same or decreased in eight animals, increased by small but significant amounts in three rats, and increased substantially in six subjects. Unexpectedly, LH lesions did not anatomically or functionally disconnect all forebrain nuclei from the VTA. Most septal and preoptic regions contained equivalent levels of True Blue label in intact and lesioned animals. In both intact and lesioned groups, VTA stimulation increased metabolic activity in the fundus of the striatum (FS), the nucleus of the diagonal band, and the medial preoptic area. On the other hand, True Blue labeling demonstrated anatomical disconnection of the accumbens, FS, substantia innominata/magnocellular preoptic nucleus (SI/MA), and bed nucleus of the stria terminalis. [14C]DG autoradiography indicated functional disconnection of the lateral preoptic area and SI/MA. Correlations between patterns of True Blue labeling or [14C]deoxyglucose accumulation and postlesion shifts in threshold pulse frequency were weak and generally negative. These direct measures of connectivity concord with the behavioral measures in suggesting a diffuse net-like connection between forebrain nuclei and the VTA.

  13. Eating breakfast enhances the efficiency of neural networks engaged during mental arithmetic in school-aged children.

    Science.gov (United States)

    Pivik, R T; Tennal, Kevin B; Chapman, Stephen D; Gu, Yuyuan

    2012-06-25

    To determine the influence of a morning meal on complex mental functions in children (8-11 y), time-frequency analyses were applied to electroencephalographic (EEG) activity recorded while children solved simple addition problems after an overnight fast and again after having either eaten or skipped breakfast. Power of low frequency EEG activity [2 Hertz (Hz) bands in the 2-12 Hz range] was determined from recordings over frontal and parietal brain regions associated with mathematical thinking during mental calculation of correctly answered problems. Analyses were adjusted for background variables known to influence or reflect the development of mathematical skills, i.e., age and measures of math competence and math fluency. Relative to fed children, those who continued to fast showed greater power increases in upper theta (6-8 Hz) and both alpha bands (8-10 Hz; 10-12 Hz) across sites. Increased theta suggests greater demands on working memory. Increased alpha may facilitate task-essential activity by suppressing non-task-essential activity. Fasting children also had greater delta (2-4 Hz) and greater lower-theta (4-6 Hz) power in left frontal recordings-indicating a region-specific emphasis on both working memory for mental calculation (theta) and activation of processes that suppress interfering activity (delta). Fed children also showed a significant increase in correct responses while children who continued to fast did not. Taken together the findings suggest that neural network activity involved in processing numerical information is functionally enhanced and performance is improved in children who have eaten breakfast, whereas greater mental effort is required for this mathematical thinking in children who skip breakfast. Copyright © 2012 Elsevier Inc. All rights reserved.

  14. Development of a thermal control algorithm using artificial neural network models for improved thermal comfort and energy efficiency in accommodation buildings

    International Nuclear Information System (INIS)

    Moon, Jin Woo; Jung, Sung Kwon

    2016-01-01

    Highlights: • An ANN model for predicting optimal start moment of the cooling system was developed. • An ANN model for predicting the amount of cooling energy consumption was developed. • An optimal control algorithm was developed employing two ANN models. • The algorithm showed the advanced thermal comfort and energy efficiency. - Abstract: The aim of this study was to develop a control algorithm to demonstrate the improved thermal comfort and building energy efficiency of accommodation buildings in the cooling season. For this, two artificial neural network (ANN)-based predictive and adaptive models were developed and employed in the algorithm. One model predicted the cooling energy consumption during the unoccupied period for different setback temperatures and the other predicted the time required for restoring current indoor temperature to the normal set-point temperature. Using numerical simulation methods, the prediction accuracy of the two ANN models and the performance of the algorithm were tested. Through the test result analysis, the two ANN models showed their prediction accuracy with an acceptable error rate when applied in the control algorithm. In addition, the two ANN models based algorithm can be used to provide a more comfortable and energy efficient indoor thermal environment than the two conventional control methods, which respectively employed a fixed set-point temperature for the entire day and a setback temperature during the unoccupied period. Therefore, the operating range was 23–26 °C during the occupied period and 25–28 °C during the unoccupied period. Based on the analysis, it can be concluded that the optimal algorithm with two predictive and adaptive ANN models can be used to design a more comfortable and energy efficient indoor thermal environment for accommodation buildings in a comprehensive manner.

  15. 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...

  16. A Wireless Implantable Switched-Capacitor Based Optogenetic Stimulating System

    Science.gov (United States)

    Lee, Hyung-Min; Kwon, Ki-Yong; Li, Wen

    2015-01-01

    This paper presents a power-efficient implantable optogenetic interface using a wireless switched-capacitor based stimulating (SCS) system. The SCS efficiently charges storage capacitors directly from an inductive link and periodically discharges them into an array of micro-LEDs, providing high instantaneous power without affecting wireless link and system supply voltage. A custom-designed computer interface in LabVIEW environment wirelessly controls stimulation parameters through the inductive link, and an optrode array enables simultaneous neural recording along with optical stimulation. The 4-channel SCS system prototype has been implemented in a 0.35-μm CMOS process and combined with the optrode array. In vivo experiments involving light-induced local field potentials verified the efficacy of the SCS system. An implantable version of the SCS system with flexible hermetic sealing is under development for chronic experiments. PMID:25570099

  17. The effect of unilateral thalamic deep brain stimulation on the vocal dysfunction in a patient with spasmodic dysphonia: interrogating cerebellar and pallidal neural circuits.

    Science.gov (United States)

    Poologaindran, Anujan; Ivanishvili, Zurab; Morrison, Murray D; Rammage, Linda A; Sandhu, Mini K; Polyhronopoulos, Nancy E; Honey, Christopher R

    2018-02-01

    Spasmodic dysphonia (SD) is a neurological disorder of the voice where a patient's ability to speak is compromised due to involuntary contractions of the intrinsic laryngeal muscles. Since the 1980s, SD has been treated with botulinum toxin A (BTX) injections into the throat. This therapy is limited by the delayed-onset of benefits, wearing-off effects, and repeated injections required every 3 months. In a patient with essential tremor (ET) and coincident SD, the authors set out to quantify the effects of thalamic deep brain stimulation (DBS) on vocal function while investigating the underlying motor thalamic circuitry. A 79-year-old right-handed woman with ET and coincident adductor SD was referred to our neurosurgical team. While primarily treating her limb tremor, the authors studied the effects of unilateral, thalamic DBS on vocal function using the Unified Spasmodic Dysphonia Rating Scale (USDRS) and voice-related quality of life (VRQOL). Since dystonia is increasingly being considered a multinodal network disorder, an anterior trajectory into the left thalamus was deliberately chosen such that the proximal contacts of the electrode were in the ventral oralis anterior (Voa) nucleus (pallidal outflow) and the distal contacts were in the ventral intermediate (Vim) nucleus (cerebellar outflow). In addition to assessing on/off unilateral thalamic Vim stimulation on voice, the authors experimentally assessed low-voltage unilateral Vim, Voa, or multitarget stimulation in a prospective, randomized, doubled-blinded manner. The evaluators were experienced at rating SD and were familiar with the vocal tremor of ET. A Wilcoxon signed-rank test was used to study the pre- and posttreatment effect of DBS on voice. Unilateral left thalamic Vim stimulation (DBS on) significantly improved SD vocal dysfunction compared with no stimulation (DBS off), as measured by the USDRS (p dysphonia. A Phase 1 pilot trial (DEBUSSY; clinical trial no. NCT02558634, clinicaltrials.gov) is

  18. Sodium-potassium synergism in Theobroma cacao: stimulation of photosynthesis, water-use efficiency and mineral nutrition.

    Science.gov (United States)

    Gattward, James N; Almeida, Alex-Alan F; Souza, José O; Gomes, Fábio P; Kronzucker, Herbert J

    2012-11-01

    In ecological setting, sodium (Na(+)) can be beneficial or toxic, depending on plant species and the Na(+) level in the soil. While its effects are more frequently studied at high saline levels, Na(+) has also been shown to be of potential benefit to some species at lower levels of supply, especially in C4 species. Here, clonal plants of the major tropical C3 crop Theobroma cacao (cacao) were grown in soil where potassium (K(+)) was partially replaced (at six levels, up to 50% replacement) by Na(+), at two concentrations (2.5 and 4.0 mmol(c) dm(-3)). At both concentrations, net photosynthesis per unit leaf area (A) increased more than twofold with increasing substitution of K(+) by Na(+). Concomitantly, instantaneous (A/E) and intrinsic (A/g(s)) water-use efficiency (WUE) more than doubled. Stomatal conductance (g(s)) and transpiration rate (E) exhibited a decline at 2.5 mmol dm(-3), but remained unchanged at 4 mmol dm(-3). Leaf nitrogen content was not impacted by Na(+) supplementation, whereas sulfur (S), calcium (Ca(2+)), magnesium (Mg(2+)) and zinc (Zn(2+)) contents were maximized at 2.5 mmol dm(-3) and intermediate (30-40%) replacement levels. Leaf K(+) did not decline significantly. In contrast, leaf Na(+) content increased steadily. The resultant elevated Na(+)/K(+) ratios in tissue correlated with increased, not decreased, plant performance. The results show that Na(+) can partially replace K(+) in the nutrition of clonal cacao, with significant beneficial effects on photosynthesis, WUE and mineral nutrition in this major perennial C3 crop. Copyright © Physiologia Plantarum 2012.

  19. A distributed transducer system for functional electrical stimulation

    DEFF Research Database (Denmark)

    Gudnason, Gunnar; Nielsen, Jannik Hammel; Bruun, Erik

    2001-01-01

    to be affected by the inductive link. Neural stimulators are affected to a lesser degree, but still benefit from the partitioning. As a test case, we have designed a transceiver and a sensor chip which implement this partitioning policy. The transceiver is designed to operate in the 6.78 MHz ISM band......Implanted transducers for functional electrical stimulation (FES) powered by inductive links are subject to conflicting requirements arising from low link efficiency, a low power budget and the need for protection of the weak signals against strong RF electromagnetic fields. We propose a solution...... to these problems by partitioning the RF transceiver and sensor/actuator functions onto separate integrated circuits. By amplifying measured neural signals directly at the measurements site and converting them into the digital domain before passing them to the transceiver the signal integrity is less likely...

  20. 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 ...

  1. Recycling of wastes from fish beneficiation by composting: chemical characteristics of the compost and efficiency of their humic acids in stimulating the growth of lettuce.

    Science.gov (United States)

    Busato, Jader Galba; de Carvalho, Caroline Moreira; Zandonadi, Daniel Basilio; Sodré, Fernando Fabriz; Mol, Alan Ribeiro; de Oliveira, Aline Lima; Navarro, Rodrigo Diana

    2017-11-23

    Waste from the beneficiation of fish was composted with crushed grass aiming to characterize their chemical composition and investigate the possibility of the use of the final compost as source of humic acids (HA) able to stimulate the growth of lettuce. Compost presented pH value, C/N ratio, and electrical conductivity that allow its use as an organic fertilizer. The element content was present in the following order of abundance in the compost: P > Ca > N > Mg > K > Fe > Zn > Mn > Mo > Cu, and the humus composition was similar to that observed in others kind of organic residues composted. The high content of oxygen pointed out a high level of oxidation of HA, in line with the predominance of phenolic acidity in the functional groups. The 13 C-NMR spectra showed marked resonances due to the presence of lipids and other materials resistant to degradation as methoxy substituent and N-alkyl groups. A concentration of 20 mg L -1 HA increased significantly both dry and wet root matter in lettuce but the CO 2 assimilation, stomatal conductance, and number of lateral roots of the plants were not affected. However, increases of 64% in the water-use efficiency was observed due to the HA addition, probably related to the root morphology alteration which resulted in 1.6-fold increase of lateral root average length and due to the higher H + extrusion activity. Reuse of residues from the fish beneficiation activity by composting may represent a safe tool to increase the value of recycled organic residues and generate HA with potential use as plant growth stimulants.

  2. [Intervening in the neural basis of one's personality: a practice-oriented ethical analysis of neuropharmacology and deep-brain stimulation].

    Science.gov (United States)

    Synofzik, M

    2007-12-01

    Through the rapid progress in neuropharmacology it seems to become possible to effectively improve our cognitive capacities and emotional states by easily applicable means. Moreover, deep-brain stimulation may allow an effective therapeutic option for those neurological and psychiatric diseases which still can not be sufficiently treated by pharmacological measures. So far, however, both the benefit and the harm of these techniques are only insufficiently understood by neuroscience and detailed ethical analyses are still missing. In this article ethical criteria and most recent empirical evidence are systematically brought together for the first time. This analysis shows that it is irrelevant for an ethical evaluation whether a drug or a brain-machine interface is categorized as "enhancement" or "treatment" or whether it changes "human nature". The only decisive criteria are whether the intervention (1.) benefits the patient, (2.) does not harm the patient and (3.) is desired by the patient. However, current empirical data in both fields, neuropharmacology and deep-brain stimulation are still too sparse to adequately evaluate these criteria. Moreover, the focus in both fields has been strongly misled by neglecting the distinction between "benefit" and "efficacy": In past years research and clinical practice have only focused on physiological effects, but not on the actual benefit to the patient.

  3. An Efficient Approach for Lipase-Catalyzed Synthesis of Retinyl Laurate Nutraceutical by Combining Ultrasound Assistance and Artificial Neural Network Optimization

    Directory of Open Access Journals (Sweden)

    Shang-Ming Huang

    2017-11-01

    Full Text Available Although retinol is an important nutrient, retinol is highly sensitive to oxidation. At present, some ester forms of retinol are generally used in nutritional supplements because of its stability and bioavailability. However, such esters are commonly synthesized by chemical procedures which are harmful to the environment. Thus, this study utilized a green method using lipase as a catalyst with sonication assistance to produce a retinol derivative named retinyl laurate. Moreover, the process was optimized by an artificial neural network (ANN. First, a three-level-four-factor central composite design (CCD was employed to design 27 experiments, which the highest relative conversion was 82.64%. Further, the optimal architecture of the CCD-employing ANN was developed, including the learning Levenberg-Marquardt algorithm, the transfer function (hyperbolic tangent, iterations (10,000, and the nodes of the hidden layer (6. The best performance of the ANN was evaluated by the root mean squared error (RMSE and the coefficient of determination (R2 from predicting and observed data, which displayed a good data-fitting property. Finally, the process performed with optimal parameters actually obtained a relative conversion of 88.31% without long-term reactions, and the lipase showed great reusability for biosynthesis. Thus, this study utilizes green technology to efficiently produce retinyl laurate, and the bioprocess is well established by ANN-mediated modeling and optimization.

  4. An Efficient Approach for Lipase-Catalyzed Synthesis of Retinyl Laurate Nutraceutical by Combining Ultrasound Assistance and Artificial Neural Network Optimization.

    Science.gov (United States)

    Huang, Shang-Ming; Li, Hsin-Ju; Liu, Yung-Chuan; Kuo, Chia-Hung; Shieh, Chwen-Jen

    2017-11-15

    Although retinol is an important nutrient, retinol is highly sensitive to oxidation. At present, some ester forms of retinol are generally used in nutritional supplements because of its stability and bioavailability. However, such esters are commonly synthesized by chemical procedures which are harmful to the environment. Thus, this study utilized a green method using lipase as a catalyst with sonication assistance to produce a retinol derivative named retinyl laurate. Moreover, the process was optimized by an artificial neural network (ANN). First, a three-level-four-factor central composite design (CCD) was employed to design 27 experiments, which the highest relative conversion was 82.64%. Further, the optimal architecture of the CCD-employing ANN was developed, including the learning Levenberg-Marquardt algorithm, the transfer function (hyperbolic tangent), iterations (10,000), and the nodes of the hidden layer (6). The best performance of the ANN was evaluated by the root mean squared error (RMSE) and the coefficient of determination ( R ²) from predicting and observed data, which displayed a good data-fitting property. Finally, the process performed with optimal parameters actually obtained a relative conversion of 88.31% without long-term reactions, and the lipase showed great reusability for biosynthesis. Thus, this study utilizes green technology to efficiently produce retinyl laurate, and the bioprocess is well established by ANN-mediated modeling and optimization.

  5. Neural cell adhesion molecule-stimulated neurite outgrowth depends on activation of protein kinase C and the Ras-mitogen-activated protein kinase pathway

    DEFF Research Database (Denmark)

    Kolkova, K; Novitskaya, V; Pedersen, N

    2000-01-01

    , inhibitors of the nonreceptor tyrosine kinase p59(fyn), PLC, PKC and MEK and an activator of PKC, phorbol-12-myristate-13-acetate (PMA). MEK2 transfection rescued cells treated with all inhibitors. The same was found for PMA treatment, except when cells concomitantly were treated with the MEK inhibitor....... Arachidonic acid rescued cells treated with antibodies to the FGF receptor or the PLC inhibitor, but not cells in which the activity of PKC, p59(fyn), FAK, Ras, or MEK was inhibited. Interaction of NCAM with a synthetic NCAM peptide ligand, known to induce neurite outgrowth, was shown to stimulate...... phosphorylation of the MAP kinases extracellular signal-regulated kinases ERK1 and ERK2. The MAP kinase activation was sustained, because ERK1 and ERK2 were phosphorylated in PC12-E2 cells and primary hippocampal neurons even after 24 hr of cultivation on NCAM-expressing fibroblasts. Based on these results, we...

  6. Immunocytochemical localization of glutamic acid decarboxylase (GAD) and substance P in neural areas mediating motion-induced emesis: Effects of vagal stimulation on GAD immunoreactivity

    Science.gov (United States)

    Damelio, F.; Gibbs, M. A.; Mehler, W. R.; Daunton, Nancy G.; Fox, Robert A.

    1991-01-01

    Immunocytochemical methods were employed to localize the neurotransmitter amino acid gamma-aminobutyric acid (GABA) by means of its biosynthetic enzyme glutamic acid decarboxylase (GAD) and the neuropeptide substance P in the area postrema (AP), area subpostrema (ASP), nucleus of the tractus solitarius (NTS), and gelatinous nucleus (GEL). In addition, electrical stimulation was applied to the night vagus nerve at the cervical level to assess the effects on GAD-immunoreactivity (GAR-IR). GAD-IR terminals and fibers were observed in the AP, ASP, NTS, and GEL. They showed pronounced density at the level of the ASP and gradual decrease towards the solitary complex. Nerve cells were not labelled in our preparations. Ultrastructural studies showed symmetric or asymmetric synaptic contracts between labelled terminals and non-immunoreactive dendrites, axons, or neurons. Some of the labelled terminals contained both clear- and dense-core vesicles. Our preliminary findings, after electrical stimulation of the vagus nerve, revealed a bilateral decrease of GAD-IR that was particularly evident at the level of the ASP. SP-immunoreactive (SP-IR) terminals and fibers showed varying densities in the AP, ASP, NTS, and GEL. In our preparations, the lateral sub-division of the NTS showed the greatest accumulation. The ASP showed medium density of immunoreactive varicosities and terminals and the AP and GEL displayed scattered varicose axon terminals. The electron microscopy revealed that all immunoreactive terminals contained clear-core vesicles which make symmetric or asymmetric synaptic contact with unlabelled dendrites. It is suggested that the GABAergic terminals might correspond to vagal afferent projections and that GAD/GABA and substance P might be co-localized in the same terminal allowing the possibility of a regulated release of the transmitters in relation to demands.

  7. Stimulation of ganglionated plexus attenuates cardiac neural remodeling and heart failure progression in a canine model of acute heart failure post-myocardial infarction.

    Science.gov (United States)

    Luo, Da; Hu, Huihui; Qin, Zhiliang; Liu, Shan; Yu, Xiaomei; Ma, Ruisong; He, Wenbo; Xie, Jing; Lu, Zhibing; He, Bo; Jiang, Hong

    2017-12-01

    Heart failure (HF) is associated with autonomic dysfunction. Vagus nerve stimulation has been shown to improve cardiac function both in HF patients and animal models of HF. The purpose of this present study is to investigate the effects of ganglionated plexus stimulation (GPS) on HF progression and autonomic remodeling in a canine model of acute HF post-myocardial infarction. Eighteen adult mongrel male dogs were randomized into the control (n=8) and GPS (n=10) groups. All dogs underwent left anterior descending artery ligation followed by 6-hour high-rate (180-220bpm) ventricular pacing to induce acute HF. Transthoracic 2-dimensional echocardiography was performed at different time points. The plasma levels of norepinephrine, B-type natriuretic peptide (BNP) and Ang-II were measured using ELISA kits. C-fos and nerve growth factor (NGF) proteins expressed in the left stellate ganglion as well as GAP43 and TH proteins expressed in the peri-infarct zone were measured using western blot. After 6h of GPS, the left ventricular end-diastolic volume, end-systolic volume and ejection fraction showed no significant differences between the 2 groups, but the interventricular septal thickness at end-systole in the GPS group was significantly higher than that in the control group. The plasma levels of norepinephrine, BNP, Ang-II were increased 1h after myocardial infarction while the increase was attenuated by GPS. The expression of c-fos and NGF proteins in the left stellate ganglion as well as GAP43 and TH proteins in cardiac peri-infarct zone in GPS group were significantly lower than that in control group. GPS inhibits cardiac sympathetic remodeling and attenuates HF progression in canines with acute HF induced by myocardial infarction and ventricular pacing. Copyright © 2017 Elsevier B.V. All rights reserved.

  8. Implantable liquid metal-based flexible neural microelectrode array and its application in recovering animal locomotion functions

    Science.gov (United States)

    Guo, Rui; Liu, Jing

    2017-10-01

    With significant advantages in rapidly restoring the nerve function, electrical stimulation of nervous tissue is a crucial treatment of peripheral nerve injuries leading to common movement disorder. However, the currently available stimulating electrodes generally based on rigid conductive materials would cause a potential mechanical mismatch with soft neural tissues which thus reduces long-term effects of electrical stimulation. Here, we proposed and fabricated a flexible neural microelectrode array system based on the liquid metal GaIn alloy (75.5% Ga and 24.5% In by weight) and via printing approach. Such an alloy with a unique low melting point (10.35 °C) owns excellent electrical conductivity and high compliance, which are beneficial to serve as implantable flexible neural electrodes. The flexible neural microelectrode array embeds four liquid metal electrodes and stretchable interconnects in a PDMS membrane (500 µm in thickness) that possess a lower elastic modulus (1.055 MPa), which is similar to neural tissues with elastic moduli in the 0.1-1.5 MPa range. The electrical experiments indicate that the liquid metal interconnects could sustain over 7000 mechanical stretch cycles with resistance approximately staying at 4 Ω. Over the conceptual experiments on animal sciatic nerve electrical stimulation, the dead bullfrog implanted with flexible neural microelectrode array could even rhythmically contract and move its lower limbs under the electrical stimulations from the implant. This demonstrates a highly efficient way for quickly recovering biological nerve functions. Further, the good biocompatibility of the liquid metal material was justified via a series of biological experiments. This liquid metal modality for neural stimulation is expected to play important roles as biologic electrodes to overcome the fundamental mismatch in mechanics between biological tissues and electronic devices in the coming time.

  9. Implantable liquid metal-based flexible neural microelectrode array and its application in recovering animal locomotion functions

    International Nuclear Information System (INIS)

    Guo, Rui; Liu, Jing

    2017-01-01

    With significant advantages in rapidly restoring the nerve function, electrical stimulation of nervous tissue is a crucial treatment of peripheral nerve injuries leading to common movement disorder. However, the currently available stimulating electrodes generally based on rigid conductive materials would cause a potential mechanical mismatch with soft neural tissues which thus reduces long-term effects of electrical stimulation. Here, we proposed and fabricated a flexible neural microelectrode array system based on the liquid metal GaIn alloy (75.5% Ga and 24.5% In by weight) and via printing approach. Such an alloy with a unique low melting point (10.35 °C) owns excellent electrical conductivity and high compliance, which are beneficial to serve as implantable flexible neural electrodes. The flexible neural microelectrode array embeds four liquid metal electrodes and stretchable interconnects in a PDMS membrane (500 µ m in thickness) that possess a lower elastic modulus (1.055 MPa), which is similar to neural tissues with elastic moduli in the 0.1–1.5 MPa range. The electrical experiments indicate that the liquid metal interconnects could sustain over 7000 mechanical stretch cycles with resistance approximately staying at 4 Ω. Over the conceptual experiments on animal sciatic nerve electrical stimulation, the dead bullfrog implanted with flexible neural microelectrode array could even rhythmically contract and move its lower limbs under the electrical stimulations from the implant. This demonstrates a highly efficient way for quickly recovering biological nerve functions. Further, the good biocompatibility of the liquid metal material was justified via a series of biological experiments. This liquid metal modality for neural stimulation is expected to play important roles as biologic electrodes to overcome the fundamental mismatch in mechanics between biological tissues and electronic devices in the coming time. (paper)

  10. Electron transfer processes occurring on platinum neural stimulating electrodes: pulsing experiments for cathodic-first, charge-balanced, biphasic pulses for 0.566  ⩽  k  ⩽  2.3 in rat subcutaneous tissues

    Science.gov (United States)

    Kumsa, Doe W.; Bhadra, Narendra; Hudak, Eric M.; Mortimer, J. Thomas

    2017-10-01

    Objective. Our mission is twofold: (1) find a way to safely inject more charge through platinum electrodes than the Shannon limit (k  =  1.75) permits and (2) nurture an interest in the neural stimulation community to understand the electron transfer process occurring on neural stimulating electrodes. Approach. We report here on measurements of the electrode potential, performed on platinum neural stimulating electrodes in the subcutaneous space of an anesthetized rat under neural stimulation conditions. Main results. The results for six platinum electrodes with areas ranging from 0.2 mm2 to 12.7 mm2 were similar to prior results in sulfuric acid, except that the measured potentials were shifted negative 0.36 V because of the pH difference between the two media. The anodic ‘end’ potential, measured at t  =  20 ms after the onset of the biphasic current pulse, was the primary focus of the data collected because previous results had shown that as charge injection crosses the Shannon limit (k  =  1.75), this potential moves into a range where platinum surface oxidation and dissolution is likely to occur. The behavior of V e(t  =  20 ms) over a range of electrode surface areas studied was consistent with our sulfuric acid study. Implicit, but little noticed, in Shannon’s formulation is that small and large platinum electrodes behave the same in terms of k value; our data supports this idea. Significance. We hypothesize that the k  =  1.75 Shannon limit for safe stimulation designates a charge-injection boundary above which platinum toxicity becomes a relevant consideration for living cells around an electrode, a possibility that can be directly tested, and is a vital step forward in mission (1).

  11. Sequential neural models with stochastic layers

    DEFF Research Database (Denmark)

    Fraccaro, Marco; Sønderby, Søren Kaae; Paquet, Ulrich

    2016-01-01

    How can we efficiently propagate uncertainty in a latent state representation with recurrent neural networks? This paper introduces stochastic recurrent neural networks which glue a deterministic recurrent neural network and a state space model together to form a stochastic and sequential neural...... generative model. The clear separation of deterministic and stochastic layers allows a structured variational inference network to track the factorization of the model's posterior distribution. By retaining both the nonlinear recursive structure of a recurrent neural network and averaging over...

  12. Dynamic impact of brief electrical nerve stimulation on the neural immune axis-polarization of macrophages toward a pro-repair phenotype in demyelinated peripheral nerve.

    Science.gov (United States)

    McLean, Nikki A; Verge, Valerie M K

    2016-09-01

    Demyelinating peripheral nerves are infiltrated by cells of the monocyte lineage, including macrophages, which are highly plastic, existing on a continuum from pro-inflammatory M1 to pro-repair M2 phenotypic states. Whether one can therapeutically manipulate demyelinated peripheral nerves to promote a pro-repair M2 phenotype remains to be elucidated. We previously identified brief electrical nerve stimulation (ES) as therapeutically beneficial for remyelination, benefits which include accelerated clearance of macrophages, making us theorize that ES alters the local immune response. Thus, the impact of ES on the immune microenvironment in the zone of demyelination was examined. Adult male rat tibial nerves were focally demyelinated via 1% lysophosphatidyl choline (LPC) injection. Five days later, half underwent 1 hour 20 Hz sciatic nerve ES proximal to the LPC injection site. ES had a remarkable and significant impact, shifting the macrophage phenotype from predominantly pro-inflammatory/M1 toward a predominantly pro-repair/M2 one, as evidenced by an increased incidence of expression of M2-associated phenotypic markers in identified macrophages and a decrease in M1-associated marker expression. This was discernible at 3 days post-ES (8 days post-LPC) and continued at the 5 day post-ES (10 days post-LPC) time point examined. ES also affected chemokine (C-C motif) ligand 2 (CCL2; aka MCP-1) expression in a manner that correlated with increases and decreases in macrophage numbers observed in the demyelination zone. The data establish that briefly increasing neuronal activity favorably alters the immune microenvironment in demyelinated nerve, rapidly polarizing macrophages toward a pro-repair phenotype, a beneficial therapeutic concept that may extend to other pathologies. GLIA 2016;64:1546-1561. © 2016 Wiley Periodicals, Inc.

  13. 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...

  14. Ocean wave forecasting using recurrent neural networks

    Digital Repository Service at National Institute of Oceanography (India)

    Mandal, S.; Prabaharan, N.

    , merchant vessel routing, nearshore construction, etc. more efficiently and safely. This paper describes an artificial neural network, namely recurrent neural network with rprop update algorithm and is applied for wave forecasting. Measured ocean waves off...

  15. Vagal nerve stimulation therapy: what is being stimulated?

    Science.gov (United States)

    Kember, Guy; Ardell, Jeffrey L; Armour, John A; Zamir, Mair

    2014-01-01

    Vagal nerve stimulation in cardiac therapy involves delivering electrical current to the vagal sympathetic complex in patients experiencing heart failure. The therapy has shown promise but the mechanisms by which any benefit accrues is not understood. In this paper we model the response to increased levels of stimulation of individual components of the vagal sympathetic complex as a differential activation of each component in the control of heart rate. The model provides insight beyond what is available in the animal experiment in as much as allowing the simultaneous assessment of neuronal activity throughout the cardiac neural axis. The results indicate that there is sensitivity of the neural network to low level subthreshold stimulation. This leads us to propose that the chronic effects of vagal nerve stimulation therapy lie within the indirect pathways that target intrinsic cardiac local circuit neurons because they have the capacity for plasticity.

  16. Vagal nerve stimulation therapy: what is being stimulated?

    Directory of Open Access Journals (Sweden)

    Guy Kember

    Full Text Available Vagal nerve stimulation in cardiac therapy involves delivering electrical current to the vagal sympathetic complex in patients experiencing heart failure. The therapy has shown promise but the mechanisms by which any benefit accrues is not understood. In this paper we model the response to increased levels of stimulation of individual components of the vagal sympathetic complex as a differential activation of each component in the control of heart rate. The model provides insight beyond what is available in the animal experiment in as much as allowing the simultaneous assessment of neuronal activity throughout the cardiac neural axis. The results indicate that there is sensitivity of the neural network to low level subthreshold stimulation. This leads us to propose that the chronic effects of vagal nerve stimulation therapy lie within the indirect pathways that target intrinsic cardiac local circuit neurons because they have the capacity for plasticity.

  17. Dynamic Information Encoding With Dynamic Synapses in Neural Adaptation

    Science.gov (United States)

    Li, Luozheng; Mi, Yuanyuan; Zhang, Wenhao; Wang, Da-Hui; Wu, Si

    2018-01-01

    Adaptation refers to the general phenomenon that the neural system dynamically adjusts its response property according to the statistics of external inputs. In response to an invariant stimulation, neuronal firing rates first increase dramatically and then decrease gradually to a low level close to the background activity. This prompts a question: during the adaptation, how does the neural system encode the repeated stimulation with attenuated firing rates? It has been suggested that the neural system may employ a dynamical encoding strategy during the adaptation, the information of stimulus is mainly encoded by the strong independent spiking of neurons at the early stage of the adaptation; while the weak but synchronized activity of neurons encodes the stimulus information at the later stage of the adaptation. The previous study demonstrated that short-term facilitation (STF) of electrical synapses, which increases the synchronization between neurons, can provide a mechanism to realize dynamical encoding. In the present study, we further explore whether short-term plasticity (STP) of chemical synapses, an interaction form more common than electrical synapse in the cortex, can support dynamical encoding. We build a large-size network with chemical synapses between neurons. Notably, facilitation of chemical synapses only enhances pair-wise correlations between neurons mildly, but its effect on increasing synchronization of the network can be significant, and hence it can serve as a mechanism to convey the stimulus information. To read-out the stimulus information, we consider that a downstream neuron receives balanced excitatory and inhibitory inputs from the network, so that the downstream neuron only responds to synchronized firings of the network. Therefore, the response of the downstream neuron indicates the presence of the repeated stimulation. Overall, our study demonstrates that STP of chemical synapse can serve as a mechanism to realize dynamical neural

  18. The modulatory effect of adaptive deep brain stimulation on beta bursts in Parkinson's disease.

    Science.gov (United States)

    Tinkhauser, Gerd; Pogosyan, Alek; Little, Simon; Beudel, Martijn; Herz, Damian M; Tan, Huiling; Brown, Peter

    2017-04-01

    Adaptive deep brain stimulation uses feedback about the state of neural circuits to control stimulation rather than delivering fixed stimulation all the time, as currently performed. In patients with Parkinson's disease, elevations in beta activity (13-35 Hz) in the subthalamic nucleus have been demonstrated to correlate with clinical impairment and have provided the basis for feedback control in trials of adaptive deep brain stimulation. These pilot studies have suggested that adaptive deep brain stimulation may potentially be more effective, efficient and selective than conventional deep brain stimulation, implying mechanistic differences between the two approaches. Here we test the hypothesis that such differences arise through differential effects on the temporal dynamics of beta activity. The latter is not constantly increased in Parkinson's disease, but comes in bursts of different durations and amplitudes. We demonstrate that the amplitude of beta activity in the subthalamic nucleus increases in proportion to burst duration, consistent with progressively increasing synchronization. Effective adaptive deep brain stimulation truncated long beta bursts shifting the distribution of burst duration away from long duration with large amplitude towards short duration, lower amplitude bursts. Critically, bursts with shorter duration are negatively and bursts with longer duration positively correlated with the motor impairment off stimulation. Conventional deep brain stimulation did not change the distribution of burst durations. Although both adaptive and conventional deep brain stimulation suppressed mean beta activity amplitude compared to the unstimulated state, this was achieved by a selective effect on burst duration during adaptive deep brain stimulation, whereas conventional deep brain stimulation globally suppressed beta activity. We posit that the relatively selective effect of adaptive deep brain stimulation provides a rationale for why this approach could

  19. A spectral element method with adaptive segmentation for accurately simulating extracellular electrical stimulation of neurons.

    Science.gov (United States)

    Eiber, Calvin D; Dokos, Socrates; Lovell, Nigel H; Suaning, Gregg J

    2017-05-01

    The capacity to quickly and accurately simulate extracellular stimulation of neurons is essential to the design of next-generation neural prostheses. Existing platforms for simulating neurons are largely based on finite-difference techniques; due to the complex geometries involved, the more powerful spectral or differential quadrature techniques cannot be applied directly. This paper presents a mathematical basis for the application of a spectral element method to the problem of simulating the extracellular stimulation of retinal neurons, which is readily extensible to neural fibers of any kind. The activating function formalism is extended to arbitrary neuron geometries, and a segmentation method to guarantee an appropriate choice of collocation points is presented. Differential quadrature may then be applied to efficiently solve the resulting cable equations. The capacity for this model to simulate action potentials propagating through branching structures and to predict minimum extracellular stimulation thresholds for individual neurons is demonstrated. The presented model is validated against published values for extracellular stimulation threshold and conduction velocity for realistic physiological parameter values. This model suggests that convoluted axon geometries are more readily activated by extracellular stimulation than linear axon geometries, which may have ramifications for the design of neural prostheses.

  20. The different effects of high-frequency stimulation of the nucleus accumbens shell and core on food consumption are possibly associated with different neural responses in the lateral hypothalamic area.

    Science.gov (United States)

    Wei, N; Wang, Y; Wang, X; He, Z; Zhang, M; Zhang, X; Pan, Y; Zhang, J; Qin, Z; Zhang, K

    2015-08-20

    Obesity may result from dysfunction of the reward system, especially in the nucleus accumbens (Acb). Based on this hypothesis, many researchers have tested the effect of high-frequency stimulation (HFS) of the Acb shell (Acb-Sh) and/or core (Acb-Co) on ingestive behaviors, but few studies have explored the possible mechanisms involved in the differences between the Acb-Sh and Acb-Co. The present study tested effects of HFS of the Acb-Sh and Acb-Co on high-fat food (HFF) consumption in rats after 24h of food deprivation. Microdialysis and electrophysiological experiments were carried out in awake rats to explore potential mechanisms. The results showed that the Acb-Sh decreased HFF consumption after food deprivation both during and post-HFS. However, HFS of the Acb-Co did not induce similar changes in food consumption. HFS of the Acb-Sh (Sh-HFS) induced an increase in GABA level in the lateral hypothalamic area (LHA) during both phases, whereas HFS of the Acb-Co (Co-HFS) did not exhibit similar effects. The electrophysiological experiment showed that nearly all the LHA neurons were inhibited by Sh-HFS, and the mean firing rate decreased significantly both during and post-HFS. In contrast, the mean firing rate of the LHA neurons did not exhibit clear changes during Co-HFS, although some individual neurons appeared to exhibit responses to Co-HFS. Considering all the data, we postulated that Sh-HFS, rather than Co-HFS, might inhibit palatable food consumption after food deprivation by decreasing the reward value of that food, which suggested that it might also disturb the process of developing obesity. The mechanisms involved in the different effects of Sh-HFS and Co-HFS on food consumption may be associated with different neural responses in the LHA. The Acb-Sh has abundant GABAergic projections to the LHA, whereas the Acb-Co has few or no GABAergic innervations to the LHA. Thus, neural activity in the LHA exhibits different responses to Sh-HFS and Co-HFS. Copyright

  1. 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

  2. Synchronization of FitzHugh-Nagumo neurons in external electrical stimulation via nonlinear control

    International Nuclear Information System (INIS)

    Wang Jiang; Zhang Ting; Deng Bin

    2007-01-01

    Synchronization of FitzHugh-Nagumo neural system under external electrical stimulation via the nonlinear control is investigated in this paper. Firstly, the different dynamical behavior of the nonlinear cable model based on the FitzHugh-Nagumo model responding to various external electrical stimulations is studied. Next, using the result of the analysis, a nonlinear feedback linearization control scheme and an adaptive control strategy are designed to synchronization two neurons. Computer simulations are provided to verify the efficiency of the designed synchronization schemes

  3. 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

  4. Neural chips, neural computers and application in high and superhigh energy physics experiments

    International Nuclear Information System (INIS)

    Nikityuk, N.M.; )

    2001-01-01

    Architecture peculiarity and characteristics of series of neural chips and neural computes used in scientific instruments are considered. Tendency of development and use of them in high energy and superhigh energy physics experiments are described. Comparative data which characterize the efficient use of neural chips for useful event selection, classification elementary particles, reconstruction of tracks of charged particles and for search of hypothesis Higgs particles are given. The characteristics of native neural chips and accelerated neural boards are considered [ru

  5. Efficient generation of smooth muscle cells from adipose-derived stromal cells by 3D mechanical stimulation can substitute the use of growth factors in vascular tissue engineering.

    Science.gov (United States)

    Parvizi, Mojtaba; Bolhuis-Versteeg, Lydia A M; Poot, André A; Harmsen, Martin C

    2016-07-01

    Occluding artery disease causes a high demand for bioartificial replacement vessels. We investigated the combined use of biodegradable and creep-free poly (1,3-trimethylene carbonate) (PTMC) with smooth muscle cells (SMC) derived by biochemical or mechanical stimulation of adipose tissue-derived stromal cells (ASC) to engineer bioartificial arteries. Biochemical induction of cultured ASC to SMC was done with TGF-β1 for 7d. Phenotype and function were assessed by qRT-PCR, immunodetection and collagen contraction assays. The influence of mechanical stimulation on non-differentiated and pre-differentiated ASC, loaded in porous tubular PTMC scaffolds, was assessed after culturing under pulsatile flow for 14d. Assays included qRT-PCR, production of extracellular matrix and scanning electron microscopy. ASC adhesion and TGF-β1-driven differentiation to contractile SMC on PTMC did not differ from tissue culture polystyrene controls. Mesenchymal and SMC markers were increased compared to controls. Interestingly, pre-differentiated ASC had only marginal higher contractility than controls. Moreover, in 3D PTMC scaffolds, mechanical stimulation yielded well-aligned ASC-derived SMC which deposited ECM. Under the same conditions, pre-differentiated ASC-derived SMC maintained their SMC phenotype. Our results show that mechanical stimulation can replace TGF-β1 pre-stimulation to generate SMC from ASC and that pre-differentiated ASC keep their SMC phenotype with increased expression of SMC markers. Copyright © 2016 WILEY-VCH Verlag GmbH & Co. KGaA, Weinheim.

  6. Augmenting distractor filtering via transcranial magnetic stimulation of the lateral occipital cortex.

    Science.gov (United States)

    Eštočinová, Jana; Lo Gerfo, Emanuele; Della Libera, Chiara; Chelazzi, Leonardo; Santandrea, Elisa

    2016-11-01

    Visual selective attention (VSA) optimizes perception and behavioral control by enabling efficient selection of relevant information and filtering of distractors. While focusing resources on task-relevant information helps counteract distraction, dedicated filtering mechanisms have recently been demonstrated, allowing neural systems to implement suitable policies for the suppression of potential interference. Limited evidence is presently available concerning the neural underpinnings of these mechanisms, and whether neural circuitry within the visual cortex might play a causal role in their instantiation, a possibility that we directly tested here. In two related experiments, transcranial magnetic stimulation (TMS) was applied over the lateral occipital cortex of healthy humans at different times during the execution of a behavioral task which entailed varying levels of distractor interference and need for attentional engagement. While earlier TMS boosted target selection, stimulation within a restricted time epoch close to (and in the course of) stimulus presentation engendered selective enhancement of distractor suppression, by affecting the ongoing, reactive instantiation of attentional filtering mechanisms required by specific task conditions. The results attest to a causal role of mid-tier ventral visual areas in distractor filtering and offer insights into the mechanisms through which TMS may have affected ongoing neural activity in the stimulated tissue. Copyright © 2016 Elsevier Ltd. All rights reserved.

  7. Experimental chronic Pseudomonas aeruginosa lung infection in rats. Non-specific stimulation with LPS reduces lethality as efficiently as specific immunization

    DEFF Research Database (Denmark)

    Lange, K H; Hougen, H P; Høiby, N

    1995-01-01

    In a rat model of chronic Pseudomonas aeruginosa lung infection mimicking cystic fibrosis, we investigated the possibility of preventing chronic lung inflammation or decreasing the progression of the infection. We compared the lethality, pathology, bacterial clearance, and immunogenicity after...... with either E. coli LPS or P. aeruginosa sonicate. Four and two weeks prior to challenge other rats were vaccinated with either E. coli LPS or P. aeruginosa sonicate. Controls did not receive any stimulation or vaccination. The lethality after challenge was lower in rats stimulated with E. coli LPS (p = 0...... but not to prevent the chronic P. aeruginosa lung infection and inflammation caused by alginate-embedded bacteria....

  8. 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

  9. Computer modeling of Motor Cortex Stimulation: Effects of Anodal, Cathodal and Bipolar Stimulation

    NARCIS (Netherlands)

    Manola, L.; Holsheimer, J.; Buitenweg, Jan R.; Veltink, Petrus H.

    2007-01-01

    Motor cortex stimulation (MCS) is a promising clinical technique for treatment of chronic pain. However, optimization of the therapeutic efficacy is hampered since it is not known how electrically activated neural structures in the motor cortex can induce pain relief. Furthermore, multiple neural

  10. Bioinspired nanocomplex for spatiotemporal imaging of sequential mRNA expression in differentiating neural stem cells.

    Science.gov (United States)

    Wang, Zhe; Zhang, Ruili; Wang, Zhongliang; Wang, He-Fang; Wang, Yu; Zhao, Jun; Wang, Fu; Li, Weitao; Niu, Gang; Kiesewetter, Dale O; Chen, Xiaoyuan

    2014-12-23

    Messenger RNA plays a pivotal role in regulating cellular activities. The expression dynamics of specific mRNA contains substantial information on the intracellular milieu. Unlike the imaging of stationary mRNAs, real-time intracellular imaging of the dynamics of mRNA expression is of great value for investigating mRNA biology and exploring specific cellular cascades. In addition to advanced imaging methods, timely extracellular stimulation is another key factor in regulating the mRNA expression repertoire. The integration of effective stimulation and imaging into a single robust system would significantly improve stimulation efficiency and imaging accuracy, producing fewer unwanted artifacts. In this study, we developed a multifunctional nanocomplex to enable self-activating and spatiotemporal imaging of the dynamics of mRNA sequential expression during the neural stem cell differentiation process. This nanocomplex showed improved enzymatic stability, fast recognition kinetics, and high specificity. With a mechanism regulated by endogenous cell machinery, this nanocomplex realized the successive stimulating motif release and the dynamic imaging of chronological mRNA expression during neural stem cell differentiation without the use of transgenetic manipulation. The dynamic imaging montage of mRNA expression ultimately facilitated genetic heterogeneity analysis. In vivo lateral ventricle injection of this nanocomplex enabled endogenous neural stem cell activation and labeling at their specific differentiation stages. This nanocomplex is highly amenable as an alternative tool to explore the dynamics of intricate mRNA activities in various physiological and pathological conditions.

  11. A Fully Implantable Stimulator With Wireless Power and Data Transmission for Experimental Investigation of Epidural Spinal Cord Stimulation.

    Science.gov (United States)

    Xu, Qi; Hu, Dingyin; Duan, Bingyu; He, Jiping

    2015-07-01

    Epidural spinal cord stimulation (ESCS) combined with partial weight-bearing therapy (PWBT) has been shown to facilitate recovery of functional walking for individuals after spinal cord injury (SCI). The investigation of neural mechanisms of recovery from SCI under this treatment has been conducted broadly in rodent models, yet a suitable ESCS system is still unavailable. This paper describes a practical, programmable, and fully implantable stimulator for laboratory research on rats to explore fundamental neurophysiological principles for functional recovery after SCI. The ESCS system is composed of a personal digital assistant (PDA), an external controller, an implantable pulse generator (IPG), lead extension, and stimulating electrodes. The stimulation parameters can be programmed and adjusted through a graphical user interface on the PDA. The external controller is placed on the rat back and communicates with the PDA via radio-frequency (RF) telemetry. An RF carrier from the class-E power amplifier in the external controller provides both data and power for the IPG through an inductive link. The IPG is built around a microcontroller unit to generate voltage-regulated pulses delivered to the bipolar electrode for ESCS in rats. The encapsulated IPG measures 22 mm × 23 mm × 7 mm with a mass of  ∼  3.78 g. This fully implantable batteryless stimulator provided a simplified and efficient method to carry out chronic experiments in untethered animals for medical electro-neurological research.

  12. Transcranial Alternating Current Stimulation Attenuates Neuronal Adaptation.

    Science.gov (United States)

    Kar, Kohitij; Duijnhouwer, Jacob; Krekelberg, Bart

    2017-03-01

    We previously showed that brief application of 2 mA (peak-to-peak) transcranial currents alternating at 10 Hz significantly reduces motion adaptation in humans. This is but one of many behavioral studies showing that weak currents applied to the scalp modulate neural processing. Transcranial stimulation has been shown to improve perception, learning, and a range of clinical symptoms. Few studies, however, have measured the neural consequences of transcranial current stimulation. We capitalized on the strong link between motion perception and neural activity in the middle temporal (MT) area of the macaque monkey to study the neural mechanisms that underlie the behavioral consequences of transcranial alternating current stimulation. First, we observed that 2 mA currents generated substantial intracranial fields, which were much stronger in the stimulated hemisphere (0.12 V/m) than on the opposite side of the brain (0.03 V/m). Second, we found that brief application of transcranial alternating current stimulation at 10 Hz reduced spike-frequency adaptation of MT neurons and led to a broadband increase in the power spectrum of local field potentials. Together, these findings provide a direct demonstration that weak electric fields applied to the scalp significantly affect neural processing in the primate brain and that this includes a hitherto unknown mechanism that attenuates sensory adaptation. SIGNIFICANCE STATEMENT Transcranial stimulation has been claimed to improve perception, learning, and a range of clinical symptoms. Little is known, however, how transcranial current stimulation generates such effects, and the search for better stimulation protocols proceeds largely by trial and error. We investigated, for the first time, the neural consequences of stimulation in the monkey brain. We found that even brief application of alternating current stimulation reduced the effects of adaptation on single-neuron firing rates and local field potentials; this mechanistic

  13. Efficient Transduction of Feline Neural Progenitor Cells for Delivery of Glial Cell Line-Derived Neurotrophic Factor Using a Feline Immunodeficiency Virus-Based Lentiviral Construct

    Directory of Open Access Journals (Sweden)

    X. Joann You

    2011-01-01

    Full Text Available Work has shown that stem cell transplantation can rescue or replace neurons in models of retinal degenerative disease. Neural progenitor cells (NPCs modified to overexpress neurotrophic factors are one means of providing sustained delivery of therapeutic gene products in vivo. To develop a nonrodent animal model of this therapeutic strategy, we previously derived NPCs from the fetal cat brain (cNPCs. Here we use bicistronic feline lentiviral vectors to transduce cNPCs with glial cell-derived neurotrophic factor (GDNF together with a GFP reporter gene. Transduction efficacy is assessed, together with transgene expression level and stability during induction of cellular differentiation, together with the influence of GDNF transduction on growth and gene expression profile. We show that GDNF overexpressing cNPCs expand in vitro, coexpress GFP, and secrete high levels of GDNF protein—before and after differentiation—all qualities advantageous for use as a cell-based approach in feline models of neural degenerative disease.

  14. An efficient approach for electric load forecasting using distributed ART (adaptive resonance theory) and HS-ARTMAP (Hyper-spherical ARTMAP network) neural network

    International Nuclear Information System (INIS)

    Cai, Yuan; Wang, Jian-zhou; Tang, Yun; Yang, Yu-chen

    2011-01-01

    This paper presents a neural network based on adaptive resonance theory, named distributed ART (adaptive resonance theory) and HS-ARTMAP (Hyper-spherical ARTMAP network), applied to the electric load forecasting problem. The distributed ART combines the stable fast learning capabilities of winner-take-all ART systems with the noise tolerance and code compression capabilities of multi-layer perceptions. The HS-ARTMAP, a hybrid of an RBF (Radial Basis Function)-network-like module which uses hyper-sphere basis function substitute the Gaussian basis function and an ART-like module, performs incremental learning capabilities in function approximation problem. The HS-ARTMAP only receives the compressed distributed coding processed by distributed ART to deal with the proliferation problem which ARTMAP (adaptive resonance theory map) architecture often encounters and still performs well in electric load forecasting. To demonstrate the performance of the methodology, data from New South Wales and Victoria in Australia are illustrated. Results show that the developed method is much better than the traditional BP and single HS-ARTMAP neural network. -- Research highlights: → The processing of the presented network is based on compressed distributed data. It's an innovation among the adaptive resonance theory architecture. → The presented network decreases the proliferation the Fuzzy ARTMAP architectures usually encounter. → The network on-line forecasts electrical load accurately, stably. → Both one-period and multi-period load forecasting are executed using data of different cities.

  15. Avoiding Internal Capsule Stimulation With a New Eight-Channel Steering Deep Brain Stimulation Lead

    NARCIS (Netherlands)

    van Dijk, Kees J.; Verhagen, Rens; Bour, Lo J.; Heida, Ciska; Veltink, Peter H.

    2017-01-01

    Objective: Novel deep brain stimulation (DBS) lead designs are currently entering the market, which are hypothesized to provide a way to steer the stimulation field away from neural populations responsible for side effects and towards populations responsible for beneficial effects. The objective of

  16. Avoiding Internal Capsule Stimulation With a New Eight-Channel Steering Deep Brain Stimulation Lead

    NARCIS (Netherlands)

    van Dijk, Kees J.; Verhagen, Rens; Bour, Lo J.; Heida, Ciska; Veltink, Peter H.

    2017-01-01

    Novel deep brain stimulation (DBS) lead designs are currently entering the market, which are hypothesized to provide a way to steer the stimulation field away from neural populations responsible for side effects and towards populations responsible for beneficial effects. The objective of this study

  17. 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

  18. growth stimulant

    African Journals Online (AJOL)

    Effects of timing and duration of supplementation of LIVFIT VET ® (growth stimulant) as substitute for fish meal on the growth performance, haematology and clinical enzymes concentration of growing pigs.

  19. 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.

  20. The neural cell adhesion molecule

    DEFF Research Database (Denmark)

    Berezin, V; Bock, E; Poulsen, F M

    2000-01-01

    During the past year, the understanding of the structure and function of neural cell adhesion has advanced considerably. The three-dimensional structures of several of the individual modules of the neural cell adhesion molecule (NCAM) have been determined, as well as the structure of the complex...... between two identical fragments of the NCAM. Also during the past year, a link between homophilic cell adhesion and several signal transduction pathways has been proposed, connecting the event of cell surface adhesion to cellular responses such as neurite outgrowth. Finally, the stimulation of neurite...

  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. Combination of counterpropagation artificial neural networks and antioxidant activities for comprehensive evaluation of associated-extraction efficiency of various cyclodextrins in the traditional Chinese formula Xue-Zhi-Ning.

    Science.gov (United States)

    Sun, Lili; Yang, Jianwen; Wang, Meng; Zhang, Huijie; Liu, Yanan; Ren, Xiaoliang; Qi, Aidi

    2015-11-10

    Xue-Zhi-Ning (XZN) is a widely used traditional Chinese medicine formula to treat hyperlipidemia. Recently, cyclodextrins (CDs) have been extensively used to minimize problems relative to medicine bioavailability, such as low solubility and poor stability. The objective of this study was to determine the associated-extraction efficiency of various CDs in XZN. Three various type CDs were evaluated, including native CDs (α-CD, β-CD), hydrophilic CD derivatives (HP-β-CD and Me-β-CD), and ionic CD derivatives (SBE-β-CD and CM-β-CD). An ultra high-performance liquid chromatography (UHPLC) fingerprint was applied to determine the components in CD extracts and original aqueous extract (OAE). A counterpropagation artificial neural network (CP-ANN) was used to analyze the components in different extracts and compare the selective extraction of various CDs. Extraction efficiencies of the various CDs in terms of extracted components follow the ranking, ionic CD derivatives>hydrophilic CD derivatives>native CDs>OAE. Besides, different types of CDs have their own selective extraction and ionic CD derivatives present the strongest associated-extraction efficiency. Antioxidant potentials of various extracts were evaluated by determining the inhibition of spontaneous, H2O2-induced, CCl4-induced and Fe(2+)/ascorbic acid-induced lipid peroxidation (LPO) and analyzing the scavenging capacity for DPPH and hydroxyl radicals. The order of extraction efficiencies of the various CDs relative to antioxidant activities is as follows: SBE-β-CD>CM-β-CD>HP-β-CD>Me-β-CD>β-CD>α-CD. It can be demonstrated that all of the CDs studied increase the extraction efficiency and that ionic CD derivatives (SBE-β-CD and CM-β-CD) present the highest extraction capability in terms of amount extracted and antioxidant activities of extracts. Copyright © 2015 Elsevier B.V. All rights reserved.

  3. Substrates of neuropsychological functioning in stimulant dependence: a review of functional neuroimaging research

    NARCIS (Netherlands)

    Crunelle, C.L.; Veltman, D.J.; Booij, J.; van Emmerik-van Oortmerssen, K.; van den Brink, W.

    2012-01-01

    Stimulant dependence is associated with neuropsychological impairments. Here, we summarize and integrate the existing neuroimaging literature on the neural substrates of neuropsychological (dys)function in stimulant dependence, including cocaine, (meth-)amphetamine, ecstasy and nicotine dependence,

  4. Substrates of neuropsychological functioning in stimulant dependence: a review of functional neuroimaging research

    NARCIS (Netherlands)

    Crunelle, Cleo L.; Veltman, Dick J.; Booij, Jan; Emmerik-van Oortmerssen, Katelijne; den Brink, Wim

    2012-01-01

    Stimulant dependence is associated with neuropsychological impairments. Here, we summarize and integrate the existing neuroimaging literature on the neural substrates of neuropsychological (dys) function in stimulant dependence, including cocaine, (meth-) amphetamine, ecstasy and nicotine

  5. Inhibition of Pre-Supplementary Motor Area by Continuous Theta Burst Stimulation Leads to More Cautious Decision-making and More Efficient Sensory Evidence Integration.

    Science.gov (United States)

    Tosun, Tuğçe; Berkay, Dilara; Sack, Alexander T; Çakmak, Yusuf Ö; Balcı, Fuat

    2017-08-01

    Decisions are made based on the integration of available evidence. The noise in evidence accumulation leads to a particular speed-accuracy tradeoff in decision-making, which can be modulated and optimized by adaptive decision threshold setting. Given the effect of pre-SMA activity on striatal excitability, we hypothesized that the inhibition of pre-SMA would lead to higher decision thresholds and an increased accuracy bias. We used offline continuous theta burst stimulation to assess the effect of transient inhibition of the right pre-SMA on the decision processes in a free-response two-alternative forced-choice task within the drift diffusion model framework. Participants became more cautious and set higher decision thresholds following right pre-SMA inhibition compared with inhibition of the control site (vertex). Increased decision thresholds were accompanied by an accuracy bias with no effects on post-error choice behavior. Participants also exhibited higher drift rates as a result of pre-SMA inhibition compared with the vertex inhibition. These results, in line with the striatal theory of speed-accuracy tradeoff, provide evidence for the functional role of pre-SMA activity in decision threshold modulation. Our results also suggest that pre-SMA might be a part of the brain network associated with the sensory evidence integration.

  6. Towards modeling of combined cooling, heating and power system with artificial neural network for exergy destruction and exergy efficiency prognostication of tri-generation components

    International Nuclear Information System (INIS)

    Taghavifar, Hadi; Anvari, Simin; Saray, Rahim Khoshbakhti; Khalilarya, Shahram; Jafarmadar, Samad; Taghavifar, Hamid

    2015-01-01

    The current study is an attempt to address the investigation of the CCHP (combined cooling, heating and power) system when 10 input variables were chosen to analyze 10 most important objective output parameters. Moreover, ANN (artificial neural network) was successfully applied on the tri-generation system on account of its capability to predict responses with great confidence. The results of sensitivity analysis were considered as foundation for selecting the most suitable and potent input parameters of the supposed cycle. Furthermore, the best ANN topology was attained based on the least amount of MSE and number of iterations. Consequently, the trainlm (Levenberg–Marquardt) training approach with 10-9-10 configuration has been exploited for ANN modeling in order to give the best output correspondence. The maximum MRE = 1.75% (mean relative error) and minimum R 2  = 0.984 represents the reliability and outperformance of the developed ANN over common conventional thermodynamic analysis carried out by EES (engineering equation solver) software. - Highlights: • Exergy analysis is undertaken for CCHP components based on operative factors. • ANN tool is applied to obtained database from thermodynamic analyses session. • The best ANN topology is detected at 10-9-10 with trainlm learning algorithm. • The input and output layer parameters were selected based on sensitivity analysis.

  7. Mechanism of orientation of stimulating currents in magnetic brain stimulation (abstract)

    Science.gov (United States)

    Ueno, S.; Matsuda, T.

    1991-04-01

    We made a functional map of the human motor cortex related to the hand and foot areas by stimulating the human brain with a focused magnetic pulse. We observed that each functional area in the cortex has an optimum direction for which stimulating currents can produce neural excitation. The present report focuses on the mechanism which is responsible for producing this anisotropic response to brain stimulation. We first obtained a functional map of the brain related to the left ADM (abductor digiti minimi muscles). When the stimulating currents were aligned in the direction from the left to the right hemisphere, clear EMG (electromyographic) responses were obtained only from the left ADM to magnetic stimulation of both hemisphere. When the stimulating currents were aligned in the direction from the right to the left hemisphere, clear EMG signals were obtained only from the right ADM to magnetic stimulation of both hemisphere. The functional maps of the brain were sensitive to changes in the direction of the stimulating currents. To explain the phenomena obtained in the experiments, we developed a model of neural excitation elicited by magnetic stimulation. When eddy currents which are induced by pulsed magnetic fields flow in the direction from soma to the distal part of neural fiber, depolarized area in the distal part are excited, and the membrane excitation propagates along the nerve fiber. In contrast, when the induced currents flow in the direction from the distal part to soma, hyperpolarized parts block or inhibit neural excitation even if the depolarized parts near the soma can be excited. The model explains our observation that the orientation of the induced current vectors reflect both the functional and anatomical organization of the neural fibers in the brain.

  8. Very low dose gamma irradiation stimulates gaseous exchange and carboxylation efficiency, but inhibits vascular sap flow in groundnut (Arachis hypogaea L.).

    Science.gov (United States)

    Ahuja, Sumedha; Singh, Bhupinder; Gupta, Vijay Kumar; Singhal, R K; Venu Babu, P

    2014-02-01

    An experiment was carried out to determine the effect of low dose gamma radiation on germination, plant growth, nitrogen and carbon fixation and carbon flow and release characteristics of groundnut. Dry seeds of groundnut variety Trombay groundnut 37A (TG 37A), a radio mutant type developed by Bhabha Atomic Research Centre (BARC), Mumbai, India, were subjected to the pre-sowing treatment of gamma radiation within low to high dose physiological range, i.e., 0.0, 0.0082, 0.0164. 0.0328, 0.0656, 0.1312, 5, 25, 100, 500 Gray (Gy) from a cobalt source ((60)Co). Observations were recorded for the radiation effect on percentage germination, vigour, gas exchange attributes such as photosynthetic rate, stomatal conductance and transpiration rate, chlorophyll content, root exudation in terms of (14)C release, vascular sap flow rate and activities of rate defining carbon and nitrogen assimilating enzymes such as ribulose-1,5-bisphosphate carboxylase (rubisco) and nitrate reductase (NR). Seed germination was increased by 10-25% at the lower doses up to 5 Gy while the improvement in plant vigour in the same dose range was much higher (22-84%) than the unirradiated control. For radiation exposure above 5 Gy, a dose-dependent decline in germination and plant vigour was measured. No significant effect was observed on the photosynthesis at radiation exposure below 5 Gy but above 5 Gy dose there was a decline in the photosynthetic rate. Stomatal conductance and transpiration rate, however, were only inhibited at a high dose of 500 Gy. Leaf rubisco activity and NR activities remained unaffected at all the investigated doses of gamma irradiation. Mean root exudation and sap flow rate of the irradiated plants, irrespective of the dose, was reduced over the unirradiated control more so in a dose-dependent manner. Results indicated that a very low dose of gamma radiation, in centigray to gray range, did not pose any threat and in fact stimulated metabolic functions in such a way to aid

  9. Direct adaptive control using feedforward neural networks

    OpenAIRE

    Cajueiro, Daniel Oliveira; Hemerly, Elder Moreira

    2003-01-01

    ABSTRACT: This paper proposes a new scheme for direct neural adaptive control that works efficiently employing only one neural network, used for simultaneously identifying and controlling the plant. The idea behind this structure of adaptive control is to compensate the control input obtained by a conventional feedback controller. The neural network training process is carried out by using two different techniques: backpropagation and extended Kalman filter algorithm. Additionally, the conver...

  10. Transcranial magnetic stimulation in schizophrenia.

    Science.gov (United States)

    Zaman, Rashid; Thind, Dilraj; Kocmur, Marga

    2008-11-01

    Transcranial magnetic stimulation (TMS) is a non-invasive and painless way of stimulating the neural tissue (cerebral cortex, spinal roots, and cranial and peripheral nerves). The first attempts at stimulating the neural tissue date back to 1896 by d'Arsonval; however, it was successfully carried out by Barker and colleagues in Sheffield, UK, in 1985. It soon became a useful tool in neuroscience for neurophysiologists and neurologists and psychiatrists. The original single-pulse TMS, largely used as an investigative tool, was further refined and developed in the early 1990s into what is known as repetitive TMS (rTMS), having a frequency range of 1-60 Hz. The stimulation by both TMS and rTMS of various cortical regions displayed alteration of movement, mood, and behavior, leading researchers to investigate a number of psychiatric and neuropsychiatric disorders, as well as to explore its therapeutic potential. There is now a large amount of literature on the use of TMS/rTMS in depression; however, its use in schizophrenia, both as an investigative and certainly as a therapeutic tool is relatively recent with a limited but increasing number of publications. In this article, we will outline the principles of TMS/rTMS and critically review their use in schizophrenia both as investigative and potential therapeutic tools.

  11. Optical stimulator for vision-based sensors

    DEFF Research Database (Denmark)

    Rössler, Dirk; Pedersen, David Arge Klevang; Benn, Mathias

    2014-01-01

    We have developed an optical stimulator system for vision-based sensors. The stimulator is an efficient tool for stimulating a camera during on-ground testing with scenes representative of spacecraft flights. Such scenes include starry sky, planetary objects, and other spacecraft. The optical...

  12. Brain Stimulation Therapies

    Science.gov (United States)

    ... Magnetic Seizure Therapy Deep Brain Stimulation Additional Resources Brain Stimulation Therapies Overview Brain stimulation therapies can play ... for a shorter recovery time than ECT Deep Brain Stimulation Deep brain stimulation (DBS) was first developed ...

  13. Emerging trends in neuro engineering and neural computation

    CERN Document Server

    Lee, Kendall; Garmestani, Hamid; Lim, Chee

    2017-01-01

    This book focuses on neuro-engineering and neural computing, a multi-disciplinary field of research attracting considerable attention from engineers, neuroscientists, microbiologists and material scientists. It explores a range of topics concerning the design and development of innovative neural and brain interfacing technologies, as well as novel information acquisition and processing algorithms to make sense of the acquired data. The book also highlights emerging trends and advances regarding the applications of neuro-engineering in real-world scenarios, such as neural prostheses, diagnosis of neural degenerative diseases, deep brain stimulation, biosensors, real neural network-inspired artificial neural networks (ANNs) and the predictive modeling of information flows in neuronal networks. The book is broadly divided into three main sections including: current trends in technological developments, neural computation techniques to make sense of the neural behavioral data, and application of these technologie...

  14. 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.

  15. A 12-Week Physical and Cognitive Exercise Program Can Improve Cognitive Function and Neural Efficiency in Community-Dwelling Older Adults: A Randomized Controlled Trial.

    Science.gov (United States)

    Nishiguchi, Shu; Yamada, Minoru; Tanigawa, Takanori; Sekiyama, Kaoru; Kawagoe, Toshikazu; Suzuki, Maki; Yoshikawa, Sakiko; Abe, Nobuhito; Otsuka, Yuki; Nakai, Ryusuke; Aoyama, Tomoki; Tsuboyama, Tadao

    2015-07-01

    To investigate whether a 12-week physical and cognitive exercise program can improve cognitive function and brain activation efficiency in community-dwelling older adults. Randomized controlled trial. Kyoto, Japan. Community-dwelling older adults (N = 48) were randomized into an exercise group (n = 24) and a control group (n = 24). Exercise group participants received a weekly dual task-based multimodal exercise class in combination with pedometer-based daily walking exercise during the 12-week intervention phase. Control group participants did not receive any intervention and were instructed to spend their time as usual during the intervention phase. The outcome measures were global cognitive function, memory function, executive function, and brain activation (measured using functional magnetic resonance imaging) associated with visual short-term memory. Exercise group participants had significantly greater postintervention improvement in memory and executive functions than the control group (P cognitive exercise program can improve the efficiency of brain activation during cognitive tasks in older adults, which is associated with improvements in memory and executive function. © 2015, Copyright the Authors Journal compilation © 2015, The American Geriatrics Society.

  16. Neural Network Algorithm for Particle Loading

    International Nuclear Information System (INIS)

    Lewandowski, J.L.V.

    2003-01-01

    An artificial neural network algorithm for continuous minimization is developed and applied to the case of numerical particle loading. It is shown that higher-order moments of the probability distribution function can be efficiently renormalized using this technique. A general neural network for the renormalization of an arbitrary number of moments is given

  17. 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.

  18. 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.

  19. 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

  20. A double-blind, placebo-controlled study on the effects of lutein and zeaxanthin on neural processing speed and efficiency.

    Directory of Open Access Journals (Sweden)

    Emily R Bovier

    Full Text Available Lutein and zeaxanthin are major carotenoids in the eye but are also found in post-receptoral visual pathways. It has been hypothesized that these pigments influence the processing of visual signals within and post-retina, and that increasing lutein and zeaxanthin levels within the visual system will lead to increased visual processing speeds. To test this, we measured macular pigment density (as a biomarker of lutein and zeaxanthin levels in brain, critical flicker fusion (CFF thresholds, and visual motor reaction time in young healthy subjects (n = 92. Changes in these outcome variables were also assessed after four months of supplementation with either placebo (n = 10, zeaxanthin only (20 mg/day; n = 29 or a mixed formulation containing 26 mg/day zeaxanthin, 8 mg/day lutein, and 190 mg/day mixed omega-3 fatty acids (n = 25. Significant correlations were found between retinal lutein and zeaxanthin (macular pigment and CFF thresholds (p<0.01 and visual motor performance (overall p<0.01. Supplementation with zeaxanthin and the mixed formulation (considered together produced significant (p<0.01 increases in CFF thresholds (∼12% and visual motor reaction time (∼10% compared to placebo. In general, increasing macular pigment density through supplementation (average increase of about 0.09 log units resulted in significant improvements in visual processing speed, even when testing young, healthy individuals who tend to be at peak efficiency.

  1. Highly efficient simultaneous ultrasonic assisted adsorption of brilliant green and eosin B onto ZnS nanoparticles loaded activated carbon: Artificial neural network modeling and central composite design optimization

    Science.gov (United States)

    Jamshidi, M.; Ghaedi, M.; Dashtian, K.; Ghaedi, A. M.; Hajati, S.; Goudarzi, A.; Alipanahpour, E.

    2016-01-01

    In this work, central composite design (CCD) combined with response surface methodology (RSM) and desirability function approach (DFA) gives useful information about operational condition and also to obtain useful information about interaction and main effect of variables concerned to simultaneous ultrasound-assisted removal of brilliant green (BG) and eosin B (EB) by zinc sulfide nanoparticles loaded on activated carbon (ZnS-NPs-AC). Spectra overlap between BG and EB dyes was extensively reduced and/or omitted by derivative spectrophotometric method, while multi-layer artificial neural network (ML-ANN) model learned with Levenberg-Marquardt (LM) algorithm was used for building up a predictive model and prediction of the BG and EB removal. The ANN efficiently was able to forecast the simultaneous BG and EB removal that was confirmed by reasonable numerical value i.e. MSE of 0.0021 and R2 of 0.9589 and MSE of 0.0022 and R2 of 0.9455 for testing data set, respectively. The results reveal acceptable agreement among experimental data and ANN predicted results. Langmuir as the best model for fitting experimental data relevant to BG and EB removal indicates high, economic and profitable adsorption capacity (258.7 and 222.2 mg g- 1) that supports and confirms its applicability for wastewater treatment.

  2. EMMPRIN overexpression in SVZ neural progenitor cells increases their migration towards ischemic cortex.

    Science.gov (United States)

    Kanemitsu, Michiko; Tsupykov, Oleg; Potter, Gaël; Boitard, Michael; Salmon, Patrick; Zgraggen, Eloisa; Gascon, Eduardo; Skibo, Galina; Dayer, Alexandre G; Kiss, Jozsef Z

    2017-11-01

    Stimulation of endogenous neurogenesis and recruitment of neural progenitors from the subventricular zone (SVZ) neurogenic site may represent a useful strategy to improve regeneration in the ischemic cortex. Here, we tested whether transgenic overexpression of extracellular matrix metalloproteinase inducer (EMMPRIN), the regulator of matrix metalloproteinases (MMPs) expression, in endogenous neural progenitor cells (NPCs) in the subventricular zone (SVZ) could increase migration towards ischemic injury. For this purpose, we applied a lentivector-mediated gene transfer system. We found that EMMPRIN-transduced progenitors exhibited enhanced MMP-2 activity in vitro and showed improved motility in 3D collagen gel as well as in cortical slices. Using a rat model of neonatal ischemia, we showed that EMMPRIN overexpressing SVZ cells invade the injured cortical tissue more efficiently than controls. Our results suggest that EMMPRIN overexpression could be suitable approach to improve capacities of endogenous or transplanted progenitors to invade the injured cortex. Copyright © 2017 Elsevier Inc. All rights reserved.

  3. Training Feedforward Neural Networks Using Symbiotic Organisms Search Algorithm

    Directory of Open Access Journals (Sweden)

    Haizhou Wu

    2016-01-01

    Full Text Available Symbiotic organisms search (SOS is a new robust and powerful metaheuristic algorithm, which stimulates the symbiotic interaction strategies adopted by organisms to survive and propagate in the ecosystem. In the supervised learning area, it is a challenging task to present a satisfactory and efficient training algorithm for feedforward neural networks (FNNs. In this paper, SOS is employed as a new method for training FNNs. To investigate the performance of the aforementioned method, eight different datasets selected from the UCI machine learning repository are employed for experiment and the results are compared among seven metaheuristic algorithms. The results show that SOS performs better than other algorithms for training FNNs in terms of converging speed. It is also proven that an FNN trained by the method of SOS has better accuracy than most algorithms compared.

  4. Vertex Stimulation as a Control Site for Transcranial Magnetic Stimulation: A Concurrent TMS/fMRI Study

    OpenAIRE

    Jung, JeYoung; Bungert, Andreas; Bowtell, Richard; Jackson, Stephen R.

    2016-01-01

    Background A common control condition for transcranial magnetic stimulation (TMS) studies is to apply stimulation at the vertex. An assumption of vertex stimulation is that it has relatively little influence over on-going brain processes involved in most experimental tasks, however there has been little attempt to measure neural changes linked to vertex TMS. Here we directly test this assumption by using a concurrent TMS/fMRI paradigm in which we investigate fMRI blood-oxygenation-level-depen...

  5. 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.

  6. DRD2 genotype predicts prefrontal activity during working memory after stimulation of D2 receptors with bromocriptine.

    Science.gov (United States)

    Gelao, Barbara; Fazio, Leonardo; Selvaggi, Pierluigi; Di Giorgio, Annabella; Taurisano, Paolo; Quarto, Tiziana; Romano, Raffaella; Porcelli, Annamaria; Mancini, Marina; Masellis, Rita; Ursini, Gianluca; De Simeis, Giuseppe; Caforio, Grazia; Ferranti, Laura; Lo Bianco, Luciana; Rampino, Antonio; Todarello, Orlando; Popolizio, Teresa; Blasi, Giuseppe; Bertolino, Alessandro

    2014-06-01

    Pharmacological stimulation of D2 receptors modulates prefrontal neural activity associated with working memory (WM) processing. The T allele of a functional single-nucleotide polymorphism (SNP) within DRD2 (rs1076560 G > T) predicts reduced relative expression of the D2S receptor isoform and less efficient neural cortical responses during WM tasks. We used functional MRI to test the hypothesis that DRD2 rs1076560 genotype interacts with pharmacological stimulation of D2 receptors with bromocriptine on prefrontal responses during different loads of a spatial WM task (N-Back). Fifty-three healthy subjects (38 GG and 15 GT) underwent two 3-T functional MRI scans while performing the 1-, 2- and 3-Back versions of the N-Back WM task. Before the imaging sessions, either bromocriptine or placebo was administered to all subjects in a counterbalanced order. A factorial repeated-measures ANOVA within SPM8 (p < 0.05, family-wise error corrected) was used. On bromocriptine, GG subjects had reduced prefrontal activity at 3-Back together with a significant decrement in performance, compared with placebo. On the other hand, GT subjects had lower activity for the same level of performance at 1-Back but a trend for reduced behavioral performance in the face of unchanged activity at 2-Back. These results indicate that bromocriptine stimulation modulates prefrontal activity in terms of disengagement or of efficiency depending on DRD2 genotype and working memory load.

  7. Dissociable neural response signatures for slow amplitude and frequency modulation in human auditory cortex.

    Science.gov (United States)

    Henry, Molly J; Obleser, Jonas

    2013-01-01

    Natural auditory stimuli are characterized by slow fluctuations in amplitude and frequency. However, the degree to which the neural responses to slow amplitude modulation (AM) and frequency modulation (FM) are capable of conveying independent time-varying information, particularly with respect to speech communication, is unclear. In the current electroencephalography (EEG) study, participants listened to amplitude- and frequency-modulated narrow-band noises with a 3-Hz modulation rate, and the resulting neural responses were compared. Spectral analyses revealed similar spectral amplitude peaks for AM and FM at the stimulation frequency (3 Hz), but amplitude at the second harmonic frequency (6 Hz) was much higher for FM than for AM. Moreover, the phase delay of neural responses with respect to the full-band stimulus envelope was shorter for FM than for AM. Finally, the critical analysis involved classification of single trials as being in response to either AM or FM based on either phase or amplitude information. Time-varying phase, but not amplitude, was sufficient to accurately classify AM and FM stimuli based on single-trial neural responses. Taken together, the current results support the dissociable nature of cortical signatures of slow AM and FM. These cortical signatures potentially provide an efficient means to dissect simultaneously communicated slow temporal and spectral information in acoustic communication signals.

  8. Noradrenergic modulation of neural erotic stimulus perception.

    Science.gov (United States)

    Graf, Heiko; Wiegers, Maike; Metzger, Coraline Danielle; Walter, Martin; Grön, Georg; Abler, Birgit

    2017-09-01

    We recently investigated neuromodulatory effects of the noradrenergic agent reboxetine and the dopamine receptor affine amisulpride in healthy subjects on dynamic erotic stimulus processing. Whereas amisulpride left sexual functions and neural activations unimpaired, we observed detrimental activations under reboxetine within the caudate nucleus corresponding to motivational components of sexual behavior. However, broadly impaired subjective sexual functioning under reboxetine suggested effects on further neural components. We now investigated the same sample under these two agents with static erotic picture stimulation as alternative stimulus presentation mode to potentially observe further neural treatment effects of reboxetine. 19 healthy males were investigated under reboxetine, amisulpride and placebo for 7 days each within a double-blind cross-over design. During fMRI static erotic picture were presented with preceding anticipation periods. Subjective sexual functions were assessed by a self-reported questionnaire. Neural activations were attenuated within the caudate nucleus, putamen, ventral striatum, the pregenual and anterior midcingulate cortex and in the orbitofrontal cortex under reboxetine. Subjective diminished sexual arousal under reboxetine was correlated with attenuated neural reactivity within the posterior insula. Again, amisulpride left neural activations along with subjective sexual functioning unimpaired. Neither reboxetine nor amisulpride altered differential neural activations during anticipation of erotic stimuli. Our results verified detrimental effects of noradrenergic agents on neural motivational but also emotional and autonomic components of sexual behavior. Considering the overlap of neural network alterations with those evoked by serotonergic agents, our results suggest similar neuromodulatory effects of serotonergic and noradrenergic agents on common neural pathways relevant for sexual behavior. Copyright © 2017 Elsevier B.V. and

  9. Inverse approach for determination of the coils location during magnetic stimulation

    International Nuclear Information System (INIS)

    Marinova, Iliana; Kovachev, Ludmil

    2002-01-01

    An inverse approach using neural networks is extended and applied for determination of coils location during magnetic stimulation. The major constructions of magnetic stimulation coils have been investigated. The electric and magnetic fields are modelled using finite element method and integral equation method. The effects of changing the construction of coils and the frequency to the effect of magnetic stimulation are analysed. The results show that the coils for magnetic stimulation characterize with different focality and magnetic field concentration. The proposed inverse approach using neural networks is very useful for determination the spatial position of the stimulation coils especially when the location of the coil system is required to be changed dynamically. (Author)

  10. Osthole Stimulated Neural Stem Cells Differentiation into Neurons in an Alzheimer's Disease Cell Model via Upregulation of MicroRNA-9 and Rescued the Functional Impairment of Hippocampal Neurons in APP/PS1 Transgenic Mice

    Directory of Open Access Journals (Sweden)

    Shao-Heng Li

    2017-06-01

    Full Text Available Alzheimer's disease (AD is the most serious neurodegenerative disease worldwide and is characterized by progressive cognitive impairment and multiple neurological changes, including neuronal loss in the brain. However, there are no available drugs to delay or cure this disease. Consequently, neuronal replacement therapy may be a strategy to treat AD. Osthole (Ost, a natural coumarin derivative, crosses the blood-brain barrier and exerts strong neuroprotective effects against AD in vitro and in vivo. Recently, microRNAs (miRNAs have demonstrated a crucial role in pathological processes of AD, implying that targeting miRNAs could be a therapeutic approach to AD. In the present study, we investigated whether Ost could enhance cell viability and prevent cell death in amyloid precursor protein (APP-expressing neural stem cells (NSCs as well as promote APP-expressing NSCs differentiation into more neurons by upregulating microRNA (miR-9 and inhibiting the Notch signaling pathway in vitro. In addition, Ost treatment in APP/PS1 double transgenic (Tg mice markedly restored cognitive functions, reduced Aβ plague production and rescued functional impairment of hippocampal neurons. The results of the present study provides evidence of the neurogenesis effects and neurobiological mechanisms of Ost against AD, suggesting that Ost is a promising drug for treatment of AD or other neurodegenerative diseases.

  11. Non-scanning fiber-optic near-infrared beam led to two-photon optogenetic stimulation in-vivo.

    Directory of Open Access Journals (Sweden)

    Kamal R Dhakal

    Full Text Available Stimulation of specific neurons expressing opsins in a targeted region to manipulate brain function has proved to be a powerful tool in neuroscience. However, the use of visible light for optogenetic stimulation is invasive due to low penetration depth and tissue damage owing to larger absorption and scattering. Here, we report, for the first time, in-depth non-scanning fiber-optic two-photon optogenetic stimulation (FO-TPOS of neurons in-vivo in transgenic mouse models. In order to optimize the deep-brain stimulation strategy, we characterized two-photon activation efficacy at different near-infrared laser parameters. The significantly-enhanced in-depth stimulation efficiency of FO-TPOS as compared to conventional single-photon beam was demonstrated both by experiments and Monte Carlo simulation. The non-scanning FO-TPOS technology will lead to better understanding of the in-vivo neural circuitry because this technology permits more precise and less invasive anatomical delivery of stimulation.

  12. The modulatory effect of adaptive deep brain stimulation on beta bursts in Parkinson's disease

    NARCIS (Netherlands)

    Tinkhauser, Gerd; Pogosyan, Alek; Little, Simon; Beudel, Martijn; Herz, Damian M.; Tan, Huiling; Brown, Peter

    Adaptive deep brain stimulation uses feedback about the state of neural circuits to control stimulation rather than delivering fixed stimulation all the time, as currently performed. In patients with Parkinson's disease, elevations in beta activity (13-35 Hz) in the subthalamic nucleus have been

  13. Electrical and optical co-stimulation in the deaf white cat

    Science.gov (United States)

    Cao, Zhiping; Xu, Yingyue; Tan, Xiaodong; Suematsu, Naofumi; Robinson, Alan; Richter, Claus-Peter

    2018-02-01

    Spatial selectivity of neural stimulation with photons, such as infrared neural stimulation (INS) is higher than the selectivity obtained with electrical stimulation. To obtain more independent channels for stimulation in neural prostheses, INS may be implemented to better restore the fidelity of the damaged neural system. However, irradiation with infrared light also bares the risk of heat accumulation in the target tissue with subsequent neural damage. Lowering the threshold for stimulation could reduce the amount of heat delivered to the tissue and the risk for subsequent tissue damage. It has been shown in the rat sciatic nerve that simultaneous irradiation with infrared light and the delivery of biphasic sub-threshold electrical pulses can reduce the threshold for INS [1]. In this study, deaf white cats have been used to test whether opto-electrical co-stimulation can reduce the stimulation threshold for INS in the auditory system too. The cochleae of the deaf white cats have largely reduced spiral ganglion neuron counts and significant degeneration of the organ of Corti and do not respond to acoustic stimuli. Combined electrical and optical stimulation was used to demonstrate that simultaneous stimulation with infrared light and biphasic electrical pulses can reduce the threshold for stimulation.

  14. A novel Bayesian learning method for information aggregation in modular neural networks

    DEFF Research Database (Denmark)

    Wang, Pan; Xu, Lida; Zhou, Shang-Ming

    2010-01-01

    Modular neural network is a popular neural network model which has many successful applications. In this paper, a sequential Bayesian learning (SBL) is proposed for modular neural networks aiming at efficiently aggregating the outputs of members of the ensemble. The experimental results on eight...... benchmark problems have demonstrated that the proposed method can perform information aggregation efficiently in data modeling....

  15. Penfield's prediction: a mechanism for deep brain stimulation

    Directory of Open Access Journals (Sweden)

    Richard W. Murrow

    2014-10-01

    Full Text Available (1Context: Despite its widespread use, the precise mechanism of action of Deep Brain Stimulation (DBS therapy remains unknown. The modern urgency to publish more and new data can obscure previously learned lessons by the giants who have preceded us and whose shoulders we now stand upon. Wilder Penfield extensively studied the effects of artificial electrical brain stimulation and his comments on the subject are still very relevant today. In particular, he noted two very different (and seemingly opposite effects of stimulation within the human brain. In some structures, artificial electrical stimulation has an effect which mimics ablation, while, in other structures, it produces a stimulatory effect on that tissue. (2Hypothesis:The hypothesis of this paper is fourfold. First, it proposes that some neural circuits are widely synchronized with other neural circuits, while some neural circuits are unsynchronized and operate independently. Second, it proposes that artificial high frequency electrical stimulation of a synchronized neural circuit results in an ablative effect, but artificial high frequency electrical stimulation of an unsynchronized neural circuit results in a stimulatory effect. Third, it suggests a part of the mechanism by which large scale physiologic synchronization of widely distributed independently processed information streams may occur. This may be the neural mechanism underlying Penfield’s centrencephalic system which he emphasized so many years ago. Fourth, it outlines the specific anatomic distribution of this physiologic synchronization, which Penfield has already clearly delineated as the distribution of his centrencephalic system. (3Evidence:This paper draws on a brief overview of previous theory regarding the mechanism of action of DBS and on historical, as well as widely known modern clinical data regarding the observed effects of stimulation delivered to various targets within the brain. Basic science in

  16. A neural network approach to burst detection.

    Science.gov (United States)

    Mounce, S R; Day, A J; Wood, A S; Khan, A; Widdop, P D; Machell, J

    2002-01-01

    This paper describes how hydraulic and water quality data from a distribution network may be used to provide a more efficient leakage management capability for the water industry. The research presented concerns the application of artificial neural networks to the issue of detection and location of leakage in treated water distribution systems. An architecture for an Artificial Neural Network (ANN) based system is outlined. The neural network uses time series data produced by sensors to directly construct an empirical model for predication and classification of leaks. Results are presented using data from an experimental site in Yorkshire Water's Keighley distribution system.

  17. Harnessing migraines for neural regeneration

    Directory of Open Access Journals (Sweden)

    Jonathan M Borkum

    2018-01-01

    Full Text Available The success of naturalistic or therapeutic neuroregeneration likely depends on an internal milieu that facilitates the survival, proliferation, migration, and differentiation of stem cells and their assimilation into neural networks. Migraine attacks are an integrated sequence of physiological processes that may protect the brain from oxidative stress by releasing growth factors, suppressing apoptosis, stimulating neurogenesis, encouraging mitochondrial biogenesis, reducing the production of oxidants, and upregulating antioxidant defenses. Thus, the migraine attack may constitute a physiologic environment conducive to stem cells. In this paper, key components of migraine are reviewed – neurogenic inflammation with release of calcitonin gene-related peptide (CGRP and substance P, plasma protein extravasation, platelet activation, release of serotonin by platelets and likely by the dorsal raphe nucleus, activation of endothelial nitric oxide synthase (eNOS, production of brain-derived neurotrophic factor (BDNF and, in migraine aura, cortical spreading depression – along with their potential neurorestorative aspects. The possibility is considered of using these components to facilitate successful stem cell transplantation. Potential methods for doing so are discussed, including chemical stimulation of the TRPA1 ion channel, conjoint activation of a subset of migraine components, invasive and noninvasive deep brain stimulation of the dorsal raphe nucleus, transcranial focused ultrasound, and stimulation of the Zusanli (ST36 acupuncture point.

  18. 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.

  19. In vitro magnetic stimulation: a simple stimulation device to deliver defined low intensity electromagnetic fields

    Directory of Open Access Journals (Sweden)

    Stephanie Grehl

    2016-11-01

    Full Text Available Non-invasive electromagnetic field brain stimulation (NIBS appears to benefit human neurological and psychiatric conditions, although the optimal stimulation parameters and underlying mechanisms remain unclear. Although in vitro studies have begun to elucidate cellular mechanisms, stimulation is delivered by a range of coils (from commercially available human stimulation coils to laboratory-built circuits so that the electromagnetic fields induced within the tissue to produce the reported effects are ill-defined.Here we develop a simple in vitro stimulation device with plug-and-play features that allow delivery of a range of stimulation parameters. We chose to test low intensity repetitive magnetic stimulation (LI-rMS delivered at 3 frequencies to hindbrain explant cultures containing the olivocerebellar pathway. We used computational modelling to define the parameters of a stimulation circuit and coil that deliver a unidirectional homogeneous magnetic field of known intensity and direction, and therefore a predictable electric field, to the target. We built the coil to be compatible with culture requirements: stimulation within an incubator; a flat surface allowing consistent position and magnetic field direction; location outside the culture plate to maintain sterility and no heating or vibration. Measurements at the explant confirmed the induced magnetic field was homogenous and matched the simulation results. To validate our system we investigated biological effects following LI-rMS at 1 Hz, 10 Hz and biomimetic high frequency (BHFS, which we have previously shown induces neural circuit reorganisation. We found that gene expression was modified by LI-rMS in a frequency-related manner. Four hours after a single 10-minute stimulation session, the number of c-fos positive cells increased, indicating that our stimulation activated the tissue. Also, after 14 days of LI-rMS, the expression of genes normally present in the tissue was differentially

  20. Computational modeling of epidural cortical stimulation

    Science.gov (United States)

    Wongsarnpigoon, Amorn; Grill, Warren M.

    2008-12-01

    Epidural cortical stimulation (ECS) is a developing therapy to treat neurological disorders. However, it is not clear how the cortical anatomy or the polarity and position of the electrode affects current flow and neural activation in the cortex. We developed a 3D computational model simulating ECS over the precentral gyrus. With the electrode placed directly above the gyrus, about half of the stimulus current flowed through the crown of the gyrus while current density was low along the banks deep in the sulci. Beneath the electrode, neurons oriented perpendicular to the cortical surface were depolarized by anodic stimulation, and neurons oriented parallel to the boundary were depolarized by cathodic stimulation. Activation was localized to the crown of the gyrus, and neurons on the banks deep in the sulci were not polarized. During regulated voltage stimulation, the magnitude of the activating function was inversely proportional to the thickness of the CSF and dura. During regulated current stimulation, the activating function was not sensitive to the thickness of the dura but was slightly more sensitive than during regulated voltage stimulation to the thickness of the CSF. Varying the width of the gyrus and the position of the electrode altered the distribution of the activating function due to changes in the orientation of the neurons beneath the electrode. Bipolar stimulation, although often used in clinical practice, reduced spatial selectivity as well as selectivity for neuron orientation.

  1. Numerical dosimetry of transcranial magnetic stimulation coils

    Science.gov (United States)

    Crowther, Lawrence; Hadimani, Ravi; Jiles, David

    2014-03-01

    Transcranial magnetic stimulation (TMS) is a non-invasive neuromodulation technique capable of stimulating neurons by means of electromagnetic induction. TMS can be used to map brain function and shows promise for the diagnosis and treatment of neurological and psychiatric disorders. Calculation of fields induced in the brain are necessary to accurately identify stimulated neural tissue during TMS. This allows the development of novel TMS coil designs capable of stimulating deeper brain regions and increasing the localization of stimulation that can be achieved. We have performed numerical calculations of magnetic and electric field with high-resolution anatomically realistic human head models to find these stimulated brain regions for a variety of proposed TMS coil designs. The realistic head models contain heterogeneous tissue structures and electrical conductivities, yielding superior results to those obtained from the simplified homogeneous head models that are commonly employed. The attenuation of electric field as a function of depth in the brain and the localization of stimulating field have been methodically investigated. In addition to providing a quantitative comparison of different TMS coil designs the variation of induced field between subjects has been investigated. We also show the differences in induced fields between adult, adolescent and child head models to preemptively identify potential safety issues in the application of pediatric TMS.

  2. 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.

  3. 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 ...

  4. Temporal-pattern learning in neural models

    CERN Document Server

    Genís, Carme Torras

    1985-01-01

    While the ability of animals to learn rhythms is an unquestionable fact, the underlying neurophysiological mechanisms are still no more than conjectures. This monograph explores the requirements of such mechanisms, reviews those previously proposed and postulates a new one based on a direct electric coding of stimulation frequencies. Experi­ mental support for the option taken is provided both at the single neuron and neural network levels. More specifically, the material presented divides naturally into four parts: a description of the experimental and theoretical framework where this work becomes meaningful (Chapter 2), a detailed specifica­ tion of the pacemaker neuron model proposed together with its valida­ tion through simulation (Chapter 3), an analytic study of the behavior of this model when submitted to rhythmic stimulation (Chapter 4) and a description of the neural network model proposed for learning, together with an analysis of the simulation results obtained when varying seve­ ral factors r...

  5. Evidence for a neural law of effect.

    Science.gov (United States)

    Athalye, Vivek R; Santos, Fernando J; Carmena, Jose M; Costa, Rui M

    2018-03-02

    Thorndike's law of effect states that actions that lead to reinforcements tend to be repeated more often. Accordingly, neural activity patterns leading to reinforcement are also reentered more frequently. Reinforcement relies on dopaminergic activity in the ventral tegmental area (VTA), and animals shape their behavior to receive dopaminergic stimulation. Seeking evidence for a neural law of effect, we found that mice learn to reenter more frequently motor cortical activity patterns that trigger optogenetic VTA self-stimulation. Learning was accompanied by gradual shaping of these patterns, with participating neurons progressively increasing and aligning their covariance to that of the target pattern. Motor cortex patterns that lead to phasic dopaminergic VTA activity are progressively reinforced and shaped, suggesting a mechanism by which animals select and shape actions to reliably achieve reinforcement. Copyright © 2018 The Authors, some rights reserved; exclusive licensee American Association for the Advancement of Science. No claim to original U.S. Government Works.

  6. Robust Adaptive Neural Control of Morphing Aircraft with Prescribed Performance

    OpenAIRE

    Wu, Zhonghua; Lu, Jingchao; Shi, Jingping; Liu, Yang; Zhou, Qing

    2017-01-01

    This study proposes a low-computational composite adaptive neural control scheme for the longitudinal dynamics of a swept-back wing aircraft subject to parameter uncertainties. To efficiently release the constraint often existing in conventional neural designs, whose closed-loop stability analysis always necessitates that neural networks (NNs) be confined in the active regions, a smooth switching function is presented to conquer this issue. By integrating minimal learning parameter (MLP) tech...

  7. Hearing loss impacts neural alpha oscillations under adverse listening conditions

    OpenAIRE

    Petersen, Eline B.; Wöstmann, Malte; Obleser, Jonas; Stenfelt, Stefan; Lunner, Thomas

    2015-01-01

    Degradations in external, acoustic stimulation have long been suspected to increase the load on working memory (WM). One neural signature of WM load is enhanced power of alpha oscillations (6–12 Hz). However, it is unknown to what extent common internal, auditory degradation, that is, hearing impairment, affects the neural mechanisms of WM when audibility has been ensured via amplification. Using an adapted auditory Sternberg paradigm, we varied the orthogonal factors memory load and backgrou...

  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. Noninvasive Deep Brain Stimulation via Temporally Interfering Electric Fields.

    Science.gov (United States)

    Grossman, Nir; Bono, David; Dedic, Nina; Kodandaramaiah, Suhasa B; Rudenko, Andrii; Suk, Ho-Jun; Cassara, Antonino M; Neufeld, Esra; Kuster, Niels; Tsai, Li-Huei; Pascual-Leone, Alvaro; Boyden, Edward S

    2017-06-01

    We report a noninvasive strategy for electrically stimulating neurons at depth. By delivering to the brain multiple electric fields at frequencies too high to recruit neural firing, but which differ by a frequency within the dynamic range of neural firing, we can electrically stimulate neurons throughout a region where interference between the multiple fields results in a prominent electric field envelope modulated at the difference frequency. We validated this temporal interference (TI) concept via modeling and physics experiments, and verified that neurons in the living mouse brain could follow the electric field envelope. We demonstrate the utility of TI stimulation by stimulating neurons in the hippocampus of living mice without recruiting neurons of the overlying cortex. Finally, we show that by altering the currents delivered to a set of immobile electrodes, we can steerably evoke different motor patterns in living mice. Copyright © 2017 Elsevier Inc. All rights reserved.

  10. Logarithmic learning for generalized classifier neural network.

    Science.gov (United States)

    Ozyildirim, Buse Melis; Avci, Mutlu

    2014-12-01

    Generalized classifier neural network is introduced as an efficient classifier among the others. Unless the initial smoothing parameter value is close to the optimal one, generalized classifier neural network suffers from convergence problem and requires quite a long time to converge. In this work, to overcome this problem, a logarithmic learning approach is proposed. The proposed method uses logarithmic cost function instead of squared error. Minimization of this cost function reduces the number of iterations used for reaching the minima. The proposed method is tested on 15 different data sets and performance of logarithmic learning generalized classifier neural network is compared with that of standard one. Thanks to operation range of radial basis function included by generalized classifier neural network, proposed logarithmic approach and its derivative has continuous values. This makes it possible to adopt the advantage of logarithmic fast convergence by the proposed learning method. Due to fast convergence ability of logarithmic cost function, training time is maximally decreased to 99.2%. In addition to decrease in training time, classification performance may also be improved till 60%. According to the test results, while the proposed method provides a solution for time requirement problem of generalized classifier neural network, it may also improve the classification accuracy. The proposed method can be considered as an efficient way for reducing the time requirement problem of generalized classifier neural network. Copyright © 2014 Elsevier Ltd. All rights reserved.

  11. Magnetic fields in noninvasive brain stimulation.

    Science.gov (United States)

    Vidal-Dourado, Marcos; Conforto, Adriana Bastos; Caboclo, Luis Otávio Sales Ferreira; Scaff, Milberto; Guilhoto, Laura Maria de Figueiredo Ferreira; Yacubian, Elza Márcia Targas

    2014-04-01

    The idea that magnetic fields could be used therapeutically arose 2000 years ago. These therapeutic possibilities were expanded after the discovery of electromagnetic induction by the Englishman Michael Faraday and the American Joseph Henry. In 1896, Arsène d'Arsonval reported his experience with noninvasive brain magnetic stimulation to the scientific French community. In the second half of the 20th century, changing magnetic fields emerged as a noninvasive tool to study the nervous system and to modulate neural function. In 1985, Barker, Jalinous, and Freeston presented transcranial magnetic stimulation, a relatively focal and painless technique. Transcranial magnetic stimulation has been proposed as a clinical neurophysiology tool and as a potential adjuvant treatment for psychiatric and neurologic conditions. This article aims to contextualize the progress of use of magnetic fields in the history of neuroscience and medical sciences, until 1985.

  12. 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).

  13. Automatic gain control of neural coupling during cooperative hand movements.

    Science.gov (United States)

    Thomas, F A; Dietz, V; Schrafl-Altermatt, M

    2018-04-13

    Cooperative hand movements (e.g. opening a bottle) are controlled by a task-specific neural coupling, reflected in EMG reflex responses contralateral to the stimulation site. In this study the contralateral reflex responses in forearm extensor muscles to ipsilateral ulnar nerve stimulation was analyzed at various resistance and velocities of cooperative hand movements. The size of contralateral reflex responses was closely related to the level of forearm muscle activation required to accomplish the various cooperative hand movement tasks. This indicates an automatic gain control of neural coupling that allows a rapid matching of corrective forces exerted at both sides of an object with the goal 'two hands one action'.

  14. Electrically polarized PLLA nanofibers as neural tissue engineering scaffolds with improved neuritogenesis.

    Science.gov (United States)

    Barroca, Nathalie; Marote, Ana; Vieira, Sandra I; Almeida, Abílio; Fernandes, Maria H V; Vilarinho, Paula M; da Cruz E Silva, Odete A B

    2018-07-01

    Tissue engineering is evolving towards the production of smart platforms exhibiting stimulatory cues to guide tissue regeneration. This work explores the benefits of electrical polarization to produce more efficient neural tissue engineering platforms. Poly (l-lactic) acid (PLLA)-based scaffolds were prepared as solvent cast films and electrospun aligned nanofibers, and electrically polarized by an in-lab built corona poling device. The characterization of the platforms by thermally stimulated depolarization currents reveals a polarization of 60 × 10 -10 C cm -2 that is stable on poled electrospun nanofibers for up to 6 months. Further in vitro studies using neuroblastoma cells reveals that platforms' polarization potentiates Retinoic Acid-induced neuronal differentiation. Additionally, in differentiating embryonic cortical neurons, poled aligned nanofibers further increased neurite outgrowth by 30% (+70 μm) over non-poled aligned nanofibers, and by 50% (+100 μm) over control conditions. Therefore, the synergy of topographical cues and electrical polarization of poled aligned nanofibers places them as promising biocompatible and bioactive platforms for neural tissue regeneration. Given their long lasting induced polarization, these PLLA poled nanofibrous scaffolds can be envisaged as therapeutic devices of long shelf life for neural repair applications. Copyright © 2018 Elsevier B.V. All rights reserved.

  15. 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.

  16. How to target inter-regional phase synchronization with dual-site Transcranial Alternating Current Stimulation

    DEFF Research Database (Denmark)

    Saturnino, Guilherme Bicalho; Madsen, Kristoffer Hougaard; Siebner, Hartwig Roman

    2017-01-01

    oscillations in two connected cortical areas. While the frequency of ds-TACS is matched, the phase of stimulation is either identical (in-phase stimulation) or opposite (anti-phase stimulation) in the two cortical target areas. In-phase stimulation is thought to synchronize the endogenous oscillations...... and hereby to improve behavioral performance. Conversely, anti-phase stimulation is thought to desynchronize neural oscillations in the two areas, which is expected to decrease performance. Critically, in- and anti-phase ds-TACS should only differ with respect to temporal phase, while all other stimulation...... unambiguously the causal contribution of phase coupling to specific cognitive processes in the human brain....

  17. Repetitive Transcranial Magnetic Stimulation to the Primary Motor Cortex Interferes with Motor Learning by Observing

    Science.gov (United States)

    Brown, Liana E.; Wilson, Elizabeth T.; Gribble, Paul L.

    2009-01-01

    Neural representations of novel motor skills can be acquired through visual observation. We used repetitive transcranial magnetic stimulation (rTMS) to test the idea that this "motor learning by observing" is based on engagement of neural processes for learning in the primary motor cortex (M1). Human subjects who observed another person learning…

  18. Neural Network for Sparse Reconstruction

    Directory of Open Access Journals (Sweden)

    Qingfa Li

    2014-01-01

    Full Text Available We construct a neural network based on smoothing approximation techniques and projected gradient method to solve a kind of sparse reconstruction problems. Neural network can be implemented by circuits and can be seen as an important method for solving optimization problems, especially large scale problems. Smoothing approximation is an efficient technique for solving nonsmooth optimization problems. We combine these two techniques to overcome the difficulties of the choices of the step size in discrete algorithms and the item in the set-valued map of differential inclusion. In theory, the proposed network can converge to the optimal solution set of the given problem. Furthermore, some numerical experiments show the effectiveness of the proposed network in this paper.

  19. Neural Networks Methodology and Applications

    CERN Document Server

    Dreyfus, Gérard

    2005-01-01

    Neural networks represent a powerful data processing technique that has reached maturity and broad application. When clearly understood and appropriately used, they are a mandatory component in the toolbox of any engineer who wants make the best use of the available data, in order to build models, make predictions, mine data, recognize shapes or signals, etc. Ranging from theoretical foundations to real-life applications, this book is intended to provide engineers and researchers with clear methodologies for taking advantage of neural networks in industrial, financial or banking applications, many instances of which are presented in the book. For the benefit of readers wishing to gain deeper knowledge of the topics, the book features appendices that provide theoretical details for greater insight, and algorithmic details for efficient programming and implementation. The chapters have been written by experts ands seemlessly edited to present a coherent and comprehensive, yet not redundant, practically-oriented...

  20. Concurrent OCT imaging of stimulus evoked retinal neural activation and hemodynamic responses

    Science.gov (United States)

    Son, Taeyoon; Wang, Benquan; Lu, Yiming; Chen, Yanjun; Cao, Dingcai; Yao, Xincheng

    2017-02-01

    It is well established that major retinal diseases involve distortions of the retinal neural physiology and blood vascular structures. However, the details of distortions in retinal neurovascular coupling associated with major eye diseases are not well understood. In this study, a multi-modal optical coherence tomography (OCT) imaging system was developed to enable concurrent imaging of retinal neural activity and vascular hemodynamics. Flicker light stimulation was applied to mouse retinas to evoke retinal neural responses and hemodynamic changes. The OCT images were acquired continuously during the pre-stimulation, light-stimulation, and post-stimulation phases. Stimulus-evoked intrinsic optical signals (IOSs) and hemodynamic changes were observed over time in blood-free and blood regions, respectively. Rapid IOSs change occurred almost immediately after stimulation. Both positive and negative signals were observed in adjacent retinal areas. The hemodynamic changes showed time delays after stimulation. The signal magnitudes induced by light stimulation were observed in blood regions and did not show significant changes in blood-free regions. These differences may arise from different mechanisms in blood vessels and neural tissues in response to light stimulation. These characteristics agreed well with our previous observations in mouse retinas. Further development of the multimodal OCT may provide a new imaging method for studying how retinal structures and metabolic and neural functions are affected by age-related macular degeneration (AMD), glaucoma, diabetic retinopathy (DR), and other diseases, which promises novel noninvasive biomarkers for early disease detection and reliable treatment evaluations of eye diseases.

  1. Direct electrical stimulation of human cortex evokes high gamma activity that predicts conscious somatosensory perception

    Science.gov (United States)

    Muller, Leah; Rolston, John D.; Fox, Neal P.; Knowlton, Robert; Rao, Vikram R.; Chang, Edward F.

    2018-04-01

    Objective. Direct electrical stimulation (DES) is a clinical gold standard for human brain mapping and readily evokes conscious percepts, yet the neurophysiological changes underlying these percepts are not well understood. Approach. To determine the neural correlates of DES, we stimulated the somatosensory cortex of ten human participants at frequency-amplitude combinations that both elicited and failed to elicit conscious percepts, meanwhile recording neural activity directly surrounding the stimulation site. We then compared the neural activity of perceived trials to that of non-perceived trials. Main results. We found that stimulation evokes distributed high gamma activity, which correlates with conscious perception better than stimulation parameters themselves. Significance. Our findings suggest that high gamma activity is a reliable biomarker for perception evoked by both natural and electrical stimuli.

  2. Weak correlations between hemodynamic signals and ongoing neural activity during the resting state

    Science.gov (United States)

    Winder, Aaron T.; Echagarruga, Christina; Zhang, Qingguang; Drew, Patrick J.

    2017-01-01

    Spontaneous fluctuations in hemodynamic signals in the absence of a task or overt stimulation are used to infer neural activity. We tested this coupling by simultaneously measuring neural activity and changes in cerebral blood volume (CBV) in the somatosensory cortex of awake, head-fixed mice during periods of true rest, and during whisker stimulation and volitional whisking. Here we show that neurovascular coupling was similar across states, and large spontaneous CBV changes in the absence of sensory input were driven by volitional whisker and body movements. Hemodynamic signals during periods of rest were weakly correlated with neural activity. Spontaneous fluctuations in CBV and vessel diameter persisted when local neural spiking and glutamatergic input was blocked, and during blockade of noradrenergic receptors, suggesting a non-neuronal origin for spontaneous CBV fluctuations. Spontaneous hemodynamic signals reflect a combination of behavior, local neural activity, and putatively non-neural processes. PMID:29184204

  3. 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)

  4. Spinal cord stimulation

    Science.gov (United States)

    ... this page: //medlineplus.gov/ency/article/007560.htm Spinal cord stimulation To use the sharing features on this page, please enable JavaScript. Spinal cord stimulation is a treatment for pain that uses ...

  5. Feldspar, Infrared Stimulated Luminescence

    DEFF Research Database (Denmark)

    Jain, Mayank

    2014-01-01

    This entry primarily concerns the characteristics and the origins of infrared-stimulated luminescence in feldspars.......This entry primarily concerns the characteristics and the origins of infrared-stimulated luminescence in feldspars....

  6. Growth hormone stimulation test

    Science.gov (United States)

    ... this page: //medlineplus.gov/ency/article/003377.htm Growth hormone stimulation test To use the sharing features on this page, please enable JavaScript. The growth hormone (GH) stimulation test measures the ability of ...

  7. Long-duration transcutaneous electric acupoint stimulation alters small-world brain functional networks.

    Science.gov (United States)

    Zhang, Yue; Jiang, Yin; Glielmi, Christopher B; Li, Longchuan; Hu, Xiaoping; Wang, Xiaoying; Han, Jisheng; Zhang, Jue; Cui, Cailian; Fang, Jing

    2013-09-01

    Acupuncture, which is recognized as an alternative and complementary treatment in Western medicine, has long shown efficiencies in chronic pain relief, drug addiction treatment, stroke rehabilitation and other clinical practices. The neural mechanism underlying acupuncture, however, is still unclear. Many studies have focused on the sustained effects of acupuncture on healthy subjects, yet there are very few on the topological organization of functional networks in the whole brain in response to long-duration acupuncture (longer than 20 min). This paper presents a novel study on the effects of long-duration transcutaneous electric acupoint stimulation (TEAS) on the small-world properties of brain functional networks. Functional magnetic resonance imaging was used to construct brain functional networks of 18 healthy subjects (9 males and 9 females) during the resting state. All subjects received both TEAS and minimal TEAS (MTEAS) and were scanned before and after each stimulation. An altered functional network was found with lower local efficiency and no significant change in global efficiency for healthy subjects after TEAS, while no significant difference was observed after MTEAS. The experiments also showed that the nodal efficiencies in several paralimbic/limbic regions were altered by TEAS, and those in middle frontal gyrus and other regions by MTEAS. To remove the psychological effects and the baseline, we compared the difference between diffTEAS (difference between after and before TEAS) and diffMTEAS (difference between after and before MTEAS). The results showed that the local efficiency was decreased and that the nodal efficiencies in frontal gyrus, orbitofrontal cortex, anterior cingulate gyrus and hippocampus gyrus were changed. Based on those observations, we conclude that long-duration TEAS may modulate the short-range connections of brain functional networks and also the limbic system. Copyright © 2013 Elsevier Inc. All rights reserved.

  8. 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.

  9. Applying Fuzzy Artificial Neural Network OSPF to develop Smart ...

    African Journals Online (AJOL)

    pc

    2018-03-05

    Mar 5, 2018 ... Fuzzy Artificial Neural Network to create Smart Routing. Protocol Algorithm. ... manufactured mental aptitude strategy. The capacity to study .... Based Energy Efficiency in Wireless Sensor Networks: A Survey",. International ...

  10. Linear matrix inequality approach to exponential synchronization of a class of chaotic neural networks with time-varying delays

    Science.gov (United States)

    Wu, Wei; Cui, Bao-Tong

    2007-07-01

    In this paper, a synchronization scheme for a class of chaotic neural networks with time-varying delays is presented. This class of chaotic neural networks covers several well-known neural networks, such as Hopfield neural networks, cellular neural networks, and bidirectional associative memory networks. The obtained criteria are expressed in terms of linear matrix inequalities, thus they can be efficiently verified. A comparison between our results and the previous results shows that our results are less restrictive.

  11. Foraging for brain stimulation: toward a neurobiology of computation.

    Science.gov (United States)

    Gallistel, C R

    1994-01-01

    The self-stimulating rat performs foraging tasks mediated by simple computations that use interreward intervals and subjective reward magnitudes to determine stay durations. This is a simplified preparation in which to study the neurobiology of the elementary computational operations that make cognition possible, because the neural signal specifying the value of a computationally relevant variable is produced by direct electrical stimulation of a neural pathway. Newly developed measurement methods yield functions relating the subjective reward mag