Eliades, Steven J.; Wang, Xiaoqin
Many behaviors of interest to neurophysiologists are difficult to study under laboratory conditions because such behaviors are often inhibited when an animal is restrained and socially isolated. Even under the best conditions, such behaviors may be sparse enough as to require long duration neural recordings or simultaneous recording of multiple neurons to gather a sufficient amount of data for analysis. We have developed a preparation for chronic, multi-electrode recordings in the auditory co...
Kim, Tae Gyo
Although clinical use of invasive neural interfaces is very limited, due to safety and reliability concerns, the potential benefits of their use in brain machine interfaces (BMIs) seem promising and so they have been widely used in the research field. Microelectrodes as invasive neural interfaces are the core tool to record neural activities and their failure is a critical issue for BMI systems. Possible sources of this failure are neural tissue motions and their interactions with stiff electrode arrays or probes fixed to the skull. To overcome these tissue motion problems, we have developed novel braided multi-electrode probes (BMEPs). By interweaving ultra-fine wires into a tubular braid structure, we obtained a highly flexible multi-electrode probe. In this thesis we described BMEP designs and how to fabricate BMEPs, and explore experiments to show the advantages of BMEPs through a mechanical compliance comparison and a chronic immunohistological comparison with single 50microm nichrome wires used as a reference electrode type. Results from the mechanical compliance test showed that the bodies of BMEPs have 4 to 21 times higher compliance than the single 50microm wire and the tethers of BMEPs were 6 to 96 times higher compliance, depending on combinations of the wire size (9.6microm or 12.7microm), the wire numbers (12 or 24), and the length of tether (3, 5 or 10 mm). Results from the immunohistological comparison showed that both BMEPs and 50microm wires anchored to the skull caused stronger tissue reactions than unanchored BMEPs and 50microm wires, and 50microm wires caused stronger tissue reactions than BMEPs. In in-vivo tests with BMEPs, we succeeded in chronic recordings from the spinal cord of freely jumping frogs and in acute recordings from the spinal cord of decerebrate rats during air stepping which was evoked by mesencephalic locomotor region (MLR) stimulation. This technology may provide a stable and reliable neural interface to spinal cord
Full Text Available Direct interfacing of transected peripheral nerves with advanced robotic prosthetic devices has been proposed as a strategy for achieving natural motor control and sensory perception of such bionic substitutes, thus fully functionally replacing missing limbs in amputees. Multi-electrode arrays placed in the brain and peripheral nerves have been used successfully to convey neural control of prosthetic devices to the user. However, reactive gliosis, micro hemorrhages, axonopathy and excessive inflammation, currently limit their long-term use. Here we demonstrate that enticement of peripheral nerve regeneration through a non-obstructive multi-electrode array, after either acute or chronic nerve amputation, offers a viable alternative to obtain early neural recordings and to enhance long-term interfacing of nerve activity. Non restrictive electrode arrays placed in the path of regenerating nerve fibers allowed the recording of action potentials as early as 8 days post-implantation with high signal-to-noise ratio, as long as 3 months in some animals, and with minimal inflammation at the nerve tissue-metal electrode interface. Our findings suggest that regenerative on-dependent multi-electrode arrays of open design allow the early and stable interfacing of neural activity from amputated peripheral nerves and might contribute towards conveying full neural control and sensory feedback to users of robotic prosthetic devices. .
Garde, Kshitija; Keefer, Edward; Botterman, Barry; Galvan, Pedro; Romero, Mario I.
Direct interfacing of transected peripheral nerves with advanced robotic prosthetic devices has been proposed as a strategy for achieving natural motor control and sensory perception of such bionic substitutes, thus fully functionally replacing missing limbs in amputees. Multi-electrode arrays placed in the brain and peripheral nerves have been used successfully to convey neural control of prosthetic devices to the user. However, reactive gliosis, micro hemorrhages, axonopathy and excessive i...
Kshitija Garde; Barry Botterman; Pedro Galvan
Direct interfacing of transected peripheral nerves with advanced robotic prosthetic devices has been proposed as a strategy for achieving natural motor control and sensory perception of such bionic substitutes, thus fully functionally replacing missing limbs in amputees. Multi-electrode arrays placed in the brain and peripheral nerves have been used successfully to convey neural control of prosthetic devices to the user. However, reactive gliosis, micro hemorrhages, axonopathy and excessive i...
Maturana, Matias I; Apollo, Nicholas V; Hadjinicolaou, Alex E; Garrett, David J; Cloherty, Shaun L; Kameneva, Tatiana; Grayden, David B; Ibbotson, Michael R; Meffin, Hamish
Implantable electrode arrays are widely used in therapeutic stimulation of the nervous system (e.g. cochlear, retinal, and cortical implants). Currently, most neural prostheses use serial stimulation (i.e. one electrode at a time) despite this severely limiting the repertoire of stimuli that can be applied. Methods to reliably predict the outcome of multi-electrode stimulation have not been available. Here, we demonstrate that a linear-nonlinear model accurately predicts neural responses to arbitrary patterns of stimulation using in vitro recordings from single retinal ganglion cells (RGCs) stimulated with a subretinal multi-electrode array. In the model, the stimulus is projected onto a low-dimensional subspace and then undergoes a nonlinear transformation to produce an estimate of spiking probability. The low-dimensional subspace is estimated using principal components analysis, which gives the neuron's electrical receptive field (ERF), i.e. the electrodes to which the neuron is most sensitive. Our model suggests that stimulation proportional to the ERF yields a higher efficacy given a fixed amount of power when compared to equal amplitude stimulation on up to three electrodes. We find that the model captures the responses of all the cells recorded in the study, suggesting that it will generalize to most cell types in the retina. The model is computationally efficient to evaluate and, therefore, appropriate for future real-time applications including stimulation strategies that make use of recorded neural activity to improve the stimulation strategy. PMID:27035143
Matias I Maturana
Full Text Available Implantable electrode arrays are widely used in therapeutic stimulation of the nervous system (e.g. cochlear, retinal, and cortical implants. Currently, most neural prostheses use serial stimulation (i.e. one electrode at a time despite this severely limiting the repertoire of stimuli that can be applied. Methods to reliably predict the outcome of multi-electrode stimulation have not been available. Here, we demonstrate that a linear-nonlinear model accurately predicts neural responses to arbitrary patterns of stimulation using in vitro recordings from single retinal ganglion cells (RGCs stimulated with a subretinal multi-electrode array. In the model, the stimulus is projected onto a low-dimensional subspace and then undergoes a nonlinear transformation to produce an estimate of spiking probability. The low-dimensional subspace is estimated using principal components analysis, which gives the neuron's electrical receptive field (ERF, i.e. the electrodes to which the neuron is most sensitive. Our model suggests that stimulation proportional to the ERF yields a higher efficacy given a fixed amount of power when compared to equal amplitude stimulation on up to three electrodes. We find that the model captures the responses of all the cells recorded in the study, suggesting that it will generalize to most cell types in the retina. The model is computationally efficient to evaluate and, therefore, appropriate for future real-time applications including stimulation strategies that make use of recorded neural activity to improve the stimulation strategy.
Maturana, Matias I.; Apollo, Nicholas V.; Hadjinicolaou, Alex E.; Garrett, David J.; Cloherty, Shaun L.; Kameneva, Tatiana; Grayden, David B.; Ibbotson, Michael R.; Meffin, Hamish
Implantable electrode arrays are widely used in therapeutic stimulation of the nervous system (e.g. cochlear, retinal, and cortical implants). Currently, most neural prostheses use serial stimulation (i.e. one electrode at a time) despite this severely limiting the repertoire of stimuli that can be applied. Methods to reliably predict the outcome of multi-electrode stimulation have not been available. Here, we demonstrate that a linear-nonlinear model accurately predicts neural responses to arbitrary patterns of stimulation using in vitro recordings from single retinal ganglion cells (RGCs) stimulated with a subretinal multi-electrode array. In the model, the stimulus is projected onto a low-dimensional subspace and then undergoes a nonlinear transformation to produce an estimate of spiking probability. The low-dimensional subspace is estimated using principal components analysis, which gives the neuron’s electrical receptive field (ERF), i.e. the electrodes to which the neuron is most sensitive. Our model suggests that stimulation proportional to the ERF yields a higher efficacy given a fixed amount of power when compared to equal amplitude stimulation on up to three electrodes. We find that the model captures the responses of all the cells recorded in the study, suggesting that it will generalize to most cell types in the retina. The model is computationally efficient to evaluate and, therefore, appropriate for future real-time applications including stimulation strategies that make use of recorded neural activity to improve the stimulation strategy. PMID:27035143
Rennaker, R L; Miller, J.; Tang, H.; Wilson, D. A.
Brain/machine interfaces could potentially be used in the treatment of a host of neurological disorders ranging from paralysis to sensory deficits. Insertion of chronic micro-electrode arrays into neural tissue initiates a host of immunological responses, which typically leads to the formation of a cellular sheath around the implant, resulting in the loss of useful signals. Minocycline has been shown to have neuroprotective and neurorestorative effects in certain neural injury and neurodegene...
Gerhard, Felipe; Pipa, Gordon; Lima, Bruss; Neuenschwander, Sergio; Gerstner, Wulfram
The simultaneous recording of the activity of many neurons poses challenges for multivariate data analysis. Here, we propose a general scheme of reconstruction of the functional network from spike train recordings. Effective, causal interactions are estimated by fitting generalized linear models on the neural responses, incorporating effects of the neurons' self-history, of input from other neurons in the recorded network and of modulation by an external stimulus. The coupling terms arising from synaptic input can be transformed by thresholding into a binary connectivity matrix which is directed. Each link between two neurons represents a causal influence from one neuron to the other, given the observation of all other neurons from the population. The resulting graph is analyzed with respect to small-world and scale-free properties using quantitative measures for directed networks. Such graph-theoretic analyses have been performed on many complex dynamic networks, including the connectivity structure between different brain areas. Only few studies have attempted to look at the structure of cortical neural networks on the level of individual neurons. Here, using multi-electrode recordings from the visual system of the awake monkey, we find that cortical networks lack scale-free behavior, but show a small, but significant small-world structure. Assuming a simple distance-dependent probabilistic wiring between neurons, we find that this connectivity structure can account for all of the networks' observed small-world ness. Moreover, for multi-electrode recordings the sampling of neurons is not uniform across the population. We show that the small-world-ness obtained by such a localized sub-sampling overestimates the strength of the true small-world structure of the network. This bias is likely to be present in all previous experiments based on multi-electrode recordings. PMID:21344015
Full Text Available The simultaneous recording of the activity of many neurons poses challenges for multivariate data analysis. Here, we propose a general scheme of reconstruction of the functional network from spike train recordings. Effective, causal interactions are estimated by fitting Generalized Linear Models (GLMs on the neural responses, incorporating effects of the neurons' self-history, of input from other neurons in the recorded network and of modulation by an external stimulus. The coupling terms arising from synaptic input can be transformed by thresholding into a binary connectivity matrix which is directed. Each link between two neurons represents a causal influence from one neuron to the other, given the observation of all other neurons from the population. The resulting graph is analyzed with respect to small-world and scale-free properties using quantitative measures for directed networks. Such graph-theoretic analyses have been performed on many complex dynamic networks, including the connectivity structure between different brain areas. Only few studies have attempted to look at the structure of cortical neural networks on the level of individual neurons. Here, using multi-electrode recordings from the visual system of the awake monkey, we find that cortical networks lack scale-free behavior, but show a small, but significant small-world structure. Assuming a simple distance-dependent probabilistic wiring between neurons, we find that this connectivity structure can account for all of the networks' observed small-world-ness. Moreover, for multi-electrode recordings the sampling of neurons is not uniform across the population. We show that the small-world-ness obtained by such a localized sub-sampling overestimates the strength of the true small-world-structure of the network. This bias is likely to be present in all previous experiments based on multi-electrode recordings.
Peripheral nerves offer unique accessibility to the innate motor and sensory pathways that can be interfaced with high degree of selectivity for intuitive and bidirectional control of advanced upper extremity prosthetic limbs. Several peripheral nerve interfaces have been proposed and investigated over the last few decades with significant progress made in the area of sensory feedback. However, clinical translation still remains a formidable challenge due to the lack of long term recordings. Prominent causes include signal degradation, eventual interface failures, and lack of specificity in the low amplitude nerve signals. This dissertation evaluates the capabilities of the newly developed Regenerative Multi-electrode Interface (REMI) by the characterization of signal quality progression, the identification of interfaced axon types, and the demonstration of "functional linkage" between acquired signals and target organs. Chapter 2 details the chronic recording of high quality signals from REMI in sciatic nerve which remained stable over a 120 day implantation period indicative of minimal ongoing tissue response with no detrimental effects on the recording ability. The dominant cause of failures was attributable to abiotic factors pertaining to the connector/wire breakage, observed in 76% of REMI implants. Also, the REMI implants had 20% higher success rate and significantly larger Signal to Noise Ratio (SNR) in comparison to the Utah Slanted Electrode Array (USEA). Chapter 3 describes the successful feasibility of interfacing with motor and sensory axons by REMI implantation in the tibial and sural fascicles of the sciatic nerve. A characteristic sampling bias towards recording signals from medium-to-large diameter axons that are primarily involved in mechanoception and proprioception sensory functions was uncovered. Specific bursting units (Inter Spike Interval of 30-70ms) were observed most frequently from the tibial fascicle during bipedal locomotion. Chapter 4
Full Text Available Stress initiates adaptive processes that allow the organism to physiologically cope with prolonged or intermittent exposure to real or perceived threats. A major component of this response is repeated activation of glucocorticoid secretion by the hypothalamo-pituitary-adrenocortical (HPA axis, which promotes redistribution of energy in a wide range of organ systems, including the brain. Prolonged or cumulative increases in glucocorticoid secretion can reduce benefits afforded by enhanced stress reactivity and eventually become maladaptive. The long-term impact of stress is kept in check by the process of habituation, which reduces HPA axis responses upon repeated exposure to homotypic stressors and likely limits deleterious actions of prolonged glucocorticoid secretion. Habituation is regulated by limbic stress-regulatory sites, and is at least in part glucocorticoid feedback-dependent. Chronic stress also sensitizes reactivity to new stimuli. While sensitization may be important in maintaining response flexibility in response to new threats, it may also add to the cumulative impact of glucocorticoids on the brain and body. Finally, unpredictable or severe stress exposure may cause long-term and lasting dysregulation of the HPA axis, likely due to altered limbic control of stress effector pathways. Stress-related disorders, such as depression and PTSD, are accompanied by glucocorticoid imbalances and structural/ functional alterations in limbic circuits that resemble those seen following chronic stress, suggesting that inappropriate processing of stressful information may be part of the pathological process.
Rennaker, R. L.; Miller, J.; Tang, H.; Wilson, D. A.
Brain/machine interfaces could potentially be used in the treatment of a host of neurological disorders ranging from paralysis to sensory deficits. Insertion of chronic micro-electrode arrays into neural tissue initiates a host of immunological responses, which typically leads to the formation of a cellular sheath around the implant, resulting in the loss of useful signals. Minocycline has been shown to have neuroprotective and neurorestorative effects in certain neural injury and neurodegenerative disease models. This study examined the effects of minocycline administration on the quality and longevity of chronic multi-channel microwire neural implants 1 week and 1 month post-implantation in auditory cortex. The mean signal-to-noise ratio for the minocycline group stabilized at the end of week 1 and remained above 4.6 throughout the following 3 weeks. The control group signal-to-noise ratio dropped throughout the duration of the study and at the end of 4 weeks was 2.6. Furthermore, 68% of electrodes from the minocycline group showed significant stimulus-driven activity at week 4 compared to 12.5% of electrodes in the control group. There was a significant reduction in the number of activated astrocytes around the implant in minocycline subjects, as well as a reduction in total area occupied by activated astrocytes at 1 and 4 weeks.
Groshev, V R; Nifontov, V I; Pishenuok, S M; Samsonov, A A; Shekhtman, L I; Telnov, V I
For viewing micro-calcifications smaller than 100 mu m investigation of image formation in mammography shows that a significant dose to the patient is imperative. We propose a novel one-dimensional Multi- electrode Ionisation Chamber (MIC), with high spatial resolution, and lowered doses. In this work, first results from a prototype are presented. High spatial resolution is demonstrated working with Xe mixture at high pressure. An addition of a Gas Electron Multiplier (GEM) allowed an improvement in sensitivity up to almost single- photon level. (8 refs).
Artificial neural networks were used in the diagnosis of chronic liver disease based on liver scintiscanning. One hundred and thirty-seven patients with chronic liver disease (12 with chronic persistent hepatitis, 39 with chronic aggressive hepatitis, and 86 with cirrhosis) and 25 healthy controls were studied. Sixty-five subjects (10 healthy controls, 20 patients with chronic hepatitis, and 35 patients with cirrhosis of the liver) were used in the establishment of a neural network. Liver scintiscans were taken starting 20 min after the intravenous injection of 111 MBq of Tc-99m-phytate. The neural network was used to evaluate five items judged from information on liver scintiscans: the ratio of the sizes of the left and right lobes, splenomegaly, radioactivity in the bone marrow, deformity of the liver and distribution of radioactivity in the liver. The neural network was designed to distinguish between three liver conditions (healthy liver, chronic hepatitis and cirrhosis) on the basis of these five items. The diagnostic accuracy with the neural network was 86% for patients with chronic hepatitis and 93% for patients with cirrhosis. With conventional scoring, the accuracy was 77% for patients with chronic hepatitis and 87% for patients with cirrhosis. Our findings suggest that artificial neural networks may be useful for the diagnosis of chronic liver diseases from liver scintiscans. (author)
Hindriks, Rikkert; Arsiwalla, Xerxes D; Panagiotaropoulos, Theofanis; Besserve, Michel; Verschure, Paul F M J; Logothetis, Nikos K; Deco, Gustavo
Multi-electrode recordings of local field potentials (LFPs) provide the opportunity to investigate the spatiotemporal organization of neural activity on the scale of several millimeters. In particular, the phases of oscillatory LFPs allow studying the coordination of neural oscillations in time and space and to tie it to cognitive processing. Given the computational roles of LFP phases, it is important to know how they relate to the phases of the underlying current source densities (CSDs) that generate them. Although CSDs and LFPs are distinct physical quantities, they are often (implicitly) identified when interpreting experimental observations. That this identification is problematic is clear from the fact that LFP phases change when switching to different electrode montages, while the underlying CSD phases remain unchanged. In this study we use a volume-conductor model to characterize discrepancies between LFP and CSD phase-patterns, to identify the contributing factors, and to assess the effect of different electrode montages. Although we focus on cortical LFPs recorded with two-dimensional (Utah) arrays, our findings are also relevant for other electrode configurations. We found that the main factors that determine the discrepancy between CSD and LFP phase-patterns are the frequency of the neural oscillations and the extent to which the laminar CSD profile is balanced. Furthermore, the presence of laminar phase-differences in cortical oscillations, as commonly observed in experiments, precludes identifying LFP phases with those of the CSD oscillations at a given cortical depth. This observation potentially complicates the interpretation of spike-LFP coherence and spike-triggered LFP averages. With respect to reference strategies, we found that the average-reference montage leads to larger discrepancies between LFP and CSD phases as compared with the referential montage, while the Laplacian montage reduces these discrepancies. We therefore advice to conduct
Cell growth characterization during culturing is an important issue in a variety of biomedical applications. In this study an electrical bioimpedance spectroscopy-based multi-electrode culture monitoring system was developed to characterize cell growth. A PC12 cell line was cultured for the cell growth study. The bioimpedance variations for PC12 cell growth within the initial 12 h were measured over a range between 1 kHz and 4 MHz at three different medium concentrations. Within this frequency range, the largest bioimpedance value was 1.9 times the smallest bioimpedance value. The phase angle decreased over the range from 1 to 10 kHz when cells were growing. Then, the phase angle approached a constant over the frequency range between 10 kHz and 2 MHz. Thereafter, the phase angle increased rapidly from 20 to 52 degrees during cell culturing between 8 and 12 h at 4 MHz. The maximum cell number after culturing for 12 h increased by 25.8% for the control sites with poly-D-lysine (PDL) pastes. For the normal growth factor, the cell number increased up to 4.78 times from 8 to 12 h, but only 0.96 and 1.60 times for the other two medium growth factors. The correlation coefficients between impedance and cell number were 0.868 (coating with PDL), and 0.836 (without PDL) for the normal concentration medium. Thus, impedance may be used as an index for cell growth characterization. (paper)
Santos, F J; Santos, M S
A computer-actuated switch was built to control, simultaneously, two automatic titration assemblies each consisting of an electrode pair and a burette, and using only one measuring device. This switch is modular, simple and versatile allowing easy adaptation and expansion; apart from its application in multiple-titration systems, this device can also be used for standard addition analysis and multi-component analysis using ion-selective electrodes (ISE). The repeatability as well as the accuracy of the measurements made with this switch were ensured using high-quality relays, and very high electrical insulation, attained through the use of two separate printed circuit boards (pcb) of good quality and careful design of these pcbs. This low-cost multi-electrode switch is controlled through the parallel port of a PC that collects the data via an inexpensive 12-bit ADC board (8-bit ISA type), and is easily programmable in any high-level language. This type of device allows the collection of a large amount of data in relatively short periods, which can be analysed later allowing the choice of the best compromise of time versus accuracy for the study of any particular system. PMID:18924850
Lu, Yi-Yu; Huang, Ji-Jer; Huang, Yu-Jie; Cheng, Kuo-Sheng
Cell growth characterization during culturing is an important issue in a variety of biomedical applications. In this study an electrical bioimpedance spectroscopy-based multi-electrode culture monitoring system was developed to characterize cell growth. A PC12 cell line was cultured for the cell growth study. The bioimpedance variations for PC12 cell growth within the initial 12 h were measured over a range between 1 kHz and 4 MHz at three different medium concentrations. Within this frequency range, the largest bioimpedance value was 1.9 times the smallest bioimpedance value. The phase angle decreased over the range from 1 to 10 kHz when cells were growing. Then, the phase angle approached a constant over the frequency range between 10 kHz and 2 MHz. Thereafter, the phase angle increased rapidly from 20 to 52 degrees during cell culturing between 8 and 12 h at 4 MHz. The maximum cell number after culturing for 12 h increased by 25.8% for the control sites with poly-D-lysine (PDL) pastes. For the normal growth factor, the cell number increased up to 4.78 times from 8 to 12 h, but only 0.96 and 1.60 times for the other two medium growth factors. The correlation coefficients between impedance and cell number were 0.868 (coating with PDL), and 0.836 (without PDL) for the normal concentration medium. Thus, impedance may be used as an index for cell growth characterization.
Frankel, Mitchell A; Dowden, Brett R; Mathews, V John; Normann, Richard A; Clark, Gregory A; Meek, Sanford G
Although asynchronous intrafascicular multi-electrode stimulation (IFMS) can evoke fatigue-resistant muscle force, a priori determination of the necessary stimulation parameters for precise force production is not possible. This paper presents a proportionally-modulated, multiple-input single-output (MISO) controller that was designed and experimentally validated for real-time, closed-loop force-feedback control of asynchronous IFMS. Experiments were conducted on anesthetized felines with a Utah Slanted Electrode Array implanted in the sciatic nerve, either acutely or chronically ( n = 1 for each). Isometric forces were evoked in plantar-flexor muscles, and target forces consisted of up to 7 min of step, sinusoidal, and more complex time-varying trajectories. The controller was successful in evoking steps in force with time-to-peak of less than 0.45 s, steady-state ripple of less than 7% of the mean steady-state force, and near-zero steady-state error even in the presence of muscle fatigue, but with transient overshoot of near 20%. The controller was also successful in evoking target sinusoidal and complex time-varying force trajectories with amplitude error of less than 0.5 N and time delay of approximately 300 ms. This MISO control strategy can potentially be used to develop closed-loop asynchronous IFMS controllers for a wide variety of multi-electrode stimulation applications to restore lost motor function. PMID:21385670
Schuettler, Martin; Donaldson, Nick; Seetohul, Vipin; Taylor, John
Objective. We investigate the ability of the method of velocity selective recording (VSR) to determine the fibre types that contribute to a compound action potential (CAP) propagating along a peripheral nerve. Real-time identification of the active fibre types by determining the direction of action potential propagation (afferent or efferent) and velocity might allow future neural prostheses to make better use of biological sensor signals and provide a new and simple tool for use in fundamental neuroscience. Approach. Fibre activity was recorded from explanted Xenopus Laevis frog sciatic nerve using a single multi-electrode cuff that records whole nerve activity with 11 equidistant ring-shaped electrodes. The recorded signals were amplified, delayed against each other with variable delay times, added and band-pass filtered. Finally, the resulting amplitudes were measured. Main Result. Our experiments showed that electrically evoked frog CAP was dominated by two fibre populations, propagating at around 20 and 40 m/s, respectively. The velocity selectivity, i.e. the ability of the system to discriminate between individual populations was increased by applying band-pass filtering. The method extracted an entire velocity spectrum from a 10 ms CAP recording sample in real time. Significance. Unlike the techniques introduced in the 1970s and subsequently, VSR requires only a single nerve cuff and does not require averaging to provide velocity spectral information. This makes it potentially suitable for the generation of highly-selective real-time control-signals for future neural prostheses. In our study, electrically evoked CAPs were analysed and it remains to be proven whether the method can reliably classify physiological nerve traffic. The work presented here was carried out at the laboratories of the Implanted Devices Group, Department of Medical Physics and Bioengineering, University College London, UK.
Agnella Izzo Matic
Full Text Available Infrared neural stimulation (INS has been proposed as a novel method for neural stimulation. In order for INS to translate to clinical use, which would involve the use of implanted devices over years or decades, the efficacy and safety of chronic INS needs to be determined. We examined a population of cats that were chronically implanted with an optical fiber to stimulate the cochlea with infrared radiation, the first known chronic application of INS. Through behavioral responses, the cats demonstrate that stimulation occurs and a perceptual event results. Long-term stimulation did not result in a change in the electrophysiological responses, either optically-evoked or acoustically-evoked. Spiral ganglion neuron counts and post implantation tissue growth, which was localized at the optical fiber, were similar in chronically stimulated and sham implanted cochleae. Results from chronic INS experiments in the cat cochlea support future work toward INS-based neuroprostheses for humans.
Poulsen, Søren Erbs; Christensen, Steen; Rasmussen, Keld Rømer;
Preliminary geophysical and hydrogeological investigations indicate that multi-electrode profiling (MEP) can be used to monitor groundwater salinity on a coastal barrier where a shallow thin aquifer discharges to the North Sea. A monitoring system including five groups of piezometers and five MEP...
Shell, Brent; Faulk, Katelynn; Cunningham, J Thomas
Sleep apnea (SA) is increasing in prevalence and is commonly comorbid with hypertension. Chronic intermittent hypoxia is used to model the arterial hypoxemia seen in SA, and through this paradigm, the mechanisms that underlie SA-induced hypertension are becoming clear. Cyclic hypoxic exposure during sleep chronically stimulates the carotid chemoreflexes, inducing sensory long-term facilitation, and drives sympathetic outflow from the hindbrain. The elevated sympathetic tone drives hypertension and renal sympathetic activity to the kidneys resulting in increased plasma renin activity and eventually angiotensin II (Ang II) peripherally. Upon waking, when respiration is normalized, the sympathetic activity does not diminish. This is partially because of adaptations leading to overactivation of the hindbrain regions controlling sympathetic outflow such as the nucleus tractus solitarius (NTS), and rostral ventrolateral medulla (RVLM). The sustained sympathetic activity is also due to enhanced synaptic signaling from the forebrain through the paraventricular nucleus (PVN). During the waking hours, when the chemoreceptors are not exposed to hypoxia, the forebrain circumventricular organs (CVOs) are stimulated by peripherally circulating Ang II from the elevated plasma renin activity. The CVOs and median preoptic nucleus chronically activate the PVN due to the Ang II signaling. All together, this leads to elevated nocturnal mean arterial pressure (MAP) as a response to hypoxemia, as well as inappropriately elevated diurnal MAP in response to maladaptations. PMID:26838032
Atalay, Nilgun Simsir; Sahin, Fusun; ATALAY, Ali; Akkaya, Nuray
The aim of this prospective study was to evaluate the effects of neural therapy, and physical therapy on level of pain, disability, quality of life, and psychological status in patients with chronic low back pain. Patients admitted to the physical therapy and rehabilitation outpatient clinic with the complaint of low back pain of at least 3 months duration. Group 1 (n=27), physical therapy (PT, hotpack, ultrasound, TENS 15 sessions), group 2 (n=33), neural therapy (NT, 1:1 mixture of 20 mg/mL...
Shah, Kedar G.; Bennett, William J.; Pannu, Satinderpall S.
A high density percutaneous chronic connector, having first and second connector structures each having an array of magnets surrounding a mounting cavity. A first electrical feedthrough array is seated in the mounting cavity of the first connector structure and a second electrical feedthrough array is seated in the mounting cavity of the second connector structure, with a feedthrough interconnect matrix positioned between a top side of the first electrical feedthrough array and a bottom side of the second electrical feedthrough array to electrically connect the first electrical feedthrough array to the second electrical feedthrough array. The two arrays of magnets are arranged to attract in a first angular position which connects the first and second connector structures together and electrically connects the percutaneously connected device to the external electronics, and to repel in a second angular position to facilitate removal of the second connector structure from the first connector structure.
Ashu Bhasin; M V Padma Srivastava; Kumaran, Senthil S; Rohit Bhatia; Sujata Mohanty
Background: Recovery in stroke is mediated by neural plasticity. Neuro-restorative therapies improve recovery after stroke by promoting repair and function. Mirror neuron system (MNS) has been studied widely in humans in stroke and phantom sensations. Materials and Methods: Study subjects included 20 patients with chronic stroke and 10 healthy controls. Patients had clinical disease-severity scores, functional magnetic resonance imaging (fMRI) and diffuse tensor imaging (DTI) at baseline, 8 a...
Hattiangady, Bharathi; Shetty, Ashok K.
Neural stem cell (NSC) transplantation into the hippocampus could offer an alternative therapy to hippocampal resection in patients with drug-resistant chronic epilepsy, which afflicts ~30% of mesial temporal lobe epilepsy (TLE) cases. Multipotent, self-renewing NSCs could be expanded from multiple regions of the developing and adult brain, human embryonic stem cells (hESCs), induced pluripotent stem cells (iPSCs). However, to provide a comprehensive methodology involved in testing the effica...
Katsura, Mari; Cyou-Nakamine, Hiromasa; Zen, Qin; Zen, Yang; Nansai, Hiroko; Amagasa, Shota; Kanki, Yasuharu; Inoue, Tsuyoshi; Kaneki, Kiyomi; Taguchi, Akashi; Kobayashi, Mika; Kaji, Toshiyuki; Kodama, Tatsuhiko; Miyagawa, Kiyoshi; Wada, Youichiro; Akimitsu, Nobuyoshi; Sone, Hideko
The effects of chronic low-dose radiation on human health have not been well established. Recent studies have revealed that neural progenitor cells are present not only in the fetal brain but also in the adult brain. Since immature cells are generally more radiosensitive, here we investigated the effects of chronic low-dose radiation on cultured human neural progenitor cells (hNPCs) derived from embryonic stem cells. Radiation at low doses of 31, 124 and 496 mGy per 72 h was administered to hNPCs. The effects were estimated by gene expression profiling with microarray analysis as well as morphological analysis. Gene expression was dose-dependently changed by radiation. By thirty-one mGy of radiation, inflammatory pathways involving interferon signaling and cell junctions were altered. DNA repair and cell adhesion molecules were affected by 124 mGy of radiation while DNA synthesis, apoptosis, metabolism, and neural differentiation were all affected by 496 mGy of radiation. These in vitro results suggest that 496 mGy radiation affects the development of neuronal progenitor cells while altered gene expression was observed at a radiation dose lower than 100 mGy. This study would contribute to the elucidation of the clinical and subclinical phenotypes of impaired neuronal development induced by chronic low-dose radiation.
Martenson, Melissa E; Halawa, Omar I; Tonsfeldt, Karen J; Maxwell, Charlene A; Hammack, Nora; Mist, Scott D; Pennesi, Mark E; Bennett, Robert M; Mauer, Kim M; Jones, Kim D; Heinricher, Mary M
Patients with functional pain disorders often complain of generalized sensory hypersensitivity, finding sounds, smells, or even everyday light aversive. The neural basis for this aversion is unknown, but it cannot be attributed to a general increase in cortical sensory processing. Here, we quantified the threshold for aversion to light in patients with fibromyalgia, a pain disorder thought to reflect dysregulation of pain-modulating systems in the brain. These individuals expressed discomfort at light levels substantially lower than that of healthy control subjects. Complementary studies in lightly anesthetized rat demonstrated that a subset of identified pain-modulating neurons in the rostral ventromedial medulla unexpectedly responds to light. Approximately half of the pain-facilitating "ON-cells" and pain-inhibiting "OFF-cells" sampled exhibited a change in firing with light exposure, shifting the system to a pronociceptive state with the activation of ON-cells and suppression of OFF-cell firing. The change in neuronal firing did not require a trigeminal or posterior thalamic relay, but it was blocked by the inactivation of the olivary pretectal nucleus. Light exposure also resulted in a measurable but modest decrease in the threshold for heat-evoked paw withdrawal, as would be expected with engagement of this pain-modulating circuitry. These data demonstrate integration of information about light intensity with somatic input at the level of single pain-modulating neurons in the brain stem of the rat under basal conditions. Taken together, our findings in rodents and humans provide a novel mechanism for abnormal photosensitivity and suggest that light has the potential to engage pain-modulating systems such that normally innocuous inputs are perceived as aversive or even painful. PMID:26785323
Chris R. Bowen
Full Text Available The adaptation of standard integrated circuit (IC technology as a transducer in cell-based biosensors in drug discovery pharmacology, neural interface systems and electrophysiology requires electrodes that are electrochemically stable, biocompatible and affordable. Unfortunately, the ubiquitous Complementary Metal Oxide Semiconductor (CMOS IC technology does not meet the first of these requirements. For devices intended only for research, modification of CMOS by post-processing using cleanroom facilities has been achieved. However, to enable adoption of CMOS as a basis for commercial biosensors, the economies of scale of CMOS fabrication must be maintained by using only low-cost post-processing techniques. This review highlights the methodologies employed in cell-based biosensor design where CMOS-based integrated circuits (ICs form an integral part of the transducer system. Particular emphasis will be placed on the application of multi-electrode arrays for in vitro neuroscience applications. Identifying suitable IC packaging methods presents further significant challenges when considering specific applications. The various challenges and difficulties are reviewed and some potential solutions are presented.
Zappaterra, Mauro; Jim, Lysander; Pangarkar, Sanjog
Chronic pain is often managed using a multidisciplinary, biopsychosocial approach. Interventions targeting the biological, psychological, and social aspects of both the patient and the pain have been demonstrated to provide objective and subjective improvement in chronic pain symptoms. The mechanism by which pain attenuation occurs after these interventions remains to be elucidated. While there is a relatively large body of empirical literature suggesting that functional and structural changes in the peripheral and central nervous systems are key in the development and maintenance of chronic pain states, less is known about changes that take place in the nervous system as a whole after biopsychosocial interventions. Using as a model the unique case of Mr. S, a patient suffering with chronic pain for 22 years who experienced a complete resolution of pain after a lucid dream following 2 years of biopsychosocial treatments, we postulate that central nervous system (CNS) reorganization (i.e., neural plasticity) serves as a possible mechanism for the therapeutic benefit of multidisciplinary treatments, and may set a neural framework for healing, in this case via a lucid dream. PMID:24398162
Jianjun NIU; Xiaopei ZHANG; Lizhi DU
Multi-electrodes Resistivity Imaging Survey (MRIS) is an array method of electrical survey. In practice how to choose a reasonable array is the key to get reliable survey results. Based on four methods of MRIS such as Wenner, Schlumberger, Pole-pole and Dipole-dipole the authors established the model, by studying the result of the forward numerical simulation modeling and inverse modeling, and analyzed the differences among the different forms of detection devices.
Rieger, R; Taylor, J; Comi, E; Donaldson, N; Russold, M; Mahony, C M O; McLaughlin, J A; McAdams, E; Demosthenous, A; Jarvis, J C
Information extracted from whole-nerve electroneurograms, recorded using electrode cuffs, can provide signals to neuroprostheses. However, the amount of information that can be extracted from a single tripole is limited. This communication demonstrates how previously unavailable information about the direction of action potential propagation and velocity can be obtained using a multi-electrode cuff and that the arrangement acts as a velocity-selective filter. Results from in vitro experiments on frog nerves are presented. PMID:15234689
Alsalman, Ola; Ost, Jan; Vanspauwen, Robby; Blaivie, Catherine; De Ridder, Dirk; Vanneste, Sven
Vestibular signals are of significant importance for variable functions including gaze stabilization, spatial perception, navigation, cognition, and bodily self-consciousness. The vestibular network governs functions that might be impaired in patients affected with vestibular dysfunction. It is currently unclear how different brain regions/networks process vestibular information and integrate the information into a unified spatial percept related to somatosensory awareness and whether people with recurrent balance complaints have a neural signature as a trait affecting their development of chronic symptoms of vertigo. Pivotal evidence points to a vestibular-related brain network in humans that is widely distributed in nature. By using resting state source localized electroencephalography in non-vertiginous state, electrophysiological changes in activity and functional connectivity of 23 patients with balance complaints where chronic symptoms of vertigo and dizziness are among the most common reported complaints are analyzed and compared to healthy subjects. The analyses showed increased alpha2 activity within the posterior cingulate cortex and the precuneues/cuneus and reduced beta3 and gamma activity within the pregenual and subgenual anterior cingulate cortex for the subjects with balance complaints. These electrophysiological variations were correlated with reported chronic symptoms of vertigo intensity. A region of interest analysis found reduced functional connectivity for gamma activity within the vestibular cortex, precuneus, frontal eye field, intra-parietal sulcus, orbitofrontal cortex, and the dorsal anterior cingulate cortex. In addition, there was a positive correlation between chronic symptoms of vertigo intensity and increased alpha-gamma nesting in the left frontal eye field. When compared to healthy subjects, there is evidence of electrophysiological changes in the brain of patients with balance complaints even outside chronic symptoms of vertigo
Full Text Available Vestibular signals are of significant importance for variable functions including gaze stabilization, spatial perception, navigation, cognition, and bodily self-consciousness. The vestibular network governs functions that might be impaired in patients affected with vestibular dysfunction. It is currently unclear how different brain regions/networks process vestibular information and integrate the information into a unified spatial percept related to somatosensory awareness and whether people with recurrent balance complaints have a neural signature as a trait affecting their development of chronic symptoms of vertigo. Pivotal evidence points to a vestibular-related brain network in humans that is widely distributed in nature. By using resting state source localized electroencephalography in non-vertiginous state, electrophysiological changes in activity and functional connectivity of 23 patients with balance complaints where chronic symptoms of vertigo and dizziness are among the most common reported complaints are analyzed and compared to healthy subjects. The analyses showed increased alpha2 activity within the posterior cingulate cortex and the precuneues/cuneus and reduced beta3 and gamma activity within the pregenual and subgenual anterior cingulate cortex for the subjects with balance complaints. These electrophysiological variations were correlated with reported chronic symptoms of vertigo intensity. A region of interest analysis found reduced functional connectivity for gamma activity within the vestibular cortex, precuneus, frontal eye field, intra-parietal sulcus, orbitofrontal cortex, and the dorsal anterior cingulate cortex. In addition, there was a positive correlation between chronic symptoms of vertigo intensity and increased alpha-gamma nesting in the left frontal eye field. When compared to healthy subjects, there is evidence of electrophysiological changes in the brain of patients with balance complaints even outside chronic
Tauskela, Joseph S; Comas, Tanya; Hewitt, Melissa; Aylsworth, Amy; Zhao, Xigeng; Martina, Marzia; Costain, Willard J
Activation of cannabinoid receptor 1 (CB1) inhibits synaptic transmission in hippocampal neurons. The goal of this study was to evaluate the ability of benchmark and emerging synthetic cannabinoids to suppress neuronal activity in vitro using two complementary techniques, Ca(2+) spiking and multi-electrode arrays (MEAs). Neuron culture and fluorescence imaging conditions were extensively optimized to provide maximum sensitivity for detection of suppression of neural activity by cannabinoids. The neuronal Ca(2+) spiking frequency was significantly suppressed within 10min by the prototypic aminoalkylindole cannabinoid, WIN 55,212-2 (10µM). Suppression by WIN 55,212-2 was not improved by pharmacological intervention with signaling pathways known to interfere with CB1 signaling. The naphthoylindole CB1 agonist, JWH-018 suppressed Ca(2+) spiking at a lower concentration (2.5µM), and the CB1 antagonist rimonabant (5µM), reversed this suppression. In the MEA assay, the ability of synthetic CB1 agonists to suppress spontaneous electrical activity of hippocampal neurons was evaluated over 80min sessions. All benchmark (WIN 55,212-2, HU-210, CP 55,940 and JWH-018) and emerging synthetic cannabinoids (XLR-11, JWH-250, 5F-PB-22, AB-PINACA and MAM-2201) suppressed neural activity at a concentration of 10µM; furthermore, several of these compounds also significantly suppressed activity at 1µM concentrations. Rimonabant partially reversed spiking suppression of 5F-PB-22 and, to a lesser extent, of MAM-2201, supporting CB1-mediated involvement, although the inactive WIN 55,212-3 also partially suppressed activity. Taken together, synthetic cannabinoid CB1-mediated suppression of neuronal activity was detected using Ca(2+) spiking and MEAs. PMID:27262380
Pardey, Margery C.; Kumar, Natasha N.; Goodchild, Ann K.; Clemens, Kelly J.; Homewood, Judi; Cornish, Jennifer L.
The diagnosis of Attention Deficit Hyperactivity Disorder (ADHD) often results in chronic treatment with psychostimulants such as methylphenidate (MPH, Ritalin®). With increases in misdiagnosis of ADHD, children may be inappropriately exposed to chronic psychostimulant treatment during development. The aim of this study was to assess the effect of chronic Ritalin treatment on cognitive and neural development in misdiagnosed “normal” (Wistar Kyoto, WKY) rats and in Spontaneously Hypertensive R...
Roshani, Amir; Erfanian, Abbas
Objective. An important issue in restoring motor function through intraspinal microstimulation (ISMS) is the motor control. To provide a physiologically plausible motor control using ISMS, it should be able to control the individual motor unit which is the lowest functional unit of motor control. By focal stimulation only a small group of motor neurons (MNs) within a motor pool can be activated. Different groups of MNs within a motor pool can potentially be activated without involving adjacent motor pools by local stimulation of different parts of a motor pool via microelectrode array implanted into a motor pool. However, since the system has multiple inputs with single output during multi-electrode ISMS, it poses a challenge to movement control. In this paper, we proposed a modular robust control strategy for movement control, whereas multi-electrode array is implanted into each motor activation pool of a muscle. Approach. The controller was based on the combination of proportional-integral-derivative and adaptive fuzzy sliding mode control. The global stability of the controller was guaranteed. Main results. The results of the experiments on rat models showed that the multi-electrode control can provide a more robust control and accurate tracking performance than a single-electrode control. The control output can be pulse amplitude (pulse amplitude modulation, PAM) or pulse width (pulse width modulation, PWM) of the stimulation signal. The results demonstrated that the controller with PAM provided faster convergence rate and better tracking performance than the controller with PWM. Significance. This work represents a promising control approach to the restoring motor functions using ISMS. The proposed controller requires no prior knowledge about the dynamics of the system to be controlled and no offline learning phase. The proposed control design is modular in the sense that each motor pool has an independent controller and each controller is able to control ISMS
Todd, Ann E; Goupell, Matthew J; Litovsky, Ruth Y
Cochlear implants (CIs) provide children with access to speech information from a young age. Despite bilateral cochlear implantation becoming common, use of spatial cues in free field is smaller than in normal-hearing children. Clinically fit CIs are not synchronized across the ears; thus binaural experiments must utilize research processors that can control binaural cues with precision. Research to date has used single pairs of electrodes, which is insufficient for representing speech. Little is known about how children with bilateral CIs process binaural information with multi-electrode stimulation. Toward the goal of improving binaural unmasking of speech, this study evaluated binaural unmasking with multi- and single-electrode stimulation. Results showed that performance with multi-electrode stimulation was similar to the best performance with single-electrode stimulation. This was similar to the pattern of performance shown by normal-hearing adults when presented an acoustic CI simulation. Diotic and dichotic signal detection thresholds of the children with CIs were similar to those of normal-hearing children listening to a CI simulation. The magnitude of binaural unmasking was not related to whether the children with CIs had good interaural time difference sensitivity. Results support the potential for benefits from binaural hearing and speech unmasking in children with bilateral CIs. PMID:27475132
Donaldson, N; Rieger, R; Schuettler, M; Taylor, J
Using a multi-electrode nerve-signal recording cuff and a method of signal processing described previously, activity in axons with different propagation velocities can be distinguished, and the relative amplitude of the small-fibre signals increased. This paper is, largely, an analysis of the selectivity and noise of this system though impedance measurements from an actual cuff are included. The signal processor includes narrow band-pass filters. It is shown that the selectivity and noise both increase with the centre frequencies of these filters. A convenient approach is to make the filter frequencies inversely related to the artificial time delays so that the filter 'Q's are approximately constant and the noise densities are equal for all velocity filters. Numerical calculations, using formulae for this system and for the conventional tripole, based on a fixed cuff size and tissue resistivity, find the number of action potentials per second that must pass through the cuff so that the signal power equals the noise power. For slow fibres (20 m/s), the rate is 14 times lower for the multi-electrode cuff than the tripole, a significant advantage for recording from these fibres. PMID:18696136
Prasad, Abhishek; Xue, Qing-Shan; Sankar, Viswanath; Nishida, Toshikazu; Shaw, Gerry; Streit, Wolfgang J.; Sanchez, Justin C.
For nearly 55 years, tungsten microwires have been widely used in neurophysiological experiments in animal models to chronically record neuronal activity. While tungsten microwires initially provide stable recordings, their inability to reliably record high-quality neural signals for tens of years has limited their efficacy for neuroprosthetic applications in humans. Comprehensive understanding of the mechanisms of electrode performance and failure is necessary for developing next generation neural interfaces for humans. In this study, we evaluated the abiotic (electrophysiology, impedance, electrode morphology) and biotic (microglial reactivity, blood-brain barrier disruption, biochemical markers of axonal injury) effects of 16-channel, 50 µm diameter, polyimide insulated tungsten microwires array for implant durations that ranged from acute to up to 9 months in 25 rats. Daily electrode impedance spectroscopy, electrophysiological recordings, blood and cerebrospinal fluid (CSF) withdrawals, and histopathological analysis were performed to study the time-varying effects of chronic electrode implantation. Structural changes at the electrode recording site were observed as early as within 2-3 h of electrode insertion. Abiotic analysis indicated the first 2-3 weeks following surgery was the most dynamic period in the chronic electrode lifetime as there were greater variations in the electrode impedance, functional electrode performance, and the structural changes occurring at the electrode recording tips. Electrode recording site deterioration continued for the long-term chronic animals as insulation damage occurred and recording surface became more recessed over time. In general, electrode impedance and functional performance had smaller daily variations combined with reduced electrode recording site changes during the chronic phase. Histopathological studies were focused largely on characterizing microglial cell responses to electrode implantation. We found that
Hattiangady, Bharathi; Shetty, Ashok K.
Neural stem cell (NSC) transplantation into the hippocampus could offer an alternative therapy to hippocampal resection in patients with drug-resistant chronic epilepsy, which afflicts ~30% of mesial temporal lobe epilepsy (TLE) cases. Multipotent, self-renewing NSCs could be expanded from multiple regions of the developing and adult brain, human embryonic stem cells (hESCs), induced pluripotent stem cells (iPSCs). However, to provide a comprehensive methodology involved in testing the efficacy of transplantation of NSCs in a rat model of chronic TLE, NSCs derived from the embryonic medial ganglionic eminence (MGE) are taken as an example in this article. The topics comprise description of the required materials, reagents and equipment, and protocols for expanding MGE-NSCs in culture, generating chronically epileptic rats, the intrahippocampal grafting, the post-grafting evaluation of the effects of NSC grafts on spontaneous recurrent seizures and cognitive impairments, analyses of the yield and the fate of graft-derived cells, and the effects of NSC grafts on the host hippocampus. PMID:21913169
彭亚鸽; 田海龙; 马玉军
阵列电极是组装阵列电化学生物传感器的基础电极，它的设计和制作是成功构建阵列电化学生物传感器的基础。文章重点介绍了四种制作阵列电极的方法，简单探讨了阵列电极发展存在的问题。%Multi-electrode array is a basis for design and fabrication of electrochemical biosensor array. Four methods of multi-electrode array fabricated arc reviewed extensively. The current problems of multi-electrode array are briefly discussed.
Full Text Available Background: Recovery in stroke is mediated by neural plasticity. Neuro-restorative therapies improve recovery after stroke by promoting repair and function. Mirror neuron system (MNS has been studied widely in humans in stroke and phantom sensations. Materials and Methods: Study subjects included 20 patients with chronic stroke and 10 healthy controls. Patients had clinical disease-severity scores, functional magnetic resonance imaging (fMRI and diffuse tensor imaging (DTI at baseline, 8 and at 24 weeks. Block design with alternate baseline and activation cycles was used with a total of 90 whole brain echo planar imaging (EPI measurements (timed repetition (TR = 4520 ms, timed echo (TE = 44 ms, slices = 31, slice thickness = 4 mm, EPI factor 127, matrix = 128 × 128, FOV = 230 mm. Whole brain T1-weighted images were acquired using 3D sequence (MPRage with 120 contiguous slices of 1.0 mm thickness. The mirror therapy was aimed via laptop system integrated with web camera, mirroring the movement of the unaffected hand. This therapy was administered for 5 days in a week for 60-90 min for 8 weeks. Results: All the patients showed statistical significant improvement in Fugl Meyer and modified Barthel Index (P < 0.05 whereas the change in Medical Research Council (MRC power grade was not significant post-therapy (8 weeks. There was an increase in the laterality index (LI of ipsilesional BA 4 and BA 6 at 8 weeks exhibiting recruitment and focusing principles of neural plasticity. Conclusions: Mirror therapy simulated the "action-observation" hypothesis exhibiting recovery in patients with chronic stroke. Therapy induced cortical reorganization was also observed from our study.
Full Text Available In the study of population coding in neurobiological systems, tracking unit identity may be critical to assess possible changes in the coding properties of neuronal constituents over prolonged periods of time. Ensuring unit stability is even more critical for reliable neural decoding of motor variables in intra-cortically controlled brain-machine interfaces (BMIs. Variability in intrinsic spike patterns, tuning characteristics, and single-unit identity over chronic use is a major challenge to maintaining this stability, requiring frequent daily calibration of neural decoders in BMI sessions by an experienced human operator. Here, we report on a unit-stability tracking algorithm that efficiently and autonomously identifies putative single-units that are stable across many sessions using a relatively short duration recording interval at the start of each session. The algorithm first builds a database of features extracted from units' average spike waveforms and firing patterns across many days of recording. It then uses these features to decide whether spike occurrences on the same channel on one day belong to the same unit recorded on another day or not. We assessed the overall performance of the algorithm for different choices of features and classifiers trained using human expert judgment, and quantified it as a function of accuracy and execution time. Overall, we found a trade-off between accuracy and execution time with increasing data volumes from chronically implanted rhesus macaques, with an average of 12 seconds processing time per channel at ~90% classification accuracy. Furthermore, 77% of the resulting putative single-units matched those tracked by human experts. These results demonstrate that over the span of a few months of recordings, automated unit tracking can be performed with high accuracy and used to streamline the calibration phase during BMI sessions.
Tobler, Philippe N; Preller, Katrin H; Campbell-Meiklejohn, Daniel K; Kirschner, Matthias; Kraehenmann, Rainer; Stämpfli, Philipp; Herdener, Marcus; Seifritz, Erich; Quednow, Boris B
Changed reward functions have been proposed as a core feature of stimulant addiction, typically observed as reduced neural responses to non-drug-related rewards. However, it was unclear yet how specific this deficit is for different types of non-drug rewards arising from social and non-social reinforcements. We used functional neuroimaging in cocaine users to investigate explicit social reward as modeled by agreement of music preferences with music experts. In addition, we investigated non-social reward as modeled by winning desired music pieces. The study included 17 chronic cocaine users and 17 matched stimulant-naive healthy controls. Cocaine users, compared with controls, showed blunted neural responses to both social and non-social reward. Activation differences were located in the ventromedial prefrontal cortex overlapping for both reward types and, thus, suggesting a non-specific deficit in the processing of non-drug rewards. Interestingly, in the posterior lateral orbitofrontal cortex, social reward responses of cocaine users decreased with the degree to which they were influenced by social feedback from the experts, a response pattern that was opposite to that observed in healthy controls. The present results suggest that cocaine users likely suffer from a generalized impairment in value representation as well as from an aberrant processing of social feedback. PMID:26969866
Objective: To determine the effectiveness of slump neural mobilization technique compared with lumber stabilization exercise (LSE) and shortwave diathermy (SWD) in the physical therapy management of chronic radicular low back pain (CRLBP). Methodology: A sample of 40 patients with CRLBP was selected and randomly placed into two groups A and B. 22 patients were treated with slump neural mobilization technique (SNMT), lumbar stabilization exercise (LSE) and Short wave diathermy (SWD), while 18 patient of group B were treated with LSE and SWD. All the patients were assessed by four point pain scale and Oswestry disability index (ODI) at the baseline and at the completion of three weeks at 5 days per week and 30 minutes single session per day. The data was collected on specially designed Performa and was analyzed by SPSS and paired t test was applied to determine the probability value at 95 % level of significance. Results: Both groups demonstrated significant improvement in pain score and ODI score, although improvement was more significant in group A (p<0.001 for both pain and ODI score) as compared to group B (p=0.003 for pain score and 0.163 for ODI score).table-I-III) Conclusion: It is concluded that SNMTalong LSE and SWD improves pain and function more as compared with LSE and SWD alone during the physical therapy management of CRLBP. (author)
GuoXiujun; HuangXiaoyu; JiaYonggang
Multi-electrode Electric Method (MEM) is an effective tool in landslide survey. A suitable working scheme in-situ and the corresponding data interpretation approach are the fundamentals for obtaining believable results. Finite element 2D forward modeling was conducted on four types of standard electric models; respectively named the homogeneous soil landside, bedding landside, sliderock landside, and beveling landside; under the utilizations of four different types of electrode arrays;respectively namely the Wenner array, Schlumberger array, dipole-dipole array and pole-pole array.The capacities of different arrays and the resistivity responses of different types of sliding faces were determined based on the resultant standard electric profiles. An innovative data processing procedure called the ratio parameter method was proposed for locating sliding faces under complex geological conditions. A series of case histories for landside survey were given.
Mukherjee, Biswarup; George, Boby; Sivaprakasam, Mohanasankar
Local anesthesia administration prior to ophthalmic surgery involves inserting a syringe needle into a confined intraorbital space at the proper position, angle and depth. During this procedure ocular structures must remain unhurt and systemic complications must be avoided while achieving quick akinesia and analgesia. Animal cadavers do not emulate human anatomy accurately and human subject based training entails risk to the patient. Therefore, a training system that closely replicates the human ocular and orbital anatomy and provides the trainee with real-time feedback on the safety and effectiveness of the block administered would help reduce risks involved with real life procedures. This paper presents an anatomically accurate, rapid-prototyped manikin based training system for ophthalmic anesthetic blocks. The depth of penetration of the needle, the proximity of the needle to extraocular muscles and the touch of the needle to the muscles or optic nerve is detected by a multi-electrode electric field/capacitive sensing system. The eye structure of the manikin does not have any electrical connections to it, rendering it replaceable, thus, enabling the emulation of anatomical variations due to pathologies of the eye. A virtual instrument measures and computes the position of the needle and displays it to the trainee through an intuitive GUI with a 3D display of the orbital anatomy. The proposed capacitive sensing scheme has been validated by tests performed on a prototype system, thus demonstrating its usefulness for practical training purposes. PMID:25361511
Furuya, N.; Sakamoto, K.; Kanai, H.
It is well known that metabolic syndrome can induce myocardial infarction and cerebral infarction. So, it is very important to measure the visceral fat volume. In the electric impedance method, information in the vicinity of the electrodes is strongly reflected. Therefore, we propose a new multi-electrode arrangement method based on the impedance sensitivity theorem to measure the visceral fat volume. This electrode arrangement is designed to enable high impedance sensitivity in the visceral and subcutaneous fat regions. Currents are simultaneously applied to several current electrodes on the body surface, and one voltage electrode pair is arranged on the body surface near the organ of interest to obtain the visceral fat information and another voltage electrode pair is arranged on the body surface near the current electrodes to obtain the subcutaneous fat information. A simulation study indicates that by weighting the impedance sensitivity distribution, as in our method, a high-sensitivity region in the visceral and the subcutaneous fat regions can be formed. In addition, it was confirmed that the visceral fat volume can be estimated by the measured impedance data.
Veerabhadrappa, R; Lim, C P; Nguyen, T T; Berk, M; Tye, S J; Monaghan, P; Nahavandi, S; Bhatti, A
Extracellular data analysis has become a quintessential method for understanding the neurophysiological responses to stimuli. This demands stringent techniques owing to the complicated nature of the recording environment. In this paper, we highlight the challenges in extracellular multi-electrode recording and data analysis as well as the limitations pertaining to some of the currently employed methodologies. To address some of the challenges, we present a unified algorithm in the form of selective sorting. Selective sorting is modelled around hypothesized generative model, which addresses the natural phenomena of spikes triggered by an intricate neuronal population. The algorithm incorporates Cepstrum of Bispectrum, ad hoc clustering algorithms, wavelet transforms, least square and correlation concepts which strategically tailors a sequence to characterize and form distinctive clusters. Additionally, we demonstrate the influence of noise modelled wavelets to sort overlapping spikes. The algorithm is evaluated using both raw and synthesized data sets with different levels of complexity and the performances are tabulated for comparison using widely accepted qualitative and quantitative indicators. PMID:27339770
Gordon, R.; Zorkova, V.; Min, M.; Rätsep, I.
We describe here an imaging system that uses bioimpedance spectroscopy with multi-electrode array to indicate the state of muscle flap regions under the array. The system is able to differentiate between different health states in the tissue and give early information about the location and size of ischemic sub-regions. The array will be 4*8 electrodes with the spacing of 5mm between the electrodes (the number of electrodes and the spacing may vary). The electrodes are minimally invasive short stainless steel needles, that penetrate 0.3 mm into the tissue with the goal of achieving a wet electric contact. We combine 32 configurations of 4-electrode multi-frequency impedance measurements to derive a health-state map for the transplanted flap. The imaging method is tested on a model consisting of 2 tissues and FEM software (Finite Element Method -COMSOL Multiphysics based) is used to conduct the measurements virtually. Dedicated multichannel bioimpedance measurement equipment has already been developed and tested, that cover the frequency range from 100 Hz to 1 MHz.
Picollo, F; Bernardi, E; Plaitano, M; Franchino, C; Gosso, S; Pasquarelli, A; Carbone, E; Olivero, P; Carabelli, V
We report on the ion beam fabrication of all-carbon multi electrode arrays (MEAs) based on 16 graphitic micro-channels embedded in single-crystal diamond (SCD) substrates. The fabricated SCD-MEAs are systematically employed for the in vitro simultaneous amperometric detection of the secretory activity from populations of chromaffin cells, demonstrating a new sensing approach with respect to standard techniques. The biochemical stability and biocompatibility of the SCD-based device combined with the parallel recording of multi-electrodes array allow: i) a significant time saving in data collection during drug screening and/or pharmacological tests over a large number of cells, ii) the possibility of comparing altered cell functionality among cell populations, and iii) the repeatition of acquisition runs over many cycles with a fully non-toxic and chemically robust bio-sensitive substrate.
Picollo, Federico; Battiato, Alfio; Bernardi, Ettore; Plaitano, Marilena; Franchino, Claudio; Gosso, Sara; Pasquarelli, Alberto; Carbone, Emilio; Olivero, Paolo; Carabelli, Valentina
We report on the ion beam fabrication of all-carbon multi electrode arrays (MEAs) based on 16 graphitic micro-channels embedded in single-crystal diamond (SCD) substrates. The fabricated SCD-MEAs are systematically employed for the in vitro simultaneous amperometric detection of the secretory activity from populations of chromaffin cells, demonstrating a new sensing approach with respect to standard techniques. The biochemical stability and biocompatibility of the SCD-based device combined with the parallel recording of multi-electrodes array allow: i) a significant time saving in data collection during drug screening and/or pharmacological tests over a large number of cells, ii) the possibility of comparing altered cell functionality among cell populations, and iii) the repeatition of acquisition runs over many cycles with a fully non-toxic and chemically robust bio-sensitive substrate.
Jennifer L. Cornish
Full Text Available The diagnosis of Attention Deficit Hyperactivity Disorder (ADHD often results in chronic treatment with psychostimulants such as methylphenidate (MPH, Ritalin®. With increases in misdiagnosis of ADHD, children may be inappropriately exposed to chronic psychostimulant treatment during development. The aim of this study was to assess the effect of chronic Ritalin treatment on cognitive and neural development in misdiagnosed “normal” (Wistar Kyoto, WKY rats and in Spontaneously Hypertensive Rats (SHR, a model of ADHD. Adolescent male animals were treated for four weeks with oral Ritalin® (2 × 2 mg/kg/day or distilled water (dH2O. The effect of chronic treatment on delayed reinforcement tasks (DRT and tyrosine hydroxylase immunoreactivity (TH-ir in the prefrontal cortex was assessed. Two weeks following chronic treatment, WKY rats previously exposed to MPH chose the delayed reinforcer significantly less than the dH2O treated controls in both the DRT and extinction task. MPH treatment did not significantly alter cognitive performance in the SHR. TH-ir in the infralimbic cortex was significantly altered by age and behavioural experience in WKY and SHR, however this effect was not evident in WKY rats treated with MPH. These results suggest that chronic treatment with MPH throughout adolescence in “normal” WKY rats increased impulsive choice and altered catecholamine development when compared to vehicle controls.
Cai, Yu; Sha, Shuang
This paper proposes a new carrier-interleaved orthogonal multi-electrode multi-carrier resistivity-measurement tool used in a cylindrical borehole environment during oil-based mud drilling processes. The new tool is an orthogonal frequency division multiplexing access-based contactless multi-measurand detection tool. The tool can measure formation resistivity in different azimuthal angles and elevational depths. It can measure many more measurands simultaneously in a specified bandwidth than the legacy frequency division multiplexing multi-measurand tool without a channel-select filter while avoiding inter-carrier interference. The paper also shows that formation resistivity is not sensitive to frequency in certain frequency bands. The average resistivity collected from N subcarriers can increase the measurement of the signal-to-noise ratio (SNR) by N times given no amplitude clipping in the current-injection electrode. If the clipping limit is taken into account, with the phase rotation of each single carrier, the amplitude peak-to-average ratio can be reduced by 3 times, and the SNR can achieve a 9/N times gain over the single-carrier system. The carrier-interleaving technique is also introduced to counter the carrier frequency offset (CFO) effect, where the CFO will cause inter-pad interference. A qualitative analysis and simulations demonstrate that block-interleaving performs better than tone-interleaving when coping with a large CFO. The theoretical analysis also suggests that increasing the subcarrier number can increase the measurement speed or enhance elevational resolution without sacrificing receiver performance. The complex orthogonal multi-pad multi-carrier resistivity logging tool, in which all subcarriers are complex signals, can provide a larger available subcarrier pool than other types of transceivers.
Hahnewald, Stefan; Tscherter, Anne; Marconi, Emanuele; Streit, Jürg; Widmer, Hans Rudolf; Garnham, Carolyn; Benav, Heval; Mueller, Marcus; Löwenheim, Hubert; Roccio, Marta; Senn, Pascal
Objective. Cochlear implants (CIs) have become the gold standard treatment for deafness. These neuroprosthetic devices feature a linear electrode array, surgically inserted into the cochlea, and function by directly stimulating the auditory neurons located within the spiral ganglion, bypassing lost or not-functioning hair cells. Despite their success, some limitations still remain, including poor frequency resolution and high-energy consumption. In both cases, the anatomical gap between the electrode array and the spiral ganglion neurons (SGNs) is believed to be an important limiting factor. The final goal of the study is to characterize response profiles of SGNs growing in intimate contact with an electrode array, in view of designing novel CI devices and stimulation protocols, featuring a gapless interface with auditory neurons. Approach. We have characterized SGN responses to extracellular stimulation using multi-electrode arrays (MEAs). This setup allows, in our view, to optimize in vitro many of the limiting interface aspects between CIs and SGNs. Main results. Early postnatal mouse SGN explants were analyzed after 6-18 days in culture. Different stimulation protocols were compared with the aim to lower the stimulation threshold and the energy needed to elicit a response. In the best case, a four-fold reduction of the energy was obtained by lengthening the biphasic stimulus from 40 μs to 160 μs. Similarly, quasi monophasic pulses were more effective than biphasic pulses and the insertion of an interphase gap moderately improved efficiency. Finally, the stimulation with an external electrode mounted on a micromanipulator showed that the energy needed to elicit a response could be reduced by a factor of five with decreasing its distance from 40 μm to 0 μm from the auditory neurons. Significance. This study is the first to show electrical activity of SGNs on MEAs. Our findings may help to improve stimulation by and to reduce energy consumption of CIs and
E Chandrasekhar; Deshmukh Ramesh; Trupti Gurav; T K Biswal
Multi-electrode resistivity imaging survey with 48 electrodes was carried out to assess the extent of salinity inland, in the shallow subsurface in Nellore district, Andhra Pradesh, in the Eastern Ghats Mobile Belt (EGMB) region. Resistivity data were recorded using Wenner–Schlumberger configuration at nine sites along a profile of about 55 km in length, laid perpendicular to the coast. An average spacing of 6 km is maintained between each site. Assessment of groundwater salinity in the study area was made by joint interpretation of the two-dimensional (2D) geoelectrical models of all the sites together with the geochemical analysis results of water samples and geology. At sites closer to the coast, 2D geoelectrical models of the subsurface indicate low resistivities (2–50 m) in the depth range from surface up to 15 m. Such low resistivities are due to the high salinity of the groundwater. Geochemical analysis results of water samples at six locations close to the electrical resistivity survey sites also suggest high salinity and high concentrations of total dissolved solids and other chemicals at sites closer to the coast. Away from the coast, the resistivities in the depth range from surface up to 15 m vary in the range of 50–150 m. Accordingly, the chemical analysis of water samples collected at these sites also showed relatively low levels of salinity and salt concentrations in them. However, away from the coast, the resistivities vary in the range of 150–1500 m in the depth range from 20–40 m. While the aquaculture and agriculture activities may contribute to high salinity at the sites closer to the coast, the presence of deep-seated paleochannels aiding in transporting seawater inland, and water–rock interactions are suspected to be the chief causes for notable salinity at places away from the coast at shallow depths. We opine that the high salinity at shallow depths, coupled with the deep-seated paleochannels transporting seawater, could pose
Sacré, Pierre; Sarma, Sridevi V.; Guan, Yun; Anderson, William S.
Chronic pain affects about 100 million adults in the US. Despite their great need, neuropharmacology and neurostimulation therapies for chronic pain have been associated with suboptimal efficacy and limited long-term success, as their mechanisms of action are unclear. Yet current computational models of pain transmission suffer from several limitations. In particular, dorsal column models do not include the fundamental underlying sensory activity traveling in these nerve fibers. We developed ...
Farrell, Mollee R.; SENGELAUB, DALE R.; Wellman, Cara L.
There are sex differences in the rates of many stress-sensitive psychological disorders such as post traumatic stress disorder (PTSD). As medial prefrontal cortex and amygdala are implicated in many of these disorders, understanding differential stress effects in these regions may shed light on the mechanisms underlying sex-dependent expression of disorders like depression and anxiety. Prefrontal cortex and amygdala are key regions in the neural circuitry underlying fear conditioning and exti...
McConnell, George C.; Rees, Howard D.; Levey, Allan I.; Gutekunst, Claire-Anne; Gross, Robert E.; Bellamkonda, Ravi V.
Prosthetic devices that are controlled by intracortical electrodes recording one's 'thoughts' are a reality today, and no longer merely in the realm of science fiction. However, widespread clinical use of implanted electrodes is hampered by a lack of reliability in chronic recordings, independent of the type of electrodes used. One major hypothesis has been that astroglial scar electrically impedes the electrodes. However, there is a temporal discrepancy between stabilization of scar's electrical properties and recording failure with recording failure lagging by 1 month. In this study, we test a possible explanation for this discrepancy: the hypothesis that chronic inflammation, due to the persistent presence of the electrode, causes a local neurodegenerative state in the immediate vicinity of the electrode. Through modulation of chronic inflammation via stab wound, electrode geometry and age-matched control, we found that after 16 weeks, animals with an increased level of chronic inflammation were associated with increased neuronal and dendritic, but not axonal, loss. We observed increased neuronal and dendritic loss 16 weeks after implantation compared to 8 weeks after implantation, suggesting that the local neurodegenerative state is progressive. After 16 weeks, we observed axonal pathology in the form of hyperphosphorylation of the protein tau in the immediate vicinity of the microelectrodes (as observed in Alzheimer's disease and other tauopathies). The results of this study suggest that a local, late onset neurodegenerative disease-like state surrounds the chronic electrodes and is a potential cause for chronic recording failure. These results also inform strategies to enhance our capability to attain reliable long-term recordings from implantable electrodes in the CNS.
Jeong, Du Won; Jung, Jongjin; Kim, Gook Hwa; Yang, Cheol-Soo; Kim, Ju Jin; Jung, Sang Don; Lee, Jeong-O.
In this work, Cath.a-differentiated (CAD) cells were used in place of primary neuronal cells to assess the performance of vertically aligned carbon nanotubes (VACNTs) multi-electrode arrays (MEA). To fabricate high-performance MEA, VACNTs were directly grown on graphene/Pt electrodes via plasma enhanced chemical deposition technique. Here, graphene served as an intermediate layer lowering contact resistance between VACNTs and Pt electrode. In order to lower the electrode impedance and to enhance the cell adhesion, VACNTs-MEAs were treated with UV-ozone for 20 min. Impedance of VACNTs electrode at 1 kHz frequency exhibits a reasonable value (110 kΩ) for extracellular signal recording, and the signal to noise ratio the is good enough to measure low signal amplitude (15.7). Spontaneous firing events from CAD cells were successfully measured with VACNTs MEAs that were also found to be surprisingly robust toward the biological interactions.
Mulder, A.A.W.; Balt, J.C.; Wijffels, M.C.; Wever, E.F.; Boersma, L.V.
AIMS: Recently, a multi-electrode catheter system using phased radiofrequency (RF) energy was developed specifically for atrial fibrillation (AF) ablation: the pulmonary vein ablation catheter (PVAC), the multi-array septal catheter (MASC), and the multi-array ablation catheter (MAAC). Initial resul
Rajan, Alexander T.; Boback, Jessica L.; Dammann, John F.; Tenore, Francesco V.; Wester, Brock A.; Otto, Kevin J.; Gaunt, Robert A.; Bensmaia, Sliman J.
Objective. One approach to conveying sensory feedback in neuroprostheses is to electrically stimulate sensory neurons in the cortex. For this approach to be viable, it is critical that intracortical microstimulation (ICMS) causes minimal damage to the brain. Here, we investigate the effects of chronic ICMS on the neuronal tissue across a variety of stimulation regimes in non-human primates. We also examine each animal’s ability to use their hand—the cortical representation of which is targeted by the ICMS—as a further assay of possible neuronal damage. Approach. We implanted electrode arrays in the primary somatosensory cortex of three Rhesus macaques and delivered ICMS four hours per day, five days per week, for six months. Multiple regimes of ICMS were delivered to investigate the effects of stimulation parameters on the tissue and behavior. Parameters included current amplitude (10-100 μA), pulse train duration (1, 5 s), and duty cycle (1/1, 1/3). We then performed a range of histopathological assays on tissue near the tips of both stimulated and unstimulated electrodes to assess the effects of chronic ICMS on the tissue and their dependence on stimulation parameters. Main results. While the implantation and residence of the arrays in the cortical tissue did cause significant damage, chronic ICMS had no detectable additional effect; furthermore, the animals exhibited no impairments in fine motor control. Significance. Chronic ICMS may be a viable means to convey sensory feedback in neuroprostheses as it does not cause significant damage to the stimulated tissue.
Tobler, Philippe N; Preller, Katrin H; Campbell-Meiklejohn, Daniel K;
-social reinforcements. We used functional neuroimaging in cocaine users to investigate explicit social reward as modeled by agreement of music preferences with music experts. In addition, we investigated non-social reward as modeled by winning desired music pieces. The study included 17 chronic cocaine users and 17...... the processing of non-drug rewards. Interestingly, in the posterior lateral orbitofrontal cortex, social reward responses of cocaine users decreased with the degree to which they were influenced by social feedback from the experts, a response pattern that was opposite to that observed in healthy...
Musick, Katherine M.; Rigosa, Jacopo; Narasimhan, Shreya; Wurth, Sophie; Capogrosso, Marco; Chew, Daniel J.; Fawcett, James W.; Micera, Silvestro; Lacour, Stéphanie P.
Reliably interfacing a nerve with an electrode array is one of the approaches to restore motor and sensory functions after an injury to the peripheral nerve. Accomplishing this with current technologies is challenging as the electrode-neuron interface often degrades over time, and surrounding myoelectric signals contaminate the neuro-signals in awake, moving animals. The purpose of this study was to evaluate the potential of microchannel electrode implants to monitor over time and in freely moving animals, neural activity from regenerating nerves. We designed and fabricated implants with silicone rubber and elastic thin-film metallization. Each implant carries an eight-by-twelve matrix of parallel microchannels (of 120 × 110 μm2 cross-section and 4 mm length) and gold thin-film electrodes embedded in the floor of ten of the microchannels. After sterilization, the soft, multi-lumen electrode implant is sutured between the stumps of the sciatic nerve. Over a period of three months and in four rats, the microchannel electrodes recorded spike activity from the regenerating sciatic nerve. Histology indicates mini-nerves formed of axons and supporting cells regenerate robustly in the implants. Analysis of the recorded spikes and gait kinematics over the ten-week period suggests firing patterns collected with the microchannel electrode implant can be associated with different phases of gait.
de Lima, O. A.; Pereira, P. D.
During the last three years we are developing hydrobiogeological researches to quantitatively describe the underground contamination of a 4.0 km2 area, including two landfill deposits and a tannery industry of Alagoinhas city, Bahia state, Brazil. We used electrical geophysics, geological, geochemical and biological analysis to gain a general understanding of the complex interactions between organic and inorganic pollutants and their environmental impacts. A geological reconnaissance work and a geoelectrical survey using vertical electrical soundings were made around the area to detect and to delineate the extent of the underground contamination plume. The results pointed out the presence of a strong conductive anomaly within the aquifer resulting from invasive fluids both from the landfills and from the surface disposal lagoons from the tannery. Water samples collected at available wells and along the Sauipe river, have shown drastic changes in the total dissolved solids, total chromium, inorganic macro-components, biochemical oxygen demand, chemical oxygen demand, nutrients and bacterial content. As a complimentary work, apparent resistivity and chargeability data were measured as a function of depth along three new multi-electrode wells, and as a function of electrode spacing along five double semi-Schlumberger subsurface profiles. A multi-electrode well is a special monitoring well where we externally install copper electrodes as thin metallic rings spaced by 0.50 m, along its entire filter and casing length. Such electrodes are connected through insulated cables to the ground surface and may be combined into different arrays. Two-side semi-Schlumberger soundings expanded up to 200 m AB/2 spacing and with centers spaced by 50 m along special transverse centered at the plume were inverted using 1D and 2D models. Both techniques were used to detail the groundwater contamination around the Alagoinhas landfills. The electrical measurements performed at the earth
Taylor, Ann M; Harris, Ashley D; Varnava, Alice; Phillips, Rhiannon; HUghes, Owen; Wilkes, Antony R.; Hall, Judith E; Wise, Richard G.
Background Chronic musculoskeletal pain (CMSKP) is attentionally demanding, complex and multi-factorial; neuroimaging research in the population seen in pain clinics is sparse. A better understanding of the neural activity underlying attentional processes to pain related information compared to healthy controls may help inform diagnosis and management in the future. Methods Blood oxygenation level dependent functional magnetic resonance imaging (BOLD fMRI) compared brain responses in patients...
We report a bi-layer lift-off resist (LOR) technique in combination with sputter deposition of silicon dioxide (SiO2) as a new passivation method in the fabrication of a multi-electrode array (MEA). Using the photo-insensitive LOR as a sacrificial bottom layer and the negative photoresist as a patterning top layer, and performing low-temperature sputter deposition of SiO2 followed by lift-off, we could successfully fabricate damage-free indium-tin oxide (ITO) and Au MEA. The bi-layer LOR sputter deposition processed Au MEA showed an impedance value of 6 × 105 Ω (at 1 kHz), with good consistency over 60 electrodes. The passivation performance of the bi-layer LOR sputter-deposited SiO2 was tested by electrodepositing Au nanoparticles (NPs) on the Au electrode, resulting in the well-confined and uniformly coated Au NPs. The bi-layer LOR sputter deposition processed ITO, Au, and Au NP-modified MEAs were evaluated and found to have a neuronal spike recording capability at a single unit level, confirming the validity of the bi-layer LOR sputter deposition as an effective passivation technique in fabrication of a MEA. These results suggest that the damage-free Au MEA fabricated with bi-layer LOR sputter deposition would be a viable platform for screening surface modification techniques that are available in neuronal interfacing. (technical note)
Full Text Available The detection of quantal exocytic events from neurons and neuroendocrine cells is a challenging task in neuroscience. One of the most promising platforms for the development of a new generation of biosensors is diamond, due to its biocompatibility, transparency and chemical inertness. Moreover, the electrical properties of diamond can be turned from a perfect insulator into a conductive material (resistivity ~mΩ·cm by exploiting the metastable nature of this allotropic form of carbon. A 16‑channels MEA (Multi Electrode Array suitable for cell culture growing has been fabricated by means of ion implantation. A focused 1.2 MeV He+ beam was scanned on a IIa single-crystal diamond sample (4.5 × 4.5 × 0.5 mm3 to cause highly damaged sub-superficial structures that were defined with micrometric spatial resolution. After implantation, the sample was annealed. This process provides the conversion of the sub-superficial highly damaged regions to a graphitic phase embedded in a highly insulating diamond matrix. Thanks to a three-dimensional masking technique, the endpoints of the sub-superficial channels emerge in contact with the sample surface, therefore being available as sensing electrodes. Cyclic voltammetry and amperometry measurements of solutions with increasing concentrations of adrenaline were performed to characterize the biosensor sensitivity. The reported results demonstrate that this new type of biosensor is suitable for in vitro detection of catecholamine release.
Ming-Gang Liu; Xue-Feng Chen; Ting He; Zhen Li; Jun Chen
Simultaneous multisite recording using multi-electrode arrays (MEAs) in cultured and acutely-dissociated brain slices and other tissues is an emerging technique in the field of network electrophysiology.Over the past 40 years,great efforts have been made by both scientists and commercial concerns,to advance this technique.The MEA technique has been widely applied to many regions of the brain,retina,heart and smooth muscle in various studies at the network level.The present review starts from the development of MEA techniques and their uses in brain preparations,and then specifically concentrates on the use of MEA recordings in studies of synaptic plasticity at the network level in both the temporal and spatial domains.Because the MEA technique helps bridge the gap between single-cell recordings and behavioral assays,its wide application will undoubtedly shed light on the mechanisms underlying brain functions and dysfunctions at the network level that remained largely unknown due to the technical difficulties before it matured.
Picollo, Federico; Battiato, Alfio; Carbone, Emilio; Croin, Luca; Enrico, Emanuele; Forneris, Jacopo; Gosso, Sara; Olivero, Paolo; Pasquarelli, Alberto; Carabelli, Valentina
The detection of quantal exocytic events from neurons and neuroendocrine cells is a challenging task in neuroscience. One of the most promising platforms for the development of a new generation of biosensors is diamond, due to its biocompatibility, transparency and chemical inertness. Moreover, the electrical properties of diamond can be turned from a perfect insulator into a conductive material (resistivity ~mΩ·cm) by exploiting the metastable nature of this allotropic form of carbon. A 16‑channels MEA (Multi Electrode Array) suitable for cell culture growing has been fabricated by means of ion implantation. A focused 1.2 MeV He+ beam was scanned on a IIa single-crystal diamond sample (4.5 × 4.5 × 0.5 mm3) to cause highly damaged sub-superficial structures that were defined with micrometric spatial resolution. After implantation, the sample was annealed. This process provides the conversion of the sub-superficial highly damaged regions to a graphitic phase embedded in a highly insulating diamond matrix. Thanks to a three-dimensional masking technique, the endpoints of the sub-superficial channels emerge in contact with the sample surface, therefore being available as sensing electrodes. Cyclic voltammetry and amperometry measurements of solutions with increasing concentrations of adrenaline were performed to characterize the biosensor sensitivity. The reported results demonstrate that this new type of biosensor is suitable for in vitro detection of catecholamine release. PMID:25558992
Picollo, F; Carbone, E; Croin, L; Enrico, E; Forneris, J; Gosso, S; Olivero, P; Pasquarelli, A; Carabelli, V
The detection of quantal exocytic events from neurons and neuroendocrine cells is a challenging task in neuroscience. One of the most promising platforms for the development of a new generation of biosensors is diamond, due to its biocompatibility, transparency and chemical inertness. Moreover, the electrical properties of diamond can be turned from a perfect insulator into a conductive material (resistivity Ohm cm) by exploiting the metastable nature of this allotropic form of carbon. A 16 channels MEA (Multi Electrode Array) suitable for cell culture growing has been fabricated by means of ion implantation. A focused 1.2 MeV He+ beam was scanned on a IIa single-crystal diamond sample (4.5x4.5x0.5 mm3) to cause highly damaged sub-superficial structures that were defined with micrometric spatial resolution. After implantation, the sample was annealed. This process provides the conversion of the sub-superficial highly damaged regions to a graphitic phase embedded in a highly insulating diamond matrix. Thanks t...
Dong-Jie Zhao; Zhong-Yi Wang; Lan Huang; Yong-Peng Jia; Leng, John Q.
Damaging thermal stimuli trigger long-lasting variation potentials (VPs) in higher plants. Owing to limitations in conventional plant electrophysiological recording techniques, recorded signals are composed of signals originating from all of the cells that are connected to an electrode. This limitation does not enable detailed spatio-temporal distributions of transmission and electrical activities in plants to be visualised. Multi-electrode array (MEA) enables the recording and imaging of dyn...
Full Text Available Bumetanide has been shown to lessen cerebral edema and reduce the infarct area in the acute stage of cerebral ischemia. Few studies focus on the effects of bumetanide on neuroprotection and neurogenesis in the chronic stage of cerebral ischemia. We established a rat model of cerebral ischemia by injecting endothelin-1 in the left cortical motor area and left corpus striatum. Seven days later, bumetanide 200 µg/kg/day was injected into the lateral ventricle for 21 consecutive days with a mini-osmotic pump. Results demonstrated that the number of neuroblasts cells and the total length of dendrites increased, escape latency reduced, and the number of platform crossings increased in the rat hippocampal dentate gyrus in the chronic stage of cerebral ischemia. These findings suggest that bumetanide promoted neural precursor cell regeneration, dendritic development and the recovery of cognitive function, and protected brain tissue in the chronic stage of ischemia.
Xu, Wang-shu; Sun, Xuan; Song, Cheng-guang; Mu, Xiao-peng; Ma, Wen-ping; Zhang, Xing-hu; Zhao, Chuan-sheng
Bumetanide has been shown to lessen cerebral edema and reduce the infarct area in the acute stage of cerebral ischemia. Few studies focus on the effects of bumetanide on neuroprotection and neurogenesis in the chronic stage of cerebral ischemia. We established a rat model of cerebral ischemia by injecting endothelin-1 in the left cortical motor area and left corpus striatum. Seven days later, bumetanide 200 µg/kg/day was injected into the lateral ventricle for 21 consecutive days with a mini-osmotic pump. Results demonstrated that the number of neuroblasts cells and the total length of dendrites increased, escape latency reduced, and the number of platform crossings increased in the rat hippocampal dentate gyrus in the chronic stage of cerebral ischemia. These findings suggest that bumetanide promoted neural precursor cell regeneration, dendritic development and the recovery of cognitive function, and protected brain tissue in the chronic stage of ischemia.
Hayes, Christopher Ruslan
INTRODUCTION: A recent single-center report indicated that the performance of atrial fibrillation ablation in patients on uninterrupted warfarin using a conventional deflectable tip electrode ablation catheter may be as safe as periprocedural discontinuation of warfarin and bridging with heparin. Novel multi-electrode array catheters for atrial fibrillation ablation are currently undergoing clinical evaluation. While offering the possibility of more rapid atrial fibrillation ablation, they are stiffer and necessitate the deployment of larger deflectable transseptal sheaths, and it remains to be determined if they increase the risk of cardiac perforation and vascular injury. Such potential risks would have implications for a strategy of uninterrupted periprocedural anticoagulation. METHOD AND RESULTS: We audited the safety outcomes of our atrial fibrillation ablation procedures using multi-electrode array ablation catheters in patients on uninterrupted warfarin (CHADS2 score>or=2) and in patients not on warfarin (uninterrupted aspirin). Two bleeding complications occurred in 49 patients on uninterrupted warfarin, both of which were managed successfully without longterm sequelae, and no bleeding complication occurred in 32 patients not on warfarin (uninterrupted aspirin). There were no thromboembolic events or other complication with either anticoagulant regimen. CONCLUSION: Despite the larger diameter and increased stiffness of multi-electrode array catheters and their deflectable transseptal sheaths, their use for catheter ablation in patients with atrial fibrillation on uninterrupted warfarin in this single-center experience does not appear to be unsafe, and thus, an adequately powered multicenter prospective randomized controlled trial should be considered.
We design a dual-sensor multi-electrode conductance probe to measure the flow parameters of gas–liquid two-phase flows in a vertical pipe with an inner diameter of 20 mm. The designed conductance probe consists of a phase volume fraction sensor (PVFS) and a cross-correlation velocity sensor (CCVS). Through inserting an insulated flow deflector in the central part of the pipe, the gas–liquid two-phase flows are forced to pass through an annual space. The multiple electrodes of the PVFS and the CCVS are flush-mounted on the inside of the pipe wall and the outside of the flow deflector, respectively. The geometry dimension of the PVFS is optimized based on the distribution characteristics of the sensor sensitivity field. In the flow loop test of vertical upward gas–liquid two-phase flows, the output signals from the dual-sensor multi-electrode conductance probe are collected by a data acquisition device from the National Instruments (NI) Corporation. The information transferring characteristics of local flow structures in the annular space are investigated using the transfer entropy theory. Additionally, the kinematic wave velocity is measured based on the drift velocity model to investigate the propagation behavior of the stable kinematic wave in the annular space. Finally, according to the motion characteristics of the gas–liquid two-phase flows, the drift velocity model based on the flow patterns is constructed to measure the individual phase flow rate with higher accuracy. (paper)
Zhai, Lu-Sheng; Bian, Peng; Han, Yun-Feng; Gao, Zhong-Ke; Jin, Ning-De
We design a dual-sensor multi-electrode conductance probe to measure the flow parameters of gas-liquid two-phase flows in a vertical pipe with an inner diameter of 20 mm. The designed conductance probe consists of a phase volume fraction sensor (PVFS) and a cross-correlation velocity sensor (CCVS). Through inserting an insulated flow deflector in the central part of the pipe, the gas-liquid two-phase flows are forced to pass through an annual space. The multiple electrodes of the PVFS and the CCVS are flush-mounted on the inside of the pipe wall and the outside of the flow deflector, respectively. The geometry dimension of the PVFS is optimized based on the distribution characteristics of the sensor sensitivity field. In the flow loop test of vertical upward gas-liquid two-phase flows, the output signals from the dual-sensor multi-electrode conductance probe are collected by a data acquisition device from the National Instruments (NI) Corporation. The information transferring characteristics of local flow structures in the annular space are investigated using the transfer entropy theory. Additionally, the kinematic wave velocity is measured based on the drift velocity model to investigate the propagation behavior of the stable kinematic wave in the annular space. Finally, according to the motion characteristics of the gas-liquid two-phase flows, the drift velocity model based on the flow patterns is constructed to measure the individual phase flow rate with higher accuracy.
This paper presents a multi-electrode and pre-deformed bilayer spring structure electrostatic attractive microelectromechanical systems (MEMS) actuator; it has large stroke at relatively low actuation voltage. Generally, electrostatic-attractive-force-based actuators have small stroke due to the instability resulted from the electrostatic ‘pull-in’ phenomenon. However, in many applications, the electrostatic micro-actuator with large stroke at low voltage is more preferred. By introducing a multi-electrode and a pre-deformed bilayer spring structure, an electrostatic attractive MEMS actuator with large stroke at very low actuation voltage has been successfully demonstrated in this paper. The actuator contains a central plate with a size of 300 µm × 300 µm × 1.5 µm and it is supported by four L-shaped bilayer springs which are pre-deformed due to residual stresses. Each bilayer spring is simultaneously attracted by three adjacent fixed electrodes, and the factors affecting the electrostatic attractive force are analyzed by a finite element analysis method. The prototype of the actuator is fabricated by poly-multi-user-MEMS-process (PolyMUMP) and the static performance is tested using a white light interferometer. The measured stroke of the actuator reaches 2 µm at 13 V dc, and it shows a good agreement with the simulation. (paper)
Upadhya, Dinesh; Hattiangady, Bharathi; Shetty, Geetha A; Zanirati, Gabriele; Kodali, Maheedhar; Shetty, Ashok K
Grafting of neural stem cells (NSCs) or GABA-ergic progenitor cells (GPCs) into the hippocampus could offer an alternative therapy to hippocampal resection in patients with drug-resistant chronic epilepsy, which afflicts >30% of temporal lobe epilepsy (TLE) cases. Multipotent, self-renewing NSCs could be expanded from multiple regions of the developing and adult brain, human embryonic stem cells (hESCs), and human induced pluripotent stem cells (hiPSCs). On the other hand, GPCs could be generated from the medial and lateral ganglionic eminences of the embryonic brain and from hESCs and hiPSCs. To provide comprehensive methodologies involved in testing the efficacy of transplantation of NSCs and GPCs in a rat model of chronic TLE, NSCs derived from the rat medial ganglionic eminence (MGE) and MGE-like GPCs derived from hiPSCs are taken as examples in this unit. The topics comprise description of the required materials, reagents and equipment, methods for obtaining rat MGE-NSCs and hiPSC-derived MGE-like GPCs in culture, generation of chronically epileptic rats, intrahippocampal grafting procedure, post-grafting evaluation of the effects of grafts on spontaneous recurrent seizures and cognitive and mood impairments, analyses of the yield and the fate of graft-derived cells, and the effects of grafts on the host hippocampus. © 2016 by John Wiley & Sons, Inc. PMID:27532817
Full Text Available Autosomal dominant nocturnal frontal lobe epilepsy (ADNFLE is a partial sleep-related epilepsy which can be caused by mutant neuronal nicotinic acetylcholine receptors (nAChR. We applied multi-electrode array (MEA recording methods to study the spontaneous firing activity of neocortical cultures obtained from mice expressing or not (WT an ADNFLE-linked nAChR subunit (β2-V287L.More than 100,000 up-states were recorded during experiments sampling from several thousand neurons. Data were analyzed by using a fast sliding-window procedure which computes histograms of the up-state durations. Differently from the WT, cultures expressing β2-V287L displayed long (10-32 s synaptic-induced up-state firing events. The occurrence of such long up-states was prevented by both negative (gabazine, penicillin G and positive (benzodiazepines modulators of GABAA receptors. Carbamazepine (CBZ, a drug of choice in ADNFLE patients, also inhibited the long up-states at micromolar concentrations. In cultures expressing β2-V287L, no significant effect was observed on the action potential waveform either in the absence or in the presence of pharmacological treatment.Our results show that some aspects of the spontaneous hyperexcitability displayed by a murine model of a human channelopathy can be reproduced in neuronal cultures. In particular, our cultures represent an in vitro chronic model of spontaneous epileptiform activity, i.e. not requiring pre-treatment with convulsants. This opens the way to the study in vitro of the role of β2-V287L on synaptic formation. Moreover, our neocortical cultures on MEA platforms allow to determine the effects of prolonged pharmacological treatment on spontaneous network hyperexcitability (which is impossible in the short-living brain slices. Methods such as the one we illustrate in the present paper should also considerably facilitate the preliminary screening of antiepileptic drugs, thereby reducing the number of in vivo
Dickey, Adam S.; Amit, Yali; Hatsopoulos, Nicholas G.
During a reach, neural activity recorded from motor cortex is typically thought to linearly encode the observed movement. However, it has also been reported that during a double-step reaching paradigm, neural coding of the original movement is replaced by that of the corrective movement. Here, we use neural data recorded from multi-electrode arrays implanted in the motor and premotor cortices of rhesus macaques to directly compare these two hypotheses. We show that while a majority of neurons display linear encoding of movement during a double-step, a minority display a dramatic drop in firing rate that is predicted by the replacement hypothesis. Neural activity in the subpopulation showing replacement is more likely to lag the observed movement, and may therefore be involved in the monitoring of the sensory consequences of a motor command. PMID:23576955
Desirée L Salazar
Full Text Available BACKGROUND: Traumatic spinal cord injury (SCI results in partial or complete paralysis and is characterized by a loss of neurons and oligodendrocytes, axonal injury, and demyelination/dysmyelination of spared axons. Approximately 1,250,000 individuals have chronic SCI in the U.S.; therefore treatment in the chronic stages is highly clinically relevant. Human neural stem cells (hCNS-SCns were prospectively isolated based on fluorescence-activated cell sorting for a CD133(+ and CD24(-/lo population from fetal brain, grown as neurospheres, and lineage restricted to generate neurons, oligodendrocytes and astrocytes. hCNS-SCns have recently been transplanted sub-acutely following spinal cord injury and found to promote improved locomotor recovery. We tested the ability of hCNS-SCns transplanted 30 days post SCI to survive, differentiate, migrate, and promote improved locomotor recovery. METHODS AND FINDINGS: hCNS-SCns were transplanted into immunodeficient NOD-scid mice 30 days post spinal cord contusion injury. hCNS-SCns transplanted mice demonstrated significantly improved locomotor recovery compared to vehicle controls using open field locomotor testing and CatWalk gait analysis. Transplanted hCNS-SCns exhibited long-term engraftment, migration, limited proliferation, and differentiation predominantly to oligodendrocytes and neurons. Astrocytic differentiation was rare and mice did not exhibit mechanical allodynia. Furthermore, differentiated hCNS-SCns integrated with the host as demonstrated by co-localization of human cytoplasm with discrete staining for the paranodal marker contactin-associated protein. CONCLUSIONS: The results suggest that hCNS-SCns are capable of surviving, differentiating, and promoting improved locomotor recovery when transplanted into an early chronic injury microenvironment. These data suggest that hCNS-SCns transplantation has efficacy in an early chronic SCI setting and thus expands the "window of opportunity" for
Bowen, Chris R.; John Taylor; Anthony H. D. Graham; Jon Robbins
The adaptation of standard integrated circuit (IC) technology as a transducer in cell-based biosensors in drug discovery pharmacology, neural interface systems and electrophysiology requires electrodes that are electrochemically stable, biocompatible and affordable. Unfortunately, the ubiquitous Complementary Metal Oxide Semiconductor (CMOS) IC technology does not meet the first of these requirements. For devices intended only for research, modification of CMOS by post-processing using cleanr...
Full Text Available Distinguishing excitatory from inhibitory neurons with multielectrode array (MEA recordings is a serious experimental challenge. The current methods, developed in vitro, mostly rely on spike waveform analysis. These however often display poor resolution and may produce errors caused by the variability of spike amplitudes and neuron shapes. Recent recordings in human brain suggest that the spike waveform features correlate with time-domain statistics such as spiking rate, autocorrelation and coefficient of variation. However, no precise criteria are available to exactly assign identified units to specific neuronal types, either in vivo or in vitro. To solve this problem, we combined MEA recording with fluorescence imaging of neocortical cultures from mice expressing green fluorescent protein (GFP in GABAergic cells. In this way, we could sort out ‘authentic excitatory neurons’ (AENs and ‘authentic inhibitory neurons’ (AINs. We thus characterized 1275 units (from 405 electrodes, n=10 experiments, based on autocorrelation, burst length, spike number, spiking rate, squared coefficient of variation and Fano factor (the ratio between spike-count variance and mean. These metrics differed by about one order of magnitude between AINs and AENs. In particular, the Fano factor turned out to provide a firing code which exactly (no overlap recognizes excitatory and inhibitory units. The difference in Fano factor between all of the identified AEN and AIN groups was highly significant (p < 10-8, ANOVA post-hoc Tukey test. Our results indicate a statistical metric-based approach to distinguish excitatory from inhibitory neurons independently from the spike width.
Distinguishing excitatory from inhibitory neurons with multielectrode array (MEA) recordings is a serious experimental challenge. The current methods, developed in vitro, mostly rely on spike waveform analysis. These however often display poor resolution and may produce errors caused by the variability of spike amplitudes and neuron shapes. Recent recordings in human brain suggest that the spike waveform features correlate with time-domain statistics such as spiking rate, autocorrelation and ...
Full Text Available There has been studied the effect of a short-term glucose deprivation on neuron net functioning of hippocampus primary culture developing within 32 days on a multi-electrode matrix MED64 (Alpha MED Sciences Company, Japan in an early and remote periods after deprivation. A short-term glucose deprivation (20 min has been shown to result in the increase of electrobiological activity of neuron net of hippocampus primary culture, with the cascade of metabolic reactions being activated leading to the death of functional neuron thereafter. In a remote period the simplification of a functional structure of neuron net occurs, with node control units being preserved. A short-term glucose deprivation creates an effect of metabolic preconditioning that in a remote period prevents a neuron net from permanent morphofunctional damages during the longer glucose deprivation.
A model of a multi-electrode ionisation chamber, with polypropylene electrodes coated with a thin layer of B4C was created within Monte Carlo N-Particle Transport Code (MCNPX) and Fluktuierende Kaskade (FLUKA) codes. The influence of the layer thickness on neutron absorption in B4C and on the neutron spectra in the consecutive intra-electrode gas volumes has been studied using the MCNPX and FLUKA codes. The results will be used for designing the new type of the ionisation chamber. Presented results of calculations provide quantitative information on attenuation and absorption of neutrons in simulated multi-electrode ionisation chamber with electrodes coated with B4C. The main interest was to compare the neutron spectra at consecutive collecting electrodes for different thicknesses of the B4C layer. The calculations were performed for neutrons from 252Cf radiation source. The results indicated that obviously, the largest effect on the spectrum shape will be observed at the thickest B4C layer; however, the layer of ∼100-300 mg cm-2 becomes of interest when one wants to combine considerable modification of the spectrum with limited attenuation of the total flux. Maximum sensitivity of the chamber can be obtained when very thin B4C layers of ∼1 mg cm-2 are used. Such layers can be considered as the optimum ones, when the chamber is used as a moderating device with detection of thermal neutrons flux in each of the intra-electrode volumes. The results of calculations performed with MCNPX and FLUKA codes are qualitatively consistent with each other; however, differs in quantitative estimations. In the low-energy range a discrepancy can be observed probably due to differences in the cross section libraries of both codes. (authors)
Carmeli, Cristian; Bonifazi, Paolo; Robinson, Hugh P C; Small, Michael
Linking the structural connectivity of brain circuits to their cooperative dynamics and emergent functions is a central aim of neuroscience research. Graph theory has recently been applied to study the structure-function relationship of networks, where dynamical similarity of different nodes has been turned into a "static" functional connection. However, the capability of the brain to adapt, learn and process external stimuli requires a constant dynamical functional rewiring between circuitries and cell assemblies. Hence, we must capture the changes of network functional connectivity over time. Multi-electrode array data present a unique challenge within this framework. We study the dynamics of gamma oscillations in acute slices of the somatosensory cortex from juvenile mice recorded by planar multi-electrode arrays. Bursts of gamma oscillatory activity lasting a few hundred milliseconds could be initiated only by brief trains of electrical stimulations applied at the deepest cortical layers and simultaneously delivered at multiple locations. Local field potentials were used to study the spatio-temporal properties and the instantaneous synchronization profile of the gamma oscillatory activity, combined with current source density (CSD) analysis. Pair-wise differences in the oscillation phase were used to determine the presence of instantaneous synchronization between the different sites of the circuitry during the oscillatory period. Despite variation in the duration of the oscillatory response over successive trials, they showed a constant average power, suggesting that the rate of expenditure of energy during the gamma bursts is consistent across repeated stimulations. Within each gamma burst, the functional connectivity map reflected the columnar organization of the neocortex. Over successive trials, an apparently random rearrangement of the functional connectivity was observed, with a more stable columnar than horizontal organization. This work reveals new
Full Text Available Linking the structural connectivity of brain circuits to their cooperative dynamics and emergent functions is a central aim of neuroscience research. Graph theory has recently been applied to study the structure-function relationship of networks, where dynamical similarity of different nodes has been turned into a static functional connection. However, the capability of the brain to adapt, learn and process external stimuli requires a constant dynamical functional rewiring between circuitries and cell assemblies. Hence, we must capture the changes of network functional connectivity over time. Multi-electrode array data present a unique challenge within this framework. We study the dynamics of gamma oscillations in acute slices of the somatosensory cortex from juvenile mice recorded by planar multi-electrode arrays. Bursts of gamma oscillatory activity lasting a few hundred milliseconds could be initiated only by brief trains of electrical stimulations applied at the deepest cortical layers and simultaneously delivered at multiple locations. Local field potentials were used to study the spatio-temporal properties and the instantaneous synchronization profile of the gamma oscillatory activity, combined with current source density analysis. Pair-wise differences in the oscillation phase were used to determine the presence of instantaneous synchronization between the different sites of the circuitry during the oscillatory period. Despite variation in the duration of the oscillatory response over successive trials, they showed a constant average power, suggesting that the rate of expenditure of energy during the oscillation represents an invariant of gamma bursts. Within each gamma burst, the functional connectivity map reflected the columnar organization of the neocortex. Over successive trials, an apparently random rearrangement of the functional connectivity was observed, with a more stable columnar than horizontal organization.
Chronic stress in adulthood followed by intermittent stress impairs spatial memory and the survival of newborn hippocampal cells in aging animals: prevention by FGL, a peptide mimetic of neural cell adhesion molecule
Borcel, Erika; Pérez-Alvarez, Laura; Herrero, Ana Isabel;
. Administration of FGL, a peptide mimetic of neural cell adhesion molecule, during the 4 weeks of continuous stress not only prevented the deleterious effects of chronic stress on spatial memory, but also reduced the survival of the newly generated hippocampal cells in aging animals. FGL treatment did not......, however, prevent the decrease in the total number of granular neurons that resulted from prolonged exposure to stress. These findings suggest that the development of new drugs that mimic neural cell adhesion molecule activity might be of therapeutic relevance to treat stress-induced cognitive impairment....
Full Text Available Self-organized critical states are found in many natural systems, from earthquakes to forest fires, they have also been observed in neural systems, particularly, in neuronal cultures. However, the presence of critical states in the awake brain remains controversial. Here, we compared avalanche analyses performed on different in vivo preparations during wakefulness, slow-wave sleep and REM sleep, using high-density electrode arrays in cat motor cortex (96 electrodes, monkey motor cortex and premotor cortex and human temporal cortex (96 electrodes in epileptic patients. In neuronal avalanches defined from units (up to 160 single units, the size of avalanches never clearly scaled as power-law, but rather scaled exponentially or displayed intermediate scaling. We also analyzed the dynamics of local field potentials (LFPs and in particular LFP negative peaks (nLFPs among the different electrodes (up to 96 sites in temporal cortex or up to 128 sites in adjacent motor and pre-motor cortices. In this case, the avalanches defined from nLFPs displayed power-law scaling in double logarithmic representations, as reported previously in monkey. However, avalanche defined as positive LFP (pLFP peaks, which are less directly related to neuronal firing, also displayed apparent power-law scaling. Closer examination of this scaling using the more reliable cumulative distribution function (CDF and other rigorous statistical measures, did not confirm power-law scaling. The same pattern was seen for cats, monkey and human, as well as for different brain states of wakefulness and sleep. We also tested other alternative distributions. Multiple exponential fitting yielded optimal fits of the avalanche dynamics with bi-exponential distributions. Collectively, these results show no clear evidence for power-law scaling or self-organized critical states in the awake and sleeping brain of mammals, from cat to man.
Full Text Available Increased neuronal spontaneous firing rates have been observed throughout the central auditory system after trauma to the cochlea and this hyperactivity is believed to be associated with the phantom perception of tinnitus. Previously we have shown in an animal model of hearing loss, that an acute injection with furosemide can significantly decrease hyperactivity after cochlear trauma and eliminate behavioural evidence of tinnitus of early onset. However, furosemide also has the potential to affect cochlear thresholds. In this paper we measured the effects of a chronic (daily injections for 7 days furosemide treatment on the spontaneous firing rate of inferior colliculus neurons and on cochlear thresholds in order to establish whether a beneficial effect on hyperactivity can be obtained without causing additional hearing loss. Guinea pigs were exposed to a 10 kHz, 124dB, 2 hour acoustic trauma, and after 5 days of recovery, were given daily i.p. injections of 80mg/kg furosemide or an equivalent amount of saline. The activity of single IC neurons was recorded 24 hours following the last injection. The furosemide treatment had no effect on cochlear thresholds compared to saline injections but did result in significant reductions in spontaneous firing rates recorded in inferior colliculus. These results that suggest a long term beneficial effect of furosemide on hyperactivity after cochlear trauma may be achievable without detrimental effects on hearing, which is important when considering therapeutic potential.
以聚乙烯不干胶掩膜版法结合金属溅射沉积技术在FR-4玻璃纤维版上制作了由6个金膜工作电极(1 mm×2 mm)、1个大面积金膜对电极(2mm× 13 mm)和1个厚膜Ag/AgCl参比电极构成的集成化金膜阵列电极系统,并利用电化学手段对阵列电极系统进行了考察.研究结果表明,K3Fe(CN)6在厚膜Ag/AgCl/1.0 mol/L NaCl参比电极上的式电位与商业Ag/AgCl/3.0 mol/L NaCl参比电极相差0.067 V；参比电极放置1个月后,测量电位未发生明显变化.利用扫描电化学显微镜对工作电极表面平整度进行考察,结果表明工作电极表面具有较好的平整度.通过测量H2SO4还原峰面积评价了工作电极电化学面积的批内、批间一致性；通过K3Fe(CN)6在电极上的Ipa/Ipc比值评价了工作电极电化学特性的批内、批间一致性.结果表明,阵列电极面积和电化学特性具有良好的批内和批间一致性.对集成化金膜阵列电极系统的研究结果表明,聚乙烯不干胶掩膜版法结合金属溅射沉积技术制作的阵列电极能够满足电化学电极的要求,可作为电化学生物传感器的基础电极.%A stable integrated gold film multi-electrode array, including six gold working electrodes (1 mm ×2 mm), a gold counter electrode (2 mm x 13 mm) and a thick-film Ag/AgCl reference e-lectrode, was fabricated by mask technique of polyethylene sticky film and the gold sputtering tech nique on FR -4 glass fiber substrate. The electrochemical characteristics of the multi-electrode array fabricated were investigated using electrochemical methods. There was a negative shift of 0. 067 V obtained on the thick - film Ag/AgCl reference electrode fabricated compared with a commercial Ag/ AgCl/3. 0 mol/L NaCl reference electrode. After one month, the potential of reference electrode did not change obviously. The surface roughness of the working electrodes was studied by scanning electrochemical microscope (SECM). The satisfied
Full Text Available Direct Current (DC electrical resistivity is a material property that is sensitive to temperature changes. In this paper, the relationship between resistivity and local temperature inside steel shell battery cells (two commercial 10 Ah and 4.5 Ah lithium-ion cells is innovatively studied by Electrical Resistance Tomography (ERT. The Schlumberger configuration in ERT is applied to divide the cell body into several blocks distributed in different levels, where the apparent resistivities are measured by multi-electrode surface probes. The investigated temperature ranges from −20 to 80 °C. Experimental results have shown that the resistivities mainly depend on temperature changes in each block of the two cells used and the function of the resistivity and temperature can be fitted to the ERT-measurement results in the logistical-plot. Subsequently, the dependence of resistivity on the state of charge (SOC is investigated, and the SOC range of 70%–100% has a remarkable impact on the resistivity at low temperatures. The proposed approach under a thermal cool down regime is demonstrated to monitor the local transient temperature.
Zheng, M-H; Shi, K-Q; Lin, X-F; Xiao, D-D; Chen, L-L; Liu, W-Y; Fan, Y-C; Chen, Y-P
Model for end-stage liver disease (MELD) scoring was initiated using traditional statistical technique by assuming a linear relationship between clinical features, but most phenomena in a clinical situation are not linearly related. The aim of this study was to predict 3-month mortality risk of acute-on-chronic hepatitis B liver failure (ACHBLF) on an individual patient level using an artificial neural network (ANN) system. The ANN model was built using data from 402 consecutive patients with ACHBLF. It was trained to predict 3-month mortality by the data of 280 patients and validated by the remaining 122 patients. The area under the curve of receiver operating characteristic (AUROC) was calculated for ANN and MELD-based scoring systems. The following variables age (P < 0.001), prothrombin activity (P < 0.001), serum sodium (P < 0.001), total bilirubin (P = 0.015), hepatitis B e antigen positivity rate (P < 0.001) and haemoglobin (P < 0.001) were significantly related to the prognosis of ACHBLF and were selected to build the ANN. The ANN performed significantly better than MELD-based scoring systems both in the training cohort (AUROC = 0.869 vs 0.667, 0.591, 0.643, 0.571 and 0.577; P < 0.001, respectively) and in the validation cohort (AUROC = 0.765 vs 0.599, 0.563, 0.601, 0.521 and 0.540; P ≤ 0.006, respectively). Thus, the ANN model was shown to be more accurate in predicting 3-month mortality of ACHBLF than MELD-based scoring systems. PMID:23490369
The past decade has seen a wealth of physiological data suggesting that neural networks may behave like critical branching processes. Concurrently, the collective activity of neurons has been studied using explicit mappings to classic statistical mechanics models such as disordered Ising models, allowing for the study of their thermodynamics, but these efforts have ignored the dynamical nature of neural activity. I will show how to reconcile these two approaches by learning effective statistical mechanics models of the full history of the collective activity of a neuron population directly from physiological data, treating time as an additional dimension. Applying this technique to multi-electrode recordings from retinal ganglion cells, and studying the thermodynamics of the inferred model, reveals a peak in specific heat reminiscent of a second-order phase transition.
Zhao, Tong; Yao, Jiafeng; Liu, Kai; Takei, Masahiro
The inertial migration of neutrally buoyant spherical particles in high particle concentration (αpi > 3%) suspension flow in a square microchannel was investigated by means of the multi-electrodes sensing method which broke through the limitation of conventional optical measurement techniques in the high particle concentration suspensions due to interference from the large particle numbers. Based on the measured particle concentrations near the wall and at the corner of the square microchannel, particle cross-sectional migration ratios are calculated to quantitatively estimate the migration degree. As a result, particle migration to four stable equilibrium positions near the centre of each face of the square microchannel is found only in the cases of low initial particle concentration up to 5.0 v/v%, while the migration phenomenon becomes partial as the initial particle concentration achieves 10.0 v/v% and disappears in the cases of the initial particle concentration αpi ≥ 15%. In order to clarify the influential mechanism of particle-particle interaction on particle migration, an Eulerian-Lagrangian numerical model was proposed by employing the Lennard-Jones potential as the inter-particle potential, while the inertial lift coefficient is calculated by a pre-processed semi-analytical simulation. Moreover, based on the experimental and simulation results, a dimensionless number named migration index was proposed to evaluate the influence of the initial particle concentration on the particle migration phenomenon. The migration index less than 0.1 is found to denote obvious particle inertial migration, while a larger migration index denotes the absence of it. This index is helpful for estimation of the maximum initial particle concentration for the design of inertial microfluidic devices. PMID:27158288
Full Text Available The balance between glutamate- and GABA-mediated neurotransmission in the brain is fundamental in the nervous system, but it is regulated by the ‘tonic’ release of a variety of endogenous factors. One such important group of molecules are the neurosteroids (NSs which, similarly to benzodiazepines (BDZs, enhance GABAergic neurotransmission. The purpose of our work was to investigate, at in-vivo physiologically relevant concentrations, the effects of NSs and BDZs as GABA modulators on dissociated neocortical neuron networks grown in long-term culture. We used a multi-electrode array (MEA recording technique and a novel analysis that was able to both identify the action potentials of engaged excitatory and inhibitory neurons and to detect drug-induced network up-states (burst. We found that the NSs tetrahydrodeoxycorticosterone (THDOC and allopregnanolone (ALLO applied at low nM concentrations, produced different modulatory effects on the two neuronal clusters. Conversely, at high concentrations (1 µM, both NSs, decreased excitatory and inhibitory neuron cluster excitability; however, even several hours after washout, the excitability of inhibitory neurons continued to be depressed, leading to a network long term depression (LTD. The BDZs clonazepam (CLZ and midazolam (MDZ also decreased the network excitability, but only MDZ caused LTD of inhibitory neuron cluster. To investigate the origin of the LTD after MDZ application, we tested finasteride (FIN, an inhibitor of endogenous NSs synthesis. FIN did not prevent the LTD induced by MDZ, but surprisingly induced it after application of CLZ. The significance and possible mechanisms underlying these LTD effects of NSs and BDZs are discussed. Taken together, our results not only demonstrate that ex-vivo networks show a sensitivity to NSs and BDZs comparable to that expressed in vivo, but also provide a new global in-vitro description that can help in understanding their activity in more complex
Avishag Laish-Farkash;Amos Katz;Ornit Cohen; Evgeny Fishman;Chaim Yosefy;Vladimir Khalameizer
Full Text Available Pulmonary vein isolation (PVI using the irrigated multi-electrode ablation system (nMARQ™ remains challenging in complex atrial anatomy cases and when CARTOMERGE™ technology is not available, due to absence of a leading guide-wire. Our objective was to assess feasibility and safety of PVI using nMARQ™ catheter with intra-procedural contrast injections through the deflectable sheath compared to nMARQ™ alone. This is a prospective non-randomized observational study of 78 consecutive patients who underwent PVI only with nMARQ™. The first group (n=37, 64±10.5 years, 62% male, 13.5% persistent AF underwent the procedure with the guidance of signal mapping, fluoroscopy, and electro-anatomical mapping (EAM alone. Since 12/2013 an automatic closed-loop contrast media injector was added to improve catheter location (n=41, 62.5±11 years, 71% male, 34% persistent AF. Total procedure time was 78±19 and 85.5±18.5 minutes, and mean fluoroscopy time was 30±9 and 29.5±8.7 minutes for the first and second groups, respectively (NS; acute success rate was 97% and 97.5%, with a mean of 14.7±5 and 17.6±5.4 RF applications, respectively (p=0.02; and mean total burning time of 10.3±3.6 and 12±4 minutes, respectively (p=0.08. Mean contrast used was 60±18 mL versus 203±65 mL, with no effect on renal function or major complications. One year freedom from AF was 77% and 83%, respectively (p=0.5. Addition of contrast injections to standard nMARQ™ procedure is feasible and safe. This tool may have an added value to EAM in catheter localization by newly trained operators and in selective cases of large/common PV anatomy.
Leondopulos, Stathis S.; Boehler, Michael D.; Wheeler, Bruce C.; Brewer, Gregory J.
Slow wave oscillations in the brain are essential for coordinated network activity but have not been shown to self-organize in vitro. Here, the development of dissociated hippocampal neurons into an active network with oscillations on multi-electrode arrays was evaluated in the absence and presence of chronic external stimulation. Significant changes in signal power were observed in the range of 1-400 Hz with an increase in amplitude during bursts. Stimulation increased oscillatory activity p...
Apkarian, A. Vania; Neugebauer, Volker; Koob, George; Edwards, Scott; Levine, Jon D.; Ferrari, Luiz; Egli, Mark; Regunathan, Soundar
An association between chronic pain conditions and alcohol dependence has been revealed in numerous studies with episodes of alcohol abuse antedating chronic pain in some people and alcohol dependence emerging after the onset of chronic pain in others. Alcohol dependence and chronic pain share common neural circuits giving rise to the possibility that chronic pain states could significantly affect alcohol use patterns and that alcohol dependence could influence pain sensitivity. The reward an...
Fernandez-Leon, Jose A.; Parajuli, Arun; Franklin, Robert; Sorenson, Michael; Felleman, Daniel J.; Hansen, Bryan J.; Hu, Ming; Dragoi, Valentin
Objective. Studying the brain in large animal models in a restrained laboratory rig severely limits our capacity to examine brain circuits in experimental and clinical applications. Approach. To overcome these limitations, we developed a high-fidelity 96-channel wireless system to record extracellular spikes and local field potentials from the neocortex. A removable, external case of the wireless device is attached to a titanium pedestal placed in the animal skull. Broadband neural signals are amplified, multiplexed, and continuously transmitted as TCP/IP data at a sustained rate of 24 Mbps. A Xilinx Spartan 6 FPGA assembles the digital signals into serial data frames for transmission at 20 kHz though an 802.11n wireless data link on a frequency-shift key-modulated signal at 5.7-5.8 GHz to a receiver up to 10 m away. The system is powered by two CR123A, 3 V batteries for 2 h of operation. Main results. We implanted a multi-electrode array in visual area V4 of one anesthetized monkey (Macaca fascicularis) and in the dorsolateral prefrontal cortex (dlPFC) of a freely moving monkey (Macaca mulatta). The implanted recording arrays were electrically stable and delivered broadband neural data over a year of testing. For the first time, we compared dlPFC neuronal responses to the same set of stimuli (food reward) in restrained and freely moving conditions. Although we did not find differences in neuronal responses as a function of reward type in the restrained and unrestrained conditions, there were significant differences in correlated activity. This demonstrates that measuring neural responses in freely moving animals can capture phenomena that are absent in the traditional head-fixed paradigm. Significance. We implemented a wireless neural interface for multi-electrode recordings in freely moving non-human primates, which can potentially move systems neuroscience to a new direction by allowing one to record neural signals while animals interact with their environment.
Han-Chiao Isaac Chen
Full Text Available Restoring neurological and cognitive function in individuals who have suffered brain damage is one of the principal objectives of modern translational neuroscience. Electrical stimulation approaches, such as deep-brain stimulation, have achieved the most clinical success, but they ultimately may be limited by the computational capacity of the residual cerebral circuitry. An alternative strategy is brain substrate expansion, in which the computational capacity of the brain is augmented through the addition of new processing units and the reconstitution of network connectivity. This latter approach has been explored to some degree using both biological and electronic means but thus far has not demonstrated the ability to reestablish the function of large-scale neuronal networks. In this review, we contend that fulfilling the potential of brain substrate expansion will require a significant shift from current methods that emphasize direct manipulations of the brain (e.g., injections of cellular suspensions and the implantation of multi-electrode arrays to the generation of more sophisticated neural tissues and neural-electric hybrids in vitro that are subsequently transplanted into the brain. Drawing from neural tissue engineering, stem cell biology, and neural interface technologies, this strategy makes greater use of the manifold techniques available in the laboratory to create biocompatible constructs that recapitulate brain architecture and thus are more easily recognized and utilized by brain networks.
Chen, H Isaac; Jgamadze, Dennis; Serruya, Mijail D; Cullen, D Kacy; Wolf, John A; Smith, Douglas H
Restoring neurological and cognitive function in individuals who have suffered brain damage is one of the principal objectives of modern translational neuroscience. Electrical stimulation approaches, such as deep-brain stimulation, have achieved the most clinical success, but they ultimately may be limited by the computational capacity of the residual cerebral circuitry. An alternative strategy is brain substrate expansion, in which the computational capacity of the brain is augmented through the addition of new processing units and the reconstitution of network connectivity. This latter approach has been explored to some degree using both biological and electronic means but thus far has not demonstrated the ability to reestablish the function of large-scale neuronal networks. In this review, we contend that fulfilling the potential of brain substrate expansion will require a significant shift from current methods that emphasize direct manipulations of the brain (e.g., injections of cellular suspensions and the implantation of multi-electrode arrays) to the generation of more sophisticated neural tissues and neural-electric hybrids in vitro that are subsequently transplanted into the brain. Drawing from neural tissue engineering, stem cell biology, and neural interface technologies, this strategy makes greater use of the manifold techniques available in the laboratory to create biocompatible constructs that recapitulate brain architecture and thus are more easily recognized and utilized by brain networks. PMID:26834579
The prototype of a primary standard has been developed, built and tested, which enables the realization of the unit of the absorbed dose to water for beta brachytherapy sources. In the course of the development of the prototype, the recommendations of the American Association of Physicists in Medicine (AAPM) Task Group 60 (TG60) and the Deutsche Gesellschaft fuer Medizinische Physik (DGMP) Arbeitskreis 18 (AK18) were taken into account. The prototype is based on a new multi-electrode extrapolation chamber (MEC) which meets, in particular, the requirements on high spatial resolution and small uncertainty. The central part of the MEC is a segmented collecting electrode which was manufactured in the clean room center of PTB by means of electron beam lithography on a wafer. A precise displacement device consisting of three piezoelectric macrotranslators has been incorporated to move the wafer collecting electrode against the entrance window. For adjustment of the wafer collecting electrode parallel to the entranc...
Resendez, Shanna L; Jennings, Josh H; Ung, Randall L; Namboodiri, Vijay Mohan K; Zhou, Zhe Charles; Otis, James M; Nomura, Hiroshi; McHenry, Jenna A; Kosyk, Oksana; Stuber, Garret D
Genetically encoded calcium indicators for visualizing dynamic cellular activity have greatly expanded our understanding of the brain. However, owing to the light-scattering properties of the brain, as well as the size and rigidity of traditional imaging technology, in vivo calcium imaging has been limited to superficial brain structures during head-fixed behavioral tasks. These limitations can now be circumvented by using miniature, integrated microscopes in conjunction with an implantable microendoscopic lens to guide light into and out of the brain, thus permitting optical access to deep brain (or superficial) neural ensembles during naturalistic behaviors. Here we describe steps to conduct such imaging studies using mice. However, we anticipate that the protocol can be easily adapted for use in other small vertebrates. Successful completion of this protocol will permit cellular imaging of neuronal activity and the generation of data sets with sufficient statistical power to correlate neural activity with stimulus presentation, physiological state and other aspects of complex behavioral tasks. This protocol takes 6-11 weeks to complete. PMID:26914316
Wang-shu Xu; Xuan Sun; Cheng-guang Song; Xiao-peng Mu; Wen-ping Ma; Xing-hu Zhang; Chuan-sheng Zhao
Bumetanide has been shown to lessen cerebral edema and reduce the infarct area in the acute stage of cerebral ischemia. Few studies focus on the effects of bumetanide on neuroprotection and neurogenesis in the chronic stage of cerebral ischemia. We established a rat model of cerebral ischemia by injecting endothelin-1 in the left cortical motor area and left corpus striatum. Seven days later, bumetanide 200 µg/kg/day was injected into the lateral ventricle for 21 consecutive days with a mini-...
Chronic pancreatitis - chronic; Pancreatitis - chronic - discharge; Pancreatic insufficiency - chronic; Acute pancreatitis - chronic ... abuse over many years. Repeated episodes of acute pancreatitis can lead to chronic pancreatitis. Genetics may be ...
Michon, Frédéric; Aarts, Arno; Holzhammer, Tobias; Ruther, Patrick; Borghs, Gustaaf; McNaughton, Bruce; Kloosterman, Fabian
Objective. Understanding how neuronal assemblies underlie cognitive function is a fundamental question in system neuroscience. It poses the technical challenge to monitor the activity of populations of neurons, potentially widely separated, in relation to behaviour. In this paper, we present a new system which aims at simultaneously recording from a large population of neurons from multiple separated brain regions in freely behaving animals. Approach. The concept of the new device is to combine the benefits of two existing electrophysiological techniques, i.e. the flexibility and modularity of micro-drive arrays and the high sampling ability of electrode-dense silicon probes. Main results. Newly engineered long bendable silicon probes were integrated into a micro-drive array. The resulting device can carry up to 16 independently movable silicon probes, each carrying 16 recording sites. Populations of neurons were recorded simultaneously in multiple cortical and/or hippocampal sites in two freely behaving implanted rats. Significance. Current approaches to monitor neuronal activity either allow to flexibly record from multiple widely separated brain regions (micro-drive arrays) but with a limited sampling density or to provide denser sampling at the expense of a flexible placement in multiple brain regions (neural probes). By combining these two approaches and their benefits, we present an alternative solution for flexible and simultaneous recordings from widely distributed populations of neurons in freely behaving rats.
Permanent verbal, visual scenic and coenaestetic hallucinations are the most prominent psychopathological symptoms aside from psychomotor disorders in speech-sluggish catatonia, a subtype of chronic catatonic schizophrenia according to Karl Leonhard. These continuous hallucinations serve as an excellent paradigm for the investigation of the assumed functional disturbances of cortical circuits in schizophrenia. Data from positron emission tomography (F-18-FDG-PET and F-18-DOPA-PET) from three patients with this rare phenotype were available (two cases of simple speech-sluggish catatonia, one case of a combined speech-prompt/speech-sluggish subtype) and were compared with a control collective. During their permanent hallucinations, all catatonic patients showed a clear bitemporal hypometabolism in the F-18-FDG-PET. Both patients with the simple speech-sluggish catatonia showed an additional bilateral thalamic hypermetabolism and an additional bilateral hypometabolism of the frontal cortex, especially on the left side. In contrast, the patient with the combined speech-prompt/speech-sluggish catatonia showed a bilateral thalamic hypo-metabolism combined with a bifrontal cortical hypermetabolism. However, the left/right ratio of the frontal cortex also showed a lateralization effect with a clear relative hypometabolism of the left frontal cortex. The F-18-DOPA-PET of both schizophrenic patients with simple speech-sluggish catatonia showed a normal F-18-DOPA storage in the striatum, whereas in the right putamen of the patient with the combined form a higher right/left ratio in F-DOPA storage was discernible, indicating an additional lateralized influence of the dopaminergic system in this subtype of chronic catatonic schizophrenia. (author)
樊晋华; 窦银科; 秦建敏; 张瑞峰
A coplanar multi-electrode capacitance sensing type ice thickness sensor is a new kind of ice situation detection sensor Which is based on different capacitance characteristic between air,ice and water.It can realize detecting ice thickness and water level under ice automatically through measuring the capacitance of different layers of air,ice and water under ice.It is mainly combined with single chip microprocessor and electronic information collection,processing and transformation technology.In this paper mechanism of sensor has been simulated with the Maxwell software and experiment data are also analyzed,the measurement principal of coplanar multi-electrode capacitance sensing type ice thickness sensor is demonstrated; Through analysis of the scene experiment data gotten in the Yellow River in the Inner Mongolia,that proved the sensor has pin-point accuracy、close tolerance and high reliability and so on advantages,and can be used in the low temperature、radiation and strongly vibration etc such bad environment,also be good for the field environment.%同面多极电容感应式冰层厚度传感器是基于空气、冰与水不同的介电特性,通过对空气层、冰层和冰下水层电容值进行分层测量,从而实现对冰层厚度与水位高度自动检测的一种新型冰情检测传感器.主要融合了单片机技术和电子信息采集,处理,转换技术.利用Maxwell软件对其机理进行仿真,对实验数据进行分析,论证了同面多电极电容感应式冰厚传感器的测量原理;通过分析该传感器在黄河内蒙段的现场检测数据,证明该传感器具有准确度高、误差小、稳定等优点,并能在低温、辐射和强烈振动等恶劣环境下工作,非常适合野外环境中使用.
... infections that cause chronic diarrhea be prevented? Chronic Diarrhea What is chronic diarrhea? Diarrhea that lasts for more than 2-4 ... represent a life-threatening illness. What causes chronic diarrhea? Chronic diarrhea has many different causes; these causes ...
Xiang Rong Zhang
Full Text Available Antipsychotic-induced sexual dysfunction is a common and serious clinical side effect. It has been demonstrated that both neuronal nitric oxide (nNOS and dopamine D2 receptor (DRD2 in the medial preoptic area (MPOA and the paraventricular nucleus (PVN of the hypothalamus have important roles in the regulation of sexual behaviour. We investigated the influences of 21 days' antipsychotic drug administration on expression of nNOS and DRD2 in the rat hypothalamus. Haloperidol (0.5 mg/kg/day i.p. significantly decreased nNOS integrated optical density in a sub-nucleus of the MPOA, medial preoptic nucleus (MPN, and decreased the nNOS integrated optical density and cell density in another sub-nucleus of the MPOA, anterodorsal preoptic nucleus (ADP. Risperidone (0.25 mg/kg inhibited the nNOS integrated optical density in the ADP. nNOS mRNA and protein in the MPOA but not the PVN was also significantly decreased by haloperidol. Haloperidol and risperidone increased DRD2 mRNA and protein expression in both the MPOA and the PVN. Quetiapine (20 mg/kg/day i.p. did not influence the expression of nNOS and DRD2 in either the MPOA or the PVN. These findings indicate that hypothalamic nNOS and DRD2 are affected to different extents by chronic administration of risperidone and haloperidol, but are unaffected by quetiapine. These central effects might play a role in sexual dysfunction induced by certain antipsychotic drugs.
Pothof, F.; Bonini, L.; Lanzilotto, M.; Livi, A.; Fogassi, L.; Orban, G. A.; Paul, O.; Ruther, P.
Objective. Drug resistant focal epilepsy can be treated by resecting the epileptic focus requiring a precise focus localisation using stereoelectroencephalography (SEEG) probes. As commercial SEEG probes offer only a limited spatial resolution, probes of higher channel count and design freedom enabling the incorporation of macro and microelectrodes would help increasing spatial resolution and thus open new perspectives for investigating mechanisms underlying focal epilepsy and its treatment. This work describes a new fabrication process for SEEG probes with materials and dimensions similar to clinical probes enabling recording single neuron activity at high spatial resolution. Approach. Polyimide is used as a biocompatible flexible substrate into which platinum electrodes and leads are integrated with a minimal feature size of 5 μm. The polyimide foils are rolled into the cylindrical probe shape at a diameter of 0.8 mm. The resulting probe features match those of clinically approved devices. Tests in saline solution confirmed the probe stability and functionality. Probes were implanted into the brain of one monkey (Macaca mulatta), trained to perform different motor tasks. Suitable configurations including up to 128 electrode sites allow the recording of task-related neuronal signals. Main results. Probes with 32 and 64 electrode sites were implanted in the posterior parietal cortex. Local field potentials and multi-unit activity were recorded as early as one hour after implantation. Stable single-unit activity was achieved for up to 26 days after implantation of a 64-channel probe. All recorded signals showed modulation during task execution. Significance. With the novel probes it is possible to record stable biologically relevant data over a time span exceeding the usual time needed for epileptic focus localisation in human patients. This is the first time that single units are recorded along cylindrical polyimide probes chronically implanted 22 mm deep into the
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 . 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
Rouse, Adam; Stanslaski, Scott; Cong, Peng; Jensen, Randy; Afshar, Pedram; Ullestad, Dave; Moran, Dan; Denison, Tim
A bi-directional neural interface (NI) system was designed and built by incorporating a novel neural recording and processing subsystem into a commercially approved neural stimulator. The NI system prototype leverages the system infrastructure from a market-approved neurostimulator to ensure reliable operation in a chronic implantation environment. In addition to providing approved therapy capabilities, the device adds key elements to facilitate chronic clinical research, such as four channel...
PROTIC DANIJELA D.
Neural cryptography based on the tree parity machine (TPM) is presented in this paper. A mutual learning-based synchronization of two networks is studied. The training of the TPM based on the Hebbian, anti-Hebbian and random walk as well as on the secure key generation protocol is described. The most important attacks on the key generation process are shown.
Stress initiates adaptive processes that allow the organism to physiologically cope with prolonged or intermittent exposure to real or perceived threats. A major component of this response is repeated activation of glucocorticoid secretion by the hypothalamo-pituitary-adrenocortical (HPA) axis, which promotes redistribution of energy in a wide range of organ systems, including the brain. Prolonged or cumulative increases in glucocorticoid secretion can reduce benefits afforded by enhanced s...
About the Series: Bioelectric Engineering presents state-of-the-art discussions on modern biomedical engineering with respect to applications of electrical engineering and information technology in biomedicine. This focus affirms Springer's commitment to publishing important reviews of the broadest interest to biomedical engineers, bioengineers, and their colleagues in affiliated disciplines. Recent volumes have covered modeling and imaging of bioelectric activity, neural engineering, biosignal processing, bionanotechnology, among other topics.
Vajda, Igor; Grim, Jiří
Oxford : Eolss Publishers-UNESCO, 2008 - (Parra-Luna, F.), s. 224-248 ISBN 978-1-84826-654-4. - (Encyclopedia of Life Support Systems. Volume III) R&D Projects: GA ČR GA102/07/1594 Institutional research plan: CEZ:AV0Z10750506 Keywords : neural networks * probabilistic approach Subject RIV: BD - Theory of Information http://library.utia.cas.cz/separaty/2008/SI/vajda-systems science and cybernetics .pdf
Zannad, Faiez; De Ferrari, Gaetano M; Tuinenburg, Anton E; Wright, David; Brugada, Josep; Butter, Christian; Klein, Helmut; Stolen, Craig; Meyer, Scott; Stein, Kenneth M; Ramuzat, Agnes; Schubert, Bernd; Daum, Doug; Neuzil, Petr; Botman, Cornelis; Castel, Maria Angeles; D'Onofrio, Antonio; Solomon, Scott D; Wold, Nicholas; Ruble, Stephen B
AIM: The neural cardiac therapy for heart failure (NECTAR-HF) was a randomized sham-controlled trial designed to evaluate whether a single dose of vagal nerve stimulation (VNS) would attenuate cardiac remodelling, improve cardiac function and increase exercise capacity in symptomatic heart failure p
Bronchitis is an inflammation of the bronchial tubes, the airways that carry air to your lungs. It ... chest tightness. There are two main types of bronchitis: acute and chronic. Chronic bronchitis is one type ...
Mok, S Y; Lim, Y M; Goh, S Y
A device to facilitate high-density seeding of dissociated neural cells on planar multi-electrode arrays (MEAs) is presented in this paper. The device comprises a metal cover with two concentric cylinders-the outer cylinder fits tightly on to the external diameter of a MEA to hold it in place and an inner cylinder holds a central glass tube for introducing a cell suspension over the electrode area of the MEA. An O-ring is placed at the bottom of the inner cylinder and the glass tube to provide a fluid-tight seal between the glass tube and the MEA electrode surface. The volume of cell suspension in the glass tube is varied according to the desired plating density. After plating, the device can be lifted from the MEA without leaving any residue on the contact surface. The device has enabled us to increase and control the plating density of neural cell suspension with low viability, and to prepare successful primary cultures from cryopreserved neurons and glia. The cultures of cryopreserved dissociated cortical neurons that we have grown in this manner remained spontaneously active over months, exhibited stable development and similar network characteristics as reported by other researchers. PMID:19428539
Sipponen, Pentti; Maaroos, Heidi-Ingrid
Abstract Prevalence of chronic gastritis has markedly declined in developed populations during the past decades. However, chronic gastritis is still one of the most common serious pandemic infections with such severe killing sequelae as peptic ulcer or gastric cancer. Globally, on average, even more than half of people may have a chronic gastritis at present. Helicobacter pylori infection in childhood is the main cause of chronic gastritis, which microbial origin is the key for the understand...
Erickson, Bradley A.; Schaeffer, Anthony J.; Le, Brian
Chronic prostatitis can cause pain and urinary symptoms, and usually occurs without positive bacterial cultures from prostatic secretions (known as chronic abacterial prostatitis or chronic pelvic pain syndrome, CP/CPPS). Bacterial infection can result from urinary tract instrumentation, but the cause and natural history of CP/CPPS are unknown.
Zannad, Faiez; De Ferrari, Gaetano M.; Tuinenburg, Anton E.; Wright, David; Brugada, Josep; Butter, Christian; Klein, Helmut; Stolen, Craig; Meyer, Scott; Stein, Kenneth M.; Ramuzat, Agnes; Schubert, Bernd; Daum, Doug; Neuzil, Petr; Botman, Cornelis
Aim The neural cardiac therapy for heart failure (NECTAR-HF) was a randomized sham-controlled trial designed to evaluate whether a single dose of vagal nerve stimulation (VNS) would attenuate cardiac remodelling, improve cardiac function and increase exercise capacity in symptomatic heart failure patients with severe left ventricular (LV) systolic dysfunction despite guideline recommended medical therapy. Methods: Patients were randomized in a 2 : 1 ratio to receive therapy (VNS ON) or contro...
Yardley, Nathan; García-Castro, Martín I
The neural crest arises at the border between the neural plate and the adjacent non-neural ectoderm. It has been suggested that both neural and non-neural ectoderm can contribute to the neural crest. Several studies have examined the molecular mechanisms that regulate neural crest induction in neuralized tissues or the neural plate border. Here, using the chick as a model system, we address the molecular mechanisms by which non-neural ectoderm generates neural crest. We report that in response to FGF the non-neural ectoderm can ectopically express several early neural crest markers (Pax7, Msx1, Dlx5, Sox9, FoxD3, Snail2, and Sox10). Importantly this response to FGF signaling can occur without inducing ectopic mesodermal tissues. Furthermore, the non-neural ectoderm responds to FGF by expressing the prospective neural marker Sox3, but it does not express definitive markers of neural or anterior neural (Sox2 and Otx2) tissues. These results suggest that the non-neural ectoderm can launch the neural crest program in the absence of mesoderm, without acquiring definitive neural character. Finally, we report that prior to the upregulation of these neural crest markers, the non-neural ectoderm upregulates both BMP and Wnt molecules in response to FGF. Our results provide the first effort to understand the molecular events leading to neural crest development via the non-neural ectoderm in amniotes and present a distinct response to FGF signaling. PMID:23000357
Atreya, Shrikant; Kumar, Gaurav; Datta, Soumitra Shankar
Vagal sensory neuropathy or vagal hypersensitivity has been implicated in the pathophysiology of chronic cough. Earlier reports have shown gabapentin to be effective in sensory laryngeal neuropathy and symptom conditions that have a proven neural origin. We present a case report of a patient with chronic refractory cough due to a soft tissue mass in the lung that caused compression of the mediastinal structures. The patient was successfully treated with gabapentin with reduction in the cough intensity, duration, and frequency. PMID:26962287
Shrikant Atreya; Gaurav Kumar; Soumitra Shankar Datta
Vagal sensory neuropathy or vagal hypersensitivity has been implicated in the pathophysiology of chronic cough. Earlier reports have shown gabapentin to be effective in sensory laryngeal neuropathy and symptom conditions that have a proven neural origin. We present a case report of a patient with chronic refractory cough due to a soft tissue mass in the lung that caused compression of the mediastinal structures. The patient was successfully treated with gabapentin with reduction in the cough ...
Full Text Available Vagal sensory neuropathy or vagal hypersensitivity has been implicated in the pathophysiology of chronic cough. Earlier reports have shown gabapentin to be effective in sensory laryngeal neuropathy and symptom conditions that have a proven neural origin. We present a case report of a patient with chronic refractory cough due to a soft tissue mass in the lung that caused compression of the mediastinal structures. The patient was successfully treated with gabapentin with reduction in the cough intensity, duration, and frequency.
Atreya, Shrikant; Kumar, Gaurav; Datta, Soumitra Shankar
Vagal sensory neuropathy or vagal hypersensitivity has been implicated in the pathophysiology of chronic cough. Earlier reports have shown gabapentin to be effective in sensory laryngeal neuropathy and symptom conditions that have a proven neural origin. We present a case report of a patient with chronic refractory cough due to a soft tissue mass in the lung that caused compression of the mediastinal structures. The patient was successfully treated with gabapentin with reduction in the cough intensity, duration, and frequency. PMID:26962287
Neural tube defects are birth defects of the brain, spine, or spinal cord. They happen in the first month ... that she is pregnant. The two most common neural tube defects are spina bifida and anencephaly. In spina bifida, ...
Schwedt, Todd J
Chronic migraine is a disabling neurologic condition that affects 2% of the general population. Patients with chronic migraine have headaches on at least 15 days a month, with at least eight days a month on which their headaches and associated symptoms meet diagnostic criteria for migraine. Chronic migraine places an enormous burden on patients owing to frequent headaches; hypersensitivity to visual, auditory, and olfactory stimuli; nausea; and vomiting. It also affects society through direct and indirect medical costs. Chronic migraine typically develops after a slow increase in headache frequency over months to years. Several factors are associated with an increased risk of transforming to chronic migraine. The diagnosis requires a carefully performed patient interview and neurologic examination, sometimes combined with additional diagnostic tests, to differentiate chronic migraine from secondary headache disorders and other primary chronic headaches of long duration. Treatment takes a multifaceted approach that may include risk factor modification, avoidance of migraine triggers, drug and non-drug based prophylaxis, and abortive migraine treatment, the frequency of which is limited to avoid drug overuse. This article provides an overview of current knowledge regarding chronic migraine, including epidemiology, risk factors for its development, pathophysiology, diagnosis, management, and guidelines. The future of chronic migraine treatment and research is also discussed. PMID:24662044
Warden, Melissa R.; Cardin, Jessica A.; Deisseroth, Karl
Genetically encoded optical actuators and indicators have changed the landscape of neuroscience, enabling targetable control and readout of specific components of intact neural circuits in behaving animals. Here, we review the development of optical neural interfaces, focusing on hardware designed for optical control of neural activity, integrated optical control and electrical readout, and optical readout of population and single-cell neural activity in freely moving mammals.
Holographic neural networks are a new and promising type of artificial neural networks. This article gives an overview of the holographic neural technology and its possibilities. The theoretical principles of holographic networks are first reviewed. Then, some other papers are presented, where holographic networks have been applied or experimentally evaluated. A case study dealing with currency exchange rate prediction is described in more detail.
Itch and pain are closely related but also clearly distinct sensations. Pain is known to suppress itch, while analgesics such as morphine can provoke itch. However, in pathological and chronic conditions, pain and itch also have similarities. Dysfunction of the nervous system, as manifested by neural plastic changes in primary sensory neurons of the peripheral nervous system (peripheral sensitization) and spinal cord and brain stem neurons in the central nervous system (central sensitization) will result in chronic pain and itch. Importantly, these diseases also result from immune dysfunction, since inflammatory mediators can directly activate or sensitize nociceptive and pruriceptive neurons in the peripheral and central nervous system, leading to pain and itch hypersensitivity. In this mini-review, I discuss the roles of Toll-like receptors (TLRs), transient receptor potential ankyrin 1 (TRPA1) ion channel, and Nav1.7 sodium channel in regulating itch and inflammation, with special emphasis of neuronal TLR signaling and the interaction of TLR7 and TRPA1. Chronic pain and chronic itch are debilitating diseases and dramatically impact the life quality of patients. Targeting TLRs for the control of inflammation, neuroinflammation (inflammation restricted in the nervous system), and hyperexcitability of nociceptors and pruriceptors will lead to new therapeutics for the relief of chronic pain and chronic itch. Finally, given the shared mechanisms among chronic cough, chronic pain, and chronic itch and the demonstrated efficacy of the neuropathic pain drug gabapentin in treating chronic cough, novel therapeutics targeting TRPA1, Nav1.7, and TLRs may also help to alleviate refractory cough via modulating neuron-immune interaction. PMID:26351759
Polyneuropathy - chronic inflammatory; CIDP; Chronic inflammatory demyelinating polyneuropathy ... of the body equally. Chronic inflammatory demyelinating polyneuropathy (CIDP) is the most common chronic neuropathy caused by ...
Kocher, Hemant M; Froeling, Fieke EM
Chronic pancreatitis is characterised by long-standing inflammation of the pancreas owing to a wide variety of causes, including recurrent acute attacks of pancreatitis. Chronic pancreatitis affects 3–9 people in 100,000; 70% of cases are alcohol-induced.
Kocher, Hemant M; Kadaba, Raghu
Chronic pancreatitis is characterised by long-standing inflammation of the pancreas due to a wide variety of causes, including recurrent acute attacks of pancreatitis. Chronic pancreatitis affects between 3 and 9 people in 100,000; 70% of cases are alcohol-induced.
Fontaine, D; Blond, S; Mertens, P; Lanteri-Minet, M
Neurosurgical treatment of pain used two kind of techniques: 1) Lesional techniques interrupt the transmission of nociceptive neural input by lesionning the nociceptive pathways (drezotomy, cordotomy, tractotomy…). They are indicated to treat morphine-resistant cancer pain and few cases of selected neuropathic pain. 2) Neuromodulation techniques try to decrease pain by reinforcing inhibitory and/or to limit activatory mechanisms. Chronic electrical stimulation of the nervous system (peripheral nerve stimulation, spinal cord stimulation, motor cortex stimulation…) is used to treat chronic neuropathic pain. Intrathecal infusion of analgesics (morphine, ziconotide…), using implantable pumps, allows to increase their efficacy and to reduce their side effects. These techniques can improve, sometimes dramatically, selected patients with severe and chronic pain, refractory to all other treatments. The quality of the analgesic outcome depends on the relevance of the indications. PMID:25681114
Iris I A Groen
Full Text Available The visual world is complex and continuously changing. Yet, our brain transforms patterns of light falling on our retina into a coherent percept within a few hundred milliseconds. Possibly, low-level neural responses already carry substantial information to facilitate rapid characterization of the visual input. Here, we computationally estimated low-level contrast responses to computer-generated naturalistic images, and tested whether spatial pooling of these responses could predict image similarity at the neural and behavioral level. Using EEG, we show that statistics derived from pooled responses explain a large amount of variance between single-image evoked potentials (ERPs in individual subjects. Dissimilarity analysis on multi-electrode ERPs demonstrated that large differences between images in pooled response statistics are predictive of more dissimilar patterns of evoked activity, whereas images with little difference in statistics give rise to highly similar evoked activity patterns. In a separate behavioral experiment, images with large differences in statistics were judged as different categories, whereas images with little differences were confused. These findings suggest that statistics derived from low-level contrast responses can be extracted in early visual processing and can be relevant for rapid judgment of visual similarity. We compared our results with two other, well- known contrast statistics: Fourier power spectra and higher-order properties of contrast distributions (skewness and kurtosis. Interestingly, whereas these statistics allow for accurate image categorization, they do not predict ERP response patterns or behavioral categorization confusions. These converging computational, neural and behavioral results suggest that statistics of pooled contrast responses contain information that corresponds with perceived visual similarity in a rapid, low-level categorization task.
Boushel, Robert Christopher; Calbet, J A; Rådegran, G; Sondergaard, H; Wagner, Poul Erik; Saltin, B
In chronic hypoxia, both heart rate (HR) and cardiac output (Q) are reduced during exercise. The role of parasympathetic neural activity in lowering HR is unresolved, and its influence on Q and oxygen transport at high altitude has never been studied.......In chronic hypoxia, both heart rate (HR) and cardiac output (Q) are reduced during exercise. The role of parasympathetic neural activity in lowering HR is unresolved, and its influence on Q and oxygen transport at high altitude has never been studied....
Wang Xing-Yuan; Zhang Yi
We propose a novel neural network based on a diagonal recurrent neural network and chaos,and its structure andlearning 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.
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)
Curtis, Steven A.
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.
... foods may relieve symptoms in people. However, the benefit of a low-fat diet has not been proven. Alternative Names Cholecystitis - chronic Images Cholecystitis, CT scan Cholecystitis, cholangiogram Cholecystolithiasis Gallstones, cholangiogram Cholecystogram References Wang ...
... who have chronic pain may also have low self-esteem, depression, and anger. Causes & Risk Factors What causes ... as stretching and strengthening activities) and low-impact exercise (such as walking, swimming, or biking) can help ...
... School Lunch Lines FDA Cracks Down on Antibacterial Soaps Health Tip: Schedule a Back-to-School Dental ... the Professional Version Meningitis Introduction to Meningitis Acute Bacterial Meningitis Viral Meningitis Noninfectious Meningitis Recurrent Meningitis Chronic ...
... Sugar Control Helps Fight Diabetic Eye Disease Are 'Workaholics' Prone to OCD, Anxiety? ALL NEWS > Resources First ... weeks after heart surgery) and is considered subacute. Causes Usually, the cause of chronic effusive pericarditis is ...
Full text: Therapeutic irradiation of the brain can cause cognitive dysfunction that is not treatable or well understood. Several lines of evidence from our laboratory suggest that radiation induced inhibition of neurogenesis in the hippocampus may be involved. To understand the mechanisms underlying these observations, we initiated studies using neural precursor cells isolated from the adult rat hippocampus. Cells were cultured exponentially and analyzed for acute (0-24h) and chronic (3-33 day) changes in apoptosis and oxidative stress following exposure to X-rays. Oxidative stress was measured using a dye sensitive to reactive oxygen species (ROS) and apoptosis was measured using annexin V binding; each endpoint was quantified by fluorescent automated cell sorting (FACS). Following exposure to X-rays, neural precursor cells exhibit a dose-responsive increase in the level of ROS and apoptosis over acute and chronic time frames. ROS and apoptosis were maximal at 12h, increasing 35 and 37% respectively over that of unirradiated controls. ROS and apoptosis peaked again at 24h, increasing 31 and 21% respectively over controls. Chronic levels of ROS and apoptosis were persistently elevated in a dose-dependent manner. ROS showed significant increases (34-180%) over a 3-4 week interval, while increases in apoptosis were less dramatic, rising 45% by week one before dropping to background. Irradiation of rat neural precursor cells was associated with an increase in p53 protein levels, and the activation of G1/S and G2/M checkpoints. These data suggest that the apoptotic and ROS responses may be tied to p53 dependent regulation of cell cycle control and stress activated pathways. We propose that oxidative stress plays a critical role in the radiation response of neural precursor cells, and discuss how this might contribute to the inhibition of neurogenesis and the cognitive impairment observed in the irradiated CNS
Full Text Available Abstract Background Parkinson's disease, the most common adult neurodegenerative movement disorder, demonstrates a brain-wide pathology that begins pre-clinically with alpha-synuclein aggregates ("Lewy neurites" in processes of gut enteric and vagal motor neurons. Rostral progression into substantia nigra with death of dopamine neurons produces the motor impairment phenotype that yields a clinical diagnosis. The vast majority of Parkinson's disease occurs sporadically, and current models of sporadic Parkinson's disease (sPD can utilize directly infused or systemic neurotoxins. Results We developed a differentiation protocol for human SH-SY5Y neuroblastoma that yielded non-dividing dopaminergic neural cells with long processes that we then exposed to 50 nM rotenone, a complex I inhibitor used in Parkinson's disease models. After 21 days of rotenone, ~60% of cells died. Their processes retracted and accumulated ASYN-(+ and UB-(+ aggregates that blocked organelle transport. Mitochondrial movement velocities were reduced by 8 days of rotenone and continued to decline over time. No cytoplasmic inclusions resembling Lewy bodies were observed. Gene microarray analyses showed that the majority of genes were under-expressed. qPCR analyses of 11 mtDNA-encoded and 10 nDNA-encoded mitochondrial electron transport chain RNAs' relative expressions revealed small increases in mtDNA-encoded genes and lesser regulation of nDNA-encoded ETC genes. Conclusion Subacute rotenone treatment of differentiated SH-SY5Y neuroblastoma cells causes process retraction and partial death over several weeks, slowed mitochondrial movement in processes and appears to reproduce the Lewy neuritic changes of early Parkinson's disease pathology but does not cause Lewy body inclusions. The overall pattern of transcriptional regulation is gene under-expression with minimal regulation of ETC genes in spite of rotenone's being a complex I toxin. This rotenone-SH-SY5Y model in a
Federal Laboratory Consortium — As part of the Electrical and Computer Engineering Department and The Institute for System Research, the Neural Systems Laboratory studies the functionality of the...
Jørgensen, Ivan Harald Holger; Bogason, Gudmundur; Bruun, Erik
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 with a...
Stieglitz, Thomas; Boretius, Tim; Ordonez, Juan; Hassler, Christina; Henle, Christian; Meier, Wolfgang; Plachta, Dennis T. T.; Schuettler, Martin
Neural prostheses are technical systems that interface nerves to treat the symptoms of neurological diseases and to restore sensory of motor functions of the body. Success stories have been written with the cochlear implant to restore hearing, with spinal cord stimulators to treat chronic pain as well as urge incontinence, and with deep brain stimulators in patients suffering from Parkinson's disease. Highly complex neural implants for novel medical applications can be miniaturized either by means of precision mechanics technologies using known and established materials for electrodes, cables, and hermetic packages or by applying microsystems technologies. Examples for both approaches will be introduced and discussed. Electrode arrays for recording of electrocorticograms during presurgical epilepsy diagnosis have been manufactured using approved materials and a marking laser to achieve an integration density that is adequate in the context of brain machine interfaces, e.g. on the motor cortex. Microtechnologies have to be used for further miniaturization to develop polymer-based flexible and light weighted electrode arrays to interface the peripheral and central nervous system. Polyimide as substrate and insulation material will be discussed as well as several application examples for nerve interfaces like cuffs, filament like electrodes and large arrays for subdural implantation.
Vonk, E.; Veelenturf, L.P.J.; Jain, L.C.
Artificial neural networks, also called neural networks, have been used successfully in many fields including engineering, science and business. This paper presents the implementation of several neural network simulators and their applications in character recognition and other engineering areas
Kello, Christopher T.
It is now well-established that intrinsic variations in human neural and behavioral activity tend to exhibit scaling laws in their fluctuations and distributions. The meaning of these scaling laws is an ongoing matter of debate between isolable causes versus pervasive causes. A spiking neural network model is presented that self-tunes to critical…
van Belle, T
Neural Darwinism is a theory of cognition developed by Gerald Edelman along with George Reeke and Olaf Sporns at Rockefeller University. As its name suggests, neural Darwinism is modeled after biological Darwinism, and its authors assert that the two processes are strongly analogous. both operate on variation in a population, amplifying the more adaptive individuals. However, from a computational perspective, neural Darwinism is quite different from other models of natural selection, such as genetic algorithms. The individuals of neural Darwinism do not replicate, thus robbing the process of the capacity to explore new solutions over time and ultimately reducing it to a random search. Because neural Darwinism does not have the computational power of a truly Darwinian process, it is misleading to label it as such. to illustrate this disparity in adaptive power, one of Edelman's early computer experiments, Darwin I, is revisited, and it is shown that adding replication greatly improves the adaptive power of the system. PMID:9090158
consciousness is related to neural processes it seems, at least prima facie, that the ability of the neural structures to change should be reflected in a theory of this relationship "Neural plasticity" refers to the fact that the brain can change due to its own activity. The brain is not static but rather a...... relation between consciousness and brain functions. If consciousness is connected to specific brain structures (as a function or in identity) what happens to consciousness when those specific underlying structures change? It is therefore possible that the understanding and theories of neural plasticity can......, something that is stable over time. Considering neural plasticity, this is not necessarily so. The NCC might change and hence literally change the way a person is conscious. What it is about the NCC that can and might change is, even though it can be relevant for the relation between the brain and...
Perry, D. W. J.; Grayden, D. B.; Shepherd, R. K.; Fallon, J. B.
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.
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Synchronization of neural networks has been used for public channel protocols in cryptography. In the case of tree parity machines the dynamics of both bidirectional synchronization and unidirectional learning is driven by attractive and repulsive stochastic forces. Thus it can be described well by a random walk model for the overlap between participating neural networks. For that purpose transition probabilities and scaling laws for the step sizes are derived analytically. Both these calculations as well as numerical simulations show that bidirectional interaction leads to full synchronization on average. In contrast, successful learning is only possible by means of fluctuations. Consequently, synchronization is much faster than learning, which is essential for the security of the neural key-exchange protocol. However, this qualitative difference between bidirectional and unidirectional interaction vanishes if tree parity machines with more than three hidden units are used, so that those neural networks are not suitable for neural cryptography. In addition, the effective number of keys which can be generated by the neural key-exchange protocol is calculated using the entropy of the weight distribution. As this quantity increases exponentially with the system size, brute-force attacks on neural cryptography can easily be made unfeasible
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This paper describes a practical introduction to the use of Artificial Neural Networks. Artificial Neural Nets are often used as an alternative to the traditional symbolic manipulation and first order logic used in Artificial Intelligence, due the high degree of difficulty to solve problems that can not be handled by programmers using algorithmic strategies. As a particular case of Neural Net a Multilayer Perception developed by programming in C language on OS9 real time operating system is presented. A detailed description about the program structure and practical use are included. Finally, several application examples that have been treated with the tool are presented, and some suggestions about hardware implementations. (Author) 15 refs
Labrador, I.; Carrasco, R.; Martinez, L.
This paper describes a practical introduction to the use of Artificial Neural Networks. Artificial Neural Nets are often used as an alternative to the traditional symbolic manipulation and first order logic used in Artificial Intelligence, due the high degree of difficulty to solve problems that can not be handled by programmers using algorithmic strategies. As a particular case of Neural Net a Multilayer Perception developed by programming in C language on OS9 real time operating system is presented. A detailed description about the program structure and practical use are included. Finally, several application examples that have been treated with the tool are presented, and some suggestions about hardware implementations. (Author) 15 refs.
The typical BDI (belief desire intention) model of agent is not efficiently computable and the strict logic expression is not easily applicable to the AUV (autonomous underwater vehicle) domain with uncertainties. In this paper, an AUV fuzzy neural BDI model is proposed. The model is a fuzzy neural network composed of five layers: input ( beliefs and desires) , fuzzification, commitment, fuzzy intention, and defuzzification layer. In the model, the fuzzy commitment rules and neural network are combined to form intentions from beliefs and desires. The model is demonstrated by solving PEG (pursuit-evasion game), and the simulation result is satisfactory.
Chronic coughing was acknowledged to result from pathological state of the respiratory organs. Cardiac diseases could be accompanied by coughing as well. It was recommended to perform x-ray examinations, including biomedical radiography of the chest, computerized tomography, scintiscanning with 67Ga-citrate, bronchi examination in order to exclude heart disease. The complex examination permitted to detect localization and type of the changes in the lungs and mediastinum, to distinguish benign tumor from malignant one
Lakra, Sachin; T. V. Prasad; G. Ramakrishna
The paper describes some recent developments in neural networks and discusses the applicability of neural networks in the development of a machine that mimics the human brain. The paper mentions a new architecture, the pulsed neural network that is being considered as the next generation of neural networks. The paper also explores the use of memristors in the development of a brain-like computer called the MoNETA. A new model, multi/infinite dimensional neural networks, are a recent developme...
Current research in Artificial Neural Networks indicates that networks offer some potential advantages in adaptation and fault tolerance. This research is directed at determining the possible applicability of neural networks to aircraft control. The first application will be to aircraft trim. Neural network node characteristics, network topology and operation, neural network learning and example histories using neighboring optimal control with a neural net are discussed.
The application of neural networks in the data mining is very wide. Although neural networks may have complex structure, long training time, and uneasily understandable representation of results, neural networks have high acceptance ability for noisy data and high accuracy and are preferable in data mining. In this paper the data mining based on neural networks is researched in detail, and the key technology and ways to achieve the data mining based on neural networks are also researched.
The relationships between artificial neural networks and graph theory are considered in detail. The applications of artificial neural networks to many difficult problems of graph theory, especially NP-complete problems, and the applications of graph theory to artificial neural networks are discussed. For example graph theory is used to study the pattern classification problem on the discrete type feedforward neural networks, and the stability analysis of feedback artificial neural networks etc.
Full Text Available The neurological mechanism used for generating rhythmic patterns for functions such as swallowing, walking, and chewing has been modeled computationally by the neural oscillator. It has been widely studied by biologists to model various aspects of organisms and by computer scientists and robotics engineers as a method for controlling and coordinating the gaits of walking robots. Although there has been significant study in this area, it is difficult to find basic guidelines for programming neural oscillators. In this paper, the authors approach neural oscillators from a programmer’s point of view, providing background and examples for developing neural oscillators to generate rhythmic patterns that can be used in biological modeling and robotics applications.
Bayro-Corrochano, E J
This paper shows the analysis and design of feedforward neural networks using the coordinate-free system of Clifford or geometric algebra. It is shown that real-, complex-, and quaternion-valued neural networks are simply particular cases of the geometric algebra multidimensional neural networks and that some of them can also be generated using support multivector machines (SMVMs). Particularly, the generation of radial basis function for neurocomputing in geometric algebra is easier using the SMVM, which allows one to find automatically the optimal parameters. The use of support vector machines in the geometric algebra framework expands its sphere of applicability for multidimensional learning. Interesting examples of nonlinear problems show the effect of the use of an adequate Clifford geometric algebra which alleviate the training of neural networks and that of SMVMs. PMID:18249926
Krogh, Anders Stærmose; Riis, Søren Kamaric
A general framework for hybrids of hidden Markov models (HMMs) and neural networks (NNs) called hidden neural networks (HNNs) is described. The article begins by reviewing standard HMMs and estimation by conditional maximum likelihood, which is used by the HNN. In the HNN, the usual HMM probability...... parameters are replaced by the outputs of state-specific neural networks. As opposed to many other hybrids, the HNN is normalized globally and therefore has a valid probabilistic interpretation. All parameters in the HNN are estimated simultaneously according to the discriminative conditional maximum...... likelihood criterion. The HNN can be viewed as an undirected probabilistic independence network (a graphical model), where the neural networks provide a compact representation of the clique functions. An evaluation of the HNN on the task of recognizing broad phoneme classes in the TIMIT database shows clear...
Ruttor, Andreas; Kinzel, Wolfgang; Shacham, Lanir; Kanter, Ido
Neural cryptography is based on a competition between attractive and repulsive stochastic forces. A feedback mechanism is added to neural cryptography which increases the repulsive forces. Using numerical simulations and an analytic approach, the probability of a successful attack is calculated for different model parameters. Scaling laws are derived which show that feedback improves the security of the system. In addition, a network with feedback generates a pseudorandom bit sequence which can be used to encrypt and decrypt a secret message.
Zaremba, Wojciech; Sutskever, Ilya; Vinyals, Oriol
We present a simple regularization technique for Recurrent Neural Networks (RNNs) with Long Short-Term Memory (LSTM) units. Dropout, the most successful technique for regularizing neural networks, does not work well with RNNs and LSTMs. In this paper, we show how to correctly apply dropout to LSTMs, and show that it substantially reduces overfitting on a variety of tasks. These tasks include language modeling, speech recognition, image caption generation, and machine translation.
Graves, Alex; Wayne, Greg; Danihelka, Ivo
We extend the capabilities of neural networks by coupling them to external memory resources, which they can interact with by attentional processes. The combined system is analogous to a Turing Machine or Von Neumann architecture but is differentiable end-to-end, allowing it to be efficiently trained with gradient descent. Preliminary results demonstrate that Neural Turing Machines can infer simple algorithms such as copying, sorting, and associative recall from input and output examples.
Greene, Nicholas D. E.; Copp, Andrew J.
Neural tube defects (NTDs), including spina bifida and anencephaly, are severe birth defects of the central nervous system that originate during embryonic development when the neural tube fails to close completely. Human NTDs are multifactorial, with contributions from both genetic and environmental factors. The genetic basis is not yet well understood, but several nongenetic risk factors have been identified as have possibilities for prevention by maternal folic acid supplementation. Mechani...
Reed, Scott; De Freitas, Nando
We propose the neural programmer-interpreter (NPI): a recurrent and compositional neural network that learns to represent and execute programs. NPI has three learnable components: a task-agnostic recurrent core, a persistent key-value program memory, and domain-specific encoders that enable a single NPI to operate in multiple perceptually diverse environments with distinct affordances. By learning to compose lower-level programs to express higher-level programs, NPI reduces sample complexity ...
The goal of this work is construction of an artificial life model and simulation of organisms in an environment with food. Organisms survive if they find food successfuly. With evolution and learning organisms develop a neural network which enables that. First neural networks and their history are introduced with the basic concepts like a neuron model, a network, transfer functions, topologies and learning. I describe the backpropagation learning on multilayer feed forward network and dem...
Denoyer, Ludovic; Gallinari, Patrick
Neural Networks sequentially build high-level features through their successive layers. We propose here a new neural network model where each layer is associated with a set of candidate mappings. When an input is processed, at each layer, one mapping among these candidates is selected according to a sequential decision process. The resulting model is structured according to a DAG like architecture, so that a path from the root to a leaf node defines a sequence of transformations. Instead of c...
Buysse, Daniel J.
Ms. F, a 42-year-old divorced woman, presents for evaluation of chronic insomnia. She complains of difficulty falling asleep, often 30 minutes or longer, and difficulty maintaining sleep during the night, with frequent awakenings that often last 30 minutes or longer. These symptoms occur nearly every night, with only one or two “good” nights per month. She typically goes to bed around 10:00 p.m. to give herself adequate time for sleep, and she gets out of bed around 7:00 a.m. on work days and...
The inverse, crack identification problem in elasticity can be formulated as an output error minimization problem which, nevertheless, can not be solved without difficulties by classical numerical optimization. A review of all these previous results, where we used neural networks, filter-driven optimization and genetic algorithms is presented and in a companion lecture during this conference. The use of neural networks for the solution of the inverse problem makes possible the on-line solution of the problem. In fact, one usually approximates the inverse mapping (measurements versus crack quantities). Most of the effort is spent for the learning of this relation, while a sufficiently trained neural network provides predictions with, practically, zero computational cost. Potential applications include on-line, in-flight health monitoring systems with applications in civil and mechanical engineering and production control. In this paper we present new developments in the design of specialized neural networks for the solution of the crack identification problem. Emphasis is posed on the effective use of the learning data, which are produced by the boundary element method. Several technical data will be discussed. They include thoughts about the effective choice of the neural network architecture, the number of training examples and of the learning algorithms will be provided, together with the results of our recent numerical investigation. A detailed application for one or more elliptical cracks using static analysis results with the use of back-propagation trained neural networks will be provided. The general methodology follows our previously published results. By using more refined algorithms for the numerical solution of the neural network learning problem, which are based on the MERLIN optimization system developed in the department of the second author, we are able to solve complicated tasks. First results based on dynamic investigations (wave propagation driven
Full Text Available The aim of this report is to analyze the relationships between reward and learning and memory processes. Different studies have described how information about rewards influences behavior and how the brain uses this reward information to control learning and memory processes. Reward nature seems to be processed in different ways by neurons in different brain structures, ranging from the detection and perception of rewards to the use of information about predicted rewards for the control of goal-directed behavior. The neural substrate underling this processing of reward information is a reliable way of improving learning and memory processes. Evidence from several studies indicates that this neural system can facilitate memory consolidation in a wide variety of learning tasks. From a molecular perspective, certain cardinal features of reward have been described as forms of memory. Studies of human addicts and studies in animal models of addiction show that chronic drug exposure produces stable changes in the brain at the cellular and molecular levels that underlie the long-lasting behavioral plasticity associated with addiction. These molecular and cellular adaptations involved in addiction are also implicated in learning and memory processes. Dopamine seems to be a critical common signal to activate different genetic mechanisms that ultimately remodel synapses and circuits. Despite memory is an active and complex process mediated by different brain areas, the neural substrate of reward is able to improve memory consolidation in a several paradigms. We believe that there are many equivalent traits between reward and learning and memory processes.
Lesscher, Heidi M B; Vanderschuren, Louk J M J
Drug addiction is a chronic relapsing brain disease, characterized by compulsive drug use. Despite the fact that drug addiction affects millions of people worldwide, treatments for this disorder are limited in number and efficacy. In our opinion, understanding the neural underpinnings of drug addiction would open new avenues for the development of innovative treatments for this disorder. Based on an awareness that drug use and drug reward do not equal drug addiction, there has been increasing interest in developing animal models of addiction that mimick the loss of control over drug use more closely than existing models aimed at studying drug reward. The present review provides an overview of animal studies of compulsive drug use and the neural mechanisms involved. First, the employed models are summarized, with a particular emphasis on models of escalation of drug use and resistance to punishment. Next, we discuss mechanisms within the (ventral and dorsal) striatum and (central) amygdala that have recently been implicated in the compulsive seeking and taking of alcohol and cocaine. The studies discussed here provide a promising line of research that will advance our knowledge of the neural circuits involved in the self-destructive behavior that characterizes drug addiction. PMID:23079511
Møller, A. R.
The brain's ability to change its organization and function is necessary for normal development of the nervous system and it makes it possible to adapt to changing demands but it can also cause disorders when going awry. This property, known as neural plasticity, is only evident when induced, very much like genes. Plastic changes may be programmed and providing a ``midcourse correction" during childhood development. If that is not executed in the normal way severe developmental disorders such as autism may results. Normal development of functions and anatomical organization of the brain and the spinal cord depend on appropriate sensory stimulation and motor activations. So-called enriched sensory environments have been shown to be beneficial for cognitive development and enriched acoustic environment may even slow the progression of age-related hearing loss. It is possible that the beneficial effect of physical exercise is achieved through activation of neural plasticity. The beneficial effect of training after trauma to the brain or spinal cord is mainly achieved through shifting functions from damaged brain area to other parts of the central nervous system and adapting these parts to take over the functions that are lost. This is accomplished through activation of neural plasticity. Plastic changes can also be harmful and cause symptoms and signs of disorders such as some forms of chronic pain (central neuropathic pain) and severe tinnitus. We will call such disorders ``plasticity disorders".
In the research of rule extraction from neural networks, fidelity describes how well the rules mimic the behavior of a neural network while accuracy describes how well the rules can be generalized. This paper identifies the fidelity-accuracy dilemma. It argues to distinguish rule extraction using neural networks and rule extraction for neural networks according to their different goals, where fidelity and accuracy should be excluded from the rule quality evaluation framework, respectively.
Jongepier, A.G. (KEMA NV, Arnhem (Netherlands))
Artificial neural networks are a new form of artificial intelligence. At this moment KEMA NV is examining the possibilities of applying artificial neural networks to processes that are related to power systems. A number of applications already gives hopeful results. Artificial neural networks are suited to pattern recognition. If a problem can be formulated in terms of pattern recognition, an artificial neural network may give a valuable contribution to the solution of this problem. 8 figs., 15 refs.
In recent years, several neural networks using Clifford algebra have been studied. Clifford algebra is also called geometric algebra. Complex-valued Hopfield neural networks (CHNNs) are the most popular neural networks using Clifford algebra. The aim of this brief is to construct hyperbolic HNNs (HHNNs) as an analog of CHNNs. Hyperbolic algebra is a Clifford algebra based on Lorentzian geometry. In this brief, a hyperbolic neuron is defined in a manner analogous to a phasor neuron, which is a typical complex-valued neuron model. HHNNs share common concepts with CHNNs, such as the angle and energy. However, HHNNs and CHNNs are different in several aspects. The states of hyperbolic neurons do not form a circle, and, therefore, the start and end states are not identical. In the quantized version, unlike complex-valued neurons, hyperbolic neurons have an infinite number of states. PMID:24808287
The note addresses introduction to signal analysis and classification based on artificial feed-forward neural networks.......The note addresses introduction to signal analysis and classification based on artificial feed-forward neural networks....
Neural tube defects refer to any defect in the morphogenesis of the neural tube, the most common types being spina bifida and anencephaly. Spina bifida has been recognised in skeletons found in north-eastern Morocco and estimated to have an age of almost 12 000 years. It was also known to the ancient Greek and Arabian physicians who thought that the bony defect was due to the tumour. The term spina bifida was first used by Professor Nicolai Tulp of Amsterdam in 1652. Many other terms have bee...
Telzer, Eva H; Fuligni, Andrew J.; Lieberman, Matthew D.; MIERNICKI, MICHELLE E.; Galván, Adriana
Adolescents' peer culture plays a key role in the development and maintenance of risk-taking behavior. Despite recent advances in developmental neuroscience suggesting that peers may increase neural sensitivity to rewards, we know relatively little about how the quality of peer relations impact adolescent risk taking. In the current 2-year three-wave longitudinal study, we examined how chronic levels of peer conflict relate to risk taking behaviorally and neurally, and whether this is modifie...
Full Text Available Morphine is one of the most potent alkaloid in opium, which has substantial medical uses and needs and it is the first active principle purified from herbal source. Morphine has commonly been used for relief of moderate to severe pain as it acts directly on the central nervous system; nonetheless, its chronic abuse increases tolerance and physical dependence, which is commonly known as opiate addiction. Morphine withdrawal syndrome is physiological and behavioral symptoms that stem from prolonged exposure to morphine. A majority of brain regions are hypofunctional over prolonged abstinence and acute morphine withdrawal. Furthermore, several neural mechanisms are likely to contribute to morphine withdrawal. The present review summarizes the literature pertaining to neural mechanisms underlying morphine withdrawal. Despite the fact that morphine withdrawal is a complex process, it is suggested that neural mechanisms play key roles in morphine withdrawal.
... myeloproliferative neoplasms, leukemia , and other conditions . Chronic Myelomonocytic Leukemia Key Points Chronic myelomonocytic leukemia is a disease ... chance of recovery) and treatment options. Chronic myelomonocytic leukemia is a disease in which too many myelocytes ...
... from the NHLBI on Twitter. Living With Chronic Bronchitis If you have chronic bronchitis, you can take steps to control your symptoms. ... and a pneumonia vaccine. If you have chronic bronchitis, you may benefit from pulmonary rehabilitation (PR). PR ...
Mathematical model of supervised learning by artificial neural network provides for simultaneous adjustments of both temperatures of neurons and synaptic weights, and includes feedback as well as feedforward synaptic connections. Extension of mathematical model described in "Adaptive Neurons For Artificial Neural Networks" (NPO-17803). Dynamics of neural network represented in new model by less-restrictive continuous formalism.
Kerr, Abigail L.; Cheng, Shao-Ying; Jones, Theresa A.
Behavioral experience is at work modifying the structure and function of the brain throughout the lifespan, but it has a particularly dramatic influence after brain injury. This review summarizes recent findings on the role of experience in reorganizing the adult damaged brain, with a focus on findings from rodent stroke models of chronic upper extremity (hand and arm) impairments. A prolonged and widespread process of repair and reorganization of surviving neural circuits is instigated by in...
Spira, Micha E.; Hai, Aviad
At present, the prime methodology for studying neuronal circuit-connectivity, physiology and pathology under in vitro or in vivo conditions is by using substrate-integrated microelectrode arrays. Although this methodology permits simultaneous, cell-non-invasive, long-term recordings of extracellular field potentials generated by action potentials, it is 'blind' to subthreshold synaptic potentials generated by single cells. On the other hand, intracellular recordings of the full electrophysiological repertoire (subthreshold synaptic potentials, membrane oscillations and action potentials) are, at present, obtained only by sharp or patch microelectrodes. These, however, are limited to single cells at a time and for short durations. Recently a number of laboratories began to merge the advantages of extracellular microelectrode arrays and intracellular microelectrodes. This Review describes the novel approaches, identifying their strengths and limitations from the point of view of the end users -- with the intention to help steer the bioengineering efforts towards the needs of brain-circuit research.
This lecture is a presentation of today's research in neural computation. Neural computation is inspired by knowledge from neuro-science. It draws its methods in large degree from statistical physics and its potential applications lie mainly in computer science and engineering. Neural networks models are algorithms for cognitive tasks, such as learning and optimization, which are based on concepts derived from research into the nature of the brain. The lecture first gives an historical presentation of neural networks development and interest in performing complex tasks. Then, an exhaustive overview of data management and networks computation methods is given: the supervised learning and the associative memory problem, the capacity of networks, the Perceptron networks, the functional link networks, the Madaline (Multiple Adalines) networks, the back-propagation networks, the reduced coulomb energy (RCE) networks, the unsupervised learning and the competitive learning and vector quantization. An example of application in high energy physics is given with the trigger systems and track recognition system (track parametrization, event selection and particle identification) developed for the CPLEAR experiment detectors from the LEAR at CERN. (J.S.). 56 refs., 20 figs., 1 tab., 1 appendix
Hansen, Lars Kai; Salamon, Peter
We propose several means for improving the performance an training of neural networks for classification. We use crossvalidation as a tool for optimizing network parameters and architecture. We show further that the remaining generalization error can be reduced by invoking ensembles of similar...... networks....
Kussul, Ernst; Baidyk, Tatiana; Wunsch, Donald C.
The title of the book, "Neural Networks and Micromechanics," seems artificial. However, the scientific and technological developments in recent decades demonstrate a very close connection between the two different areas of neural networks and micromechanics. The purpose of this book is to demonstrate this connection. Some artificial intelligence (AI) methods, including neural networks, could be used to improve automation system performance in manufacturing processes. However, the implementation of these AI methods within industry is rather slow because of the high cost of conducting experiments using conventional manufacturing and AI systems. To lower the cost, we have developed special micromechanical equipment that is similar to conventional mechanical equipment but of much smaller size and therefore of lower cost. This equipment could be used to evaluate different AI methods in an easy and inexpensive way. The proved methods could be transferred to industry through appropriate scaling. In this book, we describe the prototypes of low cost microequipment for manufacturing processes and the implementation of some AI methods to increase precision, such as computer vision systems based on neural networks for microdevice assembly and genetic algorithms for microequipment characterization and the increase of microequipment precision.
Full Text Available Sabra M Abbott,1 Aleksandar Videnovic21Department of Neurology, Northwestern Feinberg School of Medicine, Chicago, IL, USA; 2Department of Neurology, Massachusetts General Hospital, Harvard Medical School, Boston, MA, USA Abstract: Sleep–wake disruption is frequently observed and often one of the earliest reported symptoms of many neurodegenerative disorders. This provides insight into the underlying pathophysiology of these disorders, as sleep–wake abnormalities are often accompanied by neurodegenerative or neurotransmitter changes. However, in addition to being a symptom of the underlying neurodegenerative condition, there is also emerging evidence that sleep disturbance itself may contribute to the development and facilitate the progression of several of these disorders. Due to its impact both as an early symptom and as a potential factor contributing to ongoing neurodegeneration, the sleep–wake cycle is an ideal target for further study for potential interventions not only to lessen the burden of these diseases but also to slow their progression. In this review, we will highlight the sleep phenotypes associated with some of the major neurodegenerative disorders, focusing on the circadian disruption associated with Alzheimer’s disease, the rapid eye movement behavior disorder and sleep fragmentation associated with Parkinson’s disease, and the insomnia and circadian dysregulation associated with Huntington’s disease. Keywords: sleep, neurodegeneration, Alzheimer's disease, Parkinson's disease, Huntington's disease
Abbott SM; Videnovic A
Sabra M Abbott,1 Aleksandar Videnovic21Department of Neurology, Northwestern Feinberg School of Medicine, Chicago, IL, USA; 2Department of Neurology, Massachusetts General Hospital, Harvard Medical School, Boston, MA, USA Abstract: Sleep–wake disruption is frequently observed and often one of the earliest reported symptoms of many neurodegenerative disorders. This provides insight into the underlying pathophysiology of these disorders, as sleep–wake abnormalities are often accomp...
Sabra M Abbott,1 Aleksandar Videnovic21Department of Neurology, Northwestern Feinberg School of Medicine, Chicago, IL, USA; 2Department of Neurology, Massachusetts General Hospital, Harvard Medical School, Boston, MA, USA Abstract: Sleep–wake disruption is frequently observed and often one of the earliest reported symptoms of many neurodegenerative disorders. This provides insight into the underlying pathophysiology of these disorders, as sleep–wake abnormalities are ofte...
This paper presents a flexible microelectromechanical systems (MEMS) neural probe that minimizes neuron damage and immune response, suitable for chronic recording applications. MEMS neural probes with various features such as high electrode densities have been actively investigated for neuron stimulation and recording to study brain functions. However, successful recording of neural signals in chronic application using rigid silicon probes still remains challenging because of cell death and macrophages accumulated around the electrodes over time from continuous brain movement. Thus, in this paper, we propose a new flexible MEMS neural probe that consists of two segments: a polyimide-based, flexible segment for connection and a rigid segment composed of thin silicon for insertion. While the flexible connection segment is designed to reduce the long-term chronic neuron damage, the thin insertion segment is designed to minimize the brain damage during the insertion process. The proposed flexible neural probe was successfully fabricated using the MEMS process on a silicon on insulator wafer. For a successful insertion, a biodegradable sucrose gel is coated on the flexible segment to temporarily increase the probe stiffness to prevent buckling. After the insertion, the sucrose gel dissolves inside the brain exposing the polyimide probe. By performing an insertion test, we confirm that the flexible probe has enough stiffness. In addition, by monitoring immune responses and brain histology, we successfully demonstrate that the proposed flexible neural probe incurs fivefold less neural damage than that incurred by a conventional silicon neural probe. Therefore, the presented flexible neural probe is a promising candidate for recording stable neural signals for long-time chronic applications. (paper)
Jeon, Myounggun; Cho, Jeiwon; Kim, Yun Kyung; Jung, Dahee; Yoon, Eui-Sung; Shin, Sehyun; Cho, Il-Joo
This paper presents a flexible microelectromechanical systems (MEMS) neural probe that minimizes neuron damage and immune response, suitable for chronic recording applications. MEMS neural probes with various features such as high electrode densities have been actively investigated for neuron stimulation and recording to study brain functions. However, successful recording of neural signals in chronic application using rigid silicon probes still remains challenging because of cell death and macrophages accumulated around the electrodes over time from continuous brain movement. Thus, in this paper, we propose a new flexible MEMS neural probe that consists of two segments: a polyimide-based, flexible segment for connection and a rigid segment composed of thin silicon for insertion. While the flexible connection segment is designed to reduce the long-term chronic neuron damage, the thin insertion segment is designed to minimize the brain damage during the insertion process. The proposed flexible neural probe was successfully fabricated using the MEMS process on a silicon on insulator wafer. For a successful insertion, a biodegradable sucrose gel is coated on the flexible segment to temporarily increase the probe stiffness to prevent buckling. After the insertion, the sucrose gel dissolves inside the brain exposing the polyimide probe. By performing an insertion test, we confirm that the flexible probe has enough stiffness. In addition, by monitoring immune responses and brain histology, we successfully demonstrate that the proposed flexible neural probe incurs fivefold less neural damage than that incurred by a conventional silicon neural probe. Therefore, the presented flexible neural probe is a promising candidate for recording stable neural signals for long-time chronic applications.
Full Text Available Chronic urticaria (CU is a disturbing allergic condition of the skin. Although frequently benign, it may sometimes be a red flag sign of a serious internal disease. A multitude of etiologies have been implicated in the causation of CU, including physical, infective, vasculitic, psychological and idiopathic. An autoimmune basis of most of the ′idiopathic′ forms is now hypothesized. Histamine released from mast cells is the major effector in pathogenesis and it is clinically characterized by wheals that have a tendency to recur. Laboratory investigations aimed at a specific etiology are not always conclusive, though may be suggestive of an underlying condition. A clinical search for associated systemic disease is strongly advocated under appropriate circumstances. The mainstay of treatment remains H1 antihistaminics. These may be combined with complementary pharmacopeia in the form of H2 blockers, doxepin, nifedipine and leukotriene inhibitors. More radical therapy in the form of immunoglobulins, plasmapheresis and cyclophosphamide may be required for recalcitrant cases. Autologous transfusion and alternative remedies like acupuncture have prospects for future. A stepwise management results in favorable outcomes. An update on CU based on our experience with patients at a tertiary care centre is presented.
Skosnik, Patrick D; Cortes-Briones, Jose A; Hajós, Mihály
Evidence has accumulated over the past several decades suggesting that both exocannabinoids and endocannabinoids play a role in the pathophysiology of schizophrenia. The current article presents evidence suggesting that one of the mechanisms whereby cannabinoids induce psychosis is through the alteration in synchronized neural oscillations. Neural oscillations, particularly in the gamma (30-80 Hz) and theta (4-7 Hz) ranges, are disrupted in schizophrenia and are involved in various areas of perceptual and cognitive function. Regarding cannabinoids, preclinical evidence from slice and local field potential recordings has shown that central cannabinoid receptor (cannabinoid receptor type 1) agonists decrease the power of neural oscillations, particularly in the gamma and theta bands. Further, the administration of cannabinoids during critical stages of neural development has been shown to disrupt the brain's ability to generate synchronized neural oscillations in adulthood. In humans, studies examining the effects of chronic cannabis use (utilizing electroencephalography) have shown abnormalities in neural oscillations in a pattern similar to those observed in schizophrenia. Finally, recent studies in humans have also shown disruptions in neural oscillations after the acute administration of delta-9-tetrahydrocannabinol, the primary psychoactive constituent in cannabis. Taken together, these data suggest that both acute and chronic cannabinoids can disrupt the ability of the brain to generate synchronized oscillations at functionally relevant frequencies. Hence, this may represent one of the primary mechanisms whereby cannabinoids induce disruptions in attention, working memory, sensory-motor integration, and many other psychosis-related behavioral effects. PMID:26850792
Schei, Jennifer Lynn
Optical imaging technologies can be used to record neural and hemodynamic activity. Neural activity elicits physiological changes that alter the optical tissue properties. Specifically, changes in polarized light are concomitant with neural depolarization. We measured polarization changes from an isolated lobster nerve during action potential propagation using both reflected and transmitted light. In transmission mode, polarization changes were largest throughout the center of the nerve, suggesting that most of the optical signal arose from the inner nerve bundle. In reflection mode, polarization changes were largest near the edges, suggesting that most of the optical signal arose from the outer sheath. To overcome irregular cell orientation found in the brain, we measured polarization changes from a nerve tied in a knot. Our results show that neural activation produces polarization changes that can be imaged even without regular cell orientations. Neural activation expends energy resources and elicits metabolic delivery through blood vessel dilation, increasing blood flow and volume. We used spectroscopic imaging techniques combined with electrophysiological measurements to record evoked neural and hemodynamic responses from the auditory cortex of the rat. By using implantable optics, we measured responses across natural wake and sleep states, as well as responses following different amounts of sleep deprivation. During quiet sleep, evoked metabolic responses were larger compared to wake, perhaps because blood vessels were more compliant. When animals were sleep deprived, evoked hemodynamic responses were smaller following longer periods of deprivation. These results suggest that prolonged neural activity through sleep deprivation may diminish vascular compliance as indicated by the blunted vascular response. Subsequent sleep may allow vessels to relax, restoring their ability to deliver blood. These results also suggest that severe sleep deprivation or chronic
Rebecca A. Butler; Lambon Ralph, Matthew A.; Woollams, Anna M.
Stroke aphasia is a multidimensional disorder in which patient profiles reflect variation along multiple behavioural continua. We present a novel approach to separating the principal aspects of chronic aphasic performance and isolating their neural bases. Principal components analysis was used to extract core factors underlying performance of 31 participants with chronic stroke aphasia on a large, detailed battery of behavioural assessments. The rotated principle components analysis revealed ...
Kass, Robert E; Brown, Emery N
Continual improvements in data collection and processing have had a huge impact on brain research, producing data sets that are often large and complicated. By emphasizing a few fundamental principles, and a handful of ubiquitous techniques, Analysis of Neural Data provides a unified treatment of analytical methods that have become essential for contemporary researchers. Throughout the book ideas are illustrated with more than 100 examples drawn from the literature, ranging from electrophysiology, to neuroimaging, to behavior. By demonstrating the commonality among various statistical approaches the authors provide the crucial tools for gaining knowledge from diverse types of data. Aimed at experimentalists with only high-school level mathematics, as well as computationally-oriented neuroscientists who have limited familiarity with statistics, Analysis of Neural Data serves as both a self-contained introduction and a reference work.
Full Text Available Neural tube defects refer to any defect in the morphogenesis of the neural tube, the most common types being spina bifida and anencephaly. Spina bifida has been recognised in skeletons found in north-eastern Morocco and estimated to have an age of almost 12 000 years. It was also known to the ancient Greek and Arabian physicians who thought that the bony defect was due to the tumour. The term spina bifida was first used by Professor Nicolai Tulp of Amsterdam in 1652. Many other terms have been used to describe this defect, but spina bifida remains the most useful general term, as it describes the separation of the vertebral elements in the midline.
Brandsborg, B; Nikolajsen, L; Kehlet, Henrik;
BACKGROUND: Chronic pain is a well-known adverse effect of surgery, but the risk of chronic pain after gynaecological surgery is less established. METHOD: This review summarizes studies on chronic pain following hysterectomy. The underlying mechanisms and risk factors for the development of chronic...... post-hysterectomy pain are discussed. RESULTS AND CONCLUSION: Chronic pain is reported by 5-32% of women after hysterectomy. A guideline is proposed for future prospective studies. Udgivelsesdato: 2008-Mar...
Häuser, Winfried; Wolfe, Frederik; Henningsen, Peter; Schmutzer, Gabriele; Brähler, Elmar; Hinz, Andreas
Background: Chronic pain is a major public health problem. The impact of stages of chronic pain adjusted for disease load on societal burden has not been assessed in population surveys. Methods: A cross-sectional survey with 4360 people aged ≥ 14 years representative of the German population was conducted. Measures obtained included demographic variables, presence of chronic pain (based on the definition of the International Association for the Study of Pain), chronic pain stages (by chronic ...
Full Text Available An artificial neural network is an information-processing paradigm that is inspired by the way biological nervous systems, such as the brain, process information. The key element of this paradigm is the novel structure of the information processing system. It is composed of a large number of highly interconnected processing elements (neurons working in unison to solve specific problems. Ann’s, like people, learn by example.
Collobert, Ronan; Kavukcuoglu, Koray; Farabet, Clément; Montavon, Grégoire; Orr, Geneviève; Müller, K.-R.
Neural networks and machine learning algorithms in general require a flexible environment where new algorithm prototypes and experiments can be set up as quickly as possible with best possible computational performance. To that end, we provide a new framework called Torch7, that is especially suited to achieve both of these competing goals. Torch7 is a versatile numeric computing framework and machine learning library that extends a very lightweight and powerful programming language Lua. Its ...
Kolling, Nils; Behrens, Timothy EJ; Mars, Rogier B.; Rushworth, Matthew FS
Behavioural economic studies, involving limited numbers of choices, have provided key insights into neural decision-making mechanisms. By contrast, animals’ foraging choices arise in the context of sequences of encounters with prey/food. On each encounter the animal chooses to engage or whether the environment is sufficiently rich that searching elsewhere is merited. The cost of foraging is also critical. We demonstrate humans can alternate between two modes of choice, comparative decision-ma...
Venkatesan, Ragav; Gattupalli, Vijetha; Li, Baoxin
Often the filters learned by Convolutional Neural Networks (CNNs) from different datasets appear similar. This is prominent in the first few layers. This similarity of filters is being exploited for the purposes of transfer learning and some studies have been made to analyse such transferability of features. This is also being used as an initialization technique for different tasks in the same dataset or for the same task in similar datasets. Off-the-shelf CNN features have capitalized on thi...
This book covers theoretical aspects as well as recent innovative applications of Artificial Neural networks (ANNs) in natural, environmental, biological, social, industrial and automated systems. It presents recent results of ANNs in modelling small, large and complex systems under three categories, namely, 1) Networks, Structure Optimisation, Robustness and Stochasticity 2) Advances in Modelling Biological and Environmental Systems and 3) Advances in Modelling Social and Economic Systems. The book aims at serving undergraduates, postgraduates and researchers in ANN computational modelling. .
Denby, B. (Fermi National Accelerator Lab., Batavia, IL (USA)); Campbell, M. (Michigan Univ., Ann Arbor, MI (USA)); Bedeschi, F. (Istituto Nazionale di Fisica Nucleare, Pisa (Italy)); Chriss, N.; Bowers, C. (Chicago Univ., IL (USA)); Nesti, F. (Scuola Normale Superiore, Pisa (Italy))
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.
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
Pearlmutter, Barak A
We survey learning algorithms for recurrent neural networks with hidden units and attempt to put the various techniques into a common framework. We discuss fixpoint learning algorithms, namely recurrent backpropagation and deterministic Boltzmann Machines, and non-fixpoint algorithms, namely backpropagation through time, Elman's history cutoff nets, and Jordan's output feedback architecture. Forward propagation, an online technique that uses adjoint equations, is also discussed. In many cases...
Recently, several works in the domain of natural language processing presented successful methods for word embedding. Among them, the Skip-gram (SG) with negative sampling, known also as Word2Vec, advanced the state-of-the-art of various linguistics tasks. In this paper, we propose a scalable Bayesian neural word embedding algorithm that can be beneficial to general item similarity tasks as well. The algorithm relies on a Variational Bayes solution for the SG objective and a detailed step by ...
One of the properties of the nervous system is the use-dependent plasticity of neural circuits.The structure and function of neural circuits are susceptible to changes induced by prior neuronal activity,as reflected by short-and long-term modifications of synaptic efficacy and neuronal excitability.Regarded as the most attractive cellular mechanism underlying higher cognitive functions such as learning and memory,activity-dependent synaptic plasticity has been in the spotlight of modern neuroscience since 1973 when activity-induced long-term potentiation(LTP) of hippocampal synapses was first discovered.Over the last 10 years,Chinese neuroscientists have made notable contributions to the study of the cellular and molecular mechanisms of synaptic plasticity,as well as of the plasticity beyond synapses,including activity-dependent changes in intrinsic neuronal excitability,dendritic integration functions,neuron-glia signaling,and neural network activity.This work highlight some of these significant findings.
chronic exposure to poor optics caused neural insensitivity to fine spatial detail thus adversely limiting the achievable visual benefit when improving the eye's optical quality. Finally, we demonstrated that the altered, but plastic visual system could be re-adapted to improved optics such that it partially recovers its normal mechanism. These findings not only provide vast clinical implications for advanced customized vision correction methodologies for normal, pathologic and presbyopic eyes but also vital scientific insight into the neural processing of the visual system in response to the aberrated optics of the eye.
Heng, Teh Hoon
This book is the first of a series of technical reports of a key research project of the Real-World Computing Program supported by the MITI of Japan.The main goal of the project is to model human intelligence by a special class of mathematical systems called neural logic networks.The book consists of three parts. Part 1 describes the general theory of neural logic networks and their potential applications. Part 2 discusses a new logic called Neural Logic which attempts to emulate more closely the logical thinking process of human. Part 3 studies the special features of neural logic networks wh
Full Text Available Aim of this study is to investigate for the possible connection between abnormal neural crest cell (NCC development and NCC-derived abnormal facial and cerebral structures in 3 children with pyruvate-dehydrogenase (PDH and in 10 cases with oxidative phosphorylation deficiency diagnosed from the Author by standard laboratory assays [i.e. 3 cases of Kearns-Sayre syndrome (KSS, 2 cases of Leigh syndrome, 1 case of KSS with De Toni-Debrè-Fanconi and rachitis (Berio disease, 1 case of KSS with aortic insuffiency and sub-aortic septum hyperthophy, 3 cases of chronic progressive external ophthalmoplegia]. There patients presented with hyperlactacidemia, hyperpyruvicemia and facial abnormalities, similar to those observed in the fetal alcohol syndrome (a typical neurocristopathy due to PDH deficiency, down-regulating NCC genes. The Author hypothesizes that the metabolic defect of scarce energy production is responsible of abnormal NCC proliferation/migration and consequent facial abnormalities.
Recently, Neural Turing Machine and Memory Networks have shown that adding an external memory can greatly ameliorate a traditional recurrent neural network's tendency to forget after a long period of time. Here we present a new design of an external memory, wherein memories are stored in an Euclidean key space $\\mathbb R^n$. An LSTM controller performs read and write via specialized structures called read and write heads, following the design of Neural Turing Machine. It can move a head by ei...
Yongchen eWang; Liang eGuo
Neural stimulation is a critical technique in treating neurological diseases and investigating brain functions. Traditional electrical stimulation uses electrodes to directly create intervening electric fields in the immediate vicinity of neural tissues. Second-generation stimulation techniques directly use light, magnetic fields or ultrasound in a non-contact manner. An emerging generation of non- or minimally invasive neural stimulation techniques is enabled by nanotechnology to achieve a h...
Wang, Yongchen; Guo, Liang
Neural stimulation is a critical technique in treating neurological diseases and investigating brain functions. Traditional electrical stimulation uses electrodes to directly create intervening electric fields in the immediate vicinity of neural tissues. Second-generation stimulation techniques directly use light, magnetic fields or ultrasound in a non-contact manner. An emerging generation of non- or minimally invasive neural stimulation techniques is enabled by nanotechnology to achieve a h...
Parten, C.; Hartson, C.; Maren, A. (Tennessee Univ., Chattanooga, TN (USA)); Pap, R. (Accurate Automation Corp., Chattanooga, TN (US))
Here is a comprehensive guide to architectures, processes, implementation methods, and applications of neural computing systems. Unlike purely theoretical books, this handbook shows how to apply neural processing systems to problems in neurophysiology, control theories, learning theory, pattern recognition, and similar areas. This book discusses neural network theories, and shows where they came from, how they can be used, and how they can be developed for future applications.
Rudmann, Linda; Ordonez, Juan S.; Stieglitz, Thomas
Neural probes are designed to selectively record from or stimulate nerve cells. In optogenetics it is desirable to build miniaturized and long-term stable optical neural probes, in which the light sources can be directly and chronically implanted into the animals to allow free movement and behavior. Because of the size and the beam shape of the available light sources, it is difficult to target single cells as well as spatially localized networks. We therefore investigated design considerations for packages, which encapsulate the light source hermetically and have integrated hemispherical lens structures that enable to focus the light onto the desired region, by optical simulations. Integration of a biconvex lens into the package lid (diameter = 300 μm, material: silicon carbide) increased the averaged absolute irradiance ηA by 298 % compared to a system without a lens and had a spot size of around 120 μm. Solely integrating a plano-convex lens (same diameter and material) results in an ηA of up to 227 %.
Potapov, A.; Ali, M. K.
We consider the problem of stabilizing unstable equilibria by discrete controls (the controls take discrete values at discrete moments of time). We prove that discrete control typically creates a chaotic attractor in the vicinity of an equilibrium. Artificial neural networks with reinforcement learning are known to be able to learn such a control scheme. We consider examples of such systems, discuss some details of implementing the reinforcement learning to controlling unstable equilibria, and show that the arising dynamics is characterized by positive Lyapunov exponents, and hence is chaotic. This chaos can be observed both in the controlled system and in the activity patterns of the controller.
Neurally Augmented Sexual Function (NASF) is a technique utilizing epidural electrodes to restore and improve sexual function. Orgasmic dysfunction is common in adult women, affecting roughly one quarter of populations studied. Many male patients suffering from erectile dysfunction are not candidates for phosphdiesterase therapy due to concomitant nitrate therapy. Positioning the electrodes at roughly the level of the cauda equina allows for stimulation of somatic efferents and afferents as well as modifying sympathetic and parasympathetic activity. Our series of women treated by NASF is described. Our experience shows that the evaluation of potential candidates for both correctable causes and psychological screening are important considerations. PMID:17691397
In order to develop new types of information media and technology, it is essential to model complex and flexible information processing in living systems. This book presents a new approach to modeling complex information processing in living systems. Traditional information-theoretic methods in neural networks are unified in one framework, i.e. a-entropy. This new approach will enable information systems such as computers to imitate and simulate human complex behavior and to uncover the deepest secrets of the human mind.
CGD; Fatal granulomatosis of childhood; Chronic granulomatous disease of childhood; Progressive septic granulomatosis ... In chronic granulomatous disease (CGD), immune system cells called ... some types of bacteria and fungi. This disorder leads to long- ...
... Experiencing Chronic Homelessness Share This: People Experiencing Chronic Homelessness We've made significant progress in our national ... the USICH newsletter. We know how to end homelessness. Let's do it, together. Sign up for our ...
Chronic motor tic disorder is more common than Tourette syndrome . Chronic tics may be forms of Tourette syndrome. Tics usually start at age 5 or 6 and get worse until age 12. They often improve during adulthood.
... can include cramping abdominal pain nausea or vomiting fever chills bloody stools Children with chronic diarrhea who have ... can include cramping, abdominal pain, nausea or vomiting, fever, chills, or bloody stools. Children with chronic diarrhea who ...
... Content Marketing Share this: Main Content Area "Chronic Lyme Disease" What is "chronic Lyme disease?" Lyme disease is an infection caused by ... J Med 357:1422-30, 2008). How is Lyme disease treated? For early Lyme disease, a short ...
Aoki, Tomohiro; Narumiya, Shuh
Chronic inflammation is the basis of various chronic illnesses including cancer and vascular diseases. However, much has yet to be learned how inflammation becomes chronic. Prostaglandins (PGs) are well established as mediators of acute inflammation, and recent studies in experimental animals have provided evidence that they also function in transition to and maintenance of chronic inflammation. One role PGs play in such processes is amplification of cytokine signaling. As such, PGs can facil...
Chaby, Lauren E; Michael J Sheriff; Hirrlinger, Amy M.; Lim, James; Thomas B Fetherston; Braithwaite, Victoria A.
Spatial abilities allow animals to retain and cognitively manipulate information about their spatial environment and are dependent upon neural structures that mature during adolescence. Exposure to stress in adolescence is thought to disrupt neural maturation, possibly compromising cognitive processes later in life. We examined whether exposure to chronic unpredictable stress in adolescence affects spatial ability in late adulthood. We evaluated spatial learning, reference and working memory,...
Neural network capabilities include automatic and organized handling of complex information, quick adaptation to continuously changing environments, nonlinear modeling, and parallel implementation. This viewgraph presentation presents Bellcore work on applications, learning chip computational function, learning system block diagram, neural network equalization, broadband access control, calling-card fraud detection, software reliability prediction, and conclusions.
This paper summarizes neural network applications at the Fermilab Tevatron, including the first online hardware application in high energy physics (muon tracking): the CDF and DO neural network triggers; offline quark/gluon discrimination at CDF; ND a new tool for top to multijets recognition at CDF
Two neural networks are trained to act as an observer and a controller, respectively, to control a non-linear, multi-variable process.......Two neural networks are trained to act as an observer and a controller, respectively, to control a non-linear, multi-variable process....
Snyder, Robin M.
Motivated by the brain, neural networks are a right-brained approach to artificial intelligence that is used to recognize patterns based on previous training. In practice, one would not program an expert system to recognize a pattern and one would not train a neural network to make decisions from rules; but one could combine the best features of…
The purpose of this work is a unified and general treatment of activity in neural networks from a mathematical pOint of view. Possible applications of the theory presented are indica ted throughout the text. However, they are not explored in de tail for two reasons : first, the universal character of n- ral activity in nearly all animals requires some type of a general approach~ secondly, the mathematical perspicuity would suffer if too many experimental details and empirical peculiarities were interspersed among the mathematical investigation. A guide to many applications is supplied by the references concerning a variety of specific issues. Of course the theory does not aim at covering all individual problems. Moreover there are other approaches to neural network theory (see e.g. Poggio-Torre, 1978) based on the different lev els at which the nervous system may be viewed. The theory is a deterministic one reflecting the average be havior of neurons or neuron pools. In this respect the essay is writt...
Dimachkie, Mazen M.; Barohn, Richard J.
Chronic Inflammatory polyneuropathies are an important group of neuromuscular disorders that present chronically and progress over more than 8 weeks, being referred to as chronic inflammatory demyelinating polyneuropathy (CIDP). Despite tremendous progress in elucidating disease pathogenesis, the exact triggering event remains unknown. Our knowledge regarding diagnosis and management of CIDP and its variants continues to expand, resulting in improved opportunities for identification and treat...
Artificial neural networks, simply known as neural networks, have attracted considerable interest in recent years largely because of a growing recognition of the potential of these computational paradigms as powerful alternative models to conventional pattern recognition or function approximation techniques. The neural networks approach is having a profound effect on almost all fields, and has been utilised in fields Where experimental inter-disciplinary work is being carried out. Being a multidisciplinary subject with a broad knowledge base, Nondestructive Testing (NDT) or Nondestructive Evaluation (NDE) is no exception. This paper explains typical applications of neural networks in NDT/NDE. Three promising types of neural networks are highlighted, namely, back-propagation, binary Hopfield and Kohonen's self-organising maps. (Author)
Graben, Peter; Potthast, Roland; Wright, James
With this book, the editors present the first comprehensive collection in neural field studies, authored by leading scientists in the field - among them are two of the founding-fathers of neural field theory. Up to now, research results in the field have been disseminated across a number of distinct journals from mathematics, computational neuroscience, biophysics, cognitive science and others. Starting with a tutorial for novices in neural field studies, the book comprises chapters on emergent patterns, their phase transitions and evolution, on stochastic approaches, cortical development, cognition, robotics and computation, large-scale numerical simulations, the coupling of neural fields to the electroencephalogram and phase transitions in anesthesia. The intended readership are students and scientists in applied mathematics, theoretical physics, theoretical biology, and computational neuroscience. Neural field theory and its applications have a long-standing tradition in the mathematical and computational ...
Kamruzzaman, S M; Siddiquee, Abu Bakar; Mazumder, Md Ehsanul Hoque
This research is to search for alternatives to the resolution of complex medical diagnosis where human knowledge should be apprehended in a general fashion. Successful application examples show that human diagnostic capabilities are significantly worse than the neural diagnostic system. This paper describes a modified feedforward neural network constructive algorithm (MFNNCA), a new algorithm for medical diagnosis. The new constructive algorithm with backpropagation; offer an approach for the incremental construction of near-minimal neural network architectures for pattern classification. The algorithm starts with minimal number of hidden units in the single hidden layer; additional units are added to the hidden layer one at a time to improve the accuracy of the network and to get an optimal size of a neural network. The MFNNCA was tested on several benchmarking classification problems including the cancer, heart disease and diabetes. Experimental results show that the MFNNCA can produce optimal neural networ...
WANG Min; GAO Guang-hong; XIANG Dong-sheng; CAO Mao-yong; JIA Ai-bin; DING Lei; KONG Hui-min
To collect neural activity data from awake, behaving freely animals, we develop miniaturized implantable recording system by the modern chip:Programmable System on Chip(PSoC) and through chronic electrodes in the cortex. With PSoC family member CY8C29466,the system completed operational and instrument amplifiers, filters, timers, AD convertors, and serial communication, etc. The signal processing was dealt with virtual instrument technology. All of these factors can significantly affect the price and development cycle of the project. The result showed that the system was able to record and analyze neural extrocellular discharge generated by neurons continuously for a week or more. This is very useful for the interdisciplinary research of neuroscience and information engineering technique.The circuits and architecture of the devices can be adapted for neurobiology and research with other small animals.
Meteran, Howraman; Backer, Vibeke; Kyvik, Kirsten Ohm; Skytthe, Axel; Thomsen, Simon Francis
BACKGROUND: Smoking is a major risk factor for lung diseases and lower respiratory symptoms, but since not all smokers develop chronic bronchitis and since chronic bronchitis is also diagnosed in never-smokers, it has been suggested that some individuals are more susceptible to develop chronic...... bronchitis due to genetics. OBJECTIVE: To study the relative influence of genetic and environmental factors on the variation in the susceptibility to chronic bronchitis. METHODS: In a population-based questionnaire study of 13,649 twins, 50-71 years of age, from the Danish Twin Registry, we calculated sex......-specific concordance rates and heritability of chronic bronchitis. The response rate was 75%. RESULTS: The prevalence of chronic bronchitis was 9.3% among men and 8.5% among women. The concordance rate for chronic bronchitis was higher in monozygotic twins than in dizygotic twins among women; 0.30 vs. 0.17, but not...
Murphy, Stephen F; Schaeffer, Anthony J; Thumbikat, Praveen
The cause of chronic pelvic pain syndrome (CPPS) has yet to be established. Since the late 1980s, cytokine, chemokine, and immunological classification studies using human samples have focused on identifying biomarkers for CPPS, but no diagnostically beneficial biomarkers have been identified, and these studies have done little to deepen our understanding of the mechanisms underlying chronic prostatic pain. Given the large number of men thought to be affected by this condition and the ineffective nature of current treatments, there is a pressing need to elucidate these mechanisms. Prostatitis types IIIa and IIIb are classified according to the presence of pain without concurrent presence of bacteria; however, it is becoming more evident that, although levels of bacteria are not directly associated with levels of pain, the presence of bacteria might act as the initiating factor that drives primary activation of mast-cell-mediated inflammation in the prostate. Mast cell activation is also known to suppress regulatory T cell (Treg) control of self-tolerance and also activate neural sensitization. This combination of established autoimmunity coupled with peripheral and central neural sensitization can result in the development of multiple symptoms, including pelvic pain and bladder irritation. Identifying these mechanisms as central mediators in CPPS offers new insight into the prospective treatment of the disease. PMID:24686526
Pavlov, Valentin A; Tracey, Kevin J
Research during the last decade has significantly advanced our understanding of the molecular mechanisms at the interface between the nervous system and the immune system. Insight into bidirectional neuro-immune communication has characterized the nervous system as an important partner of the immune system in the regulation of inflammation. Neuronal pathways, including the vagus nerve-based inflammatory reflex, are physiological regulators of immune function and inflammation. In parallel, neuronal function is altered in conditions characterized by immune dysregulation and inflammation. Here, we review these regulatory mechanisms and describe the neural circuitry modulating immunity. Understanding these mechanisms reveals possibilities to use targeted neuromodulation as a therapeutic approach for inflammatory and autoimmune disorders. These findings and current clinical exploration of neuromodulation in the treatment of inflammatory diseases define the emerging field of Bioelectronic Medicine. PMID:26512000
Metzler, R; Kinzel, W; Kanter, I
Several scenarios of interacting neural networks which are trained either in an identical or in a competitive way are solved analytically. In the case of identical training each perceptron receives the output of its neighbor. The symmetry of the stationary state as well as the sensitivity to the used training algorithm are investigated. Two competitive perceptrons trained on mutually exclusive learning aims and a perceptron which is trained on the opposite of its own output are examined analytically. An ensemble of competitive perceptrons is used as decision-making algorithms in a model of a closed market (El Farol Bar problem or the Minority Game. In this game, a set of agents who have to make a binary decision is considered.); each network is trained on the history of minority decisions. This ensemble of perceptrons relaxes to a stationary state whose performance can be better than random. PMID:11088736
Frifelt, J J; Schønheyder, Henrik Carl; Valerius, Niels Henrik;
A boy with chronic granulomatous disease (CGD) developed glomerulonephritis at the age of 12 years. The glomerulonephritis progressed to terminal uraemia at age 15 when maintenance haemodialysis was started. The clinical course was complicated by pulmonary aspergillosis and Pseudomonas septicaemia...
Nishimura, K. (Toshiba Corp., Tokyo (Japan))
The present and future of neural network technologies were reviewed. Neural networks simulate the neurons and synapses of human brain, thus permitting the utilization of heuristic knowledge difficult to describe in a logical manner. Such networks can therefore solve optimization problems, difficult to solve by conventional computers, more rapidly while sacrificing a permissible degree of rigor. In light of these advantages, many attempts have been made to apply neural networks to a variety of engineering fields including character recognition, phonetic recognition diagnosis, operation and so on. Now that these attempts have demonstrated the great potential of neural network technology, its application to practical problems will receive increasing attention. The necessity for fundamental studies on learning algorithms, modularization techniques, hardware technologies and so on will grow in conjunction with the above trends in application. 20 refs., 11 figs., 1 tab.
Artificial neural networks are most suitable for solving problems that are complex, ill-defined, highly nonlinear, of many and different variables, and/or stochastic. Such problems are abundant in medicine, in finance, in security and beyond. This volume covers the basic theory and architecture of the major artificial neural networks. Uniquely, it presents 18 complete case studies of applications of neural networks in various fields, ranging from cell-shape classification to micro-trading in finance and to constellation recognition - all with their respective source codes. These case studies
Zak, Michail A.
Paper discusses approach to mathematical modeling of artificial neural networks exhibiting complicated behaviors reminiscent of creativity and intelligence of biological neural networks. Neural network treated as non-Lipschitzian dynamical system - as described in "Non-Lipschitzian Dynamics For Modeling Neural Networks" (NPO-17814). System serves as tool for modeling of temporal-pattern memories and recognition of complicated spatial patterns.
Oh, Min-Hee; Oh, Sun Young; Lu, Jingning; Lou, Hongfei; Myers, Allen; Zhu, Zhou; Zheng, Tao
Chronic debilitating pruritus is a cardinal feature of a topic dermatitis (AD). Little is known about the underlying mechanisms. Antihistamines lack efficacy in treating itch in AD, suggesting the existence of histamine-independent itch pathways in AD. Transient receptor potential ankyrin 1 (TRPA1) is essential in the signaling pathways that promote histamine-independent itch. In the present study, we tested the hypothesis that TRPA1-dependent neural pathways play a key role in chronic itch i...
Kälin, Samuel; Rausch-Osthoff, Anne-Kathrin; Bauer, Christoph Michael
Background Sensory discrimination training (SDT) for people with chronic low back pain (CLBP) is a novel approach based on theories of the cortical reorganization of the neural system. SDT aims to reverse cortical reorganization, which is observed in chronic pain patients. SDT is still a developing therapeutic approach and its effects have not been systematically reviewed. The aim of this systematic review was to evaluate if SDT decreases pain and improves function in people with CLBP. Method...
Thompson, Alexander C; Fallon, James B; Wise, Andrew K; Wade, Scott A; Shepherd, Robert K; Stoddart, Paul R
At present there is some debate as to the processes by which infrared neural stimulation (INS) activates neurons in the cochlea, as the lasers used for INS can potentially generate a range of secondary stimuli e.g. an acoustic stimulus is produced when the light is absorbed by water. To clarify whether INS in the cochlea requires functioning hair cells and to explore the potential relevance to cochlear implants, experiments using INS were performed in the cochleae of both normal hearing and profoundly deaf guinea pigs. A response to laser stimulation was readily evoked in normal hearing cochlea. However, no response was evoked in any profoundly deaf cochleae, for either acute or chronic deafening, contrary to previous work where a response was observed after acute deafening with ototoxic drugs. A neural response to electrical stimulation was readily evoked in all cochleae after deafening. The absence of a response from optical stimuli in profoundly deaf cochleae suggests that the response from INS in the cochlea is hair cell mediated. PMID:25796297
Baldi, Pierre F.; Toomarian, Nikzad
Modular and hierarchical approach to supervised learning by artificial neural networks leads to neural networks more structured than neural networks in which all neurons fully interconnected. These networks utilize general feedforward flow of information and sparse recurrent connections to achieve dynamical effects. The modular organization, sparsity of modular units and connections, and fact that learning is much more circumscribed are all attractive features for designing neural-network hardware. Learning streamlined by imitating some aspects of biological neural networks.
Wessendorf, Kurt O; Okandan, Murat; Pearson, Sean
A demultiplexer circuit is disclosed which can be used with a conventional neural stimulator to extend the number of electrodes which can be activated. The demultiplexer circuit, which is formed on a semiconductor substrate containing a power supply that provides all the dc electrical power for operation of the circuit, includes digital latches that receive and store addressing information from the neural stimulator one bit at a time. This addressing information is used to program one or more 1:2.sup.N demultiplexers in the demultiplexer circuit which then route neural stimulation signals from the neural stimulator to an electrode array which is connected to the outputs of the 1:2.sup.N demultiplexer. The demultiplexer circuit allows the number of individual electrodes in the electrode array to be increased by a factor of 2.sup.N with N generally being in a range of 2-4.
This book is the second enlarged and revised edition of the first successful monograph on complex-valued neural networks (CVNNs) published in 2006, which lends itself to graduate and undergraduate courses in electrical engineering, informatics, control engineering, mechanics, robotics, bioengineering, and other relevant fields. In the second edition the recent trends in CVNNs research are included, resulting in e.g. almost a doubled number of references. The parametron invented in 1954 is also referred to with discussion on analogy and disparity. Also various additional arguments on the advantages of the complex-valued neural networks enhancing the difference to real-valued neural networks are given in various sections. The book is useful for those beginning their studies, for instance, in adaptive signal processing for highly functional sensing and imaging, control in unknown and changing environment, robotics inspired by human neural systems, and brain-like information processing, as well as interdisciplina...
Bob, P.; Šusta, M.; Chládek, Jan; Glaslová, K.; Fedor-Ferybergh, P.
Roč. 13, č. 10 (2007), HY1-5. ISSN 1234-1010 Institutional research plan: CEZ:AV0Z20650511 Keywords : neural complexity * dissociation * schizophrenia Subject RIV: FH - Neurology Impact factor: 1.607, year: 2007
The intention of this report is to make a systematic examination of the possibilities of applying neural networks in those technical areas, which are familiar to a control engineer. In other words, the potential of neural networks in control applications is given higher priority than a detailed...... study of the networks themselves. With this end in view the following restrictions have been made: - Amongst numerous neural network structures, only the Multi Layer Perceptron (a feed-forward network) is applied. - Amongst numerous training algorithms, only four algorithms are examined, all in a...... recursive form (sample updating). The simplest is the Back Probagation Error Algorithm, and the most complex is the recursive Prediction Error Method using a Gauss-Newton search direction. - Over-fitting is often considered to be a serious problem when training neural networks. This problem is specifically...
Prof. Dr. Abduladhem A. Ali
Full Text Available This paper deals with the applications of Artificial Intelligence techniques for detecting internalfaults in Power generators. Three techniques are used which are Neural Net (NN, FuzzyNeural Net (FNN and Fuzzy Neural Petri Net (FNPN to implement differential protection ofgenerator. MATLAB toolbox has been used for simulations and generation of faults data fortraining the programs for different faults cases and to implement the relays. Results ofdifferent fault cases are presented and these results are compared among the threeimplemented techniques of relays and with the conventional differential relay of generator.
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
Francesca Froldi; Milán Szuperák; Cheng, Louise Y.
In the developing Drosophila CNS, two pools of neural stem cells, the symmetrically dividing progenitors in the neuroepithelium (NE) and the asymmetrically dividing neuroblasts (NBs) generate the majority of the neurons that make up the adult central nervous system (CNS). The generation of a correct sized brain depends on maintaining the fine balance between neural stem cell self-renewal and differentiation, which are regulated by cell-intrinsic and cell-extrinsic cues. In this review, we wil...
Eberhardt, Silvio P.
Concept for design of electronic neural network calls for assembly of very-large-scale integrated (VLSI) circuits of few standard types. Each VLSI chip, which contains both analog and digital circuitry, used in modular or "building-block" fashion by interconnecting it in any of variety of ways with other chips. Feedforward neural network in typical situation operates under control of host computer and receives inputs from, and sends outputs to, other equipment.
Lee, Barry B.
Neural models of retinal processing provide an important tool for analyzing retinal signals and their functional significance. However, it is here argued that in biological reality, retinal connectivity is unlikely to be as specific as ideal neural models might suggest. The retina is thought to provide functionally specific signals, but this specificity is unlikely to be anatomically complete. This is illustrated by examples of cone connectivity to macaque ganglion cells. For example, cells o...
Baldi, Pierre; Chauvin, Yves
After collecting a data base of fingerprint images, we design a neural network algorithm for fingerprint recognition. When presented with a pair of fingerprint images, the algorithm outputs an estimate of the probability that the two images originate from the same finger. In one experiment, the neural network is trained using a few hundred pairs of images and its performance is subsequently tested using several thousand pairs of images originated from a subset of the database corresponding to...
Tagliaferri, Roberto; Longo, Giuseppe; Andreon, Stefano; Capozziello, Salvatore; Donalek, Ciro; Giordano, Gerardo
We present a neural network based approach to the determination of photometric redshift. The method was tested on the Sloan Digital Sky Survey Early Data Release (SDSS-EDR) reaching an accuracy comparable and, in some cases, better than SED template fitting techniques. Different neural networks architecture have been tested and the combination of a Multi Layer Perceptron with 1 hidden layer (22 neurons) operated in a Bayesian framework, with a Self Organizing Map used to estimate the accuracy...
Artificial neural networks have been applied to problems ranging from speech recognition to prediction of protein secondary structure, classification of cancers and gene prediction. How do they work and what might they be good for? Udgivelsesdato: 2008-Feb......Artificial neural networks have been applied to problems ranging from speech recognition to prediction of protein secondary structure, classification of cancers and gene prediction. How do they work and what might they be good for? Udgivelsesdato: 2008-Feb...
Hurr, Chansol; Young, Colin N
Hypertension affects over 25 % of the population with the incidence continuing to rise, due in part to the growing obesity epidemic. Chronic elevations in sympathetic nerve activity (SNA) are a hallmark of the disease and contribute to elevations in blood pressure through influences on the vasculature, kidney, and heart (i.e., neurogenic hypertension). In this regard, a number of central nervous system mechanisms and neural pathways have emerged as crucial in chronically elevating SNA. However, it is important to consider that "sympathetic signatures" are present, with differential increases in SNA to regional organs that are dependent upon the disease progression. Here, we discuss recent findings on the central nervous system mechanisms and autonomic regulatory networks involved in neurogenic hypertension, in both non-obesity- and obesity-associated hypertension, with an emphasis on angiotensin-II, salt, oxidative and endoplasmic reticulum stress, inflammation, and the adipokine leptin. PMID:26957306
Rončević Nevenka; Stojadinović Aleksandra; Odri Irena
Introduction. The prevalence of chronic diseases in adolescence is constantly increasing, especially in the last two decades. Adolescence is a period of important changes: body growth and development, sexual development, development of cognitive abilities, change in family relations and between peers, formation of personal identity and personal system of values, making decisions on future occupation etc. Chronic diseases in adolescence. Chronic disorders affect all development issues and repr...
Lopes, Roberto I.; Silvia I Lopes; Roberto N. Lopes
Chronic penile strangulation is exceedingly rare with only 5 cases previously reported. We report an additional case of progressive penile lymphedema due to chronic intermittent strangulation caused by a rubber band applied to the penile base for 6 years. A 49-year-old man presented incapacity to exteriorize the glans penis. For erotic purposes, he had been using a rubber-enlarging band placed in the penile base for 6 years. With chronic use, he noticed that his penis swelled. Physical examin...
The global prevalence of physiologically defined chronic obstructive pulmonary disease (COPD) in adults aged >40 yr is approximately 9-10 per cent. Recently, the Indian Study on Epidemiology of Asthma, Respiratory Symptoms and Chronic Bronchitis in Adults had shown that the overall prevalence of chronic bronchitis in adults >35 yr is 3.49 per cent. The development of COPD is multifactorial and the risk factors of COPD include genetic and environmental factors. Pathological changes in COPD are...
Full Text Available Embryonic cortical neural stem cells are self-renewing progenitors that can differentiate into neurons and glia. We generated neurospheres from the developing cerebral cortex using a mouse genetic model that allows for lineage selection and found that the self-renewing neural stem cells are restricted to Sox2 expressing cells. Under normal conditions, embryonic cortical neurospheres are heterogeneous with regard to Sox2 expression and contain astrocytes, neural stem cells and neural progenitor cells sufficiently plastic to give rise to neural crest cells when transplanted into the hindbrain of E1.5 chick and E8 mouse embryos. However, when neurospheres are maintained under lineage selection, such that all cells express Sox2, neural stem cells maintain their Pax6+ cortical radial glia identity and exhibit a more restricted fate in vitro and after transplantation. These data demonstrate that Sox2 preserves the cortical identity and regulates the plasticity of self-renewing Pax6+ radial glia cells.
Katz Donald B
Full Text Available Abstract Although there have been many recent advances in the field of gustatory neurobiology, our knowledge of how the nervous system is organized to process information about taste is still far from complete. Many studies on this topic have focused on understanding how gustatory neural circuits are spatially organized to represent information about taste quality (e.g., "sweet", "salty", "bitter", etc.. Arguments pertaining to this issue have largely centered on whether taste is carried by dedicated neural channels or a pattern of activity across a neural population. But there is now mounting evidence that the timing of neural events may also importantly contribute to the representation of taste. In this review, we attempt to summarize recent findings in the field that pertain to these issues. Both space and time are variables likely related to the mechanism of the gustatory neural code: information about taste appears to reside in spatial and temporal patterns of activation in gustatory neurons. What is more, the organization of the taste network in the brain would suggest that the parameters of space and time extend to the neural processing of gustatory information on a much grander scale.
... Share this: Main Content Area Chronic Granulomatous Disease (CGD) Phagocyte (purple) engulfing Staphylococcus aureus bacteria (yellow). Credit: NIAID CGD is a genetic disorder in which white blood ...
Paparella, Michael M; Schachern, Patricia A; Cureoglu, Sebahattin
Otitis media occurs along a continuum. For example, otitis media with effusion characterized by fluid pathology can lead to chronic otitis media plus chronic mastoiditis, characterized by the presence of intractable tissue pathology such as cholesteatoma, cholesterol granuloma or granulation tissue. The literature defines chronic otitis media as having a tympanic membrane perforation and otorrhea. Amongst many other sequelae, which can result from the continuum, an important common one is chronic silent otitis media. This overlooked entity which includes pathology beneath an intact tympanic membrane is commonly seen in our human temporal bone laboratory and in patients. The clinical pathological correlates of this important disease are discussed herein. PMID:12021496
Automatic power stabilization control is the desired objective for any reactor operation , especially, nuclear power plants. A major problem in this area is inevitable gap between a real plant ant the theory of conventional analysis and the synthesis of linear time invariant systems. in particular, the trajectory tracking control of a nonlinear plant is a class of problems in which the classical linear transfer function methods break down because no transfer function can represent the system over the entire operating region . there is a considerable amount of research on the model-inverse approach using feedback linearization technique. however, this method requires a prices plant model to implement the exact linearizing feedback, for nuclear reactor systems, this approach is not an easy task because of the uncertainty in the plant parameters and un-measurable state variables . therefore, artificial neural network (ANN) is used either in self-tuning control or in improving the conventional rule-based exper system.the main objective of this thesis is to suggest an ANN, based self-learning controller structure . this method is capable of on-line reinforcement learning and control for a nuclear reactor with a totally unknown dynamics model. previously, researches are based on back- propagation algorithm . back -propagation (BP), fast back -propagation (FBP), and levenberg-marquardt (LM), algorithms are discussed and compared for reinforcement learning. it is found that, LM algorithm is quite superior
Chandar, Sarath; Khapra, Mitesh M; Larochelle, Hugo; Ravindran, Balaraman
Common representation learning (CRL), wherein different descriptions (or views) of the data are embedded in a common subspace, has been receiving a lot of attention recently. Two popular paradigms here are canonical correlation analysis (CCA)-based approaches and autoencoder (AE)-based approaches. CCA-based approaches learn a joint representation by maximizing correlation of the views when projected to the common subspace. AE-based methods learn a common representation by minimizing the error of reconstructing the two views. Each of these approaches has its own advantages and disadvantages. For example, while CCA-based approaches outperform AE-based approaches for the task of transfer learning, they are not as scalable as the latter. In this work, we propose an AE-based approach, correlational neural network (CorrNet), that explicitly maximizes correlation among the views when projected to the common subspace. Through a series of experiments, we demonstrate that the proposed CorrNet is better than AE and CCA with respect to its ability to learn correlated common representations. We employ CorrNet for several cross-language tasks and show that the representations learned using it perform better than the ones learned using other state-of-the-art approaches. PMID:26654210
Full Text Available Introduction. The prevalence of chronic diseases in adolescence is constantly increasing, especially in the last two decades. Adolescence is a period of important changes: body growth and development, sexual development, development of cognitive abilities, change in family relations and between peers, formation of personal identity and personal system of values, making decisions on future occupation etc. Chronic diseases in adolescence. Chronic disorders affect all development issues and represent an additional burden for adolescents. The interaction between chronic disorders and various development issues is complex and two-way: the disease may affect development, and development may affect the disease. Developmental, psychosocial and family factors are of great importance in the treatment of adolescents with chronic disorders. Chronic disorders affect all aspects of adolescent life, including relations with peers, school, nutrition, learning, traveling, entertainment, choice of occupation, plans for the future. Physicians should keep in mind that chronic diseases and their treatment represent only one aspect of person's life. Adolescents with chronic diseases have other needs as well, personal priorities, social roles and they expect these needs to be recognized and respected. Adolescent health care should be adjusted to the life style of adolescents.
Ravn, Iben M; Frederiksen, Kirsten; Beedholm, Kirsten
This article reports on the results of a Fairclough-inspired critical discourse analysis aiming to clarify how chronically ill patients are presented in contemporary Danish chronic care policies. Drawing on Fairclough’s three-dimensional framework for analyzing discourse, and using Dean’s concepts...... of governmentality as an interpretative lens, we analyzed and explained six policies published by the Danish Health and Medicines Authority between 2005 and 2013. The analysis revealed that discourses within the policy vision of chronic care consider chronically ill patients’ active role, lifestyle......, and health behavior to be the main factors influencing susceptibility to chronic diseases. We argue that this discursive construction naturalizes a division between people who can actively manage responsible self-care and those who cannot. Such discourses may serve the interests of those patients who...
We define chronic migraine as that clinical situation in which migraine attacks appear 15 or more days per month. Until recently, and in spite of its negative impact, patients with chronic migraine were excluded of the clinical trials. This manuscript revises the current treatment of chronic migraine. The first step should include the avoidance of potential precipitating/aggravating factors for chronic migraine, mainly analgesic overuse and the treatment of comorbid disorders, such as anxiety and depression. The symptomatic treatment should be based on the use of nonsteroidal anti-inflammatory agents and triptans (in this case ergotamine-containing medications. Preventive treatment includes a 'transitional' treatment with nonsteroidal anti-inflammatory agents or steroids, while preventive treatment exerts its actions. Even though those medications efficacious in episodic migraine prevention are used, the only drugs with demonstrated efficacy in the preventive treatment of chronic migraine are topiramate and pericranial infiltrations of Onabotulinumtoxin A. PMID:22532241
Cho, Myoung Won
Biological neurons naturally fire spontaneously due to the existence of a noisy current. Such autonomous firings may provide a driving force for network formation because synaptic connections can be modified due to neural firings. Here, we study the effect of autonomous firings on network formation. For the temporally asymmetric Hebbian learning, bidirectional connections lose their balance easily and become unidirectional ones. Defining the difference between reciprocal connections as new variables, we could express the learning dynamics as if Ising model spins interact with each other in magnetism. We present a theoretical method to estimate the interaction between the new variables in a neural system. We apply the method to some network systems and find some tendencies of autonomous neural network regulation.
Zverev, M.; Fanjul-Vélez, F.; Salas-García, I.; Arce-Diego, J. L.
Neurodegenerative diseases usually appear at advanced age. Medical advances make people live longer and as a consequence, the number of neurodegenerative diseases continuously grows. There is still no cure for these diseases, but several brain stimulation techniques have been proposed to improve patients' condition. One of them is Optical Neural Stimulation (ONS), which is based on the application of optical radiation over specific brain regions. The outer cerebral zones can be noninvasively stimulated, without the common drawbacks associated to surgical procedures. This work focuses on the analysis of ONS effects in stimulated neurons to determine their influence in neuronal activity. For this purpose a neural network model has been employed. The results show the neural network behavior when the stimulation is provided by means of different optical radiation sources and constitute a first approach to adjust the optical light source parameters to stimulate specific neocortical areas.
... People About NINDS NINDS Chronic Inflammatory Demyelinating Polyneuropathy (CIDP) Information Page Table of Contents (click to jump ... en Español What is Chronic Inflammatory Demyelinating Polyneuropathy (CIDP)? Chronic inflammatory demyelinating polyneuropathy (CIDP) is a neurological ...
... ALL Treatment Childhood AML Treatment Research Chronic Myelogenous Leukemia Treatment (PDQ®)–Patient Version General Information About Chronic Myelogenous Leukemia Go to Health Professional Version Key Points Chronic ...
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Nahum, Louis; Pignat, Jean-Michel; Bouzerda-Wahlen, Aurélie; Gabriel, Damien; Liverani, Maria Chiara; Lazeyras, François; Ptak, Radek; Richiardi, Jonas; Haller, Sven; Thorens, Gabriel; Zullino, Daniele F; Guggisberg, Adrian G; Schnider, Armin
The neural correlate of anterograde amnesia in Wernicke-Korsakoff syndrome (WKS) is still debated. While the capacity to learn new information has been associated with integrity of the medial temporal lobe (MTL), previous studies indicated that the WKS is associated with diencephalic lesions, mainly in the mammillary bodies and anterior or dorsomedial thalamic nuclei. The present study tested the hypothesis that amnesia in WKS is associated with a disrupted neural circuit between diencephalic and hippocampal structures. High-density evoked potentials were recorded in four severely amnesic patients with chronic WKS, in five patients with chronic alcoholism without WKS, and in ten age matched controls. Participants performed a continuous recognition task of pictures previously shown to induce a left medial temporal lobe dependent positive potential between 250 and 350 ms. In addition, the integrity of the fornix was assessed using diffusion tensor imaging (DTI). WKS, but not alcoholic patients without WKS, showed absence of the early, left MTL dependent positive potential following immediate picture repetitions. DTI indicated disruption of the fornix, which connects diencephalic and hippocampal structures. The findings support an interpretation of anterograde amnesia in WKS as a consequence of a disconnection between diencephalic and MTL structures with deficient contribution of the MTL to rapid consolidation. PMID:25148770
Jorgensen, Charles C.
Neural networks are being developed at NASA Ames Research Center to permit real-time adaptive control of time varying nonlinear systems, enhance the fault-tolerance of mission hardware, and permit online system reconfiguration. In general, the problem of controlling time varying nonlinear systems with unknown structures has not been solved. Adaptive neural control techniques show considerable promise and are being applied to technical challenges including automated docking of spacecraft, dynamic balancing of the space station centrifuge, online reconfiguration of damaged aircraft, and reducing cost of new air and spacecraft designs. Our experiences have shown that neural network algorithms solved certain problems that conventional control methods have been unable to effectively address. These include damage mitigation in nonlinear reconfiguration flight control, early performance estimation of new aircraft designs, compensation for damaged planetary mission hardware by using redundant manipulator capability, and space sensor platform stabilization. This presentation explored these developments in the context of neural network control theory. The discussion began with an overview of why neural control has proven attractive for NASA application domains. The more important issues in control system development were then discussed with references to significant technical advances in the literature. Examples of how these methods have been applied were given, followed by projections of emerging application needs and directions.
Rietz, B.; Krarup-Hansen, A.; Rorth, M.
Cisplatin is one of the most used antineoplastic drugs, essential for the treatment of germ cell tumours. Its use in medical treatment of cancer patients often causes chronic peripheral neuropathy in these patients. The distribution of cisplatin in neural tissues is, therefore, of great interest...
William; R; Marchand
Mindfulness is the dispassionate,moment-by-moment awareness of sensations,emotions and thoughts.Mindfulness-based interventions are being increasingly used for stress,psychological well being,coping with chronic illness as well as adjunctive treatments for psychiatric disorders.However,the neural mechanisms associated with mindfulness have not been well characterized.Recent functional and structural neuroimaging studies are beginning to provide insights into neural processes associated with the practice of mindfulness.A review of this literature revealed compelling evidence that mindfulness impacts the function of the medial cortex and associated default mode network as well as insula and amygdala.Additionally,mindfulness practice appears to effect lateral frontal regions and basal ganglia,at least in some cases.Structural imaging studies are consistent with these findings and also indicate changes in the hippocampus.While many questions remain unanswered,the current literature provides evidence of brain regions and networks relevant for understanding neural processes associated with mindfulness.
Chronic pain is a significant health problem that greatly impacts the quality of life of individuals and imparts high costs to society. Despite intense research effort in understanding of the mechanism of pain, chronic pain remains a clinical problem that has few effective therapies. The advent of human brain imaging research in recent years has changed the way that chronic pain is viewed. To further extend the use of human brain imaging techniques for better therapies, the adoption of imaging technique onto the animal pain models is essential, in which underlying brain mechanisms can be systematically studied using various combination of imaging and invasive techniques. The general goal of this thesis is to addresses how brain develops and maintains chronic pain in an animal model using fMRI. We demonstrate that nucleus accumbens, the central component of mesolimbic circuitry, is essential in development of chronic pain. To advance our imaging technique, we develop an innovative methodology to carry out fMRI in awake, conscious rat. Using this cutting-edge technique, we show that allodynia is assoicated with shift brain response toward neural circuits associated nucleus accumbens and prefrontal cortex that regulate affective and cognitive component of pain. Taken together, this thesis provides a deeper understanding of how brain mediates pain. It builds on the existing body of knowledge through maximizing the depth of insight into brain imaging of chronic pain.
Dweiri, Yazan M.; Eggers, Thomas; McCallum, Grant; Durand, Dominique M.
Objective. Peripheral nerves carry neural signals that could be used to control hybrid bionic systems. Cuff electrodes provide a robust and stable interface but the recorded signal amplitude is small (<3 μVrms 700 Hz-7 kHz), thereby requiring a baseline noise of less than 1 μVrms for a useful signal-to-noise ratio (SNR). Flat interface nerve electrode (FINE) contacts alone generate thermal noise of at least 0.5 μVrms therefore the amplifier should add as little noise as possible. Since mainstream neural amplifiers have a baseline noise of 2 μVrms or higher, novel designs are required. Approach. Here we apply the concept of hardware averaging to nerve recordings obtained with cuff electrodes. An optimization procedure is developed to minimize noise and power simultaneously. The novel design was based on existing neural amplifiers (Intan Technologies, LLC) and is validated with signals obtained from the FINE in chronic dog experiments. Main results. We showed that hardware averaging leads to a reduction in the total recording noise by a factor of 1/√N or less depending on the source resistance. Chronic recording of physiological activity with FINE using the presented design showed significant improvement on the recorded baseline noise with at least two parallel operation transconductance amplifiers leading to a 46.1% reduction at N = 8. The functionality of these recordings was quantified by the SNR improvement and shown to be significant for N = 3 or more. The present design was shown to be capable of generating <1.5 μVrms total recording baseline noise when connected to a FINE placed on the sciatic nerve of an awake animal. An algorithm was introduced to find the value of N that can minimize both the power consumption and the noise in order to design a miniaturized ultralow-noise neural amplifier. Significance. These results demonstrate the efficacy of hardware averaging on noise improvement for neural recording with cuff electrodes, and can accommodate the
Full Text Available Communication and intentional behavior are supported by the brain’s integrity at a structural and a functional level. When widespread loss of cerebral connectivity is brought about as a result of a severe brain injury, in many cases patients are not capable of conscious interactive behavior and are said to suffer from disorders of consciousness (e.g., coma, vegetative state /unresponsive wakefulness syndrome, minimally conscious states. This lesion paradigm has offered not only clinical insights, as how to improve diagnosis, prognosis and treatment, but also put forward scientific opportunities to study the brain’s plastic abilities. We here review interventional and observational studies performed in severely brain-injured patients with regards to recovery of consciousness. The study of the recovered conscious brain (spontaneous and/or after surgical or pharmacologic interventions, suggests a link between some specific brain areas and the capacity of the brain to sustain conscious experience, challenging at the same time the notion of fixed temporal boundaries in rehabilitative processes. Altered functional connectivity, cerebral structural reorganization as well as behavioral amelioration after invasive treatments will be discussed as the main indices for plasticity in these challenging patients. The study of patients with chronic disorders of consciousness may, thus, provide further insights not only at a clinical level (i.e., medical management and rehabilitation but also from a scientific-theoretical perspective (i.e., the brain’s plastic abilities and the pursuit of the neural correlate of consciousness.
Demertzi, Athena; Schnakers, Caroline; Soddu, Andrea; Bruno, Marie-Aurélie; Gosseries, Olivia; Vanhaudenhuyse, Audrey; Laureys, Steven
Communication and intentional behavior are supported by the brain's integrity at a structural and a functional level. When widespread loss of cerebral connectivity is brought about as a result of a severe brain injury, in many cases patients are not capable of conscious interactive behavior and are said to suffer from disorders of consciousness (e.g., coma, vegetative state/unresponsive wakefulness syndrome, minimally conscious states). This lesion paradigm has offered not only clinical insights, as how to improve diagnosis, prognosis, and treatment, but also put forward scientific opportunities to study the brain's plastic abilities. We here review interventional and observational studies performed in severely brain-injured patients with regards to recovery of consciousness. The study of the recovered conscious brain (spontaneous and/or after surgical or pharmacologic interventions), suggests a link between some specific brain areas and the capacity of the brain to sustain conscious experience, challenging at the same time the notion of fixed temporal boundaries in rehabilitative processes. Altered functional connectivity, cerebral structural reorganization as well as behavioral amelioration after invasive treatments will be discussed as the main indices for plasticity in these challenging patients. The study of patients with chronic disorders of consciousness may, thus, provide further insights not only at a clinical level (i.e., medical management and rehabilitation) but also from a scientific-theoretical perspective (i.e., the brain's plastic abilities and the pursuit of the neural correlate of consciousness). PMID:21833298
Demertzi, Athena; Schnakers, Caroline; Soddu, Andrea; Bruno, Marie-Aurélie; Gosseries, Olivia; Vanhaudenhuyse, Audrey; Laureys, Steven
Communication and intentional behavior are supported by the brain's integrity at a structural and a functional level. When widespread loss of cerebral connectivity is brought about as a result of a severe brain injury, in many cases patients are not capable of conscious interactive behavior and are said to suffer from disorders of consciousness (e.g., coma, vegetative state/unresponsive wakefulness syndrome, minimally conscious states). This lesion paradigm has offered not only clinical insights, as how to improve diagnosis, prognosis, and treatment, but also put forward scientific opportunities to study the brain's plastic abilities. We here review interventional and observational studies performed in severely brain-injured patients with regards to recovery of consciousness. The study of the recovered conscious brain (spontaneous and/or after surgical or pharmacologic interventions), suggests a link between some specific brain areas and the capacity of the brain to sustain conscious experience, challenging at the same time the notion of fixed temporal boundaries in rehabilitative processes. Altered functional connectivity, cerebral structural reorganization as well as behavioral amelioration after invasive treatments will be discussed as the main indices for plasticity in these challenging patients. The study of patients with chronic disorders of consciousness may, thus, provide further insights not only at a clinical level (i.e., medical management and rehabilitation) but also from a scientific-theoretical perspective (i.e., the brain's plastic abilities and the pursuit of the neural correlate of consciousness). PMID:21833298
Providing a broad but in-depth introduction to neural network and machine learning in a statistical framework, this book provides a single, comprehensive resource for study and further research. All the major popular neural network models and statistical learning approaches are covered with examples and exercises in every chapter to develop a practical working understanding of the content. Each of the twenty-five chapters includes state-of-the-art descriptions and important research results on the respective topics. The broad coverage includes the multilayer perceptron, the Hopfield network, associative memory models, clustering models and algorithms, the radial basis function network, recurrent neural networks, principal component analysis, nonnegative matrix factorization, independent component analysis, discriminant analysis, support vector machines, kernel methods, reinforcement learning, probabilistic and Bayesian networks, data fusion and ensemble learning, fuzzy sets and logic, neurofuzzy models, hardw...
Full Text Available Apart from the existing technology on image compression represented by series of JPEG, MPEG and H.26x standards, new technology such as neural networks and genetic algorithms are being developed to explore the future of image coding. Successful applications of neural networks to basic propagation algorithm have now become well established and other aspects of neural network involvement in this technology. In this paper different algorithms were implemented like gradient descent back propagation, gradient descent with momentum back propagation, gradient descent with adaptive learning back propagation, gradient descent with momentum and adaptive learning back propagation and Levenberg-Marquardt algorithm. The size of original video clip is 25MB and after compression it becomes 21.3MB giving the compression ratio as 85.2% and compression factor of 1.174. It was observed that the size remains same after compression but the difference is in the clarity.
Full Text Available Software cost estimation is an important phase in software development. It predicts the amount of effort and development time required to build a software system. It is one of the most critical tasks and an accurate estimate provides a strong base to the development procedure. In this paper, the most widely used software cost estimation model, the Constructive Cost Model (COCOMO is discussed. The model is implemented with the help of artificial neural networks and trained using the perceptron learning algorithm. The COCOMO dataset is used to train and to test the network. The test results from the trained neural network are compared with that of the COCOMO model. The aim of our research is to enhance the estimation accuracy of the COCOMO model by introducing the artificial neural networks to it.
Object-oriented database systems proved very valuable at handling and administrating complex objects. In the following guidelines for embedding neural networks into such systems are presented. It is our goal to treat networks as normal data in the database system. From the logical point of view, a neural network is a complex data value and can be stored as a normal data object. It is generally accepted that rule-based reasoning will play an important role in future database applications. The knowledge base consists of facts and rules, which are both stored and handled by the underlying database system. Neural networks can be seen as representation of intensional knowledge of intelligent database systems. So they are part of a rule based knowledge pool and can be used like conventional rules. The user has a unified view about his knowledge base regardless of the origin of the unique rules.
Nuclear Engineering has matured during the last decade. In research and design, control, supervision, maintenance and production, mathematical models and theories are used extensively. In all such applications signal processing is embedded in the process. Artificial Neural Networks (ANN), because of their nonlinear, adaptive nature are well suited to such applications where the classical assumptions of linearity and second order Gaussian noise statistics cannot be made. ANN's can be treated as nonparametric techniques, which can model an underlying process from example data. They can also adopt their model parameters to statistical change with time. Algorithms in the framework of Neural Networks in Signal processing have found new applications potentials in the field of Nuclear Engineering. This paper reviews the fundamentals of Neural Networks in signal processing and their applications in tasks such as recognition/identification and control. The topics covered include dynamic modeling, model based ANN's, statistical learning, eigen structure based processing and generalization structures. (orig.)
Seelen, Werner v
In this fundamental book the authors devise a framework that describes the working of the brain as a whole. It presents a comprehensive introduction to the principles of Neural Information Processing as well as recent and authoritative research. The books´ guiding principles are the main purpose of neural activity, namely, to organize behavior to ensure survival, as well as the understanding of the evolutionary genesis of the brain. Among the developed principles and strategies belong self-organization of neural systems, flexibility, the active interpretation of the world by means of construction and prediction as well as their embedding into the world, all of which form the framework of the presented description. Since, in brains, their partial self-organization, the lifelong adaptation and their use of various methods of processing incoming information are all interconnected, the authors have chosen not only neurobiology and evolution theory as a basis for the elaboration of such a framework, but also syst...
Nuyujukian, Paul; Kao, Jonathan C.; Fan, Joline M.; Stavisky, Sergey D.; Ryu, Stephen I.; Shenoy, Krishna V.
Objective. Neural prostheses, or brain-machine interfaces, aim to restore efficient communication and movement ability to those suffering from paralysis. A major challenge these systems face is robust performance, particularly with aging signal sources. The aim in this study was to develop a neural prosthesis that could sustain high performance in spite of signal instability while still minimizing retraining time. Approach. We trained two rhesus macaques implanted with intracortical microelectrode arrays 1-4 years prior to this study to acquire targets with a neurally-controlled cursor. We measured their performance via achieved bitrate (bits per second, bps). This task was repeated over contiguous days to evaluate the sustained performance across time. Main results. We found that in the monkey with a younger (i.e., two year old) implant and better signal quality, a fixed decoder could sustain performance for a month at a rate of 4 bps, the highest achieved communication rate reported to date. This fixed decoder was evaluated across 22 months and experienced a performance decline at a rate of 0.24 bps yr-1. In the monkey with the older (i.e., 3.5 year old) implant and poorer signal quality, a fixed decoder could not sustain performance for more than a few days. Nevertheless, performance in this monkey was maintained for two weeks without requiring additional online retraining time by utilizing prior days’ experimental data. Upon analysis of the changes in channel tuning, we found that this stability appeared partially attributable to the cancelling-out of neural tuning fluctuations when projected to two-dimensional cursor movements. Significance. The findings in this study (1) document the highest-performing communication neural prosthesis in monkeys, (2) confirm and extend prior reports of the stability of fixed decoders, and (3) demonstrate a protocol for system stability under conditions where fixed decoders would otherwise fail. These improvements to decoder
the neural network attractive. A neural network is an information processing system modeled on the structure of the dynamic process. It can solve the complex/nonlinear problems quickly once trained by operating on problems using an interconnected number...
In this paper, we descrive our motivation and approach to devloping models and the neural network architecture. Initial use of the artificial neural network for modeling the single plant process of transpiration is presented.
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...
The contribution deals with neural network application for the diagnostic system of the three-phase asynchronous electro motor. The case study is done and can be used as a model for the next application of neural network methodology.
Whyte, Susan Reynolds
This paper proposes a way of framing the study of ‘noncommunicable diseases’ within the more general area of chronic conditions. Focusing on Africa, it takes as points of departure the situation in Uganda, and the approach to health issues developed by a group of European and African colleagues...... over the years. It suggests a pragmatic analysis that places people's perceptions and practices within a field of possibilities shaped by policy, health care systems, and life conditions. In this field, the dimensions of chronicity and control are the distinctive analytical issues. They lead on to...... consideration of patterns of sociality related to chronic conditions and their treatment....
Berezin, V; Bock, E; Poulsen, F M
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...
""Neural Nets and Chaotic Carriers"" develops rational principles for the design of associative memories, with a view to applying these principles to models with irregularly oscillatory operation so evident in biological neural systems, and necessitated by the meaninglessness of absolute signal levels. Design is based on the criterion that an associative memory must be able to cope with 'fading data', i.e., to form an inference from the data even as its memory of that data degrades. The resultant net shows striking biological parallels. When these principles are combined with the Freeman speci
Distributed synchronization is known to occur at several scales in the brain, and has been suggested as playing a key functional role in perceptual grouping. State-of-the-art visual grouping algorithms, however, seem to give comparatively little attention to neural synchronization analogies. Based on the framework of concurrent synchronization of dynamic systems, simple networks of neural oscillators coupled with diffusive connections are proposed to solve visual grouping problems. Multi-layer algorithms and feedback mechanisms are also studied. The same algorithm is shown to achieve promising results on several classical visual grouping problems, including point clustering, contour integration and image segmentation.
Chung, Myung Kyu; Chung, Danielle; LaRiccia, Patrick J
Chronic upper gastrointestinal (GI) symptoms of unclear etiology are frustrating to patients and physicians alike. The integrative medicine procedures of acupuncture and neural therapy may provide treatment options. Tongue piercing, which is prevalent in 5.6% of the adolescent population, may be a contributing factor in upper gastrointestinal symptoms. The objectives of the study were as follows: (1) To demonstrate the usefulness of an integrative medicine treatment approach in two cases of patients with chronic abdominal pain, nausea, and vomiting of unclear etiology who had failed standard medical management. (2) To identify scars from tongue piercings as a possible contributing factor in chronic upper GI symptoms of unclear etiology. Two retrospective case studies are presented of young adult females who were seen in a private multi-physician integrative medicine practice in the US. The patients were treated with neural therapy and acupuncture. The desired outcome was the cessation or reduction of the frequency of abdominal pain, nausea, and vomiting. Both patients had resolution of their symptoms. From this study, we have concluded the following: (1) Tongue scars from tongue rings may be causes of chronic upper gastrointestinal symptoms. (2) Neural therapy and acupuncture may be helpful in the treatment of chronic upper GI symptoms related to tongue scars. PMID:25457444
Full Text Available Recognition of visual patterns is one of significant applications of Artificial Neural Networks, which partially emulate human thinking in the domain of artificial intelligence. In the paper, a simplified neural approach to recognition of visual patterns is portrayed and discussed. This paper is dedicated for investigators in visual patterns recognition, Artificial Neural Networking and related disciplines. The document describes also MemBrain application environment as a powerful and easy to use neural networks’ editor and simulator supporting ANN.
Bahi, Jacques M; Salomon, Michel
Chaotic neural networks have received a great deal of attention these last years. In this paper we establish a precise correspondence between the so-called chaotic iterations and a particular class of artificial neural networks: global recurrent multi-layer perceptrons. We show formally that it is possible to make these iterations behave chaotically, as defined by Devaney, and thus we obtain the first neural networks proven chaotic. Several neural networks with different architectures are trained to exhibit a chaotical behavior.
Moerland, Perry,; Fiesler,Emile
In order to take advantage of the massive parallelism offered by artificial neural networks, hardware implementations are essential.However, most standard neural network models are not very suitable for implementation in hardware and adaptations are needed. In this section an overview is given of the various issues that are encountered when mapping an ideal neural network model onto a compact and reliable neural network hardware implementation, like quantization, handling nonuniformities and ...
Moerland, Perry,; Fiesler,Emile; Beale, R
In order to take advantage of the massive parallelism offered by artificial neural networks, hardware implementations are essential. However, most standard neural network models are not very suitable for implementation in hardware and adaptations are needed. In this section an overview is given of the various issues that are encountered when mapping an ideal neural network model onto a compact and reliable neural network hardware implementation, like quantization, handling nonuniformities and...
Zak, Michail; Barhen, Jacob
Paper presents analysis of mathematical model of one-neuron/one-synapse neural network featuring coupled activation and learning dynamics and parametrical periodic excitation. Demonstrates self-programming, partly random behavior of suitable designed neural network; believed to be related to spontaneity and creativity of biological neural networks.
Katz, Paul S.
The complexity of nervous systems alters the evolvability of behaviour. Complex nervous systems are phylogenetically constrained; nevertheless particular species-specific behaviours have repeatedly evolved, suggesting a predisposition towards those behaviours. Independently evolved behaviours in animals that share a common neural architecture are generally produced by homologous neural structures, homologous neural pathways and even in the case of some invertebrates, homologous identified neu...
This book contains papers on neural networks. Included are the following topics: A self-training visual inspection system with a neural network classifier; A bifurcation theory approach to vector field programming for periodic attractors; and construction of neural nets using the radon transform.
A new neural network application for non-linear state control is described. One neural network is modelled to form a Kalmann predictor and trained to act as an optimal state observer for a non-linear process. Another neural network is modelled to form a state controller and trained to produce a...
McConnell, G. C.; Butera, R. J.; Bellamkonda, R. V.
The widespread adoption of neural prosthetic devices is currently hindered by our inability to reliably record neural signals from chronically implanted electrodes. The extent to which the local tissue response to implanted electrodes influences recording failure is not well understood. To investigate this phenomenon, impedance spectroscopy has shown promise for use as a non-invasive tool to estimate the local tissue response to microelectrodes. Here, we model impedance spectra from chronically implanted rats using the well-established Cole model, and perform a correlation analysis of modeled parameters with histological markers of astroglial scar, including glial fibrillary acid protein (GFAP) and 4',6-diamidino-2- phenylindole (DAPI). Correlations between modeled parameters and GFAP were significant for three parameters studied: Py value, Ro and |Z|1 kHz, and in all cases were confined to the first 100 µm from the interface. Py value was the only parameter also correlated with DAPI in the first 100 µm. Our experimental results, along with computer simulations, suggest that astrocytes are a predominant cellular player affecting electrical impedance spectra. The results also suggest that the largest contribution from reactive astrocytes on impedance spectra occurs in the first 100 µm from the interface, where electrodes are most likely to record electrical signals. These results form the basis for future approaches where impedance spectroscopy can be used to evaluate neural implants, evaluate strategies to minimize scar and potentially develop closed-loop prosthetic devices.
Spina bifida, anencephaly, and encephalocele are commonly grouped together and termed neural tube defects (NTD). Failure of closure of the neural tube during development results in anencephaly or spina bifida aperta but encephaloceles are possibly post-closure defects. NTD are associated with a number of other central nervous system (CNS) and non-neural malformations. Racial, geographic and seasonal variations seem to affect their incidence. Etiology of NTD is unknown. Most of the non-syndromic NTD are of multifactorial origin. Recent in vitro and in vivo studies have highlighted the molecular mechanisms of neurulation in vertebrates but the morphologic development of human neural tube is poorly understood. A multisite closure theory, extrapolated directly from mouse experiments highlighted the clinical relevance of closure mechanisms to human NTD. Animal models, such as circle tail, curly tail, loop tail, shrm and numerous knockouts provide some insight into the mechanisms of NTD. Also available in the literature are a plethora of chemically induced preclosure and a few post-closure models of NTD, which highlight the fact that CNS malformations are of hetergeneitic nature. No Mendelian pattern of inheritance has been reported. Association with single gene defects, enhanced recurrence risk among siblings, and a higher frequency in twins than in singletons indicate the presence of a strong genetic contribution to the etiology of NTD. Non-availability of families with a significant number of NTD cases makes research into genetic causation of NTD difficult. Case reports and epidemiologic studies have implicated a number of chemicals, widely differing therapeutic drugs, environmental contaminants, pollutants, infectious agents, and solvents. Maternal hyperthermia, use of valproate by epileptic women during pregnancy, deficiency and excess of certain nutrients and chronic maternal diseases (e.g. diabetes mellitus) are reported to cause a manifold increase in the
U.S. Department of Health & Human Services — The CMS Chronic Conditions Dashboard presents statistical views of information on the prevalence, utilization and Medicare spending for Medicare beneficiaries with...
Anemia of inflammation; AOCD; ACD ... Anemia is a lower-than-normal number of red blood cells in the blood. Some conditions can lead to anemia of chronic disease include: Autoimmune disorders , such as ...
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Full Text Available ... after a period of time the spinal cord has changed, after a period of time there are ... absence of an apparent cause. But chronic pain has a physiological or neurological basis even when we ...
Full Text Available ... acute pain and both naturally expect that some cause will be found, and when it’s found, it ... pain even in the absence of an apparent cause. But chronic pain has a physiological or neurological ...
Stevens, Whitney W; Lee, Robert J; Schleimer, Robert P; Cohen, Noam A
There are a variety of medical conditions associated with chronic sinonasal inflammation, including chronic rhinosinusitis (CRS) and cystic fibrosis. In particular, CRS can be divided into 2 major subgroups based on whether nasal polyps are present or absent. Unfortunately, clinical treatment strategies for patients with chronic sinonasal inflammation are limited, in part because the underlying mechanisms contributing to disease pathology are heterogeneous and not entirely known. It is hypothesized that alterations in mucociliary clearance, abnormalities in the sinonasal epithelial cell barrier, and tissue remodeling all contribute to the chronic inflammatory and tissue-deforming processes characteristic of CRS. Additionally, the host innate and adaptive immune responses are also significantly activated and might be involved in pathogenesis. Recent advancements in the understanding of CRS pathogenesis are highlighted in this review, with special focus placed on the roles of epithelial cells and the host immune response in patients with cystic fibrosis, CRS without nasal polyps, or CRS with nasal polyps. PMID:26654193
... very commonly used to treat chronic hypertension. This drug class can cause problems in the fetus, in- cluding an increased risk of birth de- fects 4 and kidney failure. Angiotensin II receptor blockers also should be avoided ...
U.S. Department of Health & Human Services — The Chronic Conditions PUFs are aggregated files in which each record is a profile or cell defined by the characteristics of Medicare beneficiaries. A profile is...
Full Text Available ... ACPA Contact Us Shop FAQs The Art of Pain Management Resources Going to the ER Glossary Surveys What We Have Learned Communication Tools Videos Pain Management Programs Resource Guide to Chronic Pain Treatments Pain ...
Lopes Roberto I
Full Text Available Chronic penile strangulation is exceedingly rare with only 5 cases previously reported. We report an additional case of progressive penile lymphedema due to chronic intermittent strangulation caused by a rubber band applied to the penile base for 6 years. A 49-year-old man presented incapacity to exteriorize the glans penis. For erotic purposes, he had been using a rubber-enlarging band placed in the penile base for 6 years. With chronic use, he noticed that his penis swelled. Physical examination revealed lymphedema of the penis, phimosis and a stricture in the penile base. The patient was submitted to circumcision and the lymphedema remained stable 10 months postoperatively. Chronic penile incarceration usually causes penile lymphedema and urinary disturbance. Treatment consists of removal of foreign devices and surgical treatment of lymphedema.
Martelletti, Paolo; Jensen, Rigmor H; Antal, Andrea;
The medical treatment of patients with chronic primary headache syndromes (chronic migraine, chronic tension-type headache, chronic cluster headache, hemicrania continua) is challenging as serious side effects frequently complicate the course of medical treatment and some patients may be even...... medically intractable. When a definitive lack of responsiveness to conservative treatments is ascertained and medication overuse headache is excluded, neuromodulation options can be considered in selected cases.Here, the various invasive and non-invasive approaches, such as hypothalamic deep brain...... proper RCT-based evidence is limited. The European Headache Federation herewith provides a consensus statement on the clinical use of neuromodulation in headache, based on theoretical background, clinical data, and side effect of each method. This international consensus further gives recommendations for...
Full Text Available ... Contact Us Shop FAQs The Art of Pain Management Resources Going to the ER Glossary Surveys What We Have Learned Communication Tools Videos Pain Management Programs Resource Guide to Chronic Pain Treatments Pain ...
U.S. Department of Health & Human Services — Chronic Conditions among Medicare Beneficiaries is a chartbook prepared by the Centers for Medicare and Medicaid Services and created to provide an overview of...
Full Text Available ... Programs Resource Guide to Chronic Pain Treatments Pain Awareness Toolkits Partners for Understanding Pain September is Pain Awareness Month Home Pain Management Tools Videos What Is ...
Full Text Available ... chronic pain there may be no apparent physical injury or illness to explain it. The physician and ... expected period of healing for an illness or injury. You can experience pain even if you are ...
U.S. Department of Health & Human Services — The CMS Chronic Condition Data Warehouse (CCW) provides researchers with Medicare and Medicaid beneficiary, claims, and assessment data linked by beneficiary across...
Chronic fatigue syndrome (CFS) is a disorder that causes extreme fatigue. This fatigue is not the kind of tired feeling that ... activities. The main symptom of CFS is severe fatigue that lasts for 6 months or more. You ...
Okoń, Krzysztof; Tomaszewska, Romana; Nowak, Krystyna; Stachura, Jerzy
The aim of the study was to test applycability of neural networks to classification of pancreatic intraductal proliferative lesions basing on nuclear features, especially chromatin texture. Material for the study was obtained from patients operated on for pancreatic cancer, chronic pancreatitis and other tumours requiring pancreatic resection. Intraductal lesions were classified as low and high grade as previously described. The image analysis system consisted of a microscope, CCD camera comb...
Purkayastha, Sudarshana; Zhang, Hai; Zhang, Guo; Ahmed, Zaghloul; Wang, Yi; Cai, Dongsheng
Chronic endoplasmic reticulum (ER) stress was recently revealed to affect hypothalamic neuroendocrine pathways that regulate feeding and body weight. However, it remains unexplored whether brain ER stress could use a neural route to rapidly cause the peripheral disorders that underlie the development of type 2 diabetes (T2D) and the metabolic syndrome. Using a pharmacologic model that delivered ER stress inducer thapsigargin into the brain, this study demonstrated that a short-term brain ER s...
Somerville, Leah; Wagner, D. D.; Wig, G. S.; Moran, Joe Michael; Whalen, P. J.; Kelley, W. M.
Anxious emotion can manifest on brief (threat response) and/or persistent (chronic apprehension and arousal) timescales, and prior work has suggested that these signals are supported by separable neural circuitries. This fMRI study utilized a mixed block-event–related emotional provocation paradigm in 55 healthy participants to simultaneously measure brief and persistent anxious emotional responses, testing the specificity of, and interactions between, these potentially distinct systems. Resu...
Kose, Samet; Steinberg, Joel L.; Moeller, F Gerard; Gowin, Joshua L.; Zuniga, Edward; Kamdar, Zahra N.; Schmitz, Joy M.; Lane, Scott D.
Alcohol-related aggression is a complex and problematic phenomenon with profound public health consequences. We examined neural correlates potentially moderating the relationship between human aggressive behavior and chronic alcohol use. Thirteen subjects meeting DSM–IV criteria for past alcohol-dependence in remission (AD) and 13 matched healthy controls (CONT) participated in an fMRI study adapted from a laboratory model of human aggressive behavior (Point Subtraction Aggression Paradigm, o...
Seth J Wilks; Sarah M Richardson-Burn; Hendricks, Jeffrey L.; David Martin; Otto, Kevin J.
Chronic microstimulation-based devices are being investigated to treat conditions such as blindness, deafness, pain, paralysis and epilepsy. Small area electrodes are desired to achieve high selectivity. However, a major trade-off with electrode miniaturization is an increase in impedance and charge density requirements. Thus, the development of novel materials with lower interfacial impedance and enhanced charge storage capacity is essential for the development of micro-neural interface-ba...
Full Text Available The spectrum of chronic dysimmune neuropathies has widened well beyond chronic demyelinating polyradiculoneuropathy (CIDP. Pure motor (multifocal motor neuropathy, sensorimotor with asymmetrical involvement (multifocal acquired demylinating sensory and motor neuropathy, exclusively distal sensory (distal acquired demyelinating sensory neuropathy and very proximal sensory (chronic immune sensory polyradiculopathy constitute the variants of CIDP. Correct diagnosis of these entities is of importance in terms of initiation of appropriate therapy as well as prognostication of these patients. The rates of detection of immune-mediated neuropathies with monoclonal cell proliferation (monoclonal gammopathy of unknown significance, multiple myeloma, etc. have been facilitated as better diagnostic tools such as serum immunofixation electrophoresis are being used more often. Immune neuropathies associated with malignancies and systemic vasculitic disorders are being defined further and treated early with better understanding of the disease processes. As this field of dysimmune neuropathies will evolve in the future, some of the curious aspects of the clinical presentations and response patterns to different immunosuppressants or immunomodulators will be further elucidated. This review also discusses representative case studies.
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
Cordier Jean-François; Marchand Eric
Abstract Idiopathic chronic eosinophilic pneumonia (ICEP) is characterized by subacute or chronic respiratory and general symptoms, alveolar and/or blood eosinophilia, and peripheral pulmonary infiltrates on chest imaging. Eosinophilia is present in most cases, usually in excess of 1000/mm3. In absence of significant blood eosinophilia, a diagnosis of ICEP is supported by the demonstration of bronchoalveolar lavage eosinophilia. ICEP is typically associated with eosinophil counts higher than ...
Gulmann, C; Young, O.; Tolan, M.; O’Riordan, D.; Leader, M
This report describes a rare case of chronic osteomyelitis in a 60 year old man mimicking a soft tissue sarcoma. Chronic osteomyelitis is an infrequent cause of a soft tissue mass and is usually diagnosed clinically by a combination of radiology and microbiology. Rarely, COM can mimic a primary bony neoplasm, but this is the first reported case where it mimicked a soft tissue sarcoma. The clinical, radiological, and histological appearances of this case will be discussed.
Chronic glomerulonephritis (GN), which includes focal segmental glomerulosclerosis and proliferative forms of GN such as IgA nephropathy, increases the risk of hypertension. Hypertension in chronic GN is primarily volume dependent, and this increase in blood volume is not related to the deterioration of renal function. Patients with chronic GN become salt sensitive as renal damage including arteriolosclerosis progresses and the consequent renal ischemia causes the stimulation of the intrarenal renin-angiotensin-aldosterone system(RAAS). Overactivity of the sympathetic nervous system also contributes to hypertension in chronic GN. According to the KDIGO guideline, the available evidence indicates that the target BP should be ≤140mmHg systolic and ≤90mmHg diastolic in chronic kidney disease patients without albuminuria. In most patients with an albumin excretion rate of ≥30mg/24 h (i.e., those with both micro-and macroalbuminuria), a lower target of ≤130mmHg systolic and ≤80mmHg diastolic is suggested. The use of agents that block the RAAS system is recommended or suggested in all patients with an albumin excretion rate of ≥30mg/ 24 h. The combination of a RAAS blockade with a calcium channel blocker and a diuretic may be effective in attaining the target BP, and in reducing the amount of urinary protein excretion in patients with chronic GN. PMID:26848302
Húsek, Dušan; Frolov, A. A.; Muraviev, I.; Řezanková, H.; Snášel, V.; Polyakov, P.Y.
Zürich : ACTA Press, 2003 - (Hamza, M.), s. 649-653 ISBN 0-88986-390-3. ISSN 1482-7913. [IASTED International Conference /3./. Benalmadena (ES), 08.09.2003-10.09.2003] R&D Projects: GA MŠk LN00B096 Keywords : Boolean factorization * recurrent neural network s * single-step approximation Subject RIV: BD - Theory of Information
This Technology Brief provides an overview of artificial neural networks (ANN). A definition and explanation of an ANN is given and situations in which an ANN is used are described. ANN applications to medicine specifically are then explored and the areas in which it is currently being used are discussed. Included are medical diagnostic aides, biochemical analysis, medical image analysis and drug development.
Wang, Yongchen; Guo, Liang
Neural stimulation is a critical technique in treating neurological diseases and investigating brain functions. Traditional electrical stimulation uses electrodes to directly create intervening electric fields in the immediate vicinity of neural tissues. Second-generation stimulation techniques directly use light, magnetic fields or ultrasound in a non-contact manner. An emerging generation of non- or minimally invasive neural stimulation techniques is enabled by nanotechnology to achieve a high spatial resolution and cell-type specificity. In these techniques, a nanomaterial converts a remotely transmitted primary stimulus such as a light, magnetic or ultrasonic signal to a localized secondary stimulus such as an electric field or heat to stimulate neurons. The ease of surface modification and bio-conjugation of nanomaterials facilitates cell-type-specific targeting, designated placement and highly localized membrane activation. This review focuses on nanomaterial-enabled neural stimulation techniques primarily involving opto-electric, opto-thermal, magneto-electric, magneto-thermal and acousto-electric transduction mechanisms. Stimulation techniques based on other possible transduction schemes and general consideration for these emerging neurotechnologies are also discussed. PMID:27013938
Full Text Available Neural stimulation is a critical technique in treating neurological diseases and investigating brain functions. Traditional electrical stimulation uses electrodes to directly create intervening electric fields in the immediate vicinity of neural tissues. Second-generation stimulation techniques directly use light, magnetic fields or ultrasound in a non-contact manner. An emerging generation of non- or minimally invasive neural stimulation techniques is enabled by nanotechnology to achieve a high spatial resolution and cell-type specificity. In these techniques, a nanomaterial converts a remotely transmitted primary stimulus such as a light, magnetic or ultrasonic signal to a localized secondary stimulus such as an electric field or heat to stimulate neurons. The ease of surface modification and bio-conjugation of nanomaterials facilitates cell-type-specific targeting, designated placement and highly localized membrane activation. This review focuses on nanomaterial-enabled neural stimulation techniques primarily involving opto-electric, opto-thermal, magneto-electric, magneto-thermal and acousto-electric transduction mechanisms. Stimulation techniques based on other possible transduction schemes and general consideration for these emerging neurotechnologies are also discussed.
The cooperative behaviour of interacting neurons and synapses is studied using models and methods from statistical physics. The competition between training error and entropy may lead to discontinuous properties of the neural network. This is demonstrated for a few examples: Perceptron, associative memory, learning from examples, generalization, multilayer networks, structure recognition, Bayesian estimate, on-line training, noise estimation and time series generation.
The objective of this paper is to provide an overview of the recent developments in the use of artificial neural networks in medical imaging. The areas of medical imaging that are covered include : ultrasound, magnetic resonance, nuclear medicine and radiological (including computerized tomography). (authors)
Axer, H.; Jantzen, Jan; Berks, G.;
A web-based software model (http://fuzzy.iau.dtu.dk/aphasia.nsf) was developed as an example for classification of aphasia using neural networks. Two multilayer perceptrons were used to classify the type of aphasia (Broca, Wernicke, anomic, global) according to the results in some subtests of the...
Kim, So-Yeon; Hopfinger, Joseph B.
The ability to maintain focus and avoid distraction by goal-irrelevant stimuli is critical for performing many tasks and may be a key deficit in attention-related problems. Recent studies have demonstrated that irrelevant stimuli that are consciously perceived may be filtered out on a neural level and not cause the distraction triggered by…
Thomas, Gail D.
The purpose of this brief review is to highlight key concepts about the neural control of the circulation that graduate and medical students should be expected to incorporate into their general knowledge of human physiology. The focus is largely on the sympathetic nerves, which have a dominant role in cardiovascular control due to their effects to…
Brian K Hall
The neural crest has long fascinated developmental biologists, and, increasingly over the past decades, evolutionary and evolutionary developmental biologists. The neural crest is the name given to the fold of ectoderm at the junction between neural and epidermal ectoderm in neurula-stage vertebrate embryos. In this sense, the neural crest is a morphological term akin to head fold or limb bud. This region of the dorsal neural tube consists of neural crest cells, a special population(s) of cell, that give rise to an astonishing number of cell types and to an equally astonishing number of tissues and organs. Neural crest cell contributions may be direct — providing cells — or indirect — providing a necessary, often inductive, environment in which other cells develop. The enormous range of cell types produced provides an important source of evidence of the neural crest as a germ layer, bringing the number of germ layers to four — ectoderm, endoderm, mesoderm, and neural crest. In this paper I provide a brief overview of the major phases of investigation into the neural crest and the major players involved, discuss how the origin of the neural crest relates to the origin of the nervous system in vertebrate embryos, discuss the impact on the germ-layer theory of the discovery of the neural crest and of secondary neurulation, and present evidence of the neural crest as the fourth germ layer. A companion paper (Hall, Evol. Biol. 2008) deals with the evolutionary origins of the neural crest and neural crest cells.
The importance of neural networks has grown dramatically during this decade. While only a few years ago they were primarily of academic interest, now dozens of companies and many universities are investigating the potential use of these systems and products are beginning to appear. The idea of building a machine whose architecture is inspired by that of the brain has roots which go far back in history. Nowadays, technological advances of computers and the availability of custom integrated circuits, permit simulations of hundreds or even thousands of neurons. In conjunction, the growing interest in learning machines, non-linear dynamics and parallel computation spurred renewed attention in artificial neural networks. Many tentative applications have been proposed, including decision systems (associative memories, classifiers, data compressors and optimizers), or parametric models for signal processing purposes (system identification, automatic control, noise canceling, etc.). While they do not always outperform standard methods, neural network approaches are already used in some real world applications for pattern recognition and signal processing tasks. The tutorial is divided into six lectures, that where presented at the Third Graduate Summer Course on Computational Physics (September 3-7, 1990) on Parallel Architectures and Applications, organized by the European Physical Society: (1) Introduction: machine learning and biological computation. (2) Adaptive artificial neurons (perceptron, ADALINE, sigmoid units, etc.): learning rules and implementations. (3) Neural network systems: architectures, learning algorithms. (4) Applications: pattern recognition, signal processing, etc. (5) Elements of learning theory: how to build networks which generalize. (6) A case study: a neural network for on-line recognition of handwritten alphanumeric characters.
Full Text Available Dynamic behavior of a new class of information-processing systems called Cellular Neural Networks is investigated. In this paper we introduce a small parameter in the state equation of a cellular neural network and we seek for periodic phenomena. New approach is used for proving stability of a cellular neural network by constructing Lyapunov's majorizing equations. This algorithm is helpful for finding a map from initial continuous state space of a cellular neural network into discrete output. A comparison between cellular neural networks and cellular automata is made.
Fuzzy logic systems and feedforward neural networks are equivalent in essence. First, interpolation representations of fuzzy logic systems are introduced and several important conclusions are given. Then three important kinds of neural networks are defined, i.e. linear neural networks, rectangle wave neural networks and nonlinear neural networks. Then it is proved that nonlinear neural networks can be represented by rectangle wave neural networks. Based on the results mentioned above, the equivalence between fuzzy logic systems and feedforward neural networks is proved, which will be very useful for theoretical research or applications on fuzzy logic systems or neural networks by means of combining fuzzy logic systems with neural networks.
Braun, Theodore P; Marks, Daniel L
Decreased appetite and involuntary weight loss are common occurrences in chronic disease and have a negative impact on both quality of life and eventual mortality. Weight loss in chronic disease comes from both fat and lean mass, and is known as cachexia. Both alterations in appetite and body weight loss occur in a wide variety of diseases, including cancer, heart failure, renal failure, chronic obstructive pulmonary disease and HIV. An increase in circulating inflammatory cytokines has been implicated as a uniting pathogenic mechanism of cachexia and associated anorexia. One of the targets of inflammatory mediators is the central nervous system, and in particular feeding centers in the hypothalamus located in the ventral diencephalon. Current research has begun to elucidate the mechanisms by which inflammation reaches the hypothalamus, and the neural substrates underlying inflammatory anorexia. Research into these neural mechanisms has suggested new therapeutic possibilities, which have produced promising results in preclinical and clinical trials. This review will discuss inflammatory signaling in the hypothalamus that mediates anorexia, and the opportunities for therapeutic intervention that these mechanisms present. PMID:21475703
Schwappach, Cordula; Hutt, Axel; Beim Graben, Peter
We present numerical simulations of metastable states in heterogeneous neural fields that are connected along heteroclinic orbits. Such trajectories are possible representations of transient neural activity as observed, for example, in the electroencephalogram. Based on previous theoretical findings on learning algorithms for neural fields, we directly construct synaptic weight kernels from Lotka-Volterra neural population dynamics without supervised training approaches. We deliver a MATLAB neural field toolbox validated by two examples of one- and two-dimensional neural fields. We demonstrate trial-to-trial variability and distributed representations in our simulations which might therefore be regarded as a proof-of-concept for more advanced neural field models of metastable dynamics in neurophysiological data. PMID:26175671
Schwab, Jan M; Zhang, Yi; Kopp, Marcel A; Brommer, Benedikt; Popovich, Phillip G
During the transition from acute to chronic stages of recovery after spinal cord injury (SCI), there is an evolving state of immunologic dysfunction that exacerbates the problems associated with the more clinically obvious neurologic deficits. Since injury directly affects cells embedded within the "immune privileged/specialized" milieu of the spinal cord, maladaptive or inefficient responses are likely to occur. Collectively, these responses qualify as part of the continuum of "SCI disease" and are important therapeutic targets to improve neural repair and neurological outcome. Generic immune suppressive therapies have been largely unsuccessful, mostly because inflammation and immunity exert both beneficial (plasticity enhancing) and detrimental (e.g. glia- and neurodegenerative; secondary damage) effects and these functions change over time. Moreover, "compartimentalized" investigations, limited to only intraspinal inflammation and associated cellular or molecular changes in the spinal cord, neglect the reality that the structure and function of the CNS are influenced by systemic immune challenges and that the immune system is 'hardwired' into the nervous system. Here, we consider this interplay during the progression from acute to chronic SCI. Specifically, we survey impaired/non-resolving intraspinal inflammation and the paradox of systemic inflammatory responses in the context of ongoing chronic immune suppression and autoimmunity. The concepts of systemic inflammatory response syndrome (SIRS), compensatory anti-inflammatory response syndrome (CARS) and "neurogenic" spinal cord injury-induced immune depression syndrome (SCI-IDS) are discussed as determinants of impaired "host-defense" and trauma-induced autoimmunity. PMID:25017893
Full Text Available Chronic Daily Headache is a descriptive term that includes disorders with headaches on more days than not and affects 4% of the general population. The condition has a debilitating effect on individuals and society through direct cost to healthcare and indirectly to the economy in general. To successfully manage chronic daily headache syndromes it is important to exclude secondary causes with comprehensive history and relevant investigations; identify risk factors that predict its development and recognise its sub-types to appropriately manage the condition. Chronic migraine, chronic tension-type headache, new daily persistent headache and medication overuse headache accounts for the vast majority of chronic daily headaches. The scope of this article is to review the primary headache disorders. Secondary headaches are not discussed except medication overuse headache that often accompanies primary headache disorders. The article critically reviews the literature on the current understanding of daily headache disorders focusing in particular on recent developments in the treatment of frequent headaches.
Full Text Available Chronic paronychia is an inflammatory disorder of the nail folds of a toe or finger presenting as redness, tenderness, and swelling. It is recalcitrant dermatoses seen commonly in housewives and housemaids. It is a multifactorial inflammatory reaction of the proximal nail fold to irritants and allergens. Repeated bouts of inflammation lead to fibrosis of proximal nail fold with poor generation of cuticle, which in turn exposes the nail further to irritants and allergens. Thus, general preventive measures form cornerstone of the therapy. Though previously anti-fungals were the mainstay of therapy, topical steroid creams have been found to be more effective in the treatment of chronic paronychia. In recalcitrant cases, surgical treatment may be resorted to, which includes en bloc excision of the proximal nail fold or an eponychial marsupialization, with or without nail plate removal. Newer therapies and surgical modalities are being employed in the management of chronic paronychia. In this overview, we review recent epidemiological studies, present current thinking on the pathophysiology leading to chronic paronychia, discuss the challenges chronic paronychia presents, and recommend a commonsense approach to management.
Li, Chunyan; Wu, Zhizhen; Limnuson, Kanokwan; Cheyuo, Cletus; Wang, Ping; Ahn, Chong H; Narayan, Raj K; Hartings, Jed A
We present a microfabricated neural catheter for real-time continuous monitoring of multiple physiological, biochemical and electrophysiological variables that are critical to the diagnosis and treatment of evolving brain injury. The first generation neural catheter was realized by polyimide-based micromachining and a spiral rolling packaging method. The mechanical design and electrical operation of the microsensors were optimized and tailored for multimodal monitoring in rat brain such that the potential thermal, chemical and electrical crosstalk among the microsensors as well as errors from micro-environmental fluctuations are minimized. In vitro cytotoxicity analyses suggest that the developed neural catheters are minimally toxic to rat cortical neuronal cultures. In addition, in vivo histopathology results showed neither acute nor chronic inflammation for 7 days post implantation. The performance of the neural catheter was assessed in an in vivo needle prick model as a translational replica of a "mini" traumatic brain injury. It successfully monitored the expected transient brain oxygen, temperature, regional cerebral blood flow, and DC potential changes during the passage of spreading depolarization waves. We envisage that the developed multimodal neural catheter can be used to decipher the causes and consequences of secondary brain injury processes with high spatial and temporal resolution while reducing the potential for iatrogenic injury inherent to current use of multiple invasive probes. PMID:26780443
Darsey, Jerry A; Griffin, William O; Joginipelli, Sravanthi; Melapu, Venkata Kiran
Advancement of science and technology has prompted researchers to develop new intelligent systems that can solve a variety of problems such as pattern recognition, prediction, and optimization. The ability of the human brain to learn in a fashion that tolerates noise and error has attracted many researchers and provided the starting point for the development of artificial neural networks: the intelligent systems. Intelligent systems can acclimatize to the environment or data and can maximize the chances of success or improve the efficiency of a search. Due to massive parallelism with large numbers of interconnected processers and their ability to learn from the data, neural networks can solve a variety of challenging computational problems. Neural networks have the ability to derive meaning from complicated and imprecise data; they are used in detecting patterns, and trends that are too complex for humans, or other computer systems. Solutions to the toughest problems will not be found through one narrow specialization; therefore we need to combine interdisciplinary approaches to discover the solutions to a variety of problems. Many researchers in different disciplines such as medicine, bioinformatics, molecular biology, and pharmacology have successfully applied artificial neural networks. This chapter helps the reader in understanding the basics of artificial neural networks, their applications, and methodology; it also outlines the network learning process and architecture. We present a brief outline of the application of neural networks to medical diagnosis, drug discovery, gene identification, and protein structure prediction. We conclude with a summary of the results from our study on tuberculosis data using neural networks, in diagnosing active tuberculosis, and predicting chronic vs. infiltrative forms of tuberculosis. PMID:25502388
Chun Xiang Jin
Full Text Available The present review is focused on the clinical significance of lactoferrin in pancreatic secretions and stone formation in chronic pancreatitis, and of serum anti-lactoferrin antibody in autoimmune pancreatitis. Lactoferrin secretion is increased in pancreatic secretions in calcified and non-calcified chronic pancreatitis. Lactoferrin, pancreatic stone protein and trypsin are present in pancreatic stones. We cannot conclude which protein is more important for the precipitate and stone formation. The presence of antilactoferrin antibody has been reported in serum in autoimmune diseases, such as autoimmune pancreatitis. The coincidental appearance of autoimmune pancreatitis with extrapancreatic autoimmune diseases strongly suggests a common autoimmune mechanism and lactoferrin is a candidate antigen. Lactoferrin may play an important role as a precipitate protein in pancreatic stone formation in chronic pancreatitis and as an autoantigen in autoimmune pancreatitis. Further studies are required to better understand the role of lactoferin.
Gordon, A S; Collier, K; Diamond, I.
The acute and chronic neurologic effects of ethanol appear to be due to its interaction with neural cell membranes. Chronic exposure to ethanol induces changes in the membrane that lead to tolerance to the effects of ethanol. However, the actual membrane changes that account for tolerance to ethanol are not understood. We have developed a model cell culture system, using NG108-15 neuroblastoma-glioma hybrid cells, to study cellular tolerance to ethanol. We have found that adenosine receptor-s...
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...
Nada M. Al Sallami
Full Text Available This paper discusses a proposed load balance technique based on artificial neural network. It distributes workload equally across all the nodes by using back propagation learning algorithm to train feed forward Artificial Neural Network (ANN. The proposed technique is simple and it can work efficiently when effective training sets are used. ANN predicts the demand and thus allocates resources according to that demand. Thus, it always maintains the active servers according to current demand, which results in low energy consumption than the conservative approach of over-provisioning. Furthermore, high utilization of server results in more power consumption, server running at higher utilization can process more workload with similar power usage. Finally the existing load balancing techniques in cloud computing are discussed and compared with the proposed technique based on various parameters like performance, scalability, associated overhead... etc. In addition energy consumption and carbon emission perspective are also considered to satisfy green computing.
Tagliaferri, R; Andreon, S; Capozziello, S; Donalek, C; Giordano, G; Tagliaferri, Roberto; Longo, Giuseppe; Andreon, Stefano; Capozziello, Salvatore; Donalek, Ciro; Giordano, Gerardo
We present a neural network based approach to the determination of photometric redshift. The method was tested on the Sloan Digital Sky Survey Early Data Release (SDSS-EDR) reaching an accuracy comparable and, in some cases, better than SED template fitting techniques. Different neural networks architecture have been tested and the combination of a Multi Layer Perceptron with 1 hidden layer (22 neurons) operated in a Bayesian framework, with a Self Organizing Map used to estimate the accuracy of the results, turned out to be the most effective. In the best experiment, the implemented network reached an accuracy of 0.020 (interquartile error) in the range 0
Neural network methods are described for color coordinate conversion between color systems. We present solutions for two problems of (1) conversion between two color-specification systems and (2) conversion between a color-specification system and a device coordinate system. First we discuss the color-notation conversion between the Munsell and CIE color systems. The conversion algorithms are developed for both directions of Munsell-to-L*a*b* and L*a*b*-to-Munsell. Second we discuss a neural network method for color reproduction on a printer. The color reproduction problem on the printer using more than four inks is considered as the problem of controlling an unknown system. The practical algorithms are presented for realizing the mapping from the L*a*b* space to the CMYK space. Moreover the method is applied to the color control using CMYK plus light cyan and light magenta.
Ruttor, Andreas; Kinzel, Wolfgang; Naeh, Rivka; Kanter, Ido
Different scaling properties for the complexity of bidirectional synchronization and unidirectional learning are essential for the security of neural cryptography. Incrementing the synaptic depth of the networks increases the synchronization time only polynomially, but the success of the geometric attack is reduced exponentially and it clearly fails in the limit of infinite synaptic depth. This method is improved by adding a genetic algorithm, which selects the fittest neural networks. The probability of a successful genetic attack is calculated for different model parameters using numerical simulations. The results show that scaling laws observed in the case of other attacks hold for the improved algorithm, too. The number of networks needed for an effective attack grows exponentially with increasing synaptic depth. In addition, finite-size effects caused by Hebbian and anti-Hebbian learning are analyzed. These learning rules converge to the random walk rule if the synaptic depth is small compared to the square root of the system size.
Different scaling properties for the complexity of bidirectional synchronization and unidirectional learning are essential for the security of neural cryptography. Incrementing the synaptic depth of the networks increases the synchronization time only polynomially, but the success of the geometric attack is reduced exponentially and it clearly fails in the limit of infinite synaptic depth. This method is improved by adding a genetic algorithm, which selects the fittest neural networks. The probability of a successful genetic attack is calculated for different model parameters using numerical simulations. The results show that scaling laws observed in the case of other attacks hold for the improved algorithm, too. The number of networks needed for an effective attack grows exponentially with increasing synaptic depth. In addition, finite-size effects caused by Hebbian and anti-Hebbian learning are analyzed. These learning rules converge to the random walk rule if the synaptic depth is small compared to the square root of the system size
Greaves, Malcolm W; Tan, Kian Teo
Chronic urticaria is an umbrella term, which encompasses physical urticarias, chronic "idiopathic" urticaria and urticarial vasculitis. It is important to recognize patients with physical urticarias as the investigation and treatment differs in important ways from patients with idiopathic chronic urticaria or urticarial vasculitis. Although relatively uncommon, urticarial vasculitis is an important diagnosis to make and requires histological confirmation by biopsy. Underlying systemic disease and systemic involvement, especially of the kidneys, should be sought. It is now recognized that chronic "idiopathic" urticaria includes a subset with an autoimmune basis caused by circulating autoantibodies against the high affinity IgE receptor (FceR1) and less commonly against IgE. Although the autologous serum skin test has been proven useful in prompting search for and characterization of circulating wheal-producing factors in chronic urticaria, its specificity as a screening test for presence of functional anti-FceR1 is low, and confirmation by demonstration of histamine-releasing activity in the patient's serum must be the benchmark test in establishing this diagnosis. Improved screening tests are being sought; for example, ability of the chronic urticaria patient's serum to evoke expression of CD 203c on donor human basophils is showing some promise. The strong association between autoimmune thyroid disease and autoimmune urticaria is also an area of ongoing research. Drug treatment continues to be centered on the H1 antihistamines, and the newer second-generation compounds appear to be safe and effective even in off-label dosage. Use of systemic steroids should be confined to special circumstances such as tapering regimens for acute flare-ups. Use of leukotriene antagonists is becoming popular, but the evidence for efficacy is conflicting. Cyclosporin is also effective and can be used in selected cases of autoimmune urticaria, and it is also effective in non
A. Fiszelew; P. Britos; G. Perichisky; R. García-Martínez
This work deals with methods for finding optimal neural network architectures to learn particular problems. A genetic algorithm is used to discover suitable domain specific architectures; this evolutionary algorithm applies direct codification and uses the error from the trained network as a performance measure to guide the evolution. The network training is accomplished by the back-propagation algorithm; techniques such as training repetition, early stopping and complex regulation are employ...
Brain-controlled prostheses have the potential to improve the quality of life of a large number of paralyzed persons by allowing them to control prosthetic limbs simply by thought. An essential requirement for natural use of such neural prostheses is that the user should be provided with somatosensory feedback from the artificial limb. This can be achieved by electrically stimulating small populations of neurons in the cortex; a process known as cortical microstimulation. This dissertation de...
Lu, Zhiyun; Sindhwani, Vikas; Sainath, Tara N.
Recurrent neural networks (RNNs), including long short-term memory (LSTM) RNNs, have produced state-of-the-art results on a variety of speech recognition tasks. However, these models are often too large in size for deployment on mobile devices with memory and latency constraints. In this work, we study mechanisms for learning compact RNNs and LSTMs via low-rank factorizations and parameter sharing schemes. Our goal is to investigate redundancies in recurrent architectures where compression ca...
Gao, Yuan; Glowacka, Dorota
This paper introduces two recurrent neural network structures called Simple Gated Unit (SGU) and Deep Simple Gated Unit (DSGU), which are general structures for learning long term dependencies. Compared to traditional Long Short-Term Memory (LSTM) and Gated Recurrent Unit (GRU), both structures require fewer parameters and less computation time in sequence classification tasks. Unlike GRU and LSTM, which require more than one gates to control information flow in the network, SGU and DSGU only...
Maggini, Marco; Jain, Lakhmi
This handbook presents some of the most recent topics in neural information processing, covering both theoretical concepts and practical applications. The contributions include: Deep architectures Recurrent, recursive, and graph neural networks Cellular neural networks Bayesian networks Approximation capabilities of neural networks Semi-supervised learning Statistical relational learning Kernel methods for structured data Multiple classifier systems Self organisation and modal learning Applications to ...
Yuichi Hori; Xueying Gu; Xiaodong Xie; Kim, Seung K.
BACKGROUND: Success in islet-transplantation-based therapies for type 1 diabetes, coupled with a worldwide shortage of transplant-ready islets, has motivated efforts to develop renewable sources of islet-replacement tissue. Islets and neurons share features, including common developmental programs, and in some species brain neurons are the principal source of systemic insulin. METHODS AND FINDINGS: Here we show that brain-derived human neural progenitor cells, exposed to a series of signals t...
ICSC, 2000 - (Bothe, H.; Rojas, R.), s. 29-35 ISBN 3-906454-21-5. [NC'2000. ICSC Symposium on Neural Computation /2./. Berlin (DE), 23.05.2000-26.05.2000] R&D Projects: GA ČR GA201/99/0092; GA ČR GA201/00/1489 Institutional research plan: AV0Z1030915 Subject RIV: BA - General Mathematics
Coombes, Stephen; Byrne, Áine
Neural mass models have been actively used since the 1970s to model the coarse grained activity of large populations of neurons and synapses. They have proven especially useful in understanding brain rhythms. However, although motivated by neurobiological considerations they are phenomenological in nature, and cannot hope to recreate some of the rich repertoire of responses seen in real neuronal tissue. In this chapter we consider the $\\theta$-neuron model that has recently been shown to admi...
Fallon, James B.; Irvine, Dexter R. F.; Shepherd, Robert K.
The success of modern neural prostheses is dependent on a complex interplay between the devices’ hardware and software and the dynamic environment in which the devices operate: the patient’s body or ‘wetware’. Over 110,000 severe/profoundly deaf individuals presently receive information enabling auditory awareness and speech perception from cochlear implants. The cochlear implant therefore provides a useful case study for a review of the complex interactions between hardware, software and wet...
Kulesa, Paul M.; McLennan, Rebecca
Embryonic cell migration patterns are amazingly complex in the timing and spatial distribution of cells throughout the vertebrate landscape. However, advances in in vivo visualization, cell interrogation, and computational modeling are extracting critical features that underlie the mechanistic nature of these patterns. The focus of this review highlights recent advances in the study of the highly invasive neural crest cells and their migratory patterns during embryonic development. We discuss...
Rispoli, Rossella; Conti, Carlo; Celli, Paolo; Caroli, Emanuela; Carletti, Sandro
Glioblastoma multiforme represents one of the most common brain cancers with a rather heterogeneous cellular composition, as indicated by the term “multiforme". Recent reports have described the isolation and identification of cancer neural stem cells from human adult glioblastoma multiforme, which possess the capacity to establish, sustain, and expand these tumours, even under the challenging settings posed by serial transplantation experiments. Our study focused on the distribution of neura...
Spiers, H. J.; Maguire, E. A.
Driving a vehicle is an indispensable daily behaviour for many people, yet we know little about how it is supported by the brain. Given that driving in the real world involves the engagement of many cognitive systems that rapidly change to meet varying environmental demands, identifying its neural basis presents substantial problems. By employing a unique combination of functional magnetic resonance imaging (fMRI), an accurate interactive virtual simulation of a bustling central London (UK) a...
Belanche Muñoz, Luis Antonio
This chapter studies a class of neuron models that computes a user-defined similarity function between inputs and weights. The neuron transfer function is formed by composition of an adapted logistic function with the quasi-linear mean of the partial input-weight similarities. The neuron model is capable of dealing directly with mixtures of continuous as well as discrete quantities, among other data types and there is provision for missing values. An artificial neural network using these n...
We investigated neural mechanisms that support voice recognition in a training paradigm with fMRI. The same listeners were trained on different weeks to categorize the mid-regions of voice-morph continua as an individual's voice. Stimuli implicitly defined a voice-acoustics space, and training explicitly defined a voice-identity space. The predefined centre of the voice category was shifted from the acoustic centre each week in opposite directions, so the same stimuli had different training h...
Kalbfleisch, M Layne
The terms gifted, talented, and intelligent all have meanings that suggest an individual's highly proficient or exceptional performance in one or more specific areas of strength. Other than Spearman's g, which theorizes about a general elevated level of potential or ability, more contemporary theories of intelligence are based on theoretical models that define ability or intelligence according to a priori categories of specific performance. Recent studies in cognitive neuroscience report on the neural basis of g from various perspectives such as the neural speed theory and the efficiency of prefrontal function. Exceptional talent is the result of interactions between goal-directed behavior and nonvolitional perceptual processes in the brain that have yet to be fully characterized and understood by the fields of psychology and cognitive neuroscience. Some developmental studies report differences in region-specific neural activation, recruitment patterns, and reaction times in subjects who are identified with high IQ scores according to traditional scales of assessment such as the WISC-III or Stanford-Binet. Although as cases of savants and prodigies illustrate, talent is not synonymous with high IQ. This review synthesizes information from the fields of psychometrics and gifted education, with findings from the neurosciences on the neural basis of intelligence, creativity, profiles of expert performers, cognitive function, and plasticity to suggest a paradigm for investigating talent as the maximal and productive use of either or both of one's high level of general intelligence or domain-specific ability. Anat Rec (Part B: New Anat) 277B:21-36, 2004. PMID:15052651
Ivyanskiy, Ilya; Sand, Carsten; Thomsen, Simon Francis
urticaria. We present a case series of 19 patients with chronic urticaria treated in a university department with omalizumab and give an overview of the existing literature comprising an additional 59 cases as well as a total of 139 patients enrolled in two randomized controlled trials comparing omalizumab......Omalizumab is a recombinant humanized monoclonal antibody that blocks the high-affinity Fc receptor of IgE. Omalizumab has been approved for the treatment of moderate to severe asthma; however, there is currently more and more data showing promising results in the management also of chronic...
Hess, K.; Straub, P.W.
A detailed description is given of the complex pathological picture observed in the case of a worker with 30 years' occupational exposure to lead in an accumulator factory (evolution of the disease, clinical findings, autopsy). In spite of a typical clinical picture, lead is not held responsible for the terminal encephalopathy, in view of the fact that Alzheimer's syndrome was discovered at autopsy. However, the neurovegetative asthenia and progressive kidney disease without hypertonia, but with uraemia, which preceded the encephalopathy are in all probability due to chronic lead poisoning. The article discusses the diagnosis and symptomatology of chronic lead poisoning, encephalopathy and kidney disease.
Linnenberger, Anna; McLeod, Robert R.; Basta, Tamara; Stowell, Michael H. B.
We investigate holographic optical tweezing combined with step-and-repeat maskless projection micro-stereolithography for fine control of 3D positioning of living cells within a 3D microstructured hydrogel grid. Samples were fabricated using three different cell lines; PC12, NT2/D1 and iPSC. PC12 cells are a rat cell line capable of differentiation into neuron-like cells NT2/D1 cells are a human cell line that exhibit biochemical and developmental properties similar to that of an early embryo and when exposed to retinoic acid the cells differentiate into human neurons useful for studies of human neurological disease. Finally induced pluripotent stem cells (iPSC) were utilized with the goal of future studies of neural networks fabricated from human iPSC derived neurons. Cells are positioned in the monomer solution with holographic optical tweezers at 1064 nm and then are encapsulated by photopolymerization of polyethylene glycol (PEG) hydrogels formed by thiol-ene photo-click chemistry via projection of a 512x512 spatial light modulator (SLM) illuminated at 405 nm. Fabricated samples are incubated in differentiation media such that cells cease to divide and begin to form axons or axon-like structures. By controlling the position of the cells within the encapsulating hydrogel structure the formation of the neural circuits is controlled. The samples fabricated with this system are a useful model for future studies of neural circuit formation, neurological disease, cellular communication, plasticity, and repair mechanisms.
Having in mind the time spent on the uneventful work of characterization of the radiation beams used in a ionizing radiation metrology laboratory, the Metrology Service of the Centro Regional de Ciencias Nucleares do Nordeste - CRCN-NE verified the applicability of artificial intelligence (artificial neural networks) to perform the spectrometry in photon fields. For this, was developed a multilayer neural network, as an application for the classification of patterns in energy, associated with a thermoluminescent dosimetric system (TLD-700 and TLD-600). A set of dosimeters was initially exposed to various well known medium energies, between 40 keV and 1.2 MeV, coinciding with the beams determined by ISO 4037 standard, for the dose of 10 mSv in the quantity Hp(10), on a chest phantom (ISO slab phantom) with the purpose of generating a set of training data for the neural network. Subsequently, a new set of dosimeters irradiated in unknown energies was presented to the network with the purpose to test the method. The methodology used in this work was suitable for application in the classification of energy beams, having obtained 100% of the classification performed. (authors)
Fallon, James B.; Irvine, Dexter R. F.; Shepherd, Robert K.
The success of modern neural prostheses is dependent on a complex interplay between the devices' hardware and software and the dynamic environment in which the devices operate: the patient's body or 'wetware'. Over 120 000 severe/profoundly deaf individuals presently receive information enabling auditory awareness and speech perception from cochlear implants. The cochlear implant therefore provides a useful case study for a review of the complex interactions between hardware, software and wetware, and of the important role of the dynamic nature of wetware. In the case of neural prostheses, the most critical component of that wetware is the central nervous system. This paper will examine the evidence of changes in the central auditory system that contribute to changes in performance with a cochlear implant, and discuss how these changes relate to electrophysiological and functional imaging studies in humans. The relationship between the human data and evidence from animals of the remarkable capacity for plastic change of the central auditory system, even into adulthood, will then be examined. Finally, we will discuss the role of brain plasticity in neural prostheses in general.
Mason, Robert A; Just, Marcel Adam
We used functional MRI (fMRI) to assess neural representations of physics concepts (momentum, energy, etc.) in juniors, seniors, and graduate students majoring in physics or engineering. Our goal was to identify the underlying neural dimensions of these representations. Using factor analysis to reduce the number of dimensions of activation, we obtained four physics-related factors that were mapped to sets of voxels. The four factors were interpretable as causal motion visualization, periodicity, algebraic form, and energy flow. The individual concepts were identifiable from their fMRI signatures with a mean rank accuracy of .75 using a machine-learning (multivoxel) classifier. Furthermore, there was commonality in participants' neural representation of physics; a classifier trained on data from all but one participant identified the concepts in the left-out participant (mean accuracy = .71 across all nine participant samples). The findings indicate that abstract scientific concepts acquired in an educational setting evoke activation patterns that are identifiable and common, indicating that science education builds abstract knowledge using inherent, repurposed brain systems. PMID:27113732
Lee, Stephen M; Peltsch, Alicia; Kilmade, Maureen; Brien, Donald C; Coe, Brian C; Johnsrude, Ingrid S; Munoz, Douglas P
Every day we generate motor responses that are timed with external cues. This phenomenon of sensorimotor synchronization has been simplified and studied extensively using finger tapping sequences that are executed in synchrony with auditory stimuli. The predictive saccade paradigm closely resembles the finger tapping task. In this paradigm, participants follow a visual target that "steps" between two fixed locations on a visual screen at predictable ISIs. Eventually, the time from target appearance to saccade initiation (i.e., saccadic RT) becomes predictive with values nearing 0 msec. Unlike the finger tapping literature, neural control of predictive behavior described within the eye movement literature has not been well established and is inconsistent, especially between neuroimaging and patient lesion studies. To resolve these discrepancies, we used fMRI to investigate the neural correlates of predictive saccades by contrasting brain areas involved with behavior generated from the predictive saccade task with behavior generated from a reactive saccade task (saccades are generated toward targets that are unpredictably timed). We observed striking differences in neural recruitment between reactive and predictive conditions: Reactive saccades recruited oculomotor structures, as predicted, whereas predictive saccades recruited brain structures that support timing in motor responses, such as the crus I of the cerebellum, and structures commonly associated with the default mode network. Therefore, our results were more consistent with those found in the finger tapping literature. PMID:27054397
Dündar, Bumin Nuri; Oktem, Faruk; Armağan, Abdullah; Dündar, Nihal Olgaç; Bircan, Sema; Yesildag, Ahmet
Neurofibromatosis (NF) is a genetic disorder of the nervous system that primarily affects the development and growth of neural cell tissues. This disorder is characterized by the development of various tumors, including neurofibromas, neuroniomas, malignant and benign peripheral nerve sheath tumors, and meningiomas. Accompanying skin changes and bone deformities are also common in NF. However, genitourinary involvement in NF is a rare condition, and penile enlargement has been reported only in a few males with plexiform NF. We report a 6-year-old boy with chronic renal failure associated with plexiform neurofibromas of the bladder and prostatic urethra which led to urinary obstruction and macrogenitalia due to genitourinary NF. PMID:19826840
LUO Fei; WANG Jin-Yan
Acute pain is a warning protective sensation for any impending harm. However, chronic pain syndromes are often resistant diseases that may consume large amount of health care costs. It has been suggested by recent studies that pain perception may be formed in central neural networks via large-scale coding processes, which involves sensory, affective, and cognitive dimensions. Many central areas are involved in these processes, including structures from the spinal cord, the brain stem, the limbic system, to the cortices. Thus, chronic painful diseases may be the result of some abnormal coding within this network. A thorough investigation of coding mechanism of pain within the central neuromatrix will bring us great insight into the mechanisms responsible for the development of chronic pain, hence leading to novel therapeutic interventions for pain management.
Lee, Keekeun; Massia, Stephen; He, Jiping
This paper presents the fabrication of a benzocyclobutene (BCB) polymer-based intracortical neural implant for reliable and stable long-term implant function. BCB polymer has many attractive features for chronic implant application: flexibility, biocompatibility, low moisture uptake, low dielectric constant and easy surface modification. A 2 µm thick silicon backbone layer was attached underneath a flexible BCB electrode to improve mechanical stiffness. No insertion trauma was observed during penetrating into the dura of a rat. In vitro cytotoxicity tests of the completed BCB electrode revealed no toxic effects on cultured cells. The modified BCB surface with a dextran coating showed a significant reduction in 3T3 cell adhesion and spreading, indicating that this coating has the potential for lowering protein adsorption, minimizing inflammatory cell adhesion and glial scar formation in vivo, and thereby enhancing long-term implant performance.
Pulcu, Erdem; Elliott, Rebecca
Major depressive disorder, a complex neuropsychiatric condition, is associated with psychosocial functioning impairments that could become chronic even after symptoms remit. Social functioning impairments in patients could also pose coping difficulties to individuals around them. In this Personal View, we trace the potential neurobiological origins of these impairments down to three candidate domains-namely, social perception and emotion processing, motivation and reward value processing, and social decision making. We argue that the neural basis of abnormalities in these domains could be detectable at different temporal stages during social interactions (eg, before and after decision stages), particularly within frontomesolimbic networks (ie, frontostriatal and amygdala-striatal circuitries). We review some of the experimental designs used to probe these circuits and suggest novel, integrative approaches. We propose that an understanding of the interactions between these domains could provide valuable insights for the clinical stratification of major depressive disorder subtypes and might inform future developments of novel treatment options in return. PMID:26360902
Kim, June Hoan; Lee, Ho Jun; Min, Cheol Hong; Lee, Kyoung J.
Synchronized neural bursts are one of the most noticeable dynamic features of neural networks, being essential for various phenomena in neuroscience, yet their complex dynamics are not well understood. With extrinsic electrical and optical manipulations on cultured neural networks, we demonstrate that the regularity (or randomness) of burst sequences is in many cases determined by a (few) low-dimensional attractor(s) working under strong neural noise. Moreover, there is an optimal level of noise strength at which the regularity of the interburst interval sequence becomes maximal—a phenomenon of coherence resonance. The experimental observations are successfully reproduced through computer simulations on a well-established neural network model, suggesting that the same phenomena may occur in many in vivo as well as in vitro neural networks.
Full Text Available In the recent years, neural networks are considered as the best candidate for fast approximation with arbitrary accuracy in the time consuming problems. Dynamic analysis of structures against earthquake has the time consuming process. We employed two kinds of neural networks: Generalized Regression neural network (GR and Back-Propagation Wavenet neural network (BPW, for approximating of dynamic time history response of frame structures. GR is a traditional radial basis function neural network while BPW categorized as a wavelet neural network. In BPW, sigmoid activation functions of hidden layer neurons are substituted with wavelets and weights training are achieved using Scaled Conjugate Gradient (SCG algorithm. Comparison the results of BPW with those of GR in the dynamic analysis of eight story steel frame indicates that accuracy of the properly trained BPW was better than that of GR and therefore, BPW can be efficiently used for approximate dynamic analysis of structures.
Morgan, Angela T.; Masterton, Richard; Pigdon, Lauren; Connelly, Alan; Liegeois, Frederique J.
Severe and persistent speech disorder, dysarthria, may be present for life after brain injury in childhood, yet the neural correlates of this chronic disorder remain elusive. Although abundant literature is available on language reorganization after lesions in childhood, little is known about the capacity of motor speech networks to reorganize…
In the context of the Chernobyl and Fukushima accidents where large territories have been contaminated durably and as consequence where local populations are submitted to chronic low radiation doses, IRSN (French institute for radiation protection and nuclear safety) has led various studies to assess the impact of chronic low doses. Studies about the effects of uranium on marine life show that the impact is strongly dependent on the initial state of the individual (zebra Danio rerio fish). The studies about the impact of chronic low doses due to cesium and strontium contamination show different bio-accumulations: 137Cs is found in the animal's whole body with higher concentrations in muscles and kidneys while 90Sr is found almost exclusively in bones and it accumulates more in female mice than in males. The study dedicated to the sanitary impact of chronic low doses on the workers of the nuclear industry shows a higher risk for developing a leukemia, a pleural cancer or a melanoma but no correlation appears between doses and the appearance of the pleural cancer or the melanoma. (A.C.)
Martelletti, Paolo; Katsarava, Zaza; Lampl, Christian;
The debate on the clinical definition of refractory Chronic Migraine (rCM) is still far to be concluded. The importance to create a clinical framing of these rCM patients resides in the complete disability they show, in the high risk of serious adverse events from acute and preventative drugs and...
Prins, J.B.; Meer, J.W.M. van der; Bleijenberg, G.
During the past two decades, there has been heated debate about chronic fatigue syndrome (CFS) among researchers, practitioners, and patients. Few illnesses have been discussed so extensively. The existence of the disorder has been questioned, its underlying pathophysiology debated, and an effective
Skorupka, M; Kuhn, A; Mahrle, G
We report on a 41-year-old woman with keratosis lichenoides chronica, a disorder first described by Kaposi in 1886 as "lichen moniliformis", who later also developed chronic lymphatic leukaemia. Since Kaposi's original report, 38 additional cases have been reported. Occurrence of keratosis lichenoides chronica associated with malignant disorders has not previously been described. PMID:1548136
Shortt, S. E. D.; Haynes, E. R.
Debilitating illness in patients with only vague symptoms and minimal findings from physical examination and routine laboratory tests is frustrating for both patient and physician. A case of chronic mononucleosis is presented, and the literature describing the clinical and laboratory features of the syndrome is reviewed, with reference to four recent studies. Guidelines for diagnosis are suggested.
Full Text Available ... with chronic pain is that when we start looking for an explanation it’s not so much that we’re looking in the wrong place, but we may be looking in the wrong time. And what I mean ...
... Cancers by Body Location Childhood Cancers Adolescent & Young Adult Cancers Metastatic Cancer Recurrent Cancer Research NCI’s Role in ... on the hands and feet. Muscle pain. Itching. Diarrhea . Stages of Chronic Myeloproliferative Neoplasms Key Points There is no standard staging system ...
Rumessen, J J; Marner, B; Pedersen, N T;
In 60 consecutive patients clinically suspected of having chronic pancreatitis the serum concentration of the immunoglobulins (IgA, IgG, IgM), the IgG- and IgA-type non-organ-specific autoantibodies against nuclear material (ANA), smooth and striated muscle, mitochondria, basal membrane, and...
Full Text Available ... manageable, but chronic pain is different. And because it is different, we need to think about it in very different ways. Ed Covington, M.D.: ... no apparent physical injury or illness to explain it. The physician and the patient are accustomed to ...
Yinbao Qi; Xianming Fu; Ruobing Qian; Chaoshi Niu; Xiangpin Wei
In this study, we investigated alterations in the resting-state functional connectivity of the pre-frontal cortex in chronic heroin abusers using functional magnetic resonance imaging. We found that, compared with normal controls, in heroin abusers the left prefrontal cortex showed decreased functional connectivity with the left hippocampus, right anterior cingulate, left middle frontal gyrus, right middle frontal gyrus and right precuneus. However, the right prefrontal cortex showed decreased functional connectivity with the left orbital frontal cortex and the left middle frontal gyrus in chronic heroin abusers. These alterations of resting-state functional connectivity in the prefrontal cortices of heroin abusers suggest that their frontal executive neural network may be impaired, and that this may contribute to their continued heroin abuse and relapse after withdrawal.
Yosinski, Jason; Clune, Jeff; Nguyen, Anh; Fuchs, Thomas; Lipson, Hod
Recent years have produced great advances in training large, deep neural networks (DNNs), including notable successes in training convolutional neural networks (convnets) to recognize natural images. However, our understanding of how these models work, especially what computations they perform at intermediate layers, has lagged behind. Progress in the field will be further accelerated by the development of better tools for visualizing and interpreting neural nets. We introduce two such tools ...
Liu, Jian; Yang, Xiaoyu; Jiang, Lianying; Wang, Chunxin; Yang, Maoguang
Plasticity changes of uninjured nerves can result in a novel neural circuit after spinal cord injury, which can restore sensory and motor functions to different degrees. Although processes of neural plasticity have been studied, the mechanism and treatment to effectively improve neural plasticity changes remain controversial. The present study reviewed studies regarding plasticity of the central nervous system and methods for promoting plasticity to improve repair of injured central nerves. T...
Pau, L. F.; Johansen, F. S.
A report is presented on the use of neural signal interpretation theory and techniques for the purpose of classifying the shapes of a set of instrumentation signals, in order to calibrate devices, diagnose anomalies, generate tuning/settings, and interpret the measurement results. Neural signal......, and an explanation facility designed to help neural signal understanding is described. The results are compared to those obtained with a knowledge-based signal interpretation system using the same instrument and data...
The goal of this thesis was to investigate how information theory could be used to analyze artificial neural networks. For this purpose, two problems, a classification problem and a controller problem were considered. The classification problem was solved with a feedforward neural network trained with backpropagation, the controller problem was solved with a continuous-time recurrent neural network optimized with evolution.Results from the classification problem shows that mutual information ...
Lavin, Andrew; Gray, Scott
Deep convolutional neural networks take GPU days of compute time to train on large data sets. Pedestrian detection for self driving cars requires very low latency. Image recognition for mobile phones is constrained by limited processing resources. The success of convolutional neural networks in these situations is limited by how fast we can compute them. Conventional FFT based convolution is fast for large filters, but state of the art convolutional neural networks use small, 3x3 filters. We ...
Thorlund, Steffen; Sørensen, Anders; Lysell, Jimmy; Ronnenberg, Lasse; Lassen, Jens; Søfren, Kasper
This rapport focuses primarily on the principles underlying one particular type of artificial neural network and the programming of a primitive artificial intelligence for controlling a Lego NXT robot. A number of experiments were conducted in this regard which contribute to an assessment of how feasible it is to control robotic movement with the aid of artificial neural networks. A brief presentation of the theoretical basis for artificial neural networks is given to improve the reader’s...
Mead, W.C.; Brown, S.K.; Jones, R.D.; Bowling, P.S.; Barnes, C.W.
Recent work has demonstrated the ability of neural-network-based controllers to optimize and control machines with complex, non-linear, relatively unknown control spaces. We present a brief overview of neural networks via a taxonomy illustrating some capabilities of different kinds of neural networks. We present some successful control examples, particularly the optimization and control of a small-angle negative ion source.
Bressloff, Paul C.
We survey recent analytical approaches to studying the spatiotemporal dynamics of continuum neural fields. Neural fields model the large-scale dynamics of spatially structured biological neural networks in terms of nonlinear integrodifferential equations whose associated integral kernels represent the spatial distribution of neuronal synaptic connections. They provide an important example of spatially extended excitable systems with nonlocal interactions and exhibit a wide range of spatially coherent dynamics including traveling waves oscillations and Turing-like patterns.
Full Text Available Artificial neural networks (ANN have recently gained attention as fast and flexible equipment for modelling and designing microwave devices. The paper reviews the opportunities to use them for undertaking the tasks on the analysis and synthesis. The article focuses on what tasks might be solved using neural networks, what challenges might rise when using artificial neural networks for carrying out tasks on microwave devices and discusses problem-solving techniques for microwave devices with intermittent characteristics.Article in Lithuanian
Wei, Sun; Lujin, Zhang; Jinhai, Zou; Siyi, Miao
In this paper, the adaptive control based on neural network is studied. Firstly, a neural network based adaptive robust tracking control design is proposed for robotic systems under the existence of uncertainties. In this proposed control strategy, the NN is used to identify the modeling uncertainties, and then the disadvantageous effects caused by neural network approximating error and external disturbances in robotic system are counteracted by robust controller. Especially the proposed cont...
Ryo Adachi; Akimichi Takemura
In this paper we propose an investing strategy based on neural network models combined with ideas from game-theoretic probability of Shafer and Vovk. Our proposed strategy uses parameter values of a neural network with the best performance until the previous round (trading day) for deciding the investment in the current round. We compare performance of our proposed strategy with various strategies including a strategy based on supervised neural network models and show that our procedure is co...
"Process Neural Networks - Theory and Applications" proposes the concept and model of a process neural network for the first time, showing how it expands the mapping relationship between the input and output of traditional neural networks, and enhancing the expression capability for practical problems, with broad applicability to solving problems relating to process in practice. Some theoretical problems such as continuity, functional approximation capability, and computing capability, are strictly proved. The application methods, network construction principles, and optimization alg
This introduction to artificial neural networks summarizes some basic concepts of computational neuroscience and the resulting models of artificial neurons. The terminology of biological and artificial neurons, biological and machine learning and neural processing is introduced. The concepts of supervised and unsupervised learning are explained with examples from the power system area. Finally, a taxonomy of different types of neurons and different classes of artificial neural networks is presented.
Artur Popko; Marek Jakubowski; Rafał Wawer
Recognition of visual patterns is one of significant applications of Artificial Neural Networks, which partially emulate human thinking in the domain of artificial intelligence. In the paper, a simplified neural approach to recognition of visual patterns is portrayed and discussed. This paper is dedicated for investigators in visual patterns recognition, Artificial Neural Networking and related disciplines. The document describes also MemBrain application environment as a powerful and easy to...
The recognition of optical characters is known to be one of the earliest applications of Artificial Neural Networks, which partially emulate human thinking in the domain of artificial intelligence. In this paper, a simplified neural approach to recognition of optical or visual characters is portrayed and discussed. The document is expected to serve as a resource for learners and amateur investigators in pattern recognition, neural networking and related disciplines.
Hill, Felix; Cho, Kyunghyun; Jean, Sebastien; Devin, Coline; Bengio, Yoshua
Neural language models learn word representations, or embeddings, that capture rich linguistic and conceptual information. Here we investigate the embeddings learned by neural machine translation models, a recently-developed class of neural language model. We show that embeddings from translation models outperform those learned by monolingual models at tasks that require knowledge of both conceptual similarity and lexical-syntactic role. We further show that these effects hold when translatin...
Any cryptographic system is used to exchange confidential information securely over the public channel without any leakage of information to the unauthorized users. Neural networks can be used to generate a common secret key because the processes involve in Cryptographic system requires large computational power and very complex. Moreover Diffi hellman key exchange is suffered from man-in –the middle attack. For overcome this problem neural networks can be used.Two neural netwo...
... in the treatment. Treatment With chronic pain, the goal of treatment is to reduce pain and improve ... some treatments used for chronic pain. Less invasive psychotherapy, relaxation therapies, biofeedback, and behavior modification may also ...
Understanding Task Force Recommendations Screening for Chronic Kidney Disease The U.S. Preventive Services Task Force (Task Force) has issued a final recommendation on Screening for Chronic Kidney Disease (CKD) . This recommendation ...
... please visit this page: About CDC.gov . Chronic Fatigue Syndrome (CFS) Share Compartir Symptoms On this Page ... Symptoms What's the Clinical Course of CFS? Chronic fatigue syndrome can be misdiagnosed or overlooked because its ...
V K Vijayan
Full Text Available The global prevalence of physiologically defined chronic obstructive pulmonary disease (COPD in adults aged >40 yr is approximately 9-10 per cent. Recently, the Indian Study on Epidemiology of Asthma, Respiratory Symptoms and Chronic Bronchitis in Adults had shown that the overall prevalence of chronic bronchitis in adults >35 yr is 3.49 per cent. The development of COPD is multifactorial and the risk factors of COPD include genetic and environmental factors. Pathological changes in COPD are observed in central airways, small airways and alveolar space. The proposed pathogenesis of COPD includes proteinase-antiproteinase hypothesis, immunological mechanisms, oxidant-antioxidant balance, systemic inflammation, apoptosis and ineffective repair. Airflow limitation in COPD is defined as a postbronchodilator FEV1 (forced expiratory volume in 1 sec to FVC (forced vital capacity ratio <0.70. COPD is characterized by an accelerated decline in FEV1. Co morbidities associated with COPD are cardiovascular disorders (coronary artery disease and chronic heart failure, hypertension, metabolic diseases (diabetes mellitus, metabolic syndrome and obesity, bone disease (osteoporosis and osteopenia, stroke, lung cancer, cachexia, skeletal muscle weakness, anaemia, depression and cognitive decline. The assessment of COPD is required to determine the severity of the disease, its impact on the health status and the risk of future events (e.g., exacerbations, hospital admissions or death and this is essential to guide therapy. COPD is treated with inhaled bronchodilators, inhaled corticosteroids, oral theophylline and oral phosphodiesterase-4 inhibitor. Non pharmacological treatment of COPD includes smoking cessation, pulmonary rehabilitation and nutritional support. Lung volume reduction surgery and lung transplantation are advised in selected severe patients. Global strategy for the diagnosis, management and prevention of Chronic Obstructive Pulmonary Disease
Frolov, A. A.; Húsek, Dušan; Muraviev, I. P.; Polyakov, P.Y.
Roč. 18, č. 3 (2007), s. 698-707. ISSN 1045-9227 R&D Projects: GA AV ČR 1ET100300419; GA ČR GA201/05/0079 Institutional research plan: CEZ:AV0Z10300504 Keywords : recurrent neural network * Hopfield-like neural network * associative memory * unsupervised learning * neural network architecture * neural network application * statistics * Boolean factor analysis * dimensionality reduction * features clustering * concepts search * information retrieval Subject RIV: BB - Applied Statistics, Operational Research Impact factor: 2.769, year: 2007
An analysis of the accessible literature on the diagnostic applicability of artificial neural networks in coronary artery disease and pulmonary embolism appears to be comparative to the diagnosis of experienced doctors dealing with nuclear medicine. Differences in the employed models of artificial neural networks indicate a constant search for the most optimal parameters, which could guarantee the ultimate accuracy in neural network activity. The diagnostic potential within systems containing artificial neural networks proves this calculation tool to be an independent or/and an additional device for supporting a doctor's diagnosis of artery disease and pulmonary embolism. (author)
This text serves as a cookbook for neural network solutions to practical problems using C++. It will enable those with moderate programming experience to select a neural network model appropriate to solving a particular problem, and to produce a working program implementing that network. The book provides guidance along the entire problem-solving path, including designing the training set, preprocessing variables, training and validating the network, and evaluating its performance. Though the book is not intended as a general course in neural networks, no background in neural works is assum
This book systematically synthesizes research achievements in the field of fuzzy neural networks in recent years. It also provides a comprehensive presentation of the developments in fuzzy neural networks, with regard to theory as well as their application to system modeling and image restoration. Special emphasis is placed on the fundamental concepts and architecture analysis of fuzzy neural networks. The book is unique in treating all kinds of fuzzy neural networks and their learning algorithms and universal approximations, and employing simulation examples which are carefully designed to he
Valdes-Hernandez, Pedro A
In spite of the large amount of existing neural models in the literature, there is a lack of a systematic review of the possible effect of choosing different initial conditions on the dynamic evolution of neural systems. In this short review we intend to give insights into this topic by discussing some published examples. First, we briefly introduce the different ingredients of a neural dynamical model. Secondly, we introduce some concepts used to describe the dynamic behavior of neural models, namely phase space and its portraits, time series, spectra, multistability and bifurcations. We end with an analysis of the irreversibility of processes and its implications on the functioning of normal and pathological brains.
Full Text Available Achieving stable, long-term performance of implanted neural prosthetic devices has been challenging because of implantation related neuron loss and a foreign body response that results in encapsulating glial scar formation. To improve neuron-prosthesis integration and form chronic, stable interfaces, we investigated the potential of neurotrophin-eluting hydrogel-electrospun fiber mat (EFM composite coatings. In particular, poly(ethylene glycol-poly(ε-caprolactone (PEGPCL hydrogel- poly(ε-caprolactone (PCL EFM composites were applied as coatings for multielectrode arrays (MEAs. Coatings were stable and persisted on electrode surfaces for over 1 month under an agarose gel tissue phantom and over 9 months in a PBS immersion bath. To demonstrate drug release, a neurotrophin, nerve growth factor (NGF, was loaded in the PEGPCL hydrogel layer, and coating cytotoxicity and sustained NGF release were evaluated using a PC12 cell culture model. Quantitative MTT assays showed that these coatings had no significant toxicity toward PC12 cells, and neurite extension at day 7 and 14 confirmed sustained release of NGF at biologically significant concentrations for at least 2 weeks. Our results demonstrate that hydrogel-EFM composite materials can be applied to neural prostheses as a means to improve neuron-electrode proximity and enhance long-term device performance and function.
This podcast is an interview with Dr. Anand Parekh, U.S. Department of Health and Human Services Deputy Assistant Secretary for Health, and Dr. Samuel Posner, Preventing Chronic Disease Editor in Chief, about the definition and burden of multiple chronic conditions in the United States. Created: 5/20/2013 by Preventing Chronic Disease (PCD), National Center for Chronic Disease Prevention and Health Promotion (NCCDPHP). Date Released: 5/20/2013.
The purpose of this study was to clarify the effect of (-)-nicotine on cerebral benzodiazepine receptors (BzR) with radiotracer methods. The effect of (-)-nicotine on BzR was examined in in vitro studies using chronic (-)-nicotine-treated rats using 3H-diazepam. The in vitro radioreceptor assay showed a 14% increase in the maximum number of binding sites of BzR in chronic (-)-nicotine-treated rats in comparison with the control rats. Moreover, a convenient in vivo uptake index of 125I-iomazenil was calculated and a higher uptake of the radioactivity was observed in the chronic (-)-nicotine-treated group than in the control group. Although further studies of the mechanism of (-)-nicotine on such BzR changes are required, an increase in the amount of BzR in the cerebral cortex was found in rats that underwent chronic (-)-nicotine treatment, and this result contributed to the understanding of the effects of (-)-nicotine and smoking on neural functions
Navratilova, Edita; Morimura, Kozo; Xie, Jennifer Y; Atcherley, Christopher W; Ossipov, Michael H; Porreca, Frank
Chronic pain is an important public health problem that negatively impacts the quality of life of affected individuals and exacts enormous socioeconomic costs. Chronic pain is often accompanied by comorbid emotional disorders including anxiety, depression, and possibly anhedonia. The neural circuits underlying the intersection of pain and pleasure are not well understood. We summarize recent human and animal investigations and demonstrate that aversive aspects of pain are encoded in brain regions overlapping with areas processing reward and motivation. We highlight findings revealing anatomical and functional alterations of reward/motivation circuits in chronic pain. Finally, we review supporting evidence for the concept that pain relief is rewarding and activates brain reward/motivation circuits. Adaptations in brain reward circuits may be fundamental to the pathology of chronic pain. Knowledge of brain reward processing in the context of pain could lead to the development of new therapeutics for the treatment of emotional aspects of pain and comorbid conditions. J. Comp. Neurol. 524:1646-1652, 2016. © 2016 Wiley Periodicals, Inc. PMID:26788716
Ramachandran, V S; Rogers-Ramachandran, D
The study of phantom limbs has received tremendous impetus from recent studies linking changes in cortical topography with perceptual experience. Systematic psychophysical testing and functional imaging studies on patients with phantom limbs provide 2 unique opportunities. First, they allow us to demonstrate neural plasticity in the adult human brain. Second, by tracking perceptual changes (such as referred sensations) and changes in cortical topography in individual patients, we can begin to explore how the activity of sensory maps gives rise to conscious experience. Finally, phantom limbs also allow us to explore intersensory effects and the manner in which the brain constructs and updates a "body image" throughout life. PMID:10714655
Allen, J.D. Jr.; Schell, F.M.; Dodd, C.V.
The material of this Technical Memorandum is intended to provide the reader with conceptual and technical background information on the LILARTI neural network system of detail sufficient to confer an understanding of the LILARTI method as it is presently allied and to facilitate application of the method to problems beyond the scope of this document. Of particular importance in this regard are the descriptive sections and the Appendices which include operating instructions, partial listings of program output and data files, and network construction information.
Haworth, Guy McCrossan; Velliste, Meel
The existence of endgame databases challenges us to extract higher-grade information and knowledge from their basic data content. Chess players, for example, would like simple and usable endgame theories if such holy grail exists: endgame experts would like to provide such insights and be inspired by computers to do so. Here, we investigate the use of artificial neural networks (NNs) to mine these databases and we report on a first use of NNs on KPK. The results encourage us to suggest furthe...
Madsen, Per Printz
active participation in the future smart grid environment. One of the main obstacles for making optimal energy consumption is to have good predictions of the future energy consumption. This study is based on real consumption data from eight houses in Denmark. There are designed two different prediction...... models. It is shown that both of the predictions model produce a better consumption prediction then a naïve model. Seen in this perspective is it concluded that it is possible to use Artificial Neural Networks for predicting the energy consumption in ordinary family houses....
Praha : Ústav informatiky AV ČR, v. v. i. & MATFYZPRESS, 2007 - (Hakl, F.), s. 87-93 ISBN 978-80-7378-019-7. [Doktorandské dny '07 Ústavu informatiky AV ČR, v. v. i.. Malá Úpa (CZ), 17.09.2007-19.09.2007] R&D Projects: GA ČR(CZ) GD201/05/H014 Institutional research plan: CEZ:AV0Z10300504 Keywords : neural neworks * robotics * genetics algorithms
van de Grind, Wim
The conclusions drawn by Benjamin Libet from his work with colleagues on the timing of somatosensorial conscious experiences has met with a lot of praise and criticism. In this issue we find three examples of the latter. Here I attempt to place the divide between the two opponent camps in a broader perspective by analyzing the question of the relation between physical timing, neural timing, and experiential (mental) timing. The nervous system does a sophisticated job of recombining and recoding messages from the sensorial surfaces and if these processes are slighted in a theory, it might become necessary to postulate weird operations, including subjective back-referral. Neuroscientifically inspired theories are of necessity still based on guesses, extrapolations, and philosophically dubious manners of speech. They often assume some neural correlate of consciousness (NCC) as a part of the nervous system that transforms neural activity in reportable experiences. The majority of neuroscientists appear to assume that the NCC can compare and bind activity patterns only if they arrive simultaneously at the NCC. This leads to a search for synchrony or to theories in terms of the compensation of differences in neural delays (latencies). This is the main dimension of the Libet discussion. Examples from vision research, such as "temporal-binding-by-synchrony" and the "flash-lag" effect, are then used to illustrate these reasoning patterns in more detail. Alternatively one could assume symbolic representations of time and space (symbolic "tags") that are not coded in their own dimension (not time in time and space in space). Unless such tags are multiplexed with the quality message (tickle, color, or motion), one gets a binding problem for tags. One of the hidden aspects of the discussion between Libet and opponents appears to be the following. Is the NCC smarter than the rest of the nervous system, so that it can solve the problems of local sign (e.g., "where is the event
Priddy, Kevin L
This tutorial text provides the reader with an understanding of artificial neural networks (ANNs) and their application, beginning with the biological systems which inspired them, through the learning methods that have been developed and the data collection processes, to the many ways ANNs are being used today. The material is presented with a minimum of math (although the mathematical details are included in the appendices for interested readers), and with a maximum of hands-on experience. All specialized terms are included in a glossary. The result is a highly readable text that will teach t
Praha: Ústav informatiky AV ČR, v. v. i. & MATFYZPRESS, 2007 - (Hakl, F.), s. 87-93 ISBN 978-80-7378-019-7. [Doktorandské dny '07 Ústavu informatiky AV ČR, v. v. i.. Malá Úpa (CZ), 17.09.2007-19.09.2007] R&D Projects: GA ČR(CZ) GD201/05/H014 Institutional research plan: CEZ:AV0Z10300504 Keywords : neural neworks * robotics * genetics algorithms
Soldal, Kim Verner
Modularity is an architectural trait that is prominent in biological neural networks, but strangely absent in evolved artificial neural networks. This report contains the results of a theoretical study focusing on two questions about modularity in neural network systems. How does modularity emerge in biological neural networks, and when could modularity be useful in artificial neural networks?The theoretical study resulted in a hypothesis that modularity in biological neural networks is the r...
Fourteen patients with prior trauma and/or surgery of the lower extremity and suspected active chronic osteomyelitis underwent MR imaging. Eleven patients also underwent In-111 scanning. All patients had surgical confirmation, MR imaging could assess the extent of abnormal marrow and distinguish abnormal marrow due to granulation tissue from active osteomyelitis. The presence and extent of soft-tissue infection could be determined and distinguished from bone involvement in spite of tissue distortion. The course and origin of sinus tracts could be followed. MR imaging was more sensitive to active infection than In-111 scanning. All 11 cases of active osteomyelitis were correctly diagnosed with MR imaging. In-111 scans were positive in only five of the eight cases of active infection in which scans were obtained. MR imaging is useful in chronic complicated osteomyelitis
Ennis, Zandra Nymand; Dideriksen, Dorthe; Vaegter, Henrik Bjarke;
conducted according to PRISMA guidelines. All studies were conducted in patients with hip- or knee osteoarthritis and six out of seven studies had observation periods of less than three months. All included studies showed no or little efficacy with dubious clinical relevance. In conclusion, there is little......Acetaminophen (paracetamol) is the most commonly used analgesic worldwide and recommended as first-line treatment in all pain conditions by WHO. We performed a systematic literature review to evaluate the efficacy of acetaminophen when used for chronic pain conditions. Applying three broad search...... evidence to support the efficacy of acetaminophen treatment in patients with chronic pain conditions. Assessment of continuous efficacy in the many patients using acetaminophen worldwide is recommended. This article is protected by copyright. All rights reserved....
Hertzberger-ten Cate, R; Fiselier, T
On basis of clinical and immunogenetic factors most children with pauciarticular juvenile chronic arthritis can be included in one of the subtypes: type 1 and type 2 pauciarticular JCA. Type 1 occurs in young children, mainly girls, with involvement of knees, ankles or elbows. In the majority of children antinuclear antibodies can be detected. The presence of these autoantibodies is associated with chronic anterior uveitis. Type 2 or the juvenile spondylarthropathies include morbus Bechterew, the reactive arthritides and arthritis associated with psoriasis and inflammatory bowel diseases. Large joints of the lower extremities are involved, back pain is unusual at onset, but enthesitis is frequently present. There is a strong association with HLA-B27. Treatment of both subsets consists of non-steroidal anti-inflammatory drugs, application of intra-articular steroids, physio- and hydrotherapy and splinting. In children with a polyarticular course of type 1, or a prolonged course of type 2 disease modifying drugs are often needed. PMID:1957301
A long-lasting immunological suppression action seems to be produced by total lymphoid irradiation; some authors emphasize the favorable effect of this treatment on chronic progressive multiple sclerosis. In order to evaluate the actual role of TLI, 6 patients affected with chronic progressive multiple sclerosis were submitted to TLI with shaped and personalized fields at the Istituto del Radio, University of Brescia, Italy. The total dose delivered was 19.8 Gy in 4 weeks, 1.8 Gy/day, 5d/w; a week elapsed between the first and the second irradiation course. Disability according to Kurtzke scale was evaluated, together with blood lymphocyte count and irradiation side-effects, over a mean follow-up period of 20.8 months (range: 13-24). Our findings indicate that: a) disease progression was not markedly reduced by TLI; b) steroid hormones responsivity was restored after irradiation, and c) side-effects were mild and tolerable
Alexander, David S.
Persistent cough in children is a symptom, and the cause should be ascertained. Reactive airways disease is the most common reason for chronic cough in children over three to six months of age, especially at night. Under three months, the cause is likely to be more serious. Cough often disturbs parents more than the child, and physicians should consider parents' need for sleep and relief when deciding whether or not to prescribe cough suppressants. Investigations depend on the child's age, th...
Wagner, Johana B Castro; Pine, Harold S
The management of chronic cough, a common complaint in children, is challenging for most health care professionals. Millions of dollars are spent every year on unnecessary testing and treatment. A rational approach based on a detailed interview and a thorough physical examination guides further intervention and management. Inexpensive and simple homemade syrups based on dark honey have proved to be an effective measure when dealing with cough in children. PMID:23905830
Straub, Rainer H.; Schradin, Carsten
It has been recognized that during chronic inflammatory systemic diseases (CIDs) maladaptations of the immune, nervous, endocrine and reproductive system occur. Maladaptation leads to disease sequelae in CIDs. The ultimate reason of disease sequelae in CIDs remained unclear because clinicians do not consider bodily energy trade-offs and evolutionary medicine. We review the evolution of physiological supersystems, fitness consequences of genes involved in CIDs during different life-history sta...
Abe, Katsumi; Kamata, Noriko; Okazaki, Eiwa [Department of Radiology, Tokyo Metropolitan Komagome Hospital, 3-18-22 Honkomagome, Bunkyo-ku, Tokyo 113-8677 (Japan); Moriyama, Sachiko; Funata, Nobuaki [Department of Pathology, Tokyo Metropolitan Komagome Hospital, 3-18-22 Honkomagome, Bunkyo-ku, Tokyo 113-8677 (Japan); Takita, Junko; Yamada, Hideo; Takayama, Naohide [Department of Pediatrics, Tokyo Metropolitan Komagome Hospital, 3-18-22 Honkomagome, Bunkyo-ku, Tokyo 113-8677 (Japan)
Chronic pneumonitis of infancy (CPI) is a very rare lung disease in infants and young children. We report a 33-day-old infant with CPI, focusing on the radiologic aspects of the disease. Chest radiographs showed variable and non-specific appearances including ground-glass shadowing, consolidation, volume loss, and hyperinflation. Dense alveolar opacities progressed as CPI advanced. The radiologic features of our case reflected pathologic changes. (orig.)
Chronic renal failure is characterised by a gradual and sustained decline in renal clearance or glomerular filtration rate (GFR). Continued progression of renal failure will lead to renal function too low to sustain healthy life. In developed countries, such people will be offered renal replacement therapy in the form of dialysis or renal transplantation. Requirement for dialysis or transplantation is termed end-stage renal disease (ESRD).Diabetes, glomerulonephritis, hypertension, pyelone...
Morice, Alyn H.
Chronic cough has been suggested to be due to three conditions, asthma, post nasal drip, and reflux disease. A different paradigm has evolved in which cough is viewed as the primary condition characterised by afferent neuronal hypersensitivity and different aspects of this syndrome are manifest in the different phenotypes of cough. There are several advantages to viewing cough hypersensitivity as the unifying diagnosis; Communication with patients is aided, aetiology is not restricted and the...
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The infection from Epstein-Barr virus (EBV or virus of infectious mononucleosis, together with other herpesviruses’ infections, represents a prototype of persistent viral infections characterized by the property of the latency. Although the reactivations of the latent infection are associated with the resumption of the viral replication and eventually with the “shedding”, it is still not clear if this virus can determine chronic infectious diseases, more or less evolutive. These diseases could include some pathological conditions actually defined as “idiopathic”and characterized by the “viral persistence” as the more credible pathogenetic factor. Among the so-called idiopathic syndromes, the “chronic fatigue syndrome” (CFS aroused a great interest around the eighties of the last century when, just for its relationship with EBV, it was called “chronic mononucleosis” or “chronic EBV infection”.
Today CFS, as defined in 1994 by the CDC of Atlanta (USA, really represents a multifactorial syndrome characterized by a chronic course, where reactivation and remission phases alternate, and by a good prognosis
Smith, R. Neal; Colvin, Robert B.
Alloantibodies clearly cause acute antibody mediated rejection, and all available evidence supports their pathogenic etiology in the development of chronic alloantibody mediated rejection (CAMR). But the slow evolution of this disease, the on-going immunosuppression, the variations in titer of alloantibodies, and variation in antigenic targets all complicate identifying which dynamic factors are most important clinically and pathologically. This review highlights the pathological factors rela...
A comprehensive clinicoroentgenological study was used to examine 494 patients with chronic pneumonia. Morphological and functional changes observed in the pulmonary pare and functional changes observed in the pulmonary parenchyma and bronchial tree were studied. Types of pneumosclerosis, tigns of exacerbation of chronic pneumonia and abscess formation, morphological and functional disorders of bronchial penetrability in the pneumonic zone were described. Three forms of chronic pneumonia: bronchial, bronchiectatic and abscessing are signled out. The bronchial form is subdivided into chronic pneumonia with chronic bronchitis without deformity and wi.th deforming chronic bronchitis. In the bronchiectatic form pneumonia can be with cylindrical, saccular and cyst-like bronchiectasia. The general diagnosis of chronic pneumonia is established clinically depending on type and variants in 89-94% of cases, by X-ray and sonographic findings in all patients; types and variants of disease are most frequently defined after bronchography
Barnes, Peter J; Burney, Peter G J; Silverman, Edwin K; Celli, Bartolome R; Vestbo, Jørgen; Wedzicha, Jadwiga A; Wouters, Emiel F M
Chronic obstructive pulmonary disease (COPD) is a common disease with high global morbidity and mortality. COPD is characterized by poorly reversible airway obstruction, which is confirmed by spirometry, and includes obstruction of the small airways (chronic obstructive bronchiolitis) and emphysema, which lead to air trapping and shortness of breath in response to physical exertion. The most common risk factor for the development of COPD is cigarette smoking, but other environmental factors, such as exposure to indoor air pollutants - especially in developing countries - might influence COPD risk. Not all smokers develop COPD and the reasons for disease susceptibility in these individuals have not been fully elucidated. Although the mechanisms underlying COPD remain poorly understood, the disease is associated with chronic inflammation that is usually corticosteroid resistant. In addition, COPD involves accelerated ageing of the lungs and an abnormal repair mechanism that might be driven by oxidative stress. Acute exacerbations, which are mainly triggered by viral or bacterial infections, are important as they are linked to a poor prognosis. The mainstay of the management of stable disease is the use of inhaled long-acting bronchodilators, whereas corticosteroids are beneficial primarily in patients who have coexisting features of asthma, such as eosinophilic inflammation and more reversibility of airway obstruction. Apart from smoking cessation, no treatments reduce disease progression. More research is needed to better understand disease mechanisms and to develop new treatments that reduce disease activity and progression. PMID:27189863
The diagnosis of chronic osteomyelitis is made on the basis of clinical, radiologic and histologic findings. The role of imaging in patients with known chronic osteomyelitis is to detect and to delineate areas of active infection. To correctly interpret the imaging findings, it is essential to take both the individual clinical findings and previous imaging studies into account. Reliable signs of active infection are bone marrow abscess, sequestra and sinus tract formation. Only the combined evaluation of bony changes together with alterations of the adjacent soft tissues provides good diagnostic accuracy. Projection radiography gives an overview of the condition of the bone, which provides the basis for follow-up and the selection of further imaging modalities. Computed tomography can be used to evaluate even discrete or complex bony alterations and to guide percutaneous biopsy or drainage. Magnetic resonance imaging achieves the best diagnostic sensitivity and specificity and provides superior contrast as well as anatomical resolution in both bone marrow and soft tissues. In this paper the features and clinical relevance of imaging in primary chronic osteomyelitis, posttraumatic osteomyelitis, tuberculous spondylitis and osteomyelitis of the diabetic foot are reviewed, with particular respect to MRI. (orig.)
Şeker, Murat; E. Selim YILDIRIM; BERKAY, Ahmet
Examples of successful applications in Artificial Intelligence (AI) field; With financial applications, Control, Communication, Processing Radar signals, Pattern Recognition, general DSP application, Nonlinear Systems can be given. In the financial applications, generally back propagation (Feedforwared) algorithms of the Neural Network (NN) uses. In this application, backpropagation algorithms applied to Multi Layer Feedforward Neural Network for the future estimations of foreign currency exc...
Schneider, Georg; Korte, Detlef; Rudolph, Stephan
Applications of neural networks have been reported on a lot in recent years, but the research on how to find reliable guidelines to design neural networks is still in its infancy. This work intends to provide some ideas on how to find useful predefined network structures for at least certain parts of the neural net. By breaking off to a certain extend the so-called black-box character of the neural net, the performance of the networks can be improved and the solutions of the nets get more transparent and understandable at the same time. Additionally, the ability of the neural nets to generalize from some training patterns to unlearned data regions is improved substantially. In this work two commonly used engineering principles such as the technique of dimensional analysis and the Laplace- transformation are used to identify suitable topologies for neural networks. The integration of the dimensional analysis in the context of feed-forward neural networks is presented. In the second part of this work the use of the Laplace- transformation in neural networks is demonstrated. Even though at the moment the application of this technique has been shown in a linear time-invariant process, a future use of this method in nonlinear system is considered.
Holeňa, Martin; Linke, D.; Steinfeldt, N.
Bangkok : King Mongkut's University of Technology Thonburi, 2009. s. 225-226. [ICONIP 2009. International Conference on Neural Information Processing /16./. 01.12.2009-05.12.2009, Bangkok] Institutional research plan: CEZ:AV0Z10300504 Keywords : evolutionary algorithms * empirical objective functions * surrogate modelling * surrogate modelling * artificial neural networks * boosting Subject RIV: IN - Informatics, Computer Science
We introduce the neural network approach to global fits of parton distribution functions. First we review previous work on unbiased parametrizations of deep-inelastic structure functions with faithful estimation of their uncertainties, and then we summarize the current status of neural network parton distribution fits
Masa, Peter; Hoen, Klaas; Wallinga, Hans
Targeted at high-energy physics research applications, our special-purpose analog neural processor can classify up to 70 dimensional vectors within 50 nanoseconds. The decision-making process of the implemented feedforward neural network enables this type of computation to tolerate weight discretiza
Jiang, J; Trundle, P; Ren, J
Given that neural networks have been widely reported in the research community of medical imaging, we provide a focused literature survey on recent neural network developments in computer-aided diagnosis, medical image segmentation and edge detection towards visual content analysis, and medical image registration for its pre-processing and post-processing, with the aims of increasing awareness of how neural networks can be applied to these areas and to provide a foundation for further research and practical development. Representative techniques and algorithms are explained in detail to provide inspiring examples illustrating: (i) how a known neural network with fixed structure and training procedure could be applied to resolve a medical imaging problem; (ii) how medical images could be analysed, processed, and characterised by neural networks; and (iii) how neural networks could be expanded further to resolve problems relevant to medical imaging. In the concluding section, a highlight of comparisons among many neural network applications is included to provide a global view on computational intelligence with neural networks in medical imaging. PMID:20713305
Training time decreases dramatically. In improved mathematical model of neural-network processor, temperature of neurons (in addition to connection strengths, also called weights, of synapses) varied during supervised-learning phase of operation according to mathematical formalism and not heuristic rule. Evidence that biological neural networks also process information at neuronal level.
Full Text Available Artificial neural networks can be used to predict share investment on the stock market, assess the reliability of credit client or predicting banking crises. Moreover, this paper discusses the principles of cooperation neural network algorithms with evolutionary method, and support vector machines. In addition, a reference is made to other methods of artificial intelligence, which are used in finance prediction.
Clark, J.W.; Winston, J.V.; Rafelski, J.
The plastic development of a neural-network model operating autonomously in discrete time is described by the temporal modification of interneuronal coupling strengths according to momentary neural activity. A simple algorithm (brainwashing) is found which, applied to nets with initially quasirandom connectivity, leads to model networks with properties conducive to the simulation of memory and learning phenomena. 18 references, 2 figures.
Clark, John W.; Winston, Jeffrey V.; Rafelski, Johann
The plastic development of a neural-network model operating autonomously in discrete time is described by the temporal modification of interneuronal coupling strengths according to momentary neural activity. A simple algorithm (“brainwashing”) is found which, applied to nets with initially quasirandom connectivity, leads to model networks with properties conductive to the simulation of memory and learning phenomena.
Sundman, Eva; Olofsson, Peder S.
Neural reflexes support homeostasis by modulating the function of organ systems. Recent advances in neuroscience and immunology have revealed that neural reflexes also regulate the immune system. Activation of the vagus nerve modulates leukocyte cytokine production and alleviates experimental shock and autoimmune disease, and recent data have…
This paper describes how a neural network, structured as a Multi Layer Perceptron, is trained to predict, simulate and control a non-linear process.......This paper describes how a neural network, structured as a Multi Layer Perceptron, is trained to predict, simulate and control a non-linear process....
Healy, Michael J.
The generalization properties of a class of neural architectures can be modelled mathematically. The model is a parallel predicate calculus based on pattern recognition and self-organization of long-term memory in a neural network. It may provide the basis for adaptive expert systems capable of inductive learning and rapid processing in a highly complex and changing environment.