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Sample records for neural circuits relevant

  1. Effects of intranasal oxytocin on neural processing within a socially relevant neural circuit.

    Science.gov (United States)

    Singh, Fiza; Nunag, Jason; Muldoon, Glennis; Cadenhead, Kristin S; Pineda, Jaime A; Feifel, David

    2016-03-01

    Dysregulation of the Mirror Neuron System (MNS) in schizophrenia (SCZ) may underlie the cognitive and behavioral manifestations of social dysfunction associated with that disorder. In healthy subjects intranasal (IN) oxytocin (OT) improves neural processing in the MNS and is associated with improved social cognition. OT's brain effects can be measured through its modulation of the MNS by suppressing EEG mu-band electrical activity (8-13Hz) in response to motion perception. Although IN OT's effects on social cognition have been tested in SCZ, OT's impact on the MNS has not been evaluated to date. Therefore, we designed a study to investigate the effects of two different OT doses on biological motion-induced mu suppression in SCZ and healthy subjects. EEG recordings were taken after each subject received a single IN administration of placebo, OT-24IU and OT-48IU in randomized order in a double-blind crossover design. The results provide support for OT's regulation of the MNS in both healthy and SCZ subjects, with the optimal dose dependent on diagnostic group and sex of subject. A statistically significant response was seen in SCZ males only, indicating a heightened sensitivity to those effects, although sex hormone related effects cannot be ruled out. In general, OT appears to have positive effects on neural circuitry that supports social cognition and socially adaptive behaviors. Published by Elsevier B.V.

  2. Robust information propagation through noisy neural circuits.

    Science.gov (United States)

    Zylberberg, Joel; Pouget, Alexandre; Latham, Peter E; Shea-Brown, Eric

    2017-04-01

    Sensory neurons give highly variable responses to stimulation, which can limit the amount of stimulus information available to downstream circuits. Much work has investigated the factors that affect the amount of information encoded in these population responses, leading to insights about the role of covariability among neurons, tuning curve shape, etc. However, the informativeness of neural responses is not the only relevant feature of population codes; of potentially equal importance is how robustly that information propagates to downstream structures. For instance, to quantify the retina's performance, one must consider not only the informativeness of the optic nerve responses, but also the amount of information that survives the spike-generating nonlinearity and noise corruption in the next stage of processing, the lateral geniculate nucleus. Our study identifies the set of covariance structures for the upstream cells that optimize the ability of information to propagate through noisy, nonlinear circuits. Within this optimal family are covariances with "differential correlations", which are known to reduce the information encoded in neural population activities. Thus, covariance structures that maximize information in neural population codes, and those that maximize the ability of this information to propagate, can be very different. Moreover, redundancy is neither necessary nor sufficient to make population codes robust against corruption by noise: redundant codes can be very fragile, and synergistic codes can-in some cases-optimize robustness against noise.

  3. Robust information propagation through noisy neural circuits.

    Directory of Open Access Journals (Sweden)

    Joel Zylberberg

    2017-04-01

    Full Text Available Sensory neurons give highly variable responses to stimulation, which can limit the amount of stimulus information available to downstream circuits. Much work has investigated the factors that affect the amount of information encoded in these population responses, leading to insights about the role of covariability among neurons, tuning curve shape, etc. However, the informativeness of neural responses is not the only relevant feature of population codes; of potentially equal importance is how robustly that information propagates to downstream structures. For instance, to quantify the retina's performance, one must consider not only the informativeness of the optic nerve responses, but also the amount of information that survives the spike-generating nonlinearity and noise corruption in the next stage of processing, the lateral geniculate nucleus. Our study identifies the set of covariance structures for the upstream cells that optimize the ability of information to propagate through noisy, nonlinear circuits. Within this optimal family are covariances with "differential correlations", which are known to reduce the information encoded in neural population activities. Thus, covariance structures that maximize information in neural population codes, and those that maximize the ability of this information to propagate, can be very different. Moreover, redundancy is neither necessary nor sufficient to make population codes robust against corruption by noise: redundant codes can be very fragile, and synergistic codes can-in some cases-optimize robustness against noise.

  4. Astrocytes: Tailored to Support the Demand of Neural Circuits?

    DEFF Research Database (Denmark)

    Rasmussen, Rune

    2017-01-01

    Anatomy, physiology, proteomics, and genomics reveal the prospect of distinct highly specialized astrocyte subtypes within neural circuits.......Anatomy, physiology, proteomics, and genomics reveal the prospect of distinct highly specialized astrocyte subtypes within neural circuits....

  5. Document analysis with neural net circuits

    Science.gov (United States)

    Graf, Hans Peter

    1994-01-01

    Document analysis is one of the main applications of machine vision today and offers great opportunities for neural net circuits. Despite more and more data processing with computers, the number of paper documents is still increasing rapidly. A fast translation of data from paper into electronic format is needed almost everywhere, and when done manually, this is a time consuming process. Markets range from small scanners for personal use to high-volume document analysis systems, such as address readers for the postal service or check processing systems for banks. A major concern with present systems is the accuracy of the automatic interpretation. Today's algorithms fail miserably when noise is present, when print quality is poor, or when the layout is complex. A common approach to circumvent these problems is to restrict the variations of the documents handled by a system. In our laboratory, we had the best luck with circuits implementing basic functions, such as convolutions, that can be used in many different algorithms. To illustrate the flexibility of this approach, three applications of the NET32K circuit are described in this short viewgraph presentation: locating address blocks, cleaning document images by removing noise, and locating areas of interest in personal checks to improve image compression. Several of the ideas realized in this circuit that were inspired by neural nets, such as analog computation with a low resolution, resulted in a chip that is well suited for real-world document analysis applications and that compares favorably with alternative, 'conventional' circuits.

  6. Timing matters: Using optogenetics to chronically manipulate neural circuits and rhythms

    Directory of Open Access Journals (Sweden)

    Michelle M Sidor

    2014-02-01

    Full Text Available The ability to probe defined neural circuits with both the spatial and temporal resolution imparted by optogenetics has transformed the field of neuroscience. Although much attention has been paid to the advantages of manipulating neural activity at millisecond timescales in order to elicit time-locked neural responses, little consideration has been given to the manipulation of circuit activity at physiologically relevant times of day, across multiple days. Nearly all biological events are governed by the circadian clock and exhibit 24-hour rhythms in activity. Indeed, neural circuit activity itself exhibits a daily rhythm with distinct temporal peaks in activity occurring at specific times of the day. Therefore, experimentally probing circuit function within and across physiologically relevant time windows (minutes to hours in behaving animals is fundamental to understanding the function of any one particular circuit within the intact brain. Furthermore, understanding how circuit function changes with repeated manipulation is important for modeling the circuit-wide disruptions that occur with chronic disease states. Here, we review recent advances in optogenetic technology that allow for chronic, temporally specific, control of circuit activity and provide examples of chronic optogenetic paradigms that have been utilized in the search for the neural circuit basis of behaviors relevant to human neuropsychiatric disease.

  7. Neural circuit mechanisms of posttraumatic epilepsy

    Directory of Open Access Journals (Sweden)

    Robert F Hunt

    2013-06-01

    Full Text Available Traumatic brain injury (TBI greatly increases the risk for a number of mental health problems and is one of the most common causes of medically intractable epilepsy in humans. Several models of TBI have been developed to investigate the relationship between trauma, seizures, and epilepsy-related changes in neural circuit function. These studies have shown that the brain initiates immediate neuronal and glial responses following an injury, usually leading to significant cell loss in areas of the injured brain. Over time, long-term changes in the organization of neural circuits, particularly in neocortex and hippocampus, lead to an imbalance between excitatory and inhibitory neurotransmission and increased risk for spontaneous seizures. These include alterations to inhibitory interneurons and formation of new, excessive recurrent excitatory synaptic connectivity. Here, we review in vivo models of TBI as well as key cellular mechanisms of synaptic reorganization associated with posttraumatic epilepsy. The potential role of inflammation and increased blood brain barrier permeability in the pathophysiology of posttraumatic epilepsy is also discussed. A better understanding of mechanisms that promote the generation of epileptic activity versus those that promote compensatory brain repair and functional recovery should aid development of successful new therapies for posttraumatic epilepsy.

  8. Marginalization in neural circuits with divisive normalization

    Science.gov (United States)

    Beck, J.M.; Latham, P.E.; Pouget, A.

    2011-01-01

    A wide range of computations performed by the nervous system involves a type of probabilistic inference known as marginalization. This computation comes up in seemingly unrelated tasks, including causal reasoning, odor recognition, motor control, visual tracking, coordinate transformations, visual search, decision making, and object recognition, to name just a few. The question we address here is: how could neural circuits implement such marginalizations? We show that when spike trains exhibit a particular type of statistics – associated with constant Fano factors and gain-invariant tuning curves, as is often reported in vivo – some of the more common marginalizations can be achieved with networks that implement a quadratic nonlinearity and divisive normalization, the latter being a type of nonlinear lateral inhibition that has been widely reported in neural circuits. Previous studies have implicated divisive normalization in contrast gain control and attentional modulation. Our results raise the possibility that it is involved in yet another, highly critical, computation: near optimal marginalization in a remarkably wide range of tasks. PMID:22031877

  9. Explicit logic circuits discriminate neural states.

    Directory of Open Access Journals (Sweden)

    Lane Yoder

    Full Text Available The magnitude and apparent complexity of the brain's connectivity have left explicit networks largely unexplored. As a result, the relationship between the organization of synaptic connections and how the brain processes information is poorly understood. A recently proposed retinal network that produces neural correlates of color vision is refined and extended here to a family of general logic circuits. For any combination of high and low activity in any set of neurons, one of the logic circuits can receive input from the neurons and activate a single output neuron whenever the input neurons have the given activity state. The strength of the output neuron's response is a measure of the difference between the smallest of the high inputs and the largest of the low inputs. The networks generate correlates of known psychophysical phenomena. These results follow directly from the most cost-effective architectures for specific logic circuits and the minimal cellular capabilities of excitation and inhibition. The networks function dynamically, making their operation consistent with the speed of most brain functions. The networks show that well-known psychophysical phenomena do not require extraordinarily complex brain structures, and that a single network architecture can produce apparently disparate phenomena in different sensory systems.

  10. Genetic control of active neural circuits

    Directory of Open Access Journals (Sweden)

    Leon Reijmers

    2009-12-01

    Full Text Available The use of molecular tools to study the neurobiology of complex behaviors has been hampered by an inability to target the desired changes to relevant groups of neurons. Specific memories and specific sensory representations are sparsely encoded by a small fraction of neurons embedded in a sea of morphologically and functionally similar cells. In this review we discuss genetics techniques that are being developed to address this difficulty. In several studies the use of promoter elements that are responsive to neural activity have been used to drive long lasting genetic alterations into neural ensembles that are activated by natural environmental stimuli. This approach has been used to examine neural activity patterns during learning and retrieval of a memory, to examine the regulation of receptor trafficking following learning and to functionally manipulate a specific memory trace. We suggest that these techniques will provide a general approach to experimentally investigate the link between patterns of environmentally activated neural firing and cognitive processes such as perception and memory.

  11. A neural circuit for angular velocity computation

    Directory of Open Access Journals (Sweden)

    Samuel B Snider

    2010-12-01

    Full Text Available In one of the most remarkable feats of motor control in the animal world, some Diptera, such as the housefly, can accurately execute corrective flight maneuvers in tens of milliseconds. These reflexive movements are achieved by the halteres, gyroscopic force sensors, in conjunction with rapidly-tunable wing-steering muscles. Specifically, the mechanosensory campaniform sensilla located at the base of the halteres transduce and transform rotation-induced gyroscopic forces into information about the angular velocity of the fly's body. But how exactly does the fly's neural architecture generate the angular velocity from the lateral strain forces on the left and right halteres? To explore potential algorithms, we built a neuro-mechanical model of the rotation detection circuit. We propose a neurobiologically plausible method by which the fly could accurately separate and measure the three-dimensional components of an imposed angular velocity. Our model assumes a single sign-inverting synapse and formally resembles some models of directional selectivity by the retina. Using multidimensional error analysis, we demonstrate the robustness of our model under a variety of input conditions. Our analysis reveals the maximum information available to the fly given its physical architecture and the mathematics governing the rotation-induced forces at the haltere's end knob.

  12. A neural circuit for angular velocity computation.

    Science.gov (United States)

    Snider, Samuel B; Yuste, Rafael; Packer, Adam M

    2010-01-01

    In one of the most remarkable feats of motor control in the animal world, some Diptera, such as the housefly, can accurately execute corrective flight maneuvers in tens of milliseconds. These reflexive movements are achieved by the halteres, gyroscopic force sensors, in conjunction with rapidly tunable wing steering muscles. Specifically, the mechanosensory campaniform sensilla located at the base of the halteres transduce and transform rotation-induced gyroscopic forces into information about the angular velocity of the fly's body. But how exactly does the fly's neural architecture generate the angular velocity from the lateral strain forces on the left and right halteres? To explore potential algorithms, we built a neuromechanical model of the rotation detection circuit. We propose a neurobiologically plausible method by which the fly could accurately separate and measure the three-dimensional components of an imposed angular velocity. Our model assumes a single sign-inverting synapse and formally resembles some models of directional selectivity by the retina. Using multidimensional error analysis, we demonstrate the robustness of our model under a variety of input conditions. Our analysis reveals the maximum information available to the fly given its physical architecture and the mathematics governing the rotation-induced forces at the haltere's end knob.

  13. Localizing complex neural circuits with MEG data.

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    Belardinelli, P; Ciancetta, L; Pizzella, V; Del Gratta, C; Romani, G L

    2006-03-01

    During cognitive processing, the various cortical areas, with specialized functions, supply for different tasks. In most cases then, the information flows are processed in a parallel way by brain networks which work together integrating the single performances for a common goal. Such a step is generally performed at higher processing levels in the associative areas. The frequency range at which neuronal pools oscillate is generally wider than the one which is detectable by bold changes in fMRI studies. A high time resolution technique like magnetoencephalography or electroencephalography is therefore required as well as new data processing algorithms for detecting different coherent brain areas cooperating for one cognitive task. Our experiments show that no algorithm for the inverse problem solution is immune from bias. We propose therefore, as a possible solution, our software LOCANTO (LOcalization and Coherence ANalysis TOol). This new package features a set of tools for the detection of coherent areas. For such a task, as a default, it employs the algorithm with best performances for the neural landscape to be detected. If the neural landscape under attention involves more than two interacting areas the SLoreta algorithm is used. Our study shows in fact that SLoreta performance is not biased when the correlation among multiple sources is high. On the other hand, the Beamforming algorithm is more precise than SLoreta at localizing single or double sources but it gets a relevant localization bias when the sources are more than three and are highly correlated.

  14. Dynamical foundations of the neural circuit for bayesian decision making.

    Science.gov (United States)

    Morita, Kenji

    2009-07-01

    On the basis of accumulating behavioral and neural evidences, it has recently been proposed that the brain neural circuits of humans and animals are equipped with several specific properties, which ensure that perceptual decision making implemented by the circuits can be nearly optimal in terms of Bayesian inference. Here, I introduce the basic ideas of such a proposal and discuss its implications from the standpoint of biophysical modeling developed in the framework of dynamical systems.

  15. Neural Control of Energy Balance: Translating Circuits to Therapies

    OpenAIRE

    Gautron, Laurent; Elmquist, Joel K.; Williams, Kevin W.

    2015-01-01

    Recent insights into the neural circuits controlling energy balance and glucose homeostasis have rekindled the hope for development of novel treatments for obesity and diabetes. However, many therapies contribute relatively modest beneficial gains with accompanying side effects, and the mechanisms of action for other interventions remain undefined. This Review summarizes current knowledge linking the neural circuits regulating energy and glucose balance with current and potential pharmacother...

  16. The neural circuit basis of learning

    Science.gov (United States)

    Patrick, Kaifosh William John

    The astounding capacity for learning ranks among the nervous system's most impressive features. This thesis comprises studies employing varied approaches to improve understanding, at the level of neural circuits, of the brain's capacity for learning. The first part of the thesis contains investigations of hippocampal circuitry -- both theoretical work and experimental work in the mouse Mus musculus -- as a model system for declarative memory. To begin, Chapter 2 presents a theory of hippocampal memory storage and retrieval that reflects nonlinear dendritic processing within hippocampal pyramidal neurons. As a prelude to the experimental work that comprises the remainder of this part, Chapter 3 describes an open source software platform that we have developed for analysis of data acquired with in vivo Ca2+ imaging, the main experimental technique used throughout the remainder of this part of the thesis. As a first application of this technique, Chapter 4 characterizes the content of signaling at synapses between GABAergic neurons of the medial septum and interneurons in stratum oriens of hippocampal area CA1. Chapter 5 then combines these techniques with optogenetic, pharmacogenetic, and pharmacological manipulations to uncover inhibitory circuit mechanisms underlying fear learning. The second part of this thesis focuses on the cerebellum-like electrosensory lobe in the weakly electric mormyrid fish Gnathonemus petersii, as a model system for non-declarative memory. In Chapter 6, we study how short-duration EOD motor commands are recoded into a complex temporal basis in the granule cell layer, which can be used to cancel Purkinje-like cell firing to the longer duration and temporally varying EOD-driven sensory responses. In Chapter 7, we consider not only the temporal aspects of the granule cell code, but also the encoding of body position provided from proprioceptive and efference copy sources. Together these studies clarify how the cerebellum-like circuitry of the

  17. Classes of feedforward neural networks and their circuit complexity

    NARCIS (Netherlands)

    Shawe-Taylor, John S.; Anthony, Martin H.G.; Kern, Walter

    1992-01-01

    This paper aims to place neural networks in the context of boolean circuit complexity. We define appropriate classes of feedforward neural networks with specified fan-in, accuracy of computation and depth and using techniques of communication complexity proceed to show that the classes fit into a

  18. Japanese studies on neural circuits and behavior of Caenorhabditis elegans

    Science.gov (United States)

    Sasakura, Hiroyuki; Tsukada, Yuki; Takagi, Shin; Mori, Ikue

    2013-01-01

    The nematode Caenorhabditis elegans is an ideal organism for studying neural plasticity and animal behaviors. A total of 302 neurons of a C. elegans hermaphrodite have been classified into 118 neuronal groups. This simple neural circuit provides a solid basis for understanding the mechanisms of the brains of higher animals, including humans. Recent studies that employ modern imaging and manipulation techniques enable researchers to study the dynamic properties of nervous systems with great precision. Behavioral and molecular genetic analyses of this tiny animal have contributed greatly to the advancement of neural circuit research. Here, we will review the recent studies on the neural circuits of C. elegans that have been conducted in Japan. Several laboratories have established unique and clever methods to study the underlying neuronal substrates of behavioral regulation in C. elegans. The technological advances applied to studies of C. elegans have allowed new approaches for the studies of complex neural systems. Through reviewing the studies on the neuronal circuits of C. elegans in Japan, we will analyze and discuss the directions of neural circuit studies. PMID:24348340

  19. Complexity and competition in appetitive and aversive neural circuits

    Directory of Open Access Journals (Sweden)

    Crista L. Barberini

    2012-11-01

    Full Text Available Decision-making often involves using sensory cues to predict possible rewarding or punishing reinforcement outcomes before selecting a course of action. Recent work has revealed complexity in how the brain learns to predict rewards and punishments. Analysis of neural signaling during and after learning in the amygdala and orbitofrontal cortex, two brain areas that process appetitive and aversive stimuli, reveals a dynamic relationship between appetitive and aversive circuits. Specifically, the relationship between signaling in appetitive and aversive circuits in these areas shifts as a function of learning. Furthermore, although appetitive and aversive circuits may often drive opposite behaviors – approaching or avoiding reinforcement depending upon its valence – these circuits can also drive similar behaviors, such as enhanced arousal or attention; these processes also may influence choice behavior. These data highlight the formidable challenges ahead in dissecting how appetitive and aversive neural circuits interact to produce a complex and nuanced range of behaviors.

  20. Neural control of energy balance: translating circuits to therapies.

    Science.gov (United States)

    Gautron, Laurent; Elmquist, Joel K; Williams, Kevin W

    2015-03-26

    Recent insights into the neural circuits controlling energy balance and glucose homeostasis have rekindled the hope for development of novel treatments for obesity and diabetes. However, many therapies contribute relatively modest beneficial gains with accompanying side effects, and the mechanisms of action for other interventions remain undefined. This Review summarizes current knowledge linking the neural circuits regulating energy and glucose balance with current and potential pharmacotherapeutic and surgical interventions for the treatment of obesity and diabetes. Copyright © 2015 Elsevier Inc. All rights reserved.

  1. Adaptive Neurotechnology for Making Neural Circuits Functional .

    Science.gov (United States)

    Jung, Ranu

    2008-03-01

    Two of the most important trends in recent technological developments are that technology is increasingly integrated with biological systems and that it is increasingly adaptive in its capabilities. Neuroprosthetic systems that provide lost sensorimotor function after a neural disability offer a platform to investigate this interplay between biological and engineered systems. Adaptive neurotechnology (hardware and software) could be designed to be biomimetic, guided by the physical and programmatic constraints observed in biological systems, and allow for real-time learning, stability, and error correction. An example will present biomimetic neural-network hardware that can be interfaced with the isolated spinal cord of a lower vertebrate to allow phase-locked real-time neural control. Another will present adaptive neural network control algorithms for functional electrical stimulation of the peripheral nervous system to provide desired movements of paralyzed limbs in rodents or people. Ultimately, the frontier lies in being able to utilize the adaptive neurotechnology to promote neuroplasticity in the living system on a long-time scale under co-adaptive conditions.

  2. Integrated Circuit For Simulation Of Neural Network

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    Thakoor, Anilkumar P.; Moopenn, Alexander W.; Khanna, Satish K.

    1988-01-01

    Ballast resistors deposited on top of circuit structure. Cascadable, programmable binary connection matrix fabricated in VLSI form as basic building block for assembly of like units into content-addressable electronic memory matrices operating somewhat like networks of neurons. Connections formed during storage of data, and data recalled from memory by prompting matrix with approximate or partly erroneous signals. Redundancy in pattern of connections causes matrix to respond with correct stored data.

  3. Integrating Neural Circuits Controlling Female Sexual Behavior

    Directory of Open Access Journals (Sweden)

    Paul E. Micevych

    2017-06-01

    Full Text Available The hypothalamus is most often associated with innate behaviors such as is hunger, thirst and sex. While the expression of these behaviors important for survival of the individual or the species is nested within the hypothalamus, the desire (i.e., motivation for them is centered within the mesolimbic reward circuitry. In this review, we will use female sexual behavior as a model to examine the interaction of these circuits. We will examine the evidence for a hypothalamic circuit that regulates consummatory aspects of reproductive behavior, i.e., lordosis behavior, a measure of sexual receptivity that involves estradiol membrane-initiated signaling in the arcuate nucleus (ARH, activating β-endorphin projections to the medial preoptic nucleus (MPN, which in turn modulate ventromedial hypothalamic nucleus (VMH activity—the common output from the hypothalamus. Estradiol modulates not only a series of neuropeptides, transmitters and receptors but induces dendritic spines that are for estrogenic induction of lordosis behavior. Simultaneously, in the nucleus accumbens of the mesolimbic system, the mating experience produces long term changes in dopamine signaling and structure. Sexual experience sensitizes the response of nucleus accumbens neurons to dopamine signaling through the induction of a long lasting early immediate gene. While estrogen alone increases spines in the ARH, sexual experience increases dendritic spine density in the nucleus accumbens. These two circuits appear to converge onto the medial preoptic area where there is a reciprocal influence of motivational circuits on consummatory behavior and vice versa. While it has not been formally demonstrated in the human, such circuitry is generally highly conserved and thus, understanding the anatomy, neurochemistry and physiology can provide useful insight into the motivation for sexual behavior and other innate behaviors in humans.

  4. Classical Conditioning with Pulsed Integrated Neural Networks: Circuits and System

    DEFF Research Database (Denmark)

    Lehmann, Torsten

    1998-01-01

    In this paper we investigate on-chip learning for pulsed, integrated neural networks. We discuss the implementational problems the technology imposes on learning systems and we find that abiologically inspired approach using simple circuit structures is most likely to bring success. We develop a ...... chip to solve simple classical conditioning tasks, thus verifying the design methodologies put forward in the paper....

  5. Railway Track Circuit Fault Diagnosis Using Recurrent Neural Networks

    NARCIS (Netherlands)

    de Bruin, T.D.; Verbert, K.A.J.; Babuska, R.

    2017-01-01

    Timely detection and identification of faults in railway track circuits are crucial for the safety and availability of railway networks. In this paper, the use of the long-short-term memory (LSTM) recurrent neural network is proposed to accomplish these tasks based on the commonly available

  6. Railway track circuit fault diagnosis using recurrent neural networks

    NARCIS (Netherlands)

    de Bruin, T.D.; Verbert, K.A.J.; Babuska, R.

    2017-01-01

    Timely detection and identification of faults in railway track circuits are crucial for the safety and availability of railway networks. In this paper, the use of the long-short-term memory (LSTM) recurrent neural network is proposed to accomplish these tasks based on the commonly available

  7. Distinct neural circuits subserve interpersonal and non-interpersonal emotions.

    Science.gov (United States)

    Landa, Alla; Wang, Zhishun; Russell, James A; Posner, Jonathan; Duan, Yunsuo; Kangarlu, Alayar; Huo, Yuankai; Fallon, Brian A; Peterson, Bradley S

    2013-01-01

    Emotions elicited by interpersonal versus non-interpersonal experiences have different effects on neurobiological functioning in both animals and humans. However, the extent to which the brain circuits underlying interpersonal and non-interpersonal emotions are distinct still remains unclear. The goal of our study was to assess whether different neural circuits are implicated in the processing of arousal and valence of interpersonal versus non-interpersonal emotions. During functional magnetic resonance imaging, participants imagined themselves in emotion-eliciting interpersonal or non-interpersonal situations and then rated the arousal and valence of emotions they experienced. We identified (1) separate neural circuits that are implicated in the arousal and valence dimensions of interpersonal versus non-interpersonal emotions, (2) circuits that are implicated in arousal and valence for both types of emotion, and (3) circuits that are responsive to the type of emotion, regardless of the valence or arousal level of the emotion. We found extensive recruitment of limbic (for arousal) and temporal-parietal (for valence) systems associated with processing of specifically interpersonal emotions compared to non-interpersonal ones. The neural bases of interpersonal and non-interpersonal emotions may, therefore, be largely distinct.

  8. Distinct Neural Circuits Subserve Interpersonal and Non-interpersonal Emotions

    Science.gov (United States)

    Landa, Alla; Wang, Zhishun; Russell, James A.; Posner, Jonathan; Duan, Yunsuo; Kangarlu, Alayar; Huo, Yuankai; Fallon, Brian A.; Peterson, Bradley S.

    2013-01-01

    Emotions elicited by interpersonal versus non-interpersonal experiences have different effects on neurobiological functioning in both animals and humans. However, the extent to which the brain circuits underlying interpersonal and non-interpersonal emotions are distinct still remains unclear. The goal of our study was to assess whether different neural circuits are implicated in the processing of arousal and valence of interpersonal versus non-interpersonal emotions. During functional magnetic resonance imaging, participants imagined themselves in emotion-eliciting interpersonal or non-interpersonal situations and then rated the arousal and valence of emotions they experienced. We identified (a) separate neural circuits that are implicated in the arousal and valence dimensions of interpersonal versus non-interpersonal emotions, (b) circuits that are implicated in arousal and valence for both types of emotion, and (c) circuits that are responsive to the type of emotion, regardless of the valence or arousal level of the emotion. We found extensive recruitment of limbic (for arousal) and temporal-parietal (for valence) systems associated with processing of specifically interpersonal emotions compared to non-interpersonal ones. The neural bases of interpersonal and non-interpersonal emotions may, therefore, be largely distinct. PMID:24028312

  9. Hox genes: choreographers in neural development, architects of circuit organization.

    Science.gov (United States)

    Philippidou, Polyxeni; Dasen, Jeremy S

    2013-10-02

    The neural circuits governing vital behaviors, such as respiration and locomotion, are comprised of discrete neuronal populations residing within the brainstem and spinal cord. Work over the past decade has provided a fairly comprehensive understanding of the developmental pathways that determine the identity of major neuronal classes within the neural tube. However, the steps through which neurons acquire the subtype diversities necessary for their incorporation into a particular circuit are still poorly defined. Studies on the specification of motor neurons indicate that the large family of Hox transcription factors has a key role in generating the subtypes required for selective muscle innervation. There is also emerging evidence that Hox genes function in multiple neuronal classes to shape synaptic specificity during development, suggesting a broader role in circuit assembly. This Review highlights the functions and mechanisms of Hox gene networks and their multifaceted roles during neuronal specification and connectivity. Copyright © 2013 Elsevier Inc. All rights reserved.

  10. Neuronify: An Educational Simulator for Neural Circuits.

    Science.gov (United States)

    Dragly, Svenn-Arne; Hobbi Mobarhan, Milad; Våvang Solbrå, Andreas; Tennøe, Simen; Hafreager, Anders; Malthe-Sørenssen, Anders; Fyhn, Marianne; Hafting, Torkel; Einevoll, Gaute T

    2017-01-01

    Educational software (apps) can improve science education by providing an interactive way of learning about complicated topics that are hard to explain with text and static illustrations. However, few educational apps are available for simulation of neural networks. Here, we describe an educational app, Neuronify, allowing the user to easily create and explore neural networks in a plug-and-play simulation environment. The user can pick network elements with adjustable parameters from a menu, i.e., synaptically connected neurons modelled as integrate-and-fire neurons and various stimulators (current sources, spike generators, visual, and touch) and recording devices (voltmeter, spike detector, and loudspeaker). We aim to provide a low entry point to simulation-based neuroscience by allowing students with no programming experience to create and simulate neural networks. To facilitate the use of Neuronify in teaching, a set of premade common network motifs is provided, performing functions such as input summation, gain control by inhibition, and detection of direction of stimulus movement. Neuronify is developed in C++ and QML using the cross-platform application framework Qt and runs on smart phones (Android, iOS) and tablet computers as well personal computers (Windows, Mac, Linux).

  11. Developmental plasticity in neural circuits for a learned behavior.

    Science.gov (United States)

    Bottjer, S W; Arnold, A P

    1997-01-01

    The neural substrate underlying learned vocal behavior in songbirds provides a textbook illustration of anatomical localization of function for a complex learned behavior in vertebrates. The song-control system has become an important model for studying neural systems related to learning, behavior, and development. The song system of zebra finches is characterized by a heightened capacity for both neural and behavioral change during development and has taught us valuable information regarding sensitive periods, rearrangement of synaptic connections, topographic specificity, cell death and neurogenesis, experience-dependent neural plasticity, and sexual differentiation. The song system differs in some interesting ways from some well-studied mammalian model systems and thus offers fresh perspectives on specific theoretical issues. In this highly selective review, we concentrate on two major questions: What are the developmental changes in the song system responsible for song learning and the restriction of learning to a sensitive period, and what factors explain the highly sexually dimorphic development of this system? We discuss the important role of sex steroid hormones and of neurotrophins in creating a male-typical neural song circuit (which can learn to produce complex vocalizations) instead of a reduced, female-typical song circuit that does not produce learned song.

  12. Synchrony and neural coding in cerebellar circuits

    Directory of Open Access Journals (Sweden)

    Abigail L Person

    2012-12-01

    circuits.

  13. Functional neural circuits that underlie developmental stuttering.

    Directory of Open Access Journals (Sweden)

    Jianping Qiao

    Full Text Available The aim of this study was to identify differences in functional and effective brain connectivity between persons who stutter (PWS and typically developing (TD fluent speakers, and to assess whether those differences can serve as biomarkers to distinguish PWS from TD controls. We acquired resting-state functional magnetic resonance imaging data in 44 PWS and 50 TD controls. We then used Independent Component Analysis (ICA together with Hierarchical Partner Matching (HPM to identify networks of robust, functionally connected brain regions that were highly reproducible across participants, and we assessed whether connectivity differed significantly across diagnostic groups. We then used Granger Causality (GC to study the causal interactions (effective connectivity between the regions that ICA and HPM identified. Finally, we used a kernel support vector machine to assess how well these measures of functional connectivity and granger causality discriminate PWS from TD controls. Functional connectivity was stronger in PWS compared with TD controls in the supplementary motor area (SMA and primary motor cortices, but weaker in inferior frontal cortex (IFG, Broca's area, caudate, putamen, and thalamus. Additionally, causal influences were significantly weaker in PWS from the IFG to SMA, and from the basal ganglia to IFG through the thalamus, compared to TD controls. ICA and GC indices together yielded an accuracy of 92.7% in classifying PWS from TD controls. Our findings suggest the presence of dysfunctional circuits that support speech planning and timing cues for the initiation and execution of motor sequences in PWS. Our high accuracy of classification further suggests that these aberrant brain features may serve as robust biomarkers for PWS.

  14. Functional neural circuits that underlie developmental stuttering

    Science.gov (United States)

    Zhao, Guihu; Huo, Yuankai; Herder, Carl L.; Sikora, Chamonix O.; Peterson, Bradley S.

    2017-01-01

    The aim of this study was to identify differences in functional and effective brain connectivity between persons who stutter (PWS) and typically developing (TD) fluent speakers, and to assess whether those differences can serve as biomarkers to distinguish PWS from TD controls. We acquired resting-state functional magnetic resonance imaging data in 44 PWS and 50 TD controls. We then used Independent Component Analysis (ICA) together with Hierarchical Partner Matching (HPM) to identify networks of robust, functionally connected brain regions that were highly reproducible across participants, and we assessed whether connectivity differed significantly across diagnostic groups. We then used Granger Causality (GC) to study the causal interactions (effective connectivity) between the regions that ICA and HPM identified. Finally, we used a kernel support vector machine to assess how well these measures of functional connectivity and granger causality discriminate PWS from TD controls. Functional connectivity was stronger in PWS compared with TD controls in the supplementary motor area (SMA) and primary motor cortices, but weaker in inferior frontal cortex (IFG, Broca’s area), caudate, putamen, and thalamus. Additionally, causal influences were significantly weaker in PWS from the IFG to SMA, and from the basal ganglia to IFG through the thalamus, compared to TD controls. ICA and GC indices together yielded an accuracy of 92.7% in classifying PWS from TD controls. Our findings suggest the presence of dysfunctional circuits that support speech planning and timing cues for the initiation and execution of motor sequences in PWS. Our high accuracy of classification further suggests that these aberrant brain features may serve as robust biomarkers for PWS. PMID:28759567

  15. Breathtaking Songs: Coordinating the Neural Circuits for Breathing and Singing.

    Science.gov (United States)

    Schmidt, Marc F; Goller, Franz

    2016-11-01

    The vocal behavior of birds is remarkable for its diversity, and songs can feature elaborate characteristics such as long duration, rapid temporal pattern, and broad frequency range. The respiratory system plays a central role in generating the complex song patterns that must be integrated with its life-sustaining functions. Here, we explore how precise coordination between the neural circuits for breathing and singing is fundamental to production of these remarkable behaviors. ©2016 Int. Union Physiol. Sci./Am. Physiol. Soc.

  16. Oxytocin modulation of neural circuits for social behavior.

    Science.gov (United States)

    Marlin, Bianca J; Froemke, Robert C

    2017-02-01

    Oxytocin is a hypothalamic neuropeptide that has gained attention for the effects on social behavior. Recent findings shed new light on the mechanisms of oxytocin in synaptic plasticity and adaptively modifying neural circuits for social interactions such as conspecific recognition, pair bonding, and maternal care. Here, we review several of these newer studies on oxytocin in the context of previous findings, with an emphasis on social behavior and circuit plasticity in various brain regions shown to be enriched for oxytocin receptors. We provide a framework that highlights current circuit-level mechanisms underlying the widespread action of oxytocin. © 2016 Wiley Periodicals, Inc. Develop Neurobiol 77: 169-189, 2017. © 2016 Wiley Periodicals, Inc.

  17. KCNQ potassium channels in sensory system and neural circuits.

    Science.gov (United States)

    Wang, Jing-jing; Li, Yang

    2016-01-01

    M channels, an important regulator of neural excitability, are composed of four subunits of the Kv7 (KCNQ) K(+) channel family. M channels were named as such because their activity was suppressed by stimulation of muscarinic acetylcholine receptors. These channels are of particular interest because they are activated at the subthreshold membrane potentials. Furthermore, neural KCNQ channels are drug targets for the treatments of epilepsy and a variety of neurological disorders, including chronic and neuropathic pain, deafness, and mental illness. This review will update readers on the roles of KCNQ channels in the sensory system and neural circuits as well as discuss their respective mechanisms and the implications for physiology and medicine. We will also consider future perspectives and the development of additional pharmacological models, such as seizure, stroke, pain and mental illness, which work in combination with drug-design targeting of KCNQ channels. These models will hopefully deepen our understanding of KCNQ channels and provide general therapeutic prospects of related channelopathies.

  18. Controlling the elements: an optogenetic approach to understanding the neural circuits of fear.

    Science.gov (United States)

    Johansen, Joshua P; Wolff, Steffen B E; Lüthi, Andreas; LeDoux, Joseph E

    2012-06-15

    Neural circuits underlie our ability to interact in the world and to learn adaptively from experience. Understanding neural circuits and how circuit structure gives rise to neural firing patterns or computations is fundamental to our understanding of human experience and behavior. Fear conditioning is a powerful model system in which to study neural circuits and information processing and relate them to learning and behavior. Until recently, technological limitations have made it difficult to study the causal role of specific circuit elements during fear conditioning. However, newly developed optogenetic tools allow researchers to manipulate individual circuit components such as anatomically or molecularly defined cell populations, with high temporal precision. Applying these tools to the study of fear conditioning to control specific neural subpopulations in the fear circuit will facilitate a causal analysis of the role of these circuit elements in fear learning and memory. By combining this approach with in vivo electrophysiological recordings in awake, behaving animals, it will also be possible to determine the functional contribution of specific cell populations to neural processing in the fear circuit. As a result, the application of optogenetics to fear conditioning could shed light on how specific circuit elements contribute to neural coding and to fear learning and memory. Furthermore, this approach may reveal general rules for how circuit structure and neural coding within circuits gives rise to sensory experience and behavior. Copyright © 2012 Society of Biological Psychiatry. Published by Elsevier Inc. All rights reserved.

  19. The Complexity of Dynamics in Small Neural Circuits.

    Directory of Open Access Journals (Sweden)

    Diego Fasoli

    2016-08-01

    Full Text Available Mean-field approximations are a powerful tool for studying large neural networks. However, they do not describe well the behavior of networks composed of a small number of neurons. In this case, major differences between the mean-field approximation and the real behavior of the network can arise. Yet, many interesting problems in neuroscience involve the study of mesoscopic networks composed of a few tens of neurons. Nonetheless, mathematical methods that correctly describe networks of small size are still rare, and this prevents us to make progress in understanding neural dynamics at these intermediate scales. Here we develop a novel systematic analysis of the dynamics of arbitrarily small networks composed of homogeneous populations of excitatory and inhibitory firing-rate neurons. We study the local bifurcations of their neural activity with an approach that is largely analytically tractable, and we numerically determine the global bifurcations. We find that for strong inhibition these networks give rise to very complex dynamics, caused by the formation of multiple branching solutions of the neural dynamics equations that emerge through spontaneous symmetry-breaking. This qualitative change of the neural dynamics is a finite-size effect of the network, that reveals qualitative and previously unexplored differences between mesoscopic cortical circuits and their mean-field approximation. The most important consequence of spontaneous symmetry-breaking is the ability of mesoscopic networks to regulate their degree of functional heterogeneity, which is thought to help reducing the detrimental effect of noise correlations on cortical information processing.

  20. Neural processing of gustatory information in insular circuits.

    Science.gov (United States)

    Maffei, Arianna; Haley, Melissa; Fontanini, Alfredo

    2012-08-01

    The insular cortex is the primary cortical site devoted to taste processing. A large body of evidence is available for how insular neurons respond to gustatory stimulation in both anesthetized and behaving animals. Most of the reports describe broadly tuned neurons that are involved in processing the chemosensory, physiological and psychological aspects of gustatory experience. However little is known about how these neural responses map onto insular circuits. Particularly mysterious is the functional role of the three subdivisions of the insular cortex: the granular, the dysgranular and the agranular insular cortices. In this article we review data on the organization of the local and long-distance circuits in the three subdivisions. The functional significance of these results is discussed in light of the latest electrophysiological data. A view of the insular cortex as a functionally integrated system devoted to processing gustatory, multimodal, cognitive and affective information is proposed. Copyright © 2012 Elsevier Ltd. All rights reserved.

  1. Emotion and decision making: multiple modulatory neural circuits.

    Science.gov (United States)

    Phelps, Elizabeth A; Lempert, Karolina M; Sokol-Hessner, Peter

    2014-01-01

    Although the prevalent view of emotion and decision making is derived from the notion that there are dual systems of emotion and reason, a modulatory relationship more accurately reflects the current research in affective neuroscience and neuroeconomics. Studies show two potential mechanisms for affect's modulation of the computation of subjective value and decisions. Incidental affective states may carry over to the assessment of subjective value and the decision, and emotional reactions to the choice may be incorporated into the value calculation. In addition, this modulatory relationship is reciprocal: Changing emotion can change choices. This research suggests that the neural mechanisms mediating the relation between affect and choice vary depending on which affective component is engaged and which decision variables are assessed. We suggest that a detailed and nuanced understanding of emotion and decision making requires characterizing the multiple modulatory neural circuits underlying the different means by which emotion and affect can influence choices.

  2. Pulse coded biologically motivated neural-type MOS circuits

    Science.gov (United States)

    1991-11-01

    This project has two aspects, one for ONR and one for AFOSR. The ONR portion is devoted to obtaining hardware implementations for the physiological representations used in the program SYNETSIM developed by the neurophysiologist Dr. D. Hartline of Bekesy Laboratories. The AFOSR portion is for evaluation capabilities of the pulse code philosophy of neural networks. On the ONR portion of the research, several chips have been fabricated for SYNETSIM pools and a neural arithmetic unit based upon the pools. Also, a number of modifications have been made to SYNETSIM to make it a much more user-friendly program. Several papers have been presented at international conferences and the DRIVER module is under continued investigation for VLSI realization. The means to implement long term potentiation are also under continued investigation. On the AFOSR portion, a means of realizing any Hopfield-type network via pulse coded circuits was obtained.

  3. Generating three-qubit quantum circuits with neural networks

    Science.gov (United States)

    Swaddle, Michael; Noakes, Lyle; Smallbone, Harry; Salter, Liam; Wang, Jingbo

    2017-10-01

    A new method for compiling quantum algorithms is proposed and tested for a three qubit system. The proposed method is to decompose a unitary matrix U, into a product of simpler Uj via a neural network. These Uj can then be decomposed into product of known quantum gates. Key to the effectiveness of this approach is the restriction of the set of training data generated to paths which approximate minimal normal subRiemannian geodesics, as this removes unnecessary redundancy and ensures the products are unique. The two neural networks are shown to work effectively, each individually returning low loss values on validation data after relatively short training periods. The two networks are able to return coefficients that are sufficiently close to the true coefficient values to validate this method as an approach for generating quantum circuits. There is scope for more work in scaling this approach for larger quantum systems.

  4. A breathing circuit alarm system based on neural networks.

    Science.gov (United States)

    Orr, J A; Westenskow, D R

    1994-03-01

    The objectives of our study were (1) to implement intelligent respiratory alarms with a neural network; and (2) to increase alarm specificity and decrease false-alarm rates compared with current alarms. We trained a neural network to recognize 13 faults in an anesthesia breathing circuit. The system extracted 30 breath-to-breath features from the airway CO2, flow, and pressure signals. We created training data for the network by introducing 13 faults repeatedly in 5 dogs (616 total faults). We used the data to train the neural network using the backward error propagation algorithm. In animals, the trained network reported the alarms correctly for 95.0% of the faults when tested during controlled ventilation, and for 86.9% of the faults during spontaneous breathing. When tested in the operating room, the system found and correctly reported 54 of 57 faults that occurred during 43.6 hr of use. The alarm system produced a total of 74 false alarms during 43.6 hr of monitoring. Neural networks may be useful in creating intelligent anesthesia alarm systems.

  5. Activity-dependent modulation of neural circuit synaptic connectivity

    Directory of Open Access Journals (Sweden)

    Charles R Tessier

    2009-07-01

    Full Text Available In many nervous systems, the establishment of neural circuits is known to proceed via a two-stage process; 1 early, activity-independent wiring to produce a rough map characterized by excessive synaptic connections, and 2 subsequent, use-dependent pruning to eliminate inappropriate connections and reinforce maintained synapses. In invertebrates, however, evidence of the activity-dependent phase of synaptic refinement has been elusive, and the dogma has long been that invertebrate circuits are “hard-wired” in a purely activity-independent manner. This conclusion has been challenged recently through the use of new transgenic tools employed in the powerful Drosophila system, which have allowed unprecedented temporal control and single neuron imaging resolution. These recent studies reveal that activity-dependent mechanisms are indeed required to refine circuit maps in Drosophila during precise, restricted windows of late-phase development. Such mechanisms of circuit refinement may be key to understanding a number of human neurological diseases, including developmental disorders such as Fragile X syndrome (FXS and autism, which are hypothesized to result from defects in synaptic connectivity and activity-dependent circuit function. This review focuses on our current understanding of activity-dependent synaptic connectivity in Drosophila, primarily through analyzing the role of the fragile X mental retardation protein (FMRP in the Drosophila FXS disease model. The particular emphasis of this review is on the expanding array of new genetically-encoded tools that are allowing cellular events and molecular players to be dissected with ever greater precision and detail.

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

    Science.gov (United States)

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

    2016-02-01

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

  7. An integrated modelling framework for neural circuits with multiple neuromodulators.

    Science.gov (United States)

    Joshi, Alok; Youssofzadeh, Vahab; Vemana, Vinith; McGinnity, T M; Prasad, Girijesh; Wong-Lin, KongFatt

    2017-01-01

    Neuromodulators are endogenous neurochemicals that regulate biophysical and biochemical processes, which control brain function and behaviour, and are often the targets of neuropharmacological drugs. Neuromodulator effects are generally complex partly owing to the involvement of broad innervation, co-release of neuromodulators, complex intra- and extrasynaptic mechanism, existence of multiple receptor subtypes and high interconnectivity within the brain. In this work, we propose an efficient yet sufficiently realistic computational neural modelling framework to study some of these complex behaviours. Specifically, we propose a novel dynamical neural circuit model that integrates the effective neuromodulator-induced currents based on various experimental data (e.g. electrophysiology, neuropharmacology and voltammetry). The model can incorporate multiple interacting brain regions, including neuromodulator sources, simulate efficiently and easily extendable to large-scale brain models, e.g. for neuroimaging purposes. As an example, we model a network of mutually interacting neural populations in the lateral hypothalamus, dorsal raphe nucleus and locus coeruleus, which are major sources of neuromodulator orexin/hypocretin, serotonin and norepinephrine/noradrenaline, respectively, and which play significant roles in regulating many physiological functions. We demonstrate that such a model can provide predictions of systemic drug effects of the popular antidepressants (e.g. reuptake inhibitors), neuromodulator antagonists or their combinations. Finally, we developed user-friendly graphical user interface software for model simulation and visualization for both fundamental sciences and pharmacological studies. © 2017 The Authors.

  8. Shared neural circuits for mentalizing about the self and others.

    Science.gov (United States)

    Lombardo, Michael V; Chakrabarti, Bhismadev; Bullmore, Edward T; Wheelwright, Sally J; Sadek, Susan A; Suckling, John; Baron-Cohen, Simon

    2010-07-01

    Although many examples exist for shared neural representations of self and other, it is unknown how such shared representations interact with the rest of the brain. Furthermore, do high-level inference-based shared mentalizing representations interact with lower level embodied/simulation-based shared representations? We used functional neuroimaging (fMRI) and a functional connectivity approach to assess these questions during high-level inference-based mentalizing. Shared mentalizing representations in ventromedial prefrontal cortex, posterior cingulate/precuneus, and temporo-parietal junction (TPJ) all exhibited identical functional connectivity patterns during mentalizing of both self and other. Connectivity patterns were distributed across low-level embodied neural systems such as the frontal operculum/ventral premotor cortex, the anterior insula, the primary sensorimotor cortex, and the presupplementary motor area. These results demonstrate that identical neural circuits are implementing processes involved in mentalizing of both self and other and that the nature of such processes may be the integration of low-level embodied processes within higher level inference-based mentalizing.

  9. Neural circuits mediating olfactory-driven behavior in fish

    Science.gov (United States)

    Kermen, Florence; Franco, Luis M.; Wyatt, Cameron; Yaksi, Emre

    2013-01-01

    The fish olfactory system processes odor signals and mediates behaviors that are crucial for survival such as foraging, courtship, and alarm response. Although the upstream olfactory brain areas (olfactory epithelium and olfactory bulb) are well-studied, less is known about their target brain areas and the role they play in generating odor-driven behaviors. Here we review a broad range of literature on the anatomy, physiology, and behavioral output of the olfactory system and its target areas in a wide range of teleost fish. Additionally, we discuss how applying recent technological advancements to the zebrafish (Danio rerio) could help in understanding the function of these target areas. We hope to provide a framework for elucidating the neural circuit computations underlying the odor-driven behaviors in this small, transparent, and genetically amenable vertebrate. PMID:23596397

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

    Science.gov (United States)

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

    2003-02-01

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

  11. Acute Stress Influences Neural Circuits of Reward Processing

    Directory of Open Access Journals (Sweden)

    Anthony John Porcelli

    2012-11-01

    Full Text Available People often make decisions under aversive conditions such as acute stress. Yet, less is known about the process in which acute stress can influence decision-making. A growing body of research has established that reward-related information associated with the outcomes of decisions exerts a powerful influence over the choices people make and that an extensive network of brain regions, prominently featuring the striatum, is involved in the processing of this reward-related information. Thus, an important step in research on the nature of acute stress’ influence over decision-making is to examine how it may modulate responses to rewards and punishments within reward-processing neural circuitry. In the current experiment, we employed a simple reward processing paradigm – where participants received monetary rewards and punishments – known to evoke robust striatal responses. Immediately prior to performing each of two task runs, participants were exposed to acute stress (i.e., cold pressor or a no stress control procedure in a between-subjects fashion. No stress group participants exhibited a pattern of activity within the dorsal striatum and orbitofrontal cortex consistent with past research on outcome processing – specifically, differential responses for monetary rewards over punishments. In contrast, acute stress group participants’ dorsal striatum and orbitofrontal cortex demonstrated decreased sensitivity to monetary outcomes and a lack of differential activity. These findings provide insight into how neural circuits may process rewards and punishments associated with simple decisions under acutely stressful conditions.

  12. Long-Lasting Neural Circuit Dysfunction Following Developmental Ethanol Exposure

    Directory of Open Access Journals (Sweden)

    Mariko Saito

    2013-04-01

    Full Text Available Fetal Alcohol Spectrum Disorder (FASD is a general diagnosis for those exhibiting long-lasting neurobehavioral and cognitive deficiencies as a result of fetal alcohol exposure. It is among the most common causes of mental deficits today. Those impacted are left to rely on advances in our understanding of the nature of early alcohol-induced disorders toward human therapies. Research findings over the last decade have developed a model where ethanol-induced neurodegeneration impacts early neural circuit development, thereby perpetuating subsequent integration and plasticity in vulnerable brain regions. Here we review our current knowledge of FASD neuropathology based on discoveries of long-lasting neurophysiological effects of acute developmental ethanol exposure in animal models. We discuss the important balance between synaptic excitation and inhibition in normal neural network function, and relate the significance of that balance to human FASD as well as related disease states. Finally, we postulate that excitation/inhibition imbalance caused by early ethanol-induced neurodegeneration results in perturbed local and regional network signaling and therefore neurobehavioral pathology.

  13. A neural circuit covarying with social hierarchy in macaques.

    Directory of Open Access Journals (Sweden)

    MaryAnn P Noonan

    2014-09-01

    Full Text Available Despite widespread interest in social dominance, little is known of its neural correlates in primates. We hypothesized that social status in primates might be related to individual variation in subcortical brain regions implicated in other aspects of social and emotional behavior in other mammals. To examine this possibility we used magnetic resonance imaging (MRI, which affords the taking of quantitative measurements noninvasively, both of brain structure and of brain function, across many regions simultaneously. We carried out a series of tests of structural and functional MRI (fMRI data in 25 group-living macaques. First, a deformation-based morphometric (DBM approach was used to show that gray matter in the amygdala, brainstem in the vicinity of the raphe nucleus, and reticular formation, hypothalamus, and septum/striatum of the left hemisphere was correlated with social status. Second, similar correlations were found in the same areas in the other hemisphere. Third, similar correlations were found in a second data set acquired several months later from a subset of the same animals. Fourth, the strength of coupling between fMRI-measured activity in the same areas was correlated with social status. The network of subcortical areas, however, had no relationship with the sizes of individuals' social networks, suggesting the areas had a simple and direct relationship with social status. By contrast a second circuit in cortex, comprising the midsuperior temporal sulcus and anterior and dorsal prefrontal cortex, covaried with both individuals' social statuses and the social network sizes they experienced. This cortical circuit may be linked to the social cognitive processes that are taxed by life in more complex social networks and that must also be used if an animal is to achieve a high social status.

  14. Clustered Protocadherins Are Required for Building Functional Neural Circuits

    Science.gov (United States)

    Hasegawa, Sonoko; Kobayashi, Hiroaki; Kumagai, Makiko; Nishimaru, Hiroshi; Tarusawa, Etsuko; Kanda, Hiro; Sanbo, Makoto; Yoshimura, Yumiko; Hirabayashi, Masumi; Hirabayashi, Takahiro; Yagi, Takeshi

    2017-01-01

    Neuronal identity is generated by the cell-surface expression of clustered protocadherin (Pcdh) isoforms. In mice, 58 isoforms from three gene clusters, Pcdhα, Pcdhβ, and Pcdhγ, are differentially expressed in neurons. Since cis-heteromeric Pcdh oligomers on the cell surface interact homophilically with that in other neurons in trans, it has been thought that the Pcdh isoform repertoire determines the binding specificity of synapses. We previously described the cooperative functions of isoforms from all three Pcdh gene clusters in neuronal survival and synapse formation in the spinal cord. However, the neuronal loss and the following neonatal lethality prevented an analysis of the postnatal development and characteristics of the clustered-Pcdh-null (Δαβγ) neural circuits. Here, we used two methods, one to generate the chimeric mice that have transplanted Δαβγ neurons into mouse embryos, and the other to generate double mutant mice harboring null alleles of both the Pcdh gene and the proapoptotic gene Bax to prevent neuronal loss. First, our results showed that the surviving chimeric mice that had a high contribution of Δαβγ cells exhibited paralysis and died in the postnatal period. An analysis of neuronal survival in postnatally developing brain regions of chimeric mice clarified that many Δαβγ neurons in the forebrain were spared from apoptosis, unlike those in the reticular formation of the brainstem. Second, in Δαβγ/Bax null double mutants, the central pattern generator (CPG) for locomotion failed to create a left-right alternating pattern even in the absence of neurodegeneraton. Third, calcium imaging of cultured hippocampal neurons showed that the network activity of Δαβγ neurons tended to be more synchronized and lost the variability in the number of simultaneously active neurons observed in the control network. Lastly, a comparative analysis for trans-homophilic interactions of the exogenously introduced single Pcdh-γA3 isoforms

  15. Clustered Protocadherins Are Required for Building Functional Neural Circuits

    Directory of Open Access Journals (Sweden)

    Takeshi Yagi

    2017-04-01

    Full Text Available Neuronal identity is generated by the cell-surface expression of clustered protocadherin (Pcdh isoforms. In mice, 58 isoforms from three gene clusters, Pcdhα, Pcdhβ, and Pcdhγ, are differentially expressed in neurons. Since cis-heteromeric Pcdh oligomers on the cell surface interact homophilically with that in other neurons in trans, it has been thought that the Pcdh isoform repertoire determines the binding specificity of synapses. We previously described the cooperative functions of isoforms from all three Pcdh gene clusters in neuronal survival and synapse formation in the spinal cord. However, the neuronal loss and the following neonatal lethality prevented an analysis of the postnatal development and characteristics of the clustered-Pcdh-null (Δαβγ neural circuits. Here, we used two methods, one to generate the chimeric mice that have transplanted Δαβγ neurons into mouse embryos, and the other to generate double mutant mice harboring null alleles of both the Pcdh gene and the proapoptotic gene Bax to prevent neuronal loss. First, our results showed that the surviving chimeric mice that had a high contribution of Δαβγ cells exhibited paralysis and died in the postnatal period. An analysis of neuronal survival in postnatally developing brain regions of chimeric mice clarified that many Δαβγ neurons in the forebrain were spared from apoptosis, unlike those in the reticular formation of the brainstem. Second, in Δαβγ/Bax null double mutants, the central pattern generator (CPG for locomotion failed to create a left-right alternating pattern even in the absence of neurodegeneraton. Third, calcium imaging of cultured hippocampal neurons showed that the network activity of Δαβγ neurons tended to be more synchronized and lost the variability in the number of simultaneously active neurons observed in the control network. Lastly, a comparative analysis for trans-homophilic interactions of the exogenously introduced single

  16. Neural circuit mechanisms of short-term memory

    Science.gov (United States)

    Goldman, Mark

    Memory over time scales of seconds to tens of seconds is thought to be maintained by neural activity that is triggered by a memorized stimulus and persists long after the stimulus is turned off. This presents a challenge to current models of memory-storing mechanisms, because the typical time scales associated with cellular and synaptic dynamics are two orders of magnitude smaller than this. While such long time scales can easily be achieved by bistable processes that toggle like a flip-flop between a baseline and elevated-activity state, many neuronal systems have been observed experimentally to be capable of maintaining a continuum of stable states. For example, in neural integrator networks involved in the accumulation of evidence for decision making and in motor control, individual neurons have been recorded whose activity reflects the mathematical integral of their inputs; in the absence of input, these neurons sustain activity at a level proportional to the running total of their inputs. This represents an analog form of memory whose dynamics can be conceptualized through an energy landscape with a continuum of lowest-energy states. Such continuous attractor landscapes are structurally non-robust, in seeming violation of the relative robustness of biological memory systems. In this talk, I will present and compare different biologically motivated circuit motifs for the accumulation and storage of signals in short-term memory. Challenges to generating robust memory maintenance will be highlighted and potential mechanisms for ameliorating the sensitivity of memory networks to perturbations will be discussed. Funding for this work was provided by NIH R01 MH065034, NSF IIS-1208218, Simons Foundation 324260, and a UC Davis Ophthalmology Research to Prevent Blindness Grant.

  17. Rapid neural circuit switching mediated by synaptic plasticity during neural morphallactic regeneration.

    Science.gov (United States)

    Lybrand, Zane R; Zoran, Mark J

    2012-09-01

    The aquatic oligochaete, Lumbriculus variegatus (Lumbriculidae), undergoes a rapid regenerative transformation of its neural circuits following body fragmentation. This type of nervous system plasticity, called neural morphallaxis, involves the remodeling of the giant fiber pathways that mediate rapid head and tail withdrawal behaviors. Extra- and intracellular electrophysiological recordings demonstrated that changes in cellular properties and synaptic connections underlie neurobehavioral plasticity during morphallaxis. Sensory-to-giant interneuron connections, undetectable prior to body injury, emerged within hours of segment amputation. The appearance of functional synaptic transmission was followed by interneuron activation, coupling of giant fiber spiking to motor outputs and overt segmental shortening. The onset of morphallactic plasticity varied along the body axis and emerged more rapidly in segments closer to regions of sensory field overlap between the two giant fiber pathways. The medial and lateral giant fibers were simultaneously activated during a transient phase of network remodeling. Thus, synaptic plasticity at sensory-to-giant interneuron connections mediates escape circuit morphallaxis in this regenerating annelid worm. Copyright © 2011 Wiley Periodicals, Inc.

  18. Self-Organizing Neural Circuits for Sensory-Guided Motor Control

    National Research Council Canada - National Science Library

    Grossberg, Stephen

    1999-01-01

    The reported projects developed mathematical models to explain how self-organizing neural circuits that operate under continuous or intermittent sensory guidance achieve flexible and accurate control of human movement...

  19. Ultra low-power integrated circuit design for wireless neural interfaces

    CERN Document Server

    Holleman, Jeremy; Otis, Brian

    2014-01-01

    Presenting results from real prototype systems, this volume provides an overview of ultra low-power integrated circuits and systems for neural signal processing and wireless communication. Topics include analog, radio, and signal processing theory and design for ultra low-power circuits.

  20. Neural Circuits via Which Single Prolonged Stress Exposure Leads to Fear Extinction Retention Deficits

    Science.gov (United States)

    Knox, Dayan; Stanfield, Briana R.; Staib, Jennifer M.; David, Nina P.; Keller, Samantha M.; DePietro, Thomas

    2016-01-01

    Single prolonged stress (SPS) has been used to examine mechanisms via which stress exposure leads to post-traumatic stress disorder symptoms. SPS induces fear extinction retention deficits, but neural circuits critical for mediating these deficits are unknown. To address this gap, we examined the effect of SPS on neural activity in brain regions…

  1. Demonstration of a neural circuit critical for imprinting behavior in chicks.

    Science.gov (United States)

    Nakamori, Tomoharu; Sato, Katsushige; Atoji, Yasuro; Kanamatsu, Tomoyuki; Tanaka, Kohichi; Ohki-Hamazaki, Hiroko

    2010-03-24

    Imprinting behavior in birds is elicited by visual and/or auditory cues. It has been demonstrated previously that visual cues are recognized and processed in the visual Wulst (VW), and imprinting memory is stored in the intermediate medial mesopallium (IMM) of the telencephalon. Alteration of neural responses in these two regions according to imprinting has been reported, yet direct evidence of the neural circuit linking these two regions is lacking. Thus, it remains unclear how memory is formed and expressed in this circuit. Here, we present anatomical as well as physiological evidence of the neural circuit connecting the VW and IMM and show that imprinting training during the critical period strengthens and refines this circuit. A functional connection established by imprint training resulted in an imprinting behavior. After the closure of the critical period, training could not activate this circuit nor induce the imprinting behavior. Glutamatergic neurons in the ventroposterior region of the VW, the core region of the hyperpallium densocellulare (HDCo), sent their axons to the periventricular part of the HD, just dorsal and afferent to the IMM. We found that the HDCo is important in imprinting behavior. The refinement and/or enhancement of this neural circuit are attributed to increased activity of HDCo cells, and the activity depended on NR2B-containing NMDA receptors. These findings show a neural connection in the telencephalon in Aves and demonstrate that NR2B function is indispensable for the plasticity of HDCo cells, which are key mediators of imprinting.

  2. Self-control of chaos in neural circuits with plastic electrical synapses

    Science.gov (United States)

    Zhigulin, V. P.; Rabinovich, M. I.

    2004-10-01

    Two kinds of connections are known to exist in neural circuits: electrical (also called gap junctions) and chemical. Whereas chemical synapses are known to be plastic (i. e., modifiable), but slow, electrical transmission through gap junctions is not modifiable, but is very fast. We suggest the new artificial synapse that combines the best properties of both: the fast reaction of a gap junction and the plasticity of a chemical synapse. Such a plastic electrical synapse can be used in hybrid neural circuits and for the development of neural prosthetics, i.e., implanted devices that can interact with the real nervous system. Based on the computer modelling we show that such a plastic electrical synapse regularizes chaos in the minimal neural circuit consisting of two chaotic bursting neurons.

  3. An Implantable Mixed Analog/Digital Neural Stimulator Circuit

    DEFF Research Database (Denmark)

    Gudnason, Gunnar; Bruun, Erik; Haugland, Morten

    1999-01-01

    This paper describes a chip for a multichannel neural stimulator for functional electrical stimulation. The chip performs all the signal processing required in an implanted neural stimulator. The power and signal transmission to the stimulator is carried out via an inductive link. From the signals...

  4. Anomalous neural circuit function in schizophrenia during a virtual Morris water task.

    Science.gov (United States)

    Folley, Bradley S; Astur, Robert; Jagannathan, Kanchana; Calhoun, Vince D; Pearlson, Godfrey D

    2010-02-15

    Previous studies have reported learning and navigation impairments in schizophrenia patients during virtual reality allocentric learning tasks. The neural bases of these deficits have not been explored using functional MRI despite well-explored anatomic characterization of these paradigms in non-human animals. Our objective was to characterize the differential distributed neural circuits involved in virtual Morris water task performance using independent component analysis (ICA) in schizophrenia patients and controls. Additionally, we present behavioral data in order to derive relationships between brain function and performance, and we have included a general linear model-based analysis in order to exemplify the incremental and differential results afforded by ICA. Thirty-four individuals with schizophrenia and twenty-eight healthy controls underwent fMRI scanning during a block design virtual Morris water task using hidden and visible platform conditions. Independent components analysis was used to deconstruct neural contributions to hidden and visible platform conditions for patients and controls. We also examined performance variables, voxel-based morphometry and hippocampal subparcellation, and regional BOLD signal variation. Independent component analysis identified five neural circuits. Mesial temporal lobe regions, including the hippocampus, were consistently task-related across conditions and groups. Frontal, striatal, and parietal circuits were recruited preferentially during the visible condition for patients, while frontal and temporal lobe regions were more saliently recruited by controls during the hidden platform condition. Gray matter concentrations and BOLD signal in hippocampal subregions were associated with task performance in controls but not patients. Patients exhibited impaired performance on the hidden and visible conditions of the task, related to negative symptom severity. While controls showed coupling between neural circuits, regional

  5. Nonlinear resonances and multi-stability in simple neural circuits

    Science.gov (United States)

    Alonso, Leandro M.

    2017-01-01

    This article describes a numerical procedure designed to tune the parameters of periodically driven dynamical systems to a state in which they exhibit rich dynamical behavior. This is achieved by maximizing the diversity of subharmonic solutions available to the system within a range of the parameters that define the driving. The procedure is applied to a problem of interest in computational neuroscience: a circuit composed of two interacting populations of neurons under external periodic forcing. Depending on the parameters that define the circuit, such as the weights of the connections between the populations, the response of the circuit to the driving can be strikingly rich and diverse. The procedure is employed to find circuits that, when driven by external input, exhibit multiple stable patterns of periodic activity organized in complex tuning diagrams and signatures of low dimensional chaos.

  6. The Vite Model: A Neural Command Circuit for Generating Arm and Articulator Trajectories,

    Science.gov (United States)

    1988-03-01

    associative map, looking at an object can activate a TPC of the hand-arm system, as Piaget (1963) noted. Then a VITE circuit can translate this latter TPC...two ways: by comparing trajectories of the neural circuit’s output stage with actual arm trajectories, and by checking for the existence of the...in precentral motor cortex could be analysed as an in vivo analogue of model DV stage neurons. Additional physiological support for the VITE model

  7. The neurobiology of sound-specific auditory plasticity: a core neural circuit.

    Science.gov (United States)

    Xiong, Ying; Zhang, Yonghai; Yan, Jun

    2009-09-01

    Auditory learning or experience induces large-scale neural plasticity in not only the auditory cortex but also in the auditory thalamus and midbrain. Such plasticity is guided by acquired sound (sound-specific auditory plasticity). The mechanisms involved in this process have been studied from various approaches and support the presence of a core neural circuit consisting of a subcortico-cortico-subcortical tonotopic loop supplemented by neuromodulatory (e.g., cholinergic) inputs. This circuit has three key functions essential for establishing large-scale and sound-specific plasticity in the auditory cortex, auditory thalamus and auditory midbrain. They include the presence of sound information for guiding the plasticity, the communication between the cortex, thalamus and midbrain for coordinating the plastic changes and the adjustment of the circuit status for augmenting the plasticity. This review begins with an overview of sound-specific auditory plasticity in the central auditory system. It then introduces the core neural circuit which plays an essential role in inducing sound-specific auditory plasticity. Finally, the core neural circuit and its relationship to auditory learning and experience are discussed.

  8. Distributed dynamical computation in neural circuits with propagating coherent activity patterns.

    Directory of Open Access Journals (Sweden)

    Pulin Gong

    2009-12-01

    Full Text Available Activity in neural circuits is spatiotemporally organized. Its spatial organization consists of multiple, localized coherent patterns, or patchy clusters. These patterns propagate across the circuits over time. This type of collective behavior has ubiquitously been observed, both in spontaneous activity and evoked responses; its function, however, has remained unclear. We construct a spatially extended, spiking neural circuit that generates emergent spatiotemporal activity patterns, thereby capturing some of the complexities of the patterns observed empirically. We elucidate what kind of fundamental function these patterns can serve by showing how they process information. As self-sustained objects, localized coherent patterns can signal information by propagating across the neural circuit. Computational operations occur when these emergent patterns interact, or collide with each other. The ongoing behaviors of these patterns naturally embody both distributed, parallel computation and cascaded logical operations. Such distributed computations enable the system to work in an inherently flexible and efficient way. Our work leads us to propose that propagating coherent activity patterns are the underlying primitives with which neural circuits carry out distributed dynamical computation.

  9. Neural systems supporting and affecting economically relevant behavior

    Directory of Open Access Journals (Sweden)

    Braeutigam S

    2012-05-01

    Full Text Available Sven BraeutigamOxford Centre for Human Brain Activity, University of Oxford, Oxford, United KingdomAbstract: For about a hundred years, theorists and traders alike have tried to unravel and understand the mechanisms and hidden rules underlying and perhaps determining economically relevant behavior. This review focuses on recent developments in neuroeconomics, where the emphasis is placed on two directions of research: first, research exploiting common experiences of urban inhabitants in industrialized societies to provide experimental paradigms with a broader real-life content; second, research based on behavioral genetics, which provides an additional dimension for experimental control and manipulation. In addition, possible limitations of state-of-the-art neuroeconomics research are addressed. It is argued that observations of neuronal systems involved in economic behavior converge to some extent across the technologies and paradigms used. Conceptually, the data available as of today raise the possibility that neuroeconomic research might provide evidence at the neuronal level for the existence of multiple systems of thought and for the importance of conflict. Methodologically, Bayesian approaches in particular may play an important role in identifying mechanisms and establishing causality between patterns of neural activity and economic behavior.Keywords: neuroeconomics, behavioral genetics, decision-making, consumer behavior, neural system

  10. Implantable neurotechnologies: bidirectional neural interfaces--applications and VLSI circuit implementations.

    Science.gov (United States)

    Greenwald, Elliot; Masters, Matthew R; Thakor, Nitish V

    2016-01-01

    A bidirectional neural interface is a device that transfers information into and out of the nervous system. This class of devices has potential to improve treatment and therapy in several patient populations. Progress in very large-scale integration has advanced the design of complex integrated circuits. System-on-chip devices are capable of recording neural electrical activity and altering natural activity with electrical stimulation. Often, these devices include wireless powering and telemetry functions. This review presents the state of the art of bidirectional circuits as applied to neuroprosthetic, neurorepair, and neurotherapeutic systems.

  11. The relevance of network micro-structure for neural dynamics

    Directory of Open Access Journals (Sweden)

    Volker ePernice

    2013-06-01

    Full Text Available The activity of cortical neurons is determined by the input they receive from presynaptic neurons. Many previousstudies have investigated how specific aspects of the statistics of the input affect the spike trains of single neurons and neuronsin recurrent networks. However, typically very simple random network models are considered in such studies. Here weuse a recently developed algorithm to construct networks based on a quasi-fractal probability measure which are much morevariable than commonly used network models, and which therefore promise to sample the space of recurrent networks ina more exhaustive fashion than previously possible. We use the generated graphs as the underlying network topology insimulations of networks of integrate-and-fire neurons in an asynchronous and irregular state. Based on an extensive datasetof networks and neuronal simulations we assess statistical relations between features of the network structure and the spikingactivity. Our results highlight the strong influence that some details of the network structure have on the activity dynamics ofboth single neurons and populations, even if some global network parameters are kept fixed. We observe specific and consistentrelations between activity characteristics like spike-train irregularity or correlations and network properties, for example thedistributions of the numbers of in- and outgoing connections or clustering. Exploiting these relations, we demonstrate that itis possible to estimate structural characteristics of the network from activity data. We also assess higher order correlationsof spiking activity in the various networks considered here, and find that their occurrence strongly depends on the networkstructure. These results provide directions for further theoretical studies on recurrent networks, as well as new ways to interpretspike train recordings from neural circuits.

  12. Deconstruction and Control of Neural Circuits in Posttraumatic Epilepsy

    Science.gov (United States)

    2017-10-01

    Holden and Frances Cho –received awards that allowed them to present their work at multiple national and international conferences. These awards...Stephanie Holden and Frances Cho – whose work focuses on this DoD-funded project, received multiple awards that allowed them to present their work at...epileptogenesis. Stephanie and Frances presented their work at multiple conferences: 8. Holden S, Paz JT (2017) Deconstruction of thalamic circuits in a mouse

  13. Neural circuit remodeling and structural plasticity in the cortex during chronic pain.

    Science.gov (United States)

    Kim, Woojin; Kim, Sun Kwang

    2016-01-01

    Damage in the periphery or spinal cord induces maladaptive plastic changes along the somatosensory nervous system from the periphery to the cortex, often leading to chronic pain. Although the role of neural circuit remodeling and structural synaptic plasticity in the 'pain matrix' cortices in chronic pain has been thought as a secondary epiphenomenon to altered nociceptive signaling in the spinal cord, progress in whole brain imaging studies on human patients and animal models has suggested a possibility that plastic changes in cortical neural circuits may actively contribute to chronic pain symptoms. Furthermore, recent development in two-photon microscopy and fluorescence labeling techniques have enabled us to longitudinally trace the structural and functional changes in local circuits, single neurons and even individual synapses in the brain of living animals. These technical advances has started to reveal that cortical structural remodeling following tissue or nerve damage could rapidly occur within days, which are temporally correlated with functional plasticity of cortical circuits as well as the development and maintenance of chronic pain behavior, thereby modifying the previous concept that it takes much longer periods (e.g. months or years). In this review, we discuss the relation of neural circuit plasticity in the 'pain matrix' cortices, such as the anterior cingulate cortex, prefrontal cortex and primary somatosensory cortex, with chronic pain. We also introduce how to apply long-term in vivo two-photon imaging approaches for the study of pathophysiological mechanisms of chronic pain.

  14. The generation effect: activating broad neural circuits during memory encoding.

    Science.gov (United States)

    Rosner, Zachary A; Elman, Jeremy A; Shimamura, Arthur P

    2013-01-01

    The generation effect is a robust memory phenomenon in which actively producing material during encoding acts to improve later memory performance. In a functional magnetic resonance imaging (fMRI) analysis, we explored the neural basis of this effect. During encoding, participants generated synonyms from word-fragment cues (e.g., GARBAGE-W_ST_) or read other synonym pairs (e.g., GARBAGE-WASTE). Compared to simply reading target words, generating target words significantly improved later recognition memory performance. During encoding, this benefit was associated with a broad neural network that involved both prefrontal (inferior frontal gyrus, middle frontal gyrus) and posterior cortex (inferior temporal gyrus, lateral occipital cortex, parahippocampal gyrus, ventral posterior parietal cortex). These findings define the prefrontal-posterior cortical dynamics associated with the mnemonic benefits underlying the generation effect. Copyright © 2012 Elsevier Ltd. All rights reserved.

  15. Priming Neural Circuits to Modulate Spinal Reflex Excitability

    OpenAIRE

    Estes, Stephen P.; Iddings, Jennifer A.; Field-Fote, Edelle C.

    2017-01-01

    While priming is most often thought of as a strategy for modulating neural excitability to facilitate voluntary motor control, priming stimulation can also be utilized to target spinal reflex excitability. In this application, priming can be used to modulate the involuntary motor output that often follows central nervous system injury. Individuals with spinal cord injury (SCI) often experience spasticity, for which antispasmodic medications are the most common treatment. Physical therapeutic/...

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

    Science.gov (United States)

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

    2012-01-01

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

  17. Monitoring activity in neural circuits with genetically encoded indicators

    Directory of Open Access Journals (Sweden)

    Gerard Joseph Broussard

    2014-12-01

    Full Text Available Recent developments in genetically encoded indicators of neural activity (GINAs have greatly advanced the field of systems neuroscience. As they are encoded by DNA, GINAs can be targeted to genetically defined cellular populations. Combined with fluorescence microscopy, most notably multi-photon imaging, GINAs allow chronic simultaneous optical recordings from large populations of neurons or glial cells in awake, behaving mammals, particularly rodents. This large-scale recording of neural activity at multiple temporal and spatial scales has greatly advanced our understanding of the dynamics of neural circuitry underlying behavior—a critical first step toward understanding the complexities of brain function, such as sensorimotor integration and learning.Here, we summarize the recent development and applications of the major classes of GINAs. In particular, we take an in-depth look at the design of available GINA families with a particular focus on genetically encoded calcium indicators, sensors probing synaptic activity, and genetically encoded voltage indicators. Using the family of the genetically encoded calcium indicator GCaMP as an example, we review established sensor optimization pipelines. We also discuss practical considerations for end users of GINAs about experimental methods including approaches for gene delivery, imaging system requirements, and data analysis techniques. With the growing toolbox of GINAs and with new microscopy techniques pushing beyond their current limits, the age of light can finally achieve the goal of broad and dense sampling of neuronal activity across time and brain structures to obtain a dynamic picture of brain function.

  18. The malleable brain: plasticity of neural circuits and behavior - a review from students to students.

    Science.gov (United States)

    Schaefer, Natascha; Rotermund, Carola; Blumrich, Eva-Maria; Lourenco, Mychael V; Joshi, Pooja; Hegemann, Regina U; Jamwal, Sumit; Ali, Nilufar; García Romero, Ezra Michelet; Sharma, Sorabh; Ghosh, Shampa; Sinha, Jitendra K; Loke, Hannah; Jain, Vishal; Lepeta, Katarzyna; Salamian, Ahmad; Sharma, Mahima; Golpich, Mojtaba; Nawrotek, Katarzyna; Paidi, Ramesh K; Shahidzadeh, Sheila M; Piermartiri, Tetsade; Amini, Elham; Pastor, Veronica; Wilson, Yvette; Adeniyi, Philip A; Datusalia, Ashok K; Vafadari, Benham; Saini, Vedangana; Suárez-Pozos, Edna; Kushwah, Neetu; Fontanet, Paula; Turner, Anthony J

    2017-06-20

    One of the most intriguing features of the brain is its ability to be malleable, allowing it to adapt continually to changes in the environment. Specific neuronal activity patterns drive long-lasting increases or decreases in the strength of synaptic connections, referred to as long-term potentiation and long-term depression, respectively. Such phenomena have been described in a variety of model organisms, which are used to study molecular, structural, and functional aspects of synaptic plasticity. This review originated from the first International Society for Neurochemistry (ISN) and Journal of Neurochemistry (JNC) Flagship School held in Alpbach, Austria (Sep 2016), and will use its curriculum and discussions as a framework to review some of the current knowledge in the field of synaptic plasticity. First, we describe the role of plasticity during development and the persistent changes of neural circuitry occurring when sensory input is altered during critical developmental stages. We then outline the signaling cascades resulting in the synthesis of new plasticity-related proteins, which ultimately enable sustained changes in synaptic strength. Going beyond the traditional understanding of synaptic plasticity conceptualized by long-term potentiation and long-term depression, we discuss system-wide modifications and recently unveiled homeostatic mechanisms, such as synaptic scaling. Finally, we describe the neural circuits and synaptic plasticity mechanisms driving associative memory and motor learning. Evidence summarized in this review provides a current view of synaptic plasticity in its various forms, offers new insights into the underlying mechanisms and behavioral relevance, and provides directions for future research in the field of synaptic plasticity. Read the Editorial Highlight for this article on doi: 10.1111/jnc.14102. © 2017 International Society for Neurochemistry.

  19. A neural space vector fault location for parallel double-circuit distribution lines

    Energy Technology Data Exchange (ETDEWEB)

    Sousa Martins, L.; Martins, J.F.; Fernao Pires, V. [Politecnico de Setubal (Portugal). Escola Sup. Tecnol.; Alegria, C.M. [Instituto Superior Tecnico, Lisbon (Portugal)

    2005-03-01

    A new approach to fault location for parallel double-circuit distribution power lines is presented. This approach uses the Clark-Concordia transformation and an artificial neural network based learning algorithm. The {alpha}, {beta}, 0 components of double line currents resulting from the Clarke-Concordia transformation are used to characterize different states of the system. The neural network is trained to map the non-linear relationship existing between fault location and characteristic eigenvalue. The proposed approach is able to identify and to locate different types of faults such as: phase-to-earth, phase-to-phase, two-phase-to-earth and three-phase. Using the eigenvalue as neural network inputs the proposed algorithm locates the fault distance. Results are presented which show the effectiveness of the proposed algorithm for a correct fault location on a parallel double-circuit distribution line. (author)

  20. Optogenetic manipulation of neural circuits in awake marmosets.

    Science.gov (United States)

    MacDougall, Matthew; Nummela, Samuel U; Coop, Shanna; Disney, Anita; Mitchell, Jude F; Miller, Cory T

    2016-09-01

    Optogenetics has revolutionized the study of functional neuronal circuitry (Boyden ES, Zhang F, Bamberg E, Nagel G, Deisseroth K. Nat Neurosci 8: 1263-1268, 2005; Deisseroth K. Nat Methods 8: 26-29, 2011). Although these techniques have been most successfully implemented in rodent models, they have the potential to be similarly impactful in studies of nonhuman primate brains. Common marmosets (Callithrix jacchus) have recently emerged as a candidate primate model for gene editing, providing a potentially powerful model for studies of neural circuitry and disease in primates. The application of viral transduction methods in marmosets for identifying and manipulating neuronal circuitry is a crucial step in developing this species for neuroscience research. In the present study we developed a novel, chronic method to successfully induce rapid photostimulation in individual cortical neurons transduced by adeno-associated virus to express channelrhodopsin (ChR2) in awake marmosets. We found that large proportions of neurons could be effectively photoactivated following viral transduction and that this procedure could be repeated for several months. These data suggest that techniques for viral transduction and optical manipulation of neuronal populations are suitable for marmosets and can be combined with existing behavioral preparations in the species to elucidate the functional neural circuitry underlying perceptual and cognitive processes. Copyright © 2016 the American Physiological Society.

  1. Ontogeny of neural circuits underlying spatial memory in the rat

    Directory of Open Access Journals (Sweden)

    James Alexander Ainge

    2012-03-01

    Full Text Available Spatial memory is a well characterised psychological function in both humans and rodents. The combined computations of a network of systems including place cells in the hippocampus, grid cells in the medial entorhinal cortex and head direction cells found in numerous structures in the brain have been suggested to form the neural instantiation of the cognitive map as first described by Tolman in 1948. However, while our understanding of the neural mechanisms underlying spatial representations in adults is relatively sophisticated, we know substantially less about how this network develops in young animals. In this article we review studies examining the developmental timescale that these systems follow. Electrophysiological recordings from very young rats show that directional information is at adult levels at the outset of navigational experience. The systems supporting allocentric memory, however, take longer to mature. This is consistent with behavioural studies of young rats which show that spatial memory based on head direction develops very early but that allocentric spatial memory takes longer to mature. We go on to report new data demonstrating that memory for associations between objects and their spatial locations is slower to develop than memory for objects alone. This is again consistent with previous reports suggesting that adult like spatial representations have a protracted development in rats and also suggests that the systems involved in processing non-spatial stimuli come online earlier.

  2. Spatiotemporal imaging of glutamate-induced biophotonic activities and transmission in neural circuits.

    Directory of Open Access Journals (Sweden)

    Rendong Tang

    Full Text Available The processing of neural information in neural circuits plays key roles in neural functions. Biophotons, also called ultra-weak photon emissions (UPE, may play potential roles in neural signal transmission, contributing to the understanding of the high functions of nervous system such as vision, learning and memory, cognition and consciousness. However, the experimental analysis of biophotonic activities (emissions in neural circuits has been hampered due to technical limitations. Here by developing and optimizing an in vitro biophoton imaging method, we characterize the spatiotemporal biophotonic activities and transmission in mouse brain slices. We show that the long-lasting application of glutamate to coronal brain slices produces a gradual and significant increase of biophotonic activities and achieves the maximal effect within approximately 90 min, which then lasts for a relatively long time (>200 min. The initiation and/or maintenance of biophotonic activities by glutamate can be significantly blocked by oxygen and glucose deprivation, together with the application of a cytochrome c oxidase inhibitor (sodium azide, but only partly by an action potential inhibitor (TTX, an anesthetic (procaine, or the removal of intracellular and extracellular Ca(2+. We also show that the detected biophotonic activities in the corpus callosum and thalamus in sagittal brain slices mostly originate from axons or axonal terminals of cortical projection neurons, and that the hyperphosphorylation of microtubule-associated protein tau leads to a significant decrease of biophotonic activities in these two areas. Furthermore, the application of glutamate in the hippocampal dentate gyrus results in increased biophotonic activities in its intrahippocampal projection areas. These results suggest that the glutamate-induced biophotonic activities reflect biophotonic transmission along the axons and in neural circuits, which may be a new mechanism for the processing of

  3. How Do Efficient Coding Strategies Depend on Origins of Noise in Neural Circuits?

    Science.gov (United States)

    Brinkman, Braden A W; Weber, Alison I; Rieke, Fred; Shea-Brown, Eric

    2016-10-01

    Neural circuits reliably encode and transmit signals despite the presence of noise at multiple stages of processing. The efficient coding hypothesis, a guiding principle in computational neuroscience, suggests that a neuron or population of neurons allocates its limited range of responses as efficiently as possible to best encode inputs while mitigating the effects of noise. Previous work on this question relies on specific assumptions about where noise enters a circuit, limiting the generality of the resulting conclusions. Here we systematically investigate how noise introduced at different stages of neural processing impacts optimal coding strategies. Using simulations and a flexible analytical approach, we show how these strategies depend on the strength of each noise source, revealing under what conditions the different noise sources have competing or complementary effects. We draw two primary conclusions: (1) differences in encoding strategies between sensory systems-or even adaptational changes in encoding properties within a given system-may be produced by changes in the structure or location of neural noise, and (2) characterization of both circuit nonlinearities as well as noise are necessary to evaluate whether a circuit is performing efficiently.

  4. How Do Efficient Coding Strategies Depend on Origins of Noise in Neural Circuits?

    Directory of Open Access Journals (Sweden)

    Braden A W Brinkman

    2016-10-01

    Full Text Available Neural circuits reliably encode and transmit signals despite the presence of noise at multiple stages of processing. The efficient coding hypothesis, a guiding principle in computational neuroscience, suggests that a neuron or population of neurons allocates its limited range of responses as efficiently as possible to best encode inputs while mitigating the effects of noise. Previous work on this question relies on specific assumptions about where noise enters a circuit, limiting the generality of the resulting conclusions. Here we systematically investigate how noise introduced at different stages of neural processing impacts optimal coding strategies. Using simulations and a flexible analytical approach, we show how these strategies depend on the strength of each noise source, revealing under what conditions the different noise sources have competing or complementary effects. We draw two primary conclusions: (1 differences in encoding strategies between sensory systems-or even adaptational changes in encoding properties within a given system-may be produced by changes in the structure or location of neural noise, and (2 characterization of both circuit nonlinearities as well as noise are necessary to evaluate whether a circuit is performing efficiently.

  5. A simple structure wavelet transform circuit employing function link neural networks and SI filters

    Science.gov (United States)

    Mu, Li; Yigang, He

    2016-12-01

    Signal processing by means of analog circuits offers advantages from a power consumption viewpoint. Implementing wavelet transform (WT) using analog circuits is of great interest when low-power consumption becomes an important issue. In this article, a novel simple structure WT circuit in analog domain is presented by employing functional link neural network (FLNN) and switched-current (SI) filters. First, the wavelet base is approximated using FLNN algorithms for giving a filter transfer function that is suitable for simple structure WT circuit implementation. Next, the WT circuit is constructed with the wavelet filter bank, whose impulse response is the approximated wavelet and its dilations. The filter design that follows is based on a follow-the-leader feedback (FLF) structure with multiple output bilinear SI integrators and current mirrors as the main building blocks. SI filter is well suited for this application since the dilation constant across different scales of the transform can be precisely implemented and controlled by the clock frequency of the circuit with the same system architecture. Finally, to illustrate the design procedure, a seventh-order FLNN-approximated Gaussian wavelet is implemented as an example. Simulations have successfully verified that the designed simple structure WT circuit has low sensitivity, low-power consumption and litter effect to the imperfections.

  6. PCSIM: A Parallel Simulation Environment for Neural Circuits Fully Integrated with Python

    Science.gov (United States)

    Pecevski, Dejan; Natschläger, Thomas; Schuch, Klaus

    2008-01-01

    The Parallel Circuit SIMulator (PCSIM) is a software package for simulation of neural circuits. It is primarily designed for distributed simulation of large scale networks of spiking point neurons. Although its computational core is written in C++, PCSIM's primary interface is implemented in the Python programming language, which is a powerful programming environment and allows the user to easily integrate the neural circuit simulator with data analysis and visualization tools to manage the full neural modeling life cycle. The main focus of this paper is to describe PCSIM's full integration into Python and the benefits thereof. In particular we will investigate how the automatically generated bidirectional interface and PCSIM's object-oriented modular framework enable the user to adopt a hybrid modeling approach: using and extending PCSIM's functionality either employing pure Python or C++ and thus combining the advantages of both worlds. Furthermore, we describe several supplementary PCSIM packages written in pure Python and tailored towards setting up and analyzing neural simulations. PMID:19543450

  7. Massively parallel neural circuits for stereoscopic color vision: encoding, decoding and identification.

    Science.gov (United States)

    Lazar, Aurel A; Slutskiy, Yevgeniy B; Zhou, Yiyin

    2015-03-01

    Past work demonstrated how monochromatic visual stimuli could be faithfully encoded and decoded under Nyquist-type rate conditions. Color visual stimuli were then traditionally encoded and decoded in multiple separate monochromatic channels. The brain, however, appears to mix information about color channels at the earliest stages of the visual system, including the retina itself. If information about color is mixed and encoded by a common pool of neurons, how can colors be demixed and perceived? We present Color Video Time Encoding Machines (Color Video TEMs) for encoding color visual stimuli that take into account a variety of color representations within a single neural circuit. We then derive a Color Video Time Decoding Machine (Color Video TDM) algorithm for color demixing and reconstruction of color visual scenes from spikes produced by a population of visual neurons. In addition, we formulate Color Video Channel Identification Machines (Color Video CIMs) for functionally identifying color visual processing performed by a spiking neural circuit. Furthermore, we derive a duality between TDMs and CIMs that unifies the two and leads to a general theory of neural information representation for stereoscopic color vision. We provide examples demonstrating that a massively parallel color visual neural circuit can be first identified with arbitrary precision and its spike trains can be subsequently used to reconstruct the encoded stimuli. We argue that evaluation of the functional identification methodology can be effectively and intuitively performed in the stimulus space. In this space, a signal reconstructed from spike trains generated by the identified neural circuit can be compared to the original stimulus. Copyright © 2014 Elsevier Ltd. All rights reserved.

  8. In search of the neural circuits of intrinsic motivation

    Directory of Open Access Journals (Sweden)

    Frederic Kaplan

    2007-10-01

    Full Text Available Children seem to acquire new know-how in a continuous and open-ended manner. In this paper, we hypothesize that an intrinsic motivation to progress in learning is at the origins of the remarkable structure of children's developmental trajectories. In this view, children engage in exploratory and playful activities for their own sake, not as steps toward other extrinsic goals. The central hypothesis of this paper is that intrinsically motivating activities correspond to expected decrease in prediction error. This motivation system pushes the infant to avoid both predictable and unpredictable situations in order to focus on the ones that are expected to maximize progress in learning. Based on a computational model and a series of robotic experiments, we show how this principle can lead to organized sequences of behavior of increasing complexity characteristic of several behavioral and developmental patterns observed in humans. We then discuss the putative circuitry underlying such an intrinsic motivation system in the brain and formulate two novel hypotheses. The first one is that tonic dopamine acts as a learning progress signal. The second is that this progress signal is directly computed through a hierarchy of microcortical circuits that act both as prediction and metaprediction systems.

  9. A neural circuit for resolving sensory conflict in Drosophila

    OpenAIRE

    Lewis, L.

    2016-01-01

    Animal habitats are highly complex and encode a surfeit of potentially meaningful information relevant to an animal’s immediate and future survival. Animals must sense and decode this complex environmental information in order to initiate an optimal behavioural response capable of meeting its survival requirements. Some environmental stimuli may elicit innate or learned attraction or aversion, while others may trigger courtship behaviour or grooming. However, the same stimuli may have differe...

  10. Neural circuits involved in the renewal of extinguished fear.

    Science.gov (United States)

    Chen, Weihai; Wang, Yan; Wang, Xiaqing; Li, Hong

    2017-07-01

    The last 10 years have witnessed a substantial progress in understanding the neural mechanisms for the renewal of the extinguished fear memory. Based on the theory of fear extinction, exposure therapy has been developed as a typical cognitive behavioral therapy for posttraumatic stress disorder. Although the fear memory can be extinguished by repeated presentation of conditioned stimulus without unconditioned stimulus, the fear memory is not erased and tends to relapse outside of extinction context, which is referred to as renewal. Therefore, the renewal is regarded as a great obstruction interfering with the effect of exposure therapy. In recent years, there has been a great deal of studies in understanding the neurobiological underpinnings of fear renewal. These offer a foundation upon which novel therapeutic interventions for the renewal may be built. This review focuses on behavioral, anatomical and electrophysiological studies that interpret roles of the hippocampus, prelimbic cortex and amygdala as well as the connections between them for the renewal of the extinguished fear. Additionally, this review suggests the possible pathways for the renewal: (1) the prelimbic cortex may integrate contextual information from hippocampal inputs and project to the basolateral amygdala to mediate the renewal of extinguished fear memory; the ventral hippocampus may innervate the activities of the basolateral amygdala or the central amygdala directly for the renewal. © 2017 IUBMB Life, 69(7):470-478, 2017. © 2017 International Union of Biochemistry and Molecular Biology.

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

    Directory of Open Access Journals (Sweden)

    Jacob T. Robinson

    2013-03-01

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

  12. Importance of Practical Relevance and Design Modules in Electrical Circuits Education

    Directory of Open Access Journals (Sweden)

    Kalpathy Sundaram

    2011-05-01

    Full Text Available The interactive technical electronic book, TechEBook, currently under development at the University of Central Florida (UCF, provides a useful tool for engineers and scientists through unique features compared to the most used traditional electrical circuit textbooks available in the market. TechEBook has comprised the two worlds of classical circuit books and an interactive operating platform such as iPads, laptops and desktops utilizing Java Virtual Machine operator. The TechEBook provides an interactive applets screen that holds many modules, in which each had a specific application in the self learning process. This paper describes two of the interactive techniques in the TechEBook known as, Practical Relevance Modules (PRM and Design Modules (DM. The Practical Relevance Module will assist the readers to learn electrical circuit analysis and to understand the practical application of the electrical network theory through solving real world examples and problems. The Design Module will help students design real-life problems. These modules will be displayed after each section in the TechEBook for the user to relate his/her understanding with the outside world, which introduces the term me-applying and me-designing, as a comprehensive full experience for self or individualized education. The main emphasis of this paper is the PRM while the DM will be discussed in brief. A practical example of applying the PRM and DM features is discussed as part of a basic electrical engineering course currently given at UCF and results show improved student performances in learning materials in Electrical Circuits. In the future, such modules can be redesigned to become highly interactive with illustrated animations.

  13. Neuromodulation of the neural circuits controlling the lower urinary tract.

    Science.gov (United States)

    Gad, Parag N; Roy, Roland R; Zhong, Hui; Gerasimenko, Yury P; Taccola, Giuliano; Edgerton, V Reggie

    2016-11-01

    The inability to control timely bladder emptying is one of the most serious challenges among the many functional deficits that occur after a spinal cord injury. We previously demonstrated that electrodes placed epidurally on the dorsum of the spinal cord can be used in animals and humans to recover postural and locomotor function after complete paralysis and can be used to enable voiding in spinal rats. In the present study, we examined the neuromodulation of lower urinary tract function associated with acute epidural spinal cord stimulation, locomotion, and peripheral nerve stimulation in adult rats. Herein we demonstrate that electrically evoked potentials in the hindlimb muscles and external urethral sphincter are modulated uniquely when the rat is stepping bipedally and not voiding, immediately pre-voiding, or when voiding. We also show that spinal cord stimulation can effectively neuromodulate the lower urinary tract via frequency-dependent stimulation patterns and that neural peripheral nerve stimulation can activate the external urethral sphincter both directly and via relays in the spinal cord. The data demonstrate that the sensorimotor networks controlling bladder and locomotion are highly integrated neurophysiologically and behaviorally and demonstrate how these two functions are modulated by sensory input from the tibial and pudental nerves. A more detailed understanding of the high level of interaction between these networks could lead to the integration of multiple neurophysiological strategies to improve bladder function. These data suggest that the development of strategies to improve bladder function should simultaneously engage these highly integrated networks in an activity-dependent manner. Copyright © 2016. Published by Elsevier Inc.

  14. [Progress in activity-dependent structural plasticity of neural circuits in cortex].

    Science.gov (United States)

    Rao, Xiao-Ping; Xu, Zhi-Xiang; Xu, Fu-Qiang

    2012-10-01

    Neural circuits of mammalian cerebral cortex have exhibited amazing abilities of structural and functional plasticity in development, learning and memory, neurological and psychiatric diseases. With the new imaging techniques and the application of molecular biology methods, observation neural circuits' structural dynamics within the cortex in vivo at the cellular and synaptic level was possible, so there were many great progresses in the field of the activity-dependent structural plasticity over the past decade. This paper reviewed some of the aspects of the experimental results, focused on the characteristics of dendritic structural plasticity in individual growth and development, rich environment, sensory deprivation, and pathological conditions, as well as learning and memory, especially the dynamics of dendritic spines on morphology and quantity; after that, we introduced axonal structural plasticity, the molecular and cellular mechanisms of structural plasticity, and proposed some future problems to be solved at last.

  15. Automated cell-specific laser detection and ablation of neural circuits in neonatal brain tissue

    Science.gov (United States)

    Wang, Xueying; Hayes, John A; Picardo, Maria Cristina D; Del Negro, Christopher A

    2013-01-01

    A key feature of neurodegenerative disease is the pathological loss of neurons that participate in generating behaviour. To investigate network properties of neural circuits and provide a complementary tool to study neurodegeneration in vitro or in situ, we developed an automated cell-specific laser detection and ablation system. The instrument consists of a two-photon and visible-wavelength confocal imaging setup, controlled by executive software, that identifies neurons in preparations based on genetically encoded fluorescent proteins or Ca2+ imaging, and then sequentially ablates cell targets while monitoring network function concurrently. Pathological changes in network function can be directly attributed to ablated cells, which are logged in real time. Here, we investigated brainstem respiratory circuits to demonstrate single-cell precision in ablation during physiological network activity, but the technique could be applied to interrogate network properties in neural systems that retain network functionality in reduced preparations in vitro or in situ. PMID:23440965

  16. A decision-making model based on a spiking neural circuit and synaptic plasticity.

    Science.gov (United States)

    Wei, Hui; Bu, Yijie; Dai, Dawei

    2017-10-01

    To adapt to the environment and survive, most animals can control their behaviors by making decisions. The process of decision-making and responding according to cues in the environment is stable, sustainable, and learnable. Understanding how behaviors are regulated by neural circuits and the encoding and decoding mechanisms from stimuli to responses are important goals in neuroscience. From results observed in Drosophila experiments, the underlying decision-making process is discussed, and a neural circuit that implements a two-choice decision-making model is proposed to explain and reproduce the observations. Compared with previous two-choice decision making models, our model uses synaptic plasticity to explain changes in decision output given the same environment. Moreover, biological meanings of parameters of our decision-making model are discussed. In this paper, we explain at the micro-level (i.e., neurons and synapses) how observable decision-making behavior at the macro-level is acquired and achieved.

  17. Engagement of neural circuits underlying 2D spatial navigation in a rodent virtual reality system.

    Science.gov (United States)

    Aronov, Dmitriy; Tank, David W

    2014-10-22

    Virtual reality (VR) enables precise control of an animal's environment and otherwise impossible experimental manipulations. Neural activity in rodents has been studied on virtual 1D tracks. However, 2D navigation imposes additional requirements, such as the processing of head direction and environment boundaries, and it is unknown whether the neural circuits underlying 2D representations can be sufficiently engaged in VR. We implemented a VR setup for rats, including software and large-scale electrophysiology, that supports 2D navigation by allowing rotation and walking in any direction. The entorhinal-hippocampal circuit, including place, head direction, and grid cells, showed 2D activity patterns similar to those in the real world. Furthermore, border cells were observed, and hippocampal remapping was driven by environment shape, suggesting functional processing of virtual boundaries. These results illustrate that 2D spatial representations can be engaged by visual and rotational vestibular stimuli alone and suggest a novel VR tool for studying rat navigation.

  18. Homology and homoplasy of swimming behaviors and neural circuits in the Nudipleura (Mollusca, Gastropoda, Opisthobranchia)

    Science.gov (United States)

    Newcomb, James M.; Sakurai, Akira; Lillvis, Joshua L.; Gunaratne, Charuni A.; Katz, Paul S.

    2012-01-01

    How neural circuit evolution relates to behavioral evolution is not well understood. Here the relationship between neural circuits and behavior is explored with respect to the swimming behaviors of the Nudipleura (Mollusca, Gastropoda, Opithobranchia). Nudipleura is a diverse monophyletic clade of sea slugs among which only a small percentage of species can swim. Swimming falls into a limited number of categories, the most prevalent of which are rhythmic left–right body flexions (LR) and rhythmic dorsal–ventral body flexions (DV). The phylogenetic distribution of these behaviors suggests a high degree of homoplasy. The central pattern generator (CPG) underlying DV swimming has been well characterized in Tritonia diomedea and in Pleurobranchaea californica. The CPG for LR swimming has been elucidated in Melibe leonina and Dendronotus iris, which are more closely related. The CPGs for the categorically distinct DV and LR swimming behaviors consist of nonoverlapping sets of homologous identified neurons, whereas the categorically similar behaviors share some homologous identified neurons, although the exact composition of neurons and synapses in the neural circuits differ. The roles played by homologous identified neurons in categorically distinct behaviors differ. However, homologous identified neurons also play different roles even in the swim CPGs of the two LR swimming species. Individual neurons can be multifunctional within a species. Some of those functions are shared across species, whereas others are not. The pattern of use and reuse of homologous neurons in various forms of swimming and other behaviors further demonstrates that the composition of neural circuits influences the evolution of behaviors. PMID:22723353

  19. Priming Neural Circuits to Modulate Spinal Reflex Excitability

    Science.gov (United States)

    Estes, Stephen P.; Iddings, Jennifer A.; Field-Fote, Edelle C.

    2017-01-01

    While priming is most often thought of as a strategy for modulating neural excitability to facilitate voluntary motor control, priming stimulation can also be utilized to target spinal reflex excitability. In this application, priming can be used to modulate the involuntary motor output that often follows central nervous system injury. Individuals with spinal cord injury (SCI) often experience spasticity, for which antispasmodic medications are the most common treatment. Physical therapeutic/electroceutic interventions offer an alternative treatment for spasticity, without the deleterious side effects that can accompany pharmacological interventions. While studies of physical therapeutic/electroceutic interventions have been published, a systematic comparison of these approaches has not been performed. The purpose of this study was to compare four non-pharmacological interventions to a sham-control intervention to assess their efficacy for spasticity reduction. Participants were individuals (n = 10) with chronic SCI (≥1 year) who exhibited stretch-induced quadriceps spasticity. Spasticity was quantified using the pendulum test before and at two time points after (immediate, 45 min delayed) each of four different physical therapeutic/electroceutic interventions, plus a sham-control intervention. Interventions included stretching, cyclic passive movement (CPM), transcutaneous spinal cord stimulation (tcSCS), and transcranial direct current stimulation (tDCS). The sham-control intervention consisted of a brief ramp-up and ramp-down of knee and ankle stimulation while reclined with legs extended. The order of interventions was randomized, and each was tested on a separate day with at least 48 h between sessions. Compared to the sham-control intervention, stretching, CPM, and tcSCS were associated with a significantly greater reduction in spasticity immediately after treatment. While the immediate effect was largest for stretching, the reduction persisted

  20. Biologically based neural circuit modelling for the study of fear learning and extinction

    Science.gov (United States)

    Nair, Satish S.; Paré, Denis; Vicentic, Aleksandra

    2016-11-01

    The neuronal systems that promote protective defensive behaviours have been studied extensively using Pavlovian conditioning. In this paradigm, an initially neutral-conditioned stimulus is paired with an aversive unconditioned stimulus leading the subjects to display behavioural signs of fear. Decades of research into the neural bases of this simple behavioural paradigm uncovered that the amygdala, a complex structure comprised of several interconnected nuclei, is an essential part of the neural circuits required for the acquisition, consolidation and expression of fear memory. However, emerging evidence from the confluence of electrophysiological, tract tracing, imaging, molecular, optogenetic and chemogenetic methodologies, reveals that fear learning is mediated by multiple connections between several amygdala nuclei and their distributed targets, dynamical changes in plasticity in local circuit elements as well as neuromodulatory mechanisms that promote synaptic plasticity. To uncover these complex relations and analyse multi-modal data sets acquired from these studies, we argue that biologically realistic computational modelling, in conjunction with experiments, offers an opportunity to advance our understanding of the neural circuit mechanisms of fear learning and to address how their dysfunction may lead to maladaptive fear responses in mental disorders.

  1. Large scale neural circuit mapping data analysis accelerated with the graphical processing unit (GPU)

    Science.gov (United States)

    Shi, Yulin; Veidenbaum, Alexander V.; Nicolau, Alex; Xu, Xiangmin

    2014-01-01

    Background Modern neuroscience research demands computing power. Neural circuit mapping studies such as those using laser scanning photostimulation (LSPS) produce large amounts of data and require intensive computation for post-hoc processing and analysis. New Method Here we report on the design and implementation of a cost-effective desktop computer system for accelerated experimental data processing with recent GPU computing technology. A new version of Matlab software with GPU enabled functions is used to develop programs that run on Nvidia GPUs to harness their parallel computing power. Results We evaluated both the central processing unit (CPU) and GPU-enabled computational performance of our system in benchmark testing and practical applications. The experimental results show that the GPU-CPU co-processing of simulated data and actual LSPS experimental data clearly outperformed the multi-core CPU with up to a 22x speedup, depending on computational tasks. Further, we present a comparison of numerical accuracy between GPU and CPU computation to verify the precision of GPU computation. In addition, we show how GPUs can be effectively adapted to improve the performance of commercial image processing software such as Adobe Photoshop. Comparison with Existing Method(s) To our best knowledge, this is the first demonstration of GPU application in neural circuit mapping and electrophysiology-based data processing. Conclusions Together, GPU enabled computation enhances our ability to process large-scale data sets derived from neural circuit mapping studies, allowing for increased processing speeds while retaining data precision. PMID:25277633

  2. Large-scale neural circuit mapping data analysis accelerated with the graphical processing unit (GPU).

    Science.gov (United States)

    Shi, Yulin; Veidenbaum, Alexander V; Nicolau, Alex; Xu, Xiangmin

    2015-01-15

    Modern neuroscience research demands computing power. Neural circuit mapping studies such as those using laser scanning photostimulation (LSPS) produce large amounts of data and require intensive computation for post hoc processing and analysis. Here we report on the design and implementation of a cost-effective desktop computer system for accelerated experimental data processing with recent GPU computing technology. A new version of Matlab software with GPU enabled functions is used to develop programs that run on Nvidia GPUs to harness their parallel computing power. We evaluated both the central processing unit (CPU) and GPU-enabled computational performance of our system in benchmark testing and practical applications. The experimental results show that the GPU-CPU co-processing of simulated data and actual LSPS experimental data clearly outperformed the multi-core CPU with up to a 22× speedup, depending on computational tasks. Further, we present a comparison of numerical accuracy between GPU and CPU computation to verify the precision of GPU computation. In addition, we show how GPUs can be effectively adapted to improve the performance of commercial image processing software such as Adobe Photoshop. To our best knowledge, this is the first demonstration of GPU application in neural circuit mapping and electrophysiology-based data processing. Together, GPU enabled computation enhances our ability to process large-scale data sets derived from neural circuit mapping studies, allowing for increased processing speeds while retaining data precision. Copyright © 2014 Elsevier B.V. All rights reserved.

  3. Neural learning circuits utilizing nano-crystalline silicon transistors and memristors.

    Science.gov (United States)

    Cantley, Kurtis D; Subramaniam, Anand; Stiegler, Harvey J; Chapman, Richard A; Vogel, Eric M

    2012-04-01

    Properties of neural circuits are demonstrated via SPICE simulations and their applications are discussed. The neuron and synapse subcircuits include ambipolar nano-crystalline silicon transistor and memristor device models based on measured data. Neuron circuit characteristics and the Hebbian synaptic learning rule are shown to be similar to biology. Changes in the average firing rate learning rule depending on various circuit parameters are also presented. The subcircuits are then connected into larger neural networks that demonstrate fundamental properties including associative learning and pulse coincidence detection. Learned extraction of a fundamental frequency component from noisy inputs is demonstrated. It is then shown that if the fundamental sinusoid of one neuron input is out of phase with the rest, its synaptic connection changes differently than the others. Such behavior indicates that the system can learn to detect which signals are important in the general population, and that there is a spike-timing-dependent component of the learning mechanism. Finally, future circuit design and considerations are discussed, including requirements for the memristive device.

  4. Circuit models and experimental noise measurements of micropipette amplifiers for extracellular neural recordings from live animals.

    Science.gov (United States)

    Chen, Chang Hao; Pun, Sio Hang; Mak, Peng Un; Vai, Mang I; Klug, Achim; Lei, Tim C

    2014-01-01

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

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

    Directory of Open Access Journals (Sweden)

    Chang Hao Chen

    2014-01-01

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

  6. Changes in the spinal neural circuits are dependent on the movement speed of the visuomotor task

    Directory of Open Access Journals (Sweden)

    Shinji eKubota

    2015-12-01

    Full Text Available Previous studies have shown that spinal neural circuits are modulated by motor skill training. However, the effects of task movement speed on changes in spinal neural circuits have not been clarified. The aim of this research was to investigate whether spinal neural circuits were affected by task movement speed. Thirty-eight healthy subjects participated in this study. In experiment 1, the effects of task movement speed on the spinal neural circuits were examined. 18 subjects performed a visuomotor task involving ankle muscle slow (9 subjects or fast (9 subjects movement speed. Another 9 subjects performed a non-visuomotor task (controls in fast movement speed. The motor task training lasted for 20 min. The amounts of D1 inhibition and reciprocal Ia inhibition were measured using H-relfex condition-test paradigm and recorded before, and at 5, 15, and 30 min after the training session. In experiment 2, using transcranial magnetic stimulation (TMS, the effects of corticospinal descending inputs on the presynaptic inhibitory pathway were examined before and after performing either a visuomotor (8 subjects or a control task (8 subjects. All measurements were taken under resting conditions. The amount of D1 inhibition increased after the visuomotor task irrespective of movement speed (P < 0.01. The amount of reciprocal Ia inhibition increased with fast movement speed conditioning (P < 0.01, but was unchanged by slow movement speed conditioning. These changes lasted up to 15 min in D1 inhibition and 5 min in reciprocal Ia inhibition after the training session. The control task did not induce changes in D1 inhibition and reciprocal Ia inhibition. The TMS conditioned inhibitory effects of presynaptic inhibitory pathways decreased following visuomotor tasks (P < 0.01. The size of test H-reflex was almost the same size throughout experiments. The results suggest that supraspinal descending inputs for controlling joint movement are responsible for changes

  7. A neuroplasticity-inspired neural circuit for acoustic navigation with obstacle avoidance that learns smooth motion paths

    DEFF Research Database (Denmark)

    Shaikh, Danish; Manoonpong, Poramate

    2018-01-01

    avoiding obstacles. We have reported earlier on a neural circuit for acoustic navigation, inspired by neuroplasticity mechanisms, which learned stable robot motion paths for a simulated mobile robot. The circuit realised a reactive behaviour-based navigation architecture where a phonotaxis behaviour...

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

    Science.gov (United States)

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

    2013-04-01

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

  9. Changed Synaptic Plasticity in Neural Circuits of Depressive-Like and Escitalopram-Treated Rats.

    Science.gov (United States)

    Li, Xiao-Li; Yuan, Yong-Gui; Xu, Hua; Wu, Di; Gong, Wei-Gang; Geng, Lei-Yu; Wu, Fang-Fang; Tang, Hao; Xu, Lin; Zhang, Zhi-Jun

    2015-04-21

    Although progress has been made in the detection and characterization of neural plasticity in depression, it has not been fully understood in individual synaptic changes in the neural circuits under chronic stress and antidepressant treatment. Using electron microscopy and Western-blot analyses, the present study quantitatively examined the changes in the Gray's Type I synaptic ultrastructures and the expression of synapse-associated proteins in the key brain regions of rats' depressive-related neural circuit after chronic unpredicted mild stress and/or escitalopram administration. Meanwhile, their depressive behaviors were also determined by several tests. The Type I synapses underwent considerable remodeling after chronic unpredicted mild stress, which resulted in the changed width of the synaptic cleft, length of the active zone, postsynaptic density thickness, and/or synaptic curvature in the subregions of medial prefrontal cortex and hippocampus, as well as the basolateral amygdaloid nucleus of the amygdala, accompanied by changed expression of several synapse-associated proteins. Chronic escitalopram administration significantly changed the above alternations in the chronic unpredicted mild stress rats but had little effect on normal controls. Also, there was a positive correlation between the locomotor activity and the maximal synaptic postsynaptic density thickness in the stratum radiatum of the Cornu Ammonis 1 region and a negative correlation between the sucrose preference and the length of the active zone in the basolateral amygdaloid nucleus region in chronic unpredicted mild stress rats. These findings strongly indicate that chronic stress and escitalopram can alter synaptic plasticity in the neural circuits, and the remodeled synaptic ultrastructure was correlated with the rats' depressive behaviors, suggesting a therapeutic target for further exploration. © The Author 2015. Published by Oxford University Press on behalf of CINP.

  10. Changed Synaptic Plasticity in Neural Circuits of Depressive-Like and Escitalopram-Treated Rats

    Science.gov (United States)

    Li, Xiao-Li; Yuan, Yong-Gui; Xu, Hua; Wu, Di; Gong, Wei-Gang; Geng, Lei-Yu; Wu, Fang-Fang; Tang, Hao; Xu, Lin

    2015-01-01

    Background: Although progress has been made in the detection and characterization of neural plasticity in depression, it has not been fully understood in individual synaptic changes in the neural circuits under chronic stress and antidepressant treatment. Methods: Using electron microscopy and Western-blot analyses, the present study quantitatively examined the changes in the Gray’s Type I synaptic ultrastructures and the expression of synapse-associated proteins in the key brain regions of rats’ depressive-related neural circuit after chronic unpredicted mild stress and/or escitalopram administration. Meanwhile, their depressive behaviors were also determined by several tests. Results: The Type I synapses underwent considerable remodeling after chronic unpredicted mild stress, which resulted in the changed width of the synaptic cleft, length of the active zone, postsynaptic density thickness, and/or synaptic curvature in the subregions of medial prefrontal cortex and hippocampus, as well as the basolateral amygdaloid nucleus of the amygdala, accompanied by changed expression of several synapse-associated proteins. Chronic escitalopram administration significantly changed the above alternations in the chronic unpredicted mild stress rats but had little effect on normal controls. Also, there was a positive correlation between the locomotor activity and the maximal synaptic postsynaptic density thickness in the stratum radiatum of the Cornu Ammonis 1 region and a negative correlation between the sucrose preference and the length of the active zone in the basolateral amygdaloid nucleus region in chronic unpredicted mild stress rats. Conclusion: These findings strongly indicate that chronic stress and escitalopram can alter synaptic plasticity in the neural circuits, and the remodeled synaptic ultrastructure was correlated with the rats’ depressive behaviors, suggesting a therapeutic target for further exploration. PMID:25899067

  11. Implementing a Bayes Filter in a Neural Circuit: The Case of Unknown Stimulus Dynamics.

    Science.gov (United States)

    Sokoloski, Sacha

    2017-09-01

    In order to interact intelligently with objects in the world, animals must first transform neural population responses into estimates of the dynamic, unknown stimuli that caused them. The Bayesian solution to this problem is known as a Bayes filter, which applies Bayes' rule to combine population responses with the predictions of an internal model. The internal model of the Bayes filter is based on the true stimulus dynamics, and in this note, we present a method for training a theoretical neural circuit to approximately implement a Bayes filter when the stimulus dynamics are unknown. To do this we use the inferential properties of linear probabilistic population codes to compute Bayes' rule and train a neural network to compute approximate predictions by the method of maximum likelihood. In particular, we perform stochastic gradient descent on the negative log-likelihood of the neural network parameters with a novel approximation of the gradient. We demonstrate our methods on a finite-state, a linear, and a nonlinear filtering problem and show how the hidden layer of the neural network develops tuning curves consistent with findings in experimental neuroscience.

  12. Genetic manipulation of specific neural circuits by use of a viral vector system.

    Science.gov (United States)

    Kobayashi, Kenta; Kato, Shigeki; Kobayashi, Kazuto

    2017-01-05

    To understand the mechanisms underlying higher brain functions, we need to analyze the roles of specific neuronal pathways or cell types forming the complex neural networks. In the neuroscience field, the transgenic approach has provided a useful gene engineering tool for experimental studies of neural functions. The conventional transgenic technique requires the appropriate promoter regions that drive a neuronal type-specific gene expression, but the promoter sequences specifically functioning in each neuronal type are limited. Previously, we developed novel types of lentiviral vectors showing high efficiency of retrograde gene transfer in the central nervous system, termed highly efficient retrograde gene transfer (HiRet) vector and neuron-specific retrograde gene transfer (NeuRet) vector. The HiRet and NeuRet vectors enable genetical manipulation of specific neural pathways in diverse model animals in combination with conditional cell targeting, synaptic transmission silencing, and gene expression systems. These newly developed vectors provide powerful experimental strategies to investigate, more precisely, the machineries exerting various neural functions. In this review, we give an outline of the HiRet and NeuRet vectors and describe recent representative applications of these viral vectors for studies on neural circuits.

  13. Spiking neural circuits with dendritic stimulus processors : encoding, decoding, and identification in reproducing kernel Hilbert spaces.

    Science.gov (United States)

    Lazar, Aurel A; Slutskiy, Yevgeniy B

    2015-02-01

    We present a multi-input multi-output neural circuit architecture for nonlinear processing and encoding of stimuli in the spike domain. In this architecture a bank of dendritic stimulus processors implements nonlinear transformations of multiple temporal or spatio-temporal signals such as spike trains or auditory and visual stimuli in the analog domain. Dendritic stimulus processors may act on both individual stimuli and on groups of stimuli, thereby executing complex computations that arise as a result of interactions between concurrently received signals. The results of the analog-domain computations are then encoded into a multi-dimensional spike train by a population of spiking neurons modeled as nonlinear dynamical systems. We investigate general conditions under which such circuits faithfully represent stimuli and demonstrate algorithms for (i) stimulus recovery, or decoding, and (ii) identification of dendritic stimulus processors from the observed spikes. Taken together, our results demonstrate a fundamental duality between the identification of the dendritic stimulus processor of a single neuron and the decoding of stimuli encoded by a population of neurons with a bank of dendritic stimulus processors. This duality result enabled us to derive lower bounds on the number of experiments to be performed and the total number of spikes that need to be recorded for identifying a neural circuit.

  14. Neural circuit dynamics underlying accumulation of time-varying evidence during perceptual decision making

    Directory of Open Access Journals (Sweden)

    Kong-Fatt Wong

    2007-11-01

    Full Text Available How do neurons in a decision circuit integrate time-varying signals, in favor of or against alternative choice options? To address this question, we used a recurrent neural circuit model to simulate an experiment in which monkeys performed a direction-discrimination task on a visual motion stimulus. In a recent study, it was found that brief pulses of motion perturbed neural activity in the lateral intraparietal area (LIP, and exerted corresponding effects on the monkey's choices and response times. Our model reproduces the behavioral observations and replicates LIP activity which, depending on whether the direction of the pulse is the same or opposite to that of a preferred motion stimulus, increases or decreases persistently over a few hundred milliseconds. Furthermore, our model accounts for the observation that the pulse exerts a weaker influence on LIP neuronal responses when the pulse is late relative to motion stimulus onset. We show that this violation of time-shift invariance (TSI is consistent with a recurrent circuit mechanism of time integration. We further examine time integration using two consecutive pulses of the same or opposite motion directions. The induced changes in the performance are not additive, and the second of the paired pulses is less effective than its standalone impact, a prediction that is experimentally testable. Taken together, these findings lend further support for an attractor network model of time integration in perceptual decision making.

  15. Dynamical systems, attractors, and neural circuits [version 1; referees: 3 approved

    Directory of Open Access Journals (Sweden)

    Paul Miller

    2016-05-01

    Full Text Available Biology is the study of dynamical systems. Yet most of us working in biology have limited pedagogical training in the theory of dynamical systems, an unfortunate historical fact that can be remedied for future generations of life scientists. In my particular field of systems neuroscience, neural circuits are rife with nonlinearities at all levels of description, rendering simple methodologies and our own intuition unreliable. Therefore, our ideas are likely to be wrong unless informed by good models. These models should be based on the mathematical theories of dynamical systems since functioning neurons are dynamic—they change their membrane potential and firing rates with time. Thus, selecting the appropriate type of dynamical system upon which to base a model is an important first step in the modeling process. This step all too easily goes awry, in part because there are many frameworks to choose from, in part because the sparsely sampled data can be consistent with a variety of dynamical processes, and in part because each modeler has a preferred modeling approach that is difficult to move away from. This brief review summarizes some of the main dynamical paradigms that can arise in neural circuits, with comments on what they can achieve computationally and what signatures might reveal their presence within empirical data. I provide examples of different dynamical systems using simple circuits of two or three cells, emphasizing that any one connectivity pattern is compatible with multiple, diverse functions.

  16. A Circuit-Based Neural Network with Hybrid Learning of Backpropagation and Random Weight Change Algorithms

    Science.gov (United States)

    Yang, Changju; Kim, Hyongsuk; Adhikari, Shyam Prasad; Chua, Leon O.

    2016-01-01

    A hybrid learning method of a software-based backpropagation learning and a hardware-based RWC learning is proposed for the development of circuit-based neural networks. The backpropagation is known as one of the most efficient learning algorithms. A weak point is that its hardware implementation is extremely difficult. The RWC algorithm, which is very easy to implement with respect to its hardware circuits, takes too many iterations for learning. The proposed learning algorithm is a hybrid one of these two. The main learning is performed with a software version of the BP algorithm, firstly, and then, learned weights are transplanted on a hardware version of a neural circuit. At the time of the weight transplantation, a significant amount of output error would occur due to the characteristic difference between the software and the hardware. In the proposed method, such error is reduced via a complementary learning of the RWC algorithm, which is implemented in a simple hardware. The usefulness of the proposed hybrid learning system is verified via simulations upon several classical learning problems. PMID:28025566

  17. Cell biology in neuroscience: Architects in neural circuit design: glia control neuron numbers and connectivity.

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    Corty, Megan M; Freeman, Marc R

    2013-11-11

    Glia serve many important functions in the mature nervous system. In addition, these diverse cells have emerged as essential participants in nearly all aspects of neural development. Improved techniques to study neurons in the absence of glia, and to visualize and manipulate glia in vivo, have greatly expanded our knowledge of glial biology and neuron-glia interactions during development. Exciting studies in the last decade have begun to identify the cellular and molecular mechanisms by which glia exert control over neuronal circuit formation. Recent findings illustrate the importance of glial cells in shaping the nervous system by controlling the number and connectivity of neurons.

  18. Distinct neural circuits underlie assessment of a diversity of natural dangers by American crows

    Science.gov (United States)

    Cross, Donna J.; Marzluff, John M.; Palmquist, Ila; Minoshima, Satoshi; Shimizu, Toru; Miyaoka, Robert

    2013-01-01

    Social animals encountering natural dangers face decisions such as whether to freeze, flee or harass the threat. The American crow, Corvus brachyrhynchos, conspicuously mobs dangers. We used positron emission tomography to test the hypothesis that distinct neuronal substrates underlie the crow's consistent behavioural response to different dangers. We found that crows activated brain regions associated with attention and arousal (nucleus isthmo-opticus/locus coeruleus), and with motor response (arcopallium), as they fixed their gaze on a threat. However, despite this consistent behavioural and neural response, the sight of a person who previously captured the crow, a person holding a dead crow and a taxidermy-mounted hawk activated distinct forebrain regions (amygdala, hippocampus and portion of the caudal nidopallium, respectively). We suggest that aspects of mobbing behaviour are guided by unique neural circuits that respond to differences in mental processing—learning, memory formation and multisensory discrimination—required to appropriately nuance a risky behaviour to specific dangers. PMID:23825209

  19. Distinct neural circuits underlie assessment of a diversity of natural dangers by American crows.

    Science.gov (United States)

    Cross, Donna J; Marzluff, John M; Palmquist, Ila; Minoshima, Satoshi; Shimizu, Toru; Miyaoka, Robert

    2013-08-22

    Social animals encountering natural dangers face decisions such as whether to freeze, flee or harass the threat. The American crow, Corvus brachyrhynchos, conspicuously mobs dangers. We used positron emission tomography to test the hypothesis that distinct neuronal substrates underlie the crow's consistent behavioural response to different dangers. We found that crows activated brain regions associated with attention and arousal (nucleus isthmo-opticus/locus coeruleus), and with motor response (arcopallium), as they fixed their gaze on a threat. However, despite this consistent behavioural and neural response, the sight of a person who previously captured the crow, a person holding a dead crow and a taxidermy-mounted hawk activated distinct forebrain regions (amygdala, hippocampus and portion of the caudal nidopallium, respectively). We suggest that aspects of mobbing behaviour are guided by unique neural circuits that respond to differences in mental processing-learning, memory formation and multisensory discrimination-required to appropriately nuance a risky behaviour to specific dangers.

  20. Are deep neural networks really learning relevant features?

    DEFF Research Database (Denmark)

    Kereliuk, Corey; Sturm, Bob L.; Larsen, Jan

    In recent years deep neural networks (DNNs) have become a popular choice for audio content analysis. This may be attributed to various factors including advancements in training algorithms, computational power, and the potential for DNNs to implicitly learn a set of feature detectors. We have...... recently re-examined two works \\cite{sigtiaimproved}\\cite{hamel2010learning} that consider DNNs for the task of music genre recognition (MGR). These papers conclude that frame-level features learned by DNNs offer an improvement over traditional, hand-crafted features such as Mel-frequency cepstrum...... leads one to question the degree to which the learned frame-level features are actually useful for MGR. We make available a reproducible software package allowing other researchers to completely duplicate our figures and results....

  1. Are deep neural networks really learning relevant features?

    DEFF Research Database (Denmark)

    Kereliuk, Corey Mose; Larsen, Jan; Sturm, Bob L.

    In recent years deep neural networks (DNNs) have become a popular choice for audio content analysis. This may be attributed to various factors including advancements in training algorithms, computational power, and the potential for DNNs to implicitly learn a set of feature detectors. We have...... recently re-examined two works that consider DNNs for the task of music genre recognition (MGR). These papers conclude that frame-level features learned by DNNs offer an improvement over traditional, hand-crafted features such as Mel-frequency cepstrum coefficients (MFCCs). However, these conclusions were...... drawn based on training/testing using the GTZAN dataset, which is now known to contain several flaws including replicated observations and artists. We illustrate how considering these flaws dramatically changes the results, which leads one to question the degree to which the learned frame-level features...

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

    Science.gov (United States)

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

    2013-04-01

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

  3. Impaired activity-dependent neural circuit assembly and refinement in autism spectrum disorder genetic models

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    Caleb Andrew Doll

    2014-02-01

    Full Text Available Early-use activity during circuit-specific critical periods refines brain circuitry by the coupled processes of eliminating inappropriate synapses and strengthening maintained synapses. We theorize these activity-dependent developmental processes are specifically impaired in autism spectrum disorders (ASDs. ASD genetic models in both mouse and Drosophila have pioneered our insights into normal activity-dependent neural circuit assembly and consolidation, and how these developmental mechanisms go awry in specific genetic conditions. The monogenic Fragile X syndrome (FXS, a common cause of heritable ASD and intellectual disability, has been particularly well linked to defects in activity-dependent critical period processes. The Fragile X Mental Retardation Protein (FMRP is positively activity-regulated in expression and function, in turn regulates excitability and activity in a negative feedback loop, and appears to be required for the activity-dependent remodeling of synaptic connectivity during early-use critical periods. The Drosophila FXS model has been shown to functionally conserve the roles of human FMRP in synaptogenesis, and has been centrally important in generating our current mechanistic understanding of the FXS disease state. Recent advances in Drosophila optogenetics, transgenic calcium reporters, highly-targeted transgenic drivers for individually-identified neurons, and a vastly improved connectome of the brain are now being combined to provide unparalleled opportunities to both manipulate and monitor activity-dependent processes during critical period brain development in defined neural circuits. The field is now poised to exploit this new Drosophila transgenic toolbox for the systematic dissection of activity-dependent mechanisms in normal versus ASD brain development, particularly utilizing the well-established Drosophila FXS disease model.

  4. The neural circuits and sensory channels mediating harsh touch sensation in Caenorhabditis elegans.

    Science.gov (United States)

    Li, Wei; Kang, Lijun; Piggott, Beverly J; Feng, Zhaoyang; Xu, X Z Shawn

    2011-01-01

    Most animals can distinguish two distinct types of touch stimuli: gentle (innocuous) and harsh (noxious/painful) touch, however, the underlying mechanisms are not well understood. Caenorhabditis elegans is a useful model for the study of gentle touch sensation. However, little is known about harsh touch sensation in this organism. Here we characterize harsh touch sensation in C. elegans. We show that C. elegans exhibits differential behavioural responses to harsh touch and gentle touch. Laser ablations identify distinct sets of sensory neurons and interneurons required for harsh touch sensation at different body segments. Optogenetic stimulation of the circuitry can drive behaviour. Patch-clamp recordings reveal that TRP family and amiloride-sensitive Na(+) channels mediate touch-evoked currents in different sensory neurons. Our work identifies the neural circuits and characterizes the sensory channels mediating harsh touch sensation in C. elegans, establishing it as a genetic model for studying this sensory modality.

  5. Cross-talk between the epigenome and neural circuits in drug addiction.

    Science.gov (United States)

    Mews, Philipp; Calipari, Erin S

    2017-01-01

    Drug addiction is a behavioral disorder characterized by dysregulated learning about drugs and associated cues that result in compulsive drug seeking and relapse. Learning about drug rewards and predictive cues is a complex process controlled by a computational network of neural connections interacting with transcriptional and molecular mechanisms within each cell to precisely guide behavior. The interplay between rapid, temporally specific neuronal activation, and longer-term changes in transcription is of critical importance in the expression of appropriate, or in the case of drug addiction, inappropriate behaviors. Thus, these factors and their interactions must be considered together, especially in the context of treatment. Understanding the complex interplay between epigenetic gene regulation and circuit connectivity will allow us to formulate novel therapies to normalize maladaptive reward behaviors, with a goal of modulating addictive behaviors, while leaving natural reward-associated behavior unaffected. © 2017 Elsevier B.V. All rights reserved.

  6. Multiple conserved cell adhesion protein interactions mediate neural wiring of a sensory circuit in C. elegans.

    Science.gov (United States)

    Kim, Byunghyuk; Emmons, Scott W

    2017-09-13

    Nervous system function relies on precise synaptic connections. A number of widely-conserved cell adhesion proteins are implicated in cell recognition between synaptic partners, but how these proteins act as a group to specify a complex neural network is poorly understood. Taking advantage of known connectivity in C. elegans, we identified and studied cell adhesion genes expressed in three interacting neurons in the mating circuits of the adult male. Two interacting pairs of cell surface proteins independently promote fasciculation between sensory neuron HOA and its postsynaptic target interneuron AVG: BAM-2/neurexin-related in HOA binds to CASY-1/calsyntenin in AVG; SAX-7/L1CAM in sensory neuron PHC binds to RIG-6/contactin in AVG. A third, basal pathway results in considerable HOA-AVG fasciculation and synapse formation in the absence of the other two. The features of this multiplexed mechanism help to explain how complex connectivity is encoded and robustly established during nervous system development.

  7. Application of viral vectors to the study of neural connectivities and neural circuits in the marmoset brain.

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    Watakabe, Akiya; Sadakane, Osamu; Hata, Katsusuke; Ohtsuka, Masanari; Takaji, Masafumi; Yamamori, Tetsuo

    2017-03-01

    It is important to study the neural connectivities and functions in primates. For this purpose, it is critical to be able to transfer genes to certain neurons in the primate brain so that we can image the neuronal signals and analyze the function of the transferred gene. Toward this end, our team has been developing gene transfer systems using viral vectors. In this review, we summarize our current achievements as follows. 1) We compared the features of gene transfer using five different AAV serotypes in combination with three different promoters, namely, CMV, mouse CaMKII (CaMKII), and human synapsin 1 (hSyn1), in the marmoset cortex with those in the mouse and macaque cortices. 2) We used target-specific double-infection techniques in combination with TET-ON and TET-OFF using lentiviral retrograde vectors for enhanced visualization of neural connections. 3) We used an AAV-mediated gene transfer method to study the transcriptional control for amplifying fluorescent signals using the TET/TRE system in the primate neocortex. We also established systems for shRNA mediated gene targeting in a neocortical region where a gene is significantly expressed and for expressing the gene using the CMV promoter for an unexpressed neocortical area in the primate cortex using AAV vectors to understand the regulation of downstream genes. Our findings have demonstrated the feasibility of using viral vector mediated gene transfer systems for the study of primate cortical circuits using the marmoset as an animal model. © 2016 Wiley Periodicals, Inc. Develop Neurobiol 77: 354-372, 2017. © 2016 The Authors. Developmental Neurobiology Published by Wiley Periodicals, Inc.

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

    Science.gov (United States)

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

    2017-03-01

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

  9. Equivalent Circuit Parameters Estimation for PEM Fuel Cell Using RBF Neural Network and Enhanced Particle Swarm Optimization

    Directory of Open Access Journals (Sweden)

    Wen-Yeau Chang

    2013-01-01

    Full Text Available This paper proposes an equivalent circuit parameters measurement and estimation method for proton exchange membrane fuel cell (PEMFC. The parameters measurement method is based on current loading technique; in current loading test a no load PEMFC is suddenly turned on to obtain the waveform of the transient terminal voltage. After the equivalent circuit parameters were measured, a hybrid method that combines a radial basis function (RBF neural network and enhanced particle swarm optimization (EPSO algorithm is further employed for the equivalent circuit parameters estimation. The RBF neural network is adopted such that the estimation problem can be effectively processed when the considered data have different features and ranges. In the hybrid method, EPSO algorithm is used to tune the connection weights, the centers, and the widths of RBF neural network. Together with the current loading technique, the proposed hybrid estimation method can effectively estimate the equivalent circuit parameters of PEMFC. To verify the proposed approach, experiments were conducted to demonstrate the equivalent circuit parameters estimation of PEMFC. A practical PEMFC stack was purposely created to produce the common current loading activities of PEMFC for the experiments. The practical results of the proposed method were studied in accordance with the conditions for different loading conditions.

  10. Fluorescence-based monitoring of in vivo neural activity using a circuit-tracing pseudorabies virus.

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    Andrea E Granstedt

    Full Text Available The study of coordinated activity in neuronal circuits has been challenging without a method to simultaneously report activity and connectivity. Here we present the first use of pseudorabies virus (PRV, which spreads through synaptically connected neurons, to express a fluorescent calcium indicator protein and monitor neuronal activity in a living animal. Fluorescence signals were proportional to action potential number and could reliably detect single action potentials in vitro. With two-photon imaging in vivo, we observed both spontaneous and stimulated activity in neurons of infected murine peripheral autonomic submandibular ganglia (SMG. We optically recorded the SMG response in the salivary circuit to direct electrical stimulation of the presynaptic axons and to physiologically relevant sensory stimulation of the oral cavity. During a time window of 48 hours after inoculation, few spontaneous transients occurred. By 72 hours, we identified more frequent and prolonged spontaneous calcium transients, suggestive of neuronal or tissue responses to infection that influence calcium signaling. Our work establishes in vivo investigation of physiological neuronal circuit activity and subsequent effects of infection with single cell resolution.

  11. Estimating neural background input with controlled and fast perturbations: A bandwidth comparison between inhibitory opsins and neural circuits

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    David Eriksson

    2016-08-01

    Full Text Available To test the importance of a certain cell type or brain area it is common to make a lack of function experiment in which the neuronal population of interest is inhibited. Here we review physiological and methodological constraints for making controlled perturbations using the corticothalamic circuit as an example. The brain with its many types of cells and rich interconnectivity offers many paths through which a perturbation can spread within a short time. To understand the side effects of the perturbation one should record from those paths. We find that ephaptic effects, gap-junctions, and fast chemical synapses are so fast that they can react to the perturbation during the few milliseconds it takes for an opsin to change the membrane potential. The slow chemical synapses, astrocytes, extracellular ions and vascular signals, will continue to give their physiological input for around 20 milliseconds before they also react to the perturbation. Although we show that some pathways can react within milliseconds the strength/speed reported in this review should be seen as an upper bound since we have omitted how polysynaptic signals are attenuated. Thus the number of additional recordings that has to be made to control for the perturbation side effects is expected to be fewer than proposed here. To summarize, the reviewed literature not only suggests that it is possible to make controlled lack of function experiments, but, it also suggests that such a lack of function experiment can be used to measure the context of local neural computations.

  12. Analgesic Neural Circuits Are Activated by Electroacupuncture at Two Sets of Acupoints

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    Man-Li Hu

    2016-01-01

    Full Text Available To investigate analgesic neural circuits activated by electroacupuncture (EA at different sets of acupoints in the brain, goats were stimulated by EA at set of Baihui-Santai acupoints or set of Housanli acupoints for 30 min. The pain threshold was measured using the potassium iontophoresis method. The levels of c-Fos were determined with Streptavidin-Biotin Complex immunohistochemistry. The results showed pain threshold induced by EA at set of Baihui-Santai acupoints was 44.74%±4.56% higher than that by EA at set of Housanli acupoints (32.64%±5.04%. Compared with blank control, EA at two sets of acupoints increased c-Fos expression in the medial septal nucleus (MSN, the arcuate nucleus (ARC, the nucleus amygdala basalis (AB, the lateral habenula nucleus (HL, the ventrolateral periaqueductal grey (vlPAG, the locus coeruleus (LC, the nucleus raphe magnus (NRM, the pituitary gland, and spinal cord dorsal horn (SDH. Compared with EA at set of Housanli points, EA at set of Baihui-Santai points induced increased c-Fos expression in AB but decrease in MSN, the paraventricular nucleus of the hypothalamus, HL, and SDH. It suggests that ARC-PAG-NRM/LC-SDH and the hypothalamus-pituitary may be the common activated neural pathways taking part in EA-induced analgesia at the two sets of acupoints.

  13. Information processing in micro and meso-scale neural circuits during normal and disease states

    Science.gov (United States)

    Luongo, Francisco

    Neural computation can occur at multiple spatial and temporal timescales. The sum total of all of these processes is to guide optimal behaviors within the context of the constraints imposed by the physical world. How the circuits of the brain achieves this goal represents a central question in systems neuroscience. Here I explore the many ways in which the circuits of the brain can process information at both the micro and meso scale. Understanding the way information is represented and processed in the brain could shed light on the neuropathology underlying complex neuropsychiatric diseases such as autism and schizophrenia. Chapter 2 establishes an experimental paradigm for assaying patterns of microcircuit activity and examines the role of dopaminergic modulation on prefrontal microcircuits. We find that dopamine type 2 (D2) receptor activation results in an increase in spontaneous activity while dopamine type 1 (D1) activation does not. Chapter 3 of this dissertation presents a study that illustrates how cholingergic activation normally produces what has been suggested as a neural substrate of attention; pairwise decorrelation in microcircuit activity. This study also shows that in two etiologicall distinct mouse models of autism, FMR1 knockout mice and Valproic Acid exposed mice, this ability to decorrelate in the presence of cholinergic activation is lost. This represents a putative microcircuit level biomarker of autism. Chapter 4 examines the structure/function relationship within the prefrontal microcircuit. Spontaneous activity in prefrontal microcircuits is shown to be organized according to a small world architecture. Interestingly, this architecture is important for one concrete function of neuronal microcircuits; the ability to produce temporally stereotyped patterns of activation. In the final chapter, we identify subnetworks in chronic intracranial electrocorticographic (ECoG) recordings using pairwise electrode coherence and dimensionality reduction

  14. Antagonistic Serotonergic and Octopaminergic Neural Circuits Mediate Food-Dependent Locomotory Behavior in Caenorhabditis elegans.

    Science.gov (United States)

    Churgin, Matthew A; McCloskey, Richard J; Peters, Emily; Fang-Yen, Christopher

    2017-08-16

    Biogenic amines are conserved signaling molecules that link food cues to behavior and metabolism in a wide variety of organisms. In the nematode Caenorhabditis elegans, the biogenic amines serotonin (5-HT) and octopamine regulate a number of food-related behaviors. Using a novel method for long-term quantitative behavioral imaging, we show that 5-HT and octopamine jointly influence locomotor activity and quiescence in feeding and fasting hermaphrodites, and we define the neural circuits through which this modulation occurs. We show that 5-HT produced by the ADF neurons acts via the SER-5 receptor in muscles and neurons to suppress quiescent behavior and promote roaming in fasting worms, whereas 5-HT produced by the NSM neurons acts on the MOD-1 receptor in AIY neurons to promote low-amplitude locomotor behavior characteristic of well fed animals. Octopamine, produced by the RIC neurons, acts via SER-3 and SER-6 receptors in SIA neurons to promote roaming behaviors characteristic of fasting animals. We find that 5-HT signaling is required for animals to assume food-appropriate behavior, whereas octopamine signaling is required for animals to assume fasting-appropriate behavior. The requirement for both neurotransmitters in both the feeding and fasting states enables increased behavioral adaptability. Our results define the molecular and neural pathways through which parallel biogenic amine signaling tunes behavior appropriately to nutrient conditions.SIGNIFICANCE STATEMENT Animals adjust behavior in response to environmental changes, such as fluctuations in food abundance, to maximize survival and reproduction. Biogenic amines, such as like serotonin, are conserved neurotransmitters that regulate behavior and metabolism in relation to energy status. Disruptions of biogenic amine signaling contribute to human neurological diseases of mood, appetite, and movement. In this study, we investigated the roles of the biogenic amines serotonin and octopamine in regulating

  15. NEURAL CORRELATES FOR APATHY: FRONTAL - PREFRONTAL AND PARIETAL CORTICAL - SUBCORTICAL CIRCUITS

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    Rita Moretti

    2016-12-01

    Full Text Available Apathy is an uncertain nosographical entity, which includes reduced motivation, abulia, decreased empathy, and lack of emotional invovlement; it is an important and heavy-burden clinical condition which strongly impacts in every day life events, affects the common daily living abilities, reduced the inner goal directed behavior, and gives the heaviest burden on caregivers. Is a quite common comorbidity of many neurological disease, However, there is no definite consensus on the role of apathy in clinical practice, no definite data on anatomical circuits involved in its development, and no definite instrument to detect it at bedside. As a general observation, the occurrence of apathy is connected to damage of prefrontal cortex (PFC and basal ganglia; emotional affective apathy may be related to the orbitomedial PFC and ventral striatum; cognitive apathy may be associated with dysfunction of lateral PFC and dorsal caudate nuclei; deficit of autoactivation may be due to bilateral lesions of the internal portion of globus pallidus, bilateral paramedian thalamic lesions, or the dorsomedial portion of PFC. On the other hand, apathy severity has been connected to neurofibrillary tangles density in the anterior cingulate gyrus and to grey matter atrophy in the anterior cingulate (ACC and in the left medial frontal cortex, confirmed by functional imaging studies. These neural networks are linked to projects, judjing and planning, execution and selection common actions, and through the basolateral amygdala and nucleus accumbens projects to the frontostriatal and to the dorsolateral prefrontal cortex. Therefore, an alteration of these circuitry caused a lack of insight, a reduction of decision-making strategies and a reduced speedness in action decsion, major resposnible for apathy. Emergent role concerns also the parietal cortex, with its direct action motivation control.We will discuss the importance of these circuits in different pathologies

  16. Neural Correlates for Apathy: Frontal-Prefrontal and Parietal Cortical- Subcortical Circuits

    Science.gov (United States)

    Moretti, Rita; Signori, Riccardo

    2016-01-01

    Apathy is an uncertain nosographical entity, which includes reduced motivation, abulia, decreased empathy, and lack of emotional involvement; it is an important and heavy-burden clinical condition which strongly impacts in everyday life events, affects the common daily living abilities, reduced the inner goal directed behavior, and gives the heaviest burden on caregivers. Is a quite common comorbidity of many neurological disease, However, there is no definite consensus on the role of apathy in clinical practice, no definite data on anatomical circuits involved in its development, and no definite instrument to detect it at bedside. As a general observation, the occurrence of apathy is connected to damage of prefrontal cortex (PFC) and basal ganglia; “emotional affective” apathy may be related to the orbitomedial PFC and ventral striatum; “cognitive apathy” may be associated with dysfunction of lateral PFC and dorsal caudate nuclei; deficit of “autoactivation” may be due to bilateral lesions of the internal portion of globus pallidus, bilateral paramedian thalamic lesions, or the dorsomedial portion of PFC. On the other hand, apathy severity has been connected to neurofibrillary tangles density in the anterior cingulate gyrus and to gray matter atrophy in the anterior cingulate (ACC) and in the left medial frontal cortex, confirmed by functional imaging studies. These neural networks are linked to projects, judjing and planning, execution and selection common actions, and through the basolateral amygdala and nucleus accumbens projects to the frontostriatal and to the dorsolateral prefrontal cortex. Therefore, an alteration of these circuitry caused a lack of insight, a reduction of decision-making strategies, and a reduced speedness in action decision, major responsible for apathy. Emergent role concerns also the parietal cortex, with its direct action motivation control. We will discuss the importance of these circuits in different pathologies

  17. Navigating Monogamy: Nonapeptide Sensitivity in a Memory Neural Circuit May Shape Social Behavior and Mating Decisions

    Directory of Open Access Journals (Sweden)

    Alexander G. Ophir

    2017-07-01

    Full Text Available The role of memory in mating systems is often neglected despite the fact that most mating systems are defined in part by how animals use space. Monogamy, for example, is usually characterized by affiliative (e.g., pairbonding and defensive (e.g., mate guarding behaviors, but a high degree of spatial overlap in home range use is the easiest defining feature of monogamous animals in the wild. The nonapeptides vasopressin and oxytocin have been the focus of much attention for their importance in modulating social behavior, however this work has largely overshadowed their roles in learning and memory. To date, the understanding of memory systems and mechanisms governing social behavior have progressed relatively independently. Bridging these two areas will provide a deeper appreciation for understanding behavior, and in particular the mechanisms that mediate reproductive decision-making. Here, I argue that the ability to mate effectively as monogamous individuals is linked to the ability to track conspecifics in space. I discuss the connectivity across some well-known social and spatial memory nuclei, and propose that the nonapeptide receptors within these structures form a putative “socio-spatial memory neural circuit.” This purported circuit may function to integrate social and spatial information to shape mating decisions in a context-dependent fashion. The lateral septum and/or the nucleus accumbens, and neuromodulation therein, may act as an intermediary to relate socio-spatial information with social behavior. Identifying mechanisms responsible for relating information about the social world with mechanisms mediating mating tactics is crucial to fully appreciate the suite of factors driving reproductive decisions and social decision-making.

  18. The neural circuits recruited for the production of signs and fingerspelled words.

    Science.gov (United States)

    Emmorey, Karen; Mehta, Sonya; McCullough, Stephen; Grabowski, Thomas J

    2016-09-01

    Signing differs from typical non-linguistic hand actions because movements are not visually guided, finger movements are complex (particularly for fingerspelling), and signs are not produced as holistic gestures. We used positron emission tomography to investigate the neural circuits involved in the production of American Sign Language (ASL). Different types of signs (one-handed (articulated in neutral space), two-handed (neutral space), and one-handed body-anchored signs) were elicited by asking deaf native signers to produce sign translations of English words. Participants also fingerspelled (one-handed) printed English words. For the baseline task, participants indicated whether a word contained a descending letter. Fingerspelling engaged ipsilateral motor cortex and cerebellar cortex in contrast to both one-handed signs and the descender baseline task, which may reflect greater timing demands and complexity of handshape sequences required for fingerspelling. Greater activation in the visual word form area was also observed for fingerspelled words compared to one-handed signs. Body-anchored signs engaged bilateral superior parietal cortex to a greater extent than the descender baseline task and neutral space signs, reflecting the motor control and proprioceptive monitoring required to direct the hand toward a specific location on the body. Less activation in parts of the motor circuit was observed for two-handed signs compared to one-handed signs, possibly because, for half of the signs, handshape and movement goals were spread across the two limbs. Finally, the conjunction analysis comparing each sign type with the descender baseline task revealed common activation in the supramarginal gyrus bilaterally, which we interpret as reflecting phonological retrieval and encoding processes. Copyright © 2016 Elsevier Inc. All rights reserved.

  19. Navigating Monogamy: Nonapeptide Sensitivity in a Memory Neural Circuit May Shape Social Behavior and Mating Decisions.

    Science.gov (United States)

    Ophir, Alexander G

    2017-01-01

    The role of memory in mating systems is often neglected despite the fact that most mating systems are defined in part by how animals use space. Monogamy, for example, is usually characterized by affiliative (e.g., pairbonding) and defensive (e.g., mate guarding) behaviors, but a high degree of spatial overlap in home range use is the easiest defining feature of monogamous animals in the wild. The nonapeptides vasopressin and oxytocin have been the focus of much attention for their importance in modulating social behavior, however this work has largely overshadowed their roles in learning and memory. To date, the understanding of memory systems and mechanisms governing social behavior have progressed relatively independently. Bridging these two areas will provide a deeper appreciation for understanding behavior, and in particular the mechanisms that mediate reproductive decision-making. Here, I argue that the ability to mate effectively as monogamous individuals is linked to the ability to track conspecifics in space. I discuss the connectivity across some well-known social and spatial memory nuclei, and propose that the nonapeptide receptors within these structures form a putative "socio-spatial memory neural circuit." This purported circuit may function to integrate social and spatial information to shape mating decisions in a context-dependent fashion. The lateral septum and/or the nucleus accumbens, and neuromodulation therein, may act as an intermediary to relate socio-spatial information with social behavior. Identifying mechanisms responsible for relating information about the social world with mechanisms mediating mating tactics is crucial to fully appreciate the suite of factors driving reproductive decisions and social decision-making.

  20. Structural basis for cholinergic regulation of neural circuits in the mouse olfactory bulb.

    Science.gov (United States)

    Hamamoto, Masakazu; Kiyokage, Emi; Sohn, Jaerin; Hioki, Hiroyuki; Harada, Tamotsu; Toida, Kazunori

    2017-02-15

    Odor information is regulated by olfactory inputs, bulbar interneurons, and centrifugal inputs in the olfactory bulb (OB). Cholinergic neurons projecting from the nucleus of the horizontal limb of the diagonal band of Broca and the magnocellular preoptic nucleus are one of the primary centrifugal inputs to the OB. In this study, we focused on cholinergic regulation of the OB and analyzed neural morphology with a particular emphasis on the projection pathways of cholinergic neurons. Single-cell imaging of a specific neuron within dense fibers is critical to evaluate the structure and function of the neural circuits. We labeled cholinergic neurons by infection with virus vector and then reconstructed them three-dimensionally. We also examined the ultramicrostructure of synapses by electron microscopy tomography. To further clarify the function of cholinergic neurons, we performed confocal laser scanning microscopy to investigate whether other neurotransmitters are present within cholinergic axons in the OB. Our results showed the first visualization of complete cholinergic neurons, including axons projecting to the OB, and also revealed frequent axonal branching within the OB where it innervated multiple glomeruli in different areas. Furthermore, electron tomography demonstrated that cholinergic axons formed asymmetrical synapses with a morphological variety of thicknesses of the postsynaptic density. Although we have not yet detected the presence of other neurotransmitters, the range of synaptic morphology suggests multiple modes of transmission. The present study elucidates the ways that cholinergic neurons could contribute to the elaborate mechanisms involved in olfactory processing in the OB. J. Comp. Neurol. 525:574-591, 2017. © 2016 Wiley Periodicals, Inc. © 2016 Wiley Periodicals, Inc.

  1. Uncertainty-Dependent Extinction of Fear Memory in an Amygdala-mPFC Neural Circuit Model

    Science.gov (United States)

    Li, Yuzhe; Nakae, Ken; Ishii, Shin; Naoki, Honda

    2016-01-01

    Uncertainty of fear conditioning is crucial for the acquisition and extinction of fear memory. Fear memory acquired through partial pairings of a conditioned stimulus (CS) and an unconditioned stimulus (US) is more resistant to extinction than that acquired through full pairings; this effect is known as the partial reinforcement extinction effect (PREE). Although the PREE has been explained by psychological theories, the neural mechanisms underlying the PREE remain largely unclear. Here, we developed a neural circuit model based on three distinct types of neurons (fear, persistent and extinction neurons) in the amygdala and medial prefrontal cortex (mPFC). In the model, the fear, persistent and extinction neurons encode predictions of net severity, of unconditioned stimulus (US) intensity, and of net safety, respectively. Our simulation successfully reproduces the PREE. We revealed that unpredictability of the US during extinction was represented by the combined responses of the three types of neurons, which are critical for the PREE. In addition, we extended the model to include amygdala subregions and the mPFC to address a recent finding that the ventral mPFC (vmPFC) is required for consolidating extinction memory but not for memory retrieval. Furthermore, model simulations led us to propose a novel procedure to enhance extinction learning through re-conditioning with a stronger US; strengthened fear memory up-regulates the extinction neuron, which, in turn, further inhibits the fear neuron during re-extinction. Thus, our models increased the understanding of the functional roles of the amygdala and vmPFC in the processing of uncertainty in fear conditioning and extinction. PMID:27617747

  2. Acute genetic manipulation of neuronal activity for the functional dissection of neural circuits-a dream come true for the pioneers of behavioral genetics.

    Science.gov (United States)

    Yoshihara, Moto; Ito, Kei

    2012-03-01

    Abstract: This review summarizes technical development of the functional manipulation of specific neural circuits through genetic techniques in Drosophila. Long after pioneers' efforts for the genetic dissection of behavior using this organism as a model, analyses with acute activation of specific neural circuits have finally become feasible using transgenic Drosophila that expresses light-, heat-, or cold-activatable cation channels by xxx/upstream activation sequence (Gal4/UAS)-based induction system. This methodology opened a new avenue to dissect functions of neural circuits to make dreams of the pioneers into reality.

  3. Hybrid Spintronic-CMOS Spiking Neural Network with On-Chip Learning: Devices, Circuits, and Systems

    Science.gov (United States)

    Sengupta, Abhronil; Banerjee, Aparajita; Roy, Kaushik

    2016-12-01

    Over the past decade, spiking neural networks (SNNs) have emerged as one of the popular architectures to emulate the brain. In SNNs, information is temporally encoded and communication between neurons is accomplished by means of spikes. In such networks, spike-timing-dependent plasticity mechanisms require the online programing of synapses based on the temporal information of spikes transmitted by spiking neurons. In this work, we propose a spintronic synapse with decoupled spike-transmission and programing-current paths. The spintronic synapse consists of a ferromagnet-heavy-metal heterostructure where the programing current through the heavy metal generates spin-orbit torque to modulate the device conductance. Low programing energy and fast programing times demonstrate the efficacy of the proposed device as a nanoelectronic synapse. We perform a simulation study based on an experimentally benchmarked device-simulation framework to demonstrate the interfacing of such spintronic synapses with CMOS neurons and learning circuits operating in the transistor subthreshold region to form a network of spiking neurons that can be utilized for pattern-recognition problems.

  4. Impact of adolescent social experiences on behavior and neural circuits implicated in mental illnesses.

    Science.gov (United States)

    Burke, Andrew R; McCormick, Cheryl M; Pellis, Sergio M; Lukkes, Jodi L

    2017-05-01

    Negative social experiences during adolescence are central features for several stress-related mental illnesses. Social play fighting behavior in rats peaks during early adolescence and is essential for the final maturation of brain and behavior. Manipulation of the rat adolescent social experience alters many neurobehavioral measurements implicated in anxiety, depression, and substance abuse. In this review, we will highlight the importance of social play and the use of three separate social stress models (isolation-rearing, social defeat, and social instability stress) to disrupt the acquisition of this adaptive behavior. Social stress during adolescence leads to the development of anxiety and depressive behavior as well as escalated drug use in adulthood. Furthermore, sex- and age-dependent effects on the hormonal stress response following adolescent social stress are also observed. Finally, manipulation of the social experience during adolescence alters stress-related neural circuits and monoaminergic systems. Overall, positive social experiences among age-matched conspecifics during rat adolescence are critical for healthy neurobehavioral maturation. Copyright © 2017 Elsevier Ltd. All rights reserved.

  5. Segregated and overlapping neural circuits exist for the production of static and dynamic precision grip force

    Science.gov (United States)

    Neely, Kristina A.; Coombes, Stephen A.; Planetta, Peggy J.; Vaillancourt, David E.

    2011-01-01

    A central topic in sensorimotor neuroscience is the static-dynamic dichotomy that exists throughout the nervous system. Previous work examining motor unit synchronization reports that the activation strategy and timing of motor units differ for static and dynamic tasks. However, it remains unclear whether segregated or overlapping blood-oxygen-level-dependent (BOLD) activity exists in the brain for static and dynamic motor control. This study compared the neural circuits associated with the production of static force to those associated with the production of dynamic force pulses. To that end, healthy young adults (n = 17) completed static and dynamic precision grip force tasks during functional magnetic resonance imaging (fMRI). Both tasks activated core regions within the visuomotor network, including primary and sensory motor cortices, premotor cortices, multiple visual areas, putamen, and cerebellum. Static force was associated with unique activity in a right-lateralized cortical network including inferior parietal lobe, ventral premotor cortex, and dorsolateral prefrontal cortex. In contrast, dynamic force was associated with unique activity in left-lateralized and midline cortical regions, including supplementary motor area, superior parietal lobe, fusiform gyrus, and visual area V3. These findings provide the first neuroimaging evidence supporting a lateralized pattern of brain activity for the production of static and dynamic precision grip force. PMID:22109998

  6. The primary visual cortex in the neural circuit for visual orienting

    Science.gov (United States)

    Zhaoping, Li

    The primary visual cortex (V1) is traditionally viewed as remote from influencing brain's motor outputs. However, V1 provides the most abundant cortical inputs directly to the sensory layers of superior colliculus (SC), a midbrain structure to command visual orienting such as shifting gaze and turning heads. I will show physiological, anatomical, and behavioral data suggesting that V1 transforms visual input into a saliency map to guide a class of visual orienting that is reflexive or involuntary. In particular, V1 receives a retinotopic map of visual features, such as orientation, color, and motion direction of local visual inputs; local interactions between V1 neurons perform a local-to-global computation to arrive at a saliency map that highlights conspicuous visual locations by higher V1 responses. The conspicuous location are usually, but not always, where visual input statistics changes. The population V1 outputs to SC, which is also retinotopic, enables SC to locate, by lateral inhibition between SC neurons, the most salient location as the saccadic target. Experimental tests of this hypothesis will be shown. Variations of the neural circuit for visual orienting across animal species, with more or less V1 involvement, will be discussed. Supported by the Gatsby Charitable Foundation.

  7. The Neuropsychiatry of Hyperkinetic Movement Disorders: Insights from Neuroimaging into the Neural Circuit Bases of Dysfunction

    Directory of Open Access Journals (Sweden)

    Bradleigh D. Hayhow

    2013-09-01

    Full Text Available Background: Movement disorders, particularly those associated with basal ganglia disease, have a high rate of comorbid neuropsychiatric illness.Methods: We consider the pathophysiological basis of the comorbidity between movement disorders and neuropsychiatric illness by 1 reviewing the epidemiology of neuropsychiatric illness in a range of hyperkinetic movement disorders, and 2 correlating findings to evidence from studies that have utilized modern neuroimaging techniques to investigate these disorders. In addition to diseases classically associated with basal ganglia pathology, such as Huntington disease, Wilson disease, the neuroacanthocytoses, and diseases of brain iron accumulation, we include diseases associated with pathology of subcortical white matter tracts, brain stem nuclei, and the cerebellum, such as metachromatic leukodystrophy, dentatorubropallidoluysian atrophy, and the spinocerebellar ataxias.Conclusions: Neuropsychiatric symptoms are integral to a thorough phenomenological account of hyperkinetic movement disorders. Drawing on modern theories of cortico-subcortical circuits, we argue that these disorders can be conceptualized as disorders of complex subcortical networks with distinct functional architectures. Damage to any component of these complex information-processing networks can have variable and often profound consequences for the function of more remote neural structures, creating a diverse but nonetheless rational pattern of clinical symptomatology.

  8. Functional and neurochemical interactions within the amygdala-medial prefrontal cortex circuit and their relevance to emotional processing.

    Science.gov (United States)

    Delli Pizzi, Stefano; Chiacchiaretta, Piero; Mantini, Dante; Bubbico, Giovanna; Ferretti, Antonio; Edden, Richard A; Di Giulio, Camillo; Onofrj, Marco; Bonanni, Laura

    2017-04-01

    The amygdala-medial prefrontal cortex (mPFC) circuit plays a key role in emotional processing. GABA-ergic inhibition within the mPFC has been suggested to play a role in the shaping of amygdala activity. However, the functional and neurochemical interactions within the amygdala-mPFC circuits and their relevance to emotional processing remain unclear. To investigate this circuit, we obtained resting-state functional magnetic resonance imaging (rs-fMRI) and proton MR spectroscopy in 21 healthy subjects to assess the potential relationship between GABA levels within mPFC and the amygdala-mPFC functional connectivity. Trait anxiety was assessed using the State-Trait Anxiety Inventory (STAI-Y2). Partial correlations were used to measure the relationships among the functional connectivity outcomes, mPFC GABA levels and STAI-Y2 scores. Age, educational level and amount of the gray and white matters within 1 H-MRS volume of interest were included as nuisance variables. The rs-fMRI signals of the amygdala and the vmPFC were significantly anti-correlated. This negative functional coupling between the two regions was inversely correlated with the GABA+/tCr level within the mPFC and the STAI-Y2 scores. We suggest a close relationship between mPFC GABA levels and functional interactions within the amygdala-vmPFC circuit, providing new insights in the physiology of emotion.

  9. Geometric structure of chemistry-relevant graphs zigzags and central circuits

    CERN Document Server

    Deza, Michel-Marie; Shtogrin, Mikhail Ivanovitch

    2015-01-01

    The central theme of the present book is zigzags and central-circuits of three- or four-regular plane graphs, which allow a double covering or covering of the edgeset to be obtained. The book presents zigzag and central circuit structures of geometric fullerenes and several other classes of graph of interest in the fields of chemistry and mathematics. It also discusses the symmetries, parameterization and the Goldberg–Coxeter construction for those graphs. It is the first book on this subject, presenting full structure theory of such graphs. While many previous publications only addressed particular questions about selected graphs, this book is based on numerous computations and presents extensive data (tables and figures), as well as algorithmic and computational information. It will be of interest to researchers and students of discrete geometry, mathematical chemistry and combinatorics, as well as to lay mathematicians.

  10. Modulatory effects of modafinil on neural circuits regulating emotion and cognition.

    Science.gov (United States)

    Rasetti, Roberta; Mattay, Venkata S; Stankevich, Beth; Skjei, Kelsey; Blasi, Giuseppe; Sambataro, Fabio; Arrillaga-Romany, Isabel C; Goldberg, Terry E; Callicott, Joseph H; Apud, José A; Weinberger, Daniel R

    2010-09-01

    Modafinil differs from other arousal-enhancing agents in chemical structure, neurochemical profile, and behavioral effects. Most functional neuroimaging studies to date examined the effect of modafinil only on information processing underlying executive cognition, but cognitive enhancers in general have been shown to have pronounced effects on emotional behavior, too. We examined the effect of modafinil on neural circuits underlying affective processing and cognitive functions. Healthy volunteers were enrolled in this double-blinded placebo-controlled trial (100 mg/day for 7 days). They underwent BOLD fMRI while performing an emotion information-processing task that activates the amygdala and two prefrontally dependent cognitive tasks-a working memory (WM) task and a variable attentional control (VAC) task. A clinical assessment that included measurement of blood pressure, heart rate, the Hamilton anxiety scale, and the profile of mood state (POMS) questionnaire was also performed on each test day. BOLD fMRI revealed significantly decreased amygdala reactivity to fearful stimuli on modafinil compared with the placebo condition. During executive cognition tasks, a WM task and a VAC task, modafinil reduced BOLD signal in the prefrontal cortex and anterior cingulate. Although not statistically significant, there were trends for reduced anxiety, for decreased fatigue-inertia and increased vigor-activity, as well as decreased anger-hostility on modafinil. Modafinil in low doses has a unique physiologic profile compared with stimulant drugs: it enhances the efficiency of prefrontal cortical cognitive information processing, while dampening reactivity to threatening stimuli in the amygdala, a brain region implicated in anxiety.

  11. Modulatory Effects of Modafinil on Neural Circuits Regulating Emotion and Cognition

    Science.gov (United States)

    Rasetti, Roberta; Mattay, Venkata S; Stankevich, Beth; Skjei, Kelsey; Blasi, Giuseppe; Sambataro, Fabio; Arrillaga-Romany, Isabel C; Goldberg, Terry E; Callicott, Joseph H; Apud, José A; Weinberger, Daniel R

    2010-01-01

    Modafinil differs from other arousal-enhancing agents in chemical structure, neurochemical profile, and behavioral effects. Most functional neuroimaging studies to date examined the effect of modafinil only on information processing underlying executive cognition, but cognitive enhancers in general have been shown to have pronounced effects on emotional behavior, too. We examined the effect of modafinil on neural circuits underlying affective processing and cognitive functions. Healthy volunteers were enrolled in this double-blinded placebo-controlled trial (100 mg/day for 7 days). They underwent BOLD fMRI while performing an emotion information-processing task that activates the amygdala and two prefrontally dependent cognitive tasks—a working memory (WM) task and a variable attentional control (VAC) task. A clinical assessment that included measurement of blood pressure, heart rate, the Hamilton anxiety scale, and the profile of mood state (POMS) questionnaire was also performed on each test day. BOLD fMRI revealed significantly decreased amygdala reactivity to fearful stimuli on modafinil compared with the placebo condition. During executive cognition tasks, a WM task and a VAC task, modafinil reduced BOLD signal in the prefrontal cortex and anterior cingulate. Although not statistically significant, there were trends for reduced anxiety, for decreased fatigue-inertia and increased vigor-activity, as well as decreased anger-hostility on modafinil. Modafinil in low doses has a unique physiologic profile compared with stimulant drugs: it enhances the efficiency of prefrontal cortical cognitive information processing, while dampening reactivity to threatening stimuli in the amygdala, a brain region implicated in anxiety. PMID:20555311

  12. Raindrop Kinetic Energy Piezoelectric Harvesters and Relevant Interface Circuits: Review, Issues and Outlooks

    Directory of Open Access Journals (Sweden)

    Kok Gnee CHUA

    2016-05-01

    Full Text Available As an ecological source of renewable energy, the available kinetic energy of rainfall is not trifling, especially in tropical countries at the equators. The research on the use of piezoelectric transducer to harvest raindrop kinetic energy is gaining more and more attention recently. This article reviews the state-of-the-art energy harvesting technology from the conversion of raindrop kinetic energy using piezoelectric transducers as well as its interface circuits for vibration-based energy harvesters. Performance of different types of piezoelectric harvesters in terms of power output, area power density and energy conversion efficiency are compared. Summaries of key problems and suggestions on the optimization of the performance of the piezoelectric harvesters are also provided for future works.

  13. Refinement and Pattern Formation in Neural Circuits by the Interaction of Traveling Waves with Spike-Timing Dependent Plasticity

    Science.gov (United States)

    Bennett, James E. M.; Bair, Wyeth

    2015-01-01

    Traveling waves in the developing brain are a prominent source of highly correlated spiking activity that may instruct the refinement of neural circuits. A candidate mechanism for mediating such refinement is spike-timing dependent plasticity (STDP), which translates correlated activity patterns into changes in synaptic strength. To assess the potential of these phenomena to build useful structure in developing neural circuits, we examined the interaction of wave activity with STDP rules in simple, biologically plausible models of spiking neurons. We derive an expression for the synaptic strength dynamics showing that, by mapping the time dependence of STDP into spatial interactions, traveling waves can build periodic synaptic connectivity patterns into feedforward circuits with a broad class of experimentally observed STDP rules. The spatial scale of the connectivity patterns increases with wave speed and STDP time constants. We verify these results with simulations and demonstrate their robustness to likely sources of noise. We show how this pattern formation ability, which is analogous to solutions of reaction-diffusion systems that have been widely applied to biological pattern formation, can be harnessed to instruct the refinement of postsynaptic receptive fields. Our results hold for rich, complex wave patterns in two dimensions and over several orders of magnitude in wave speeds and STDP time constants, and they provide predictions that can be tested under existing experimental paradigms. Our model generalizes across brain areas and STDP rules, allowing broad application to the ubiquitous occurrence of traveling waves and to wave-like activity patterns induced by moving stimuli. PMID:26308406

  14. Disrupted insula-based neural circuit organization and conflict interference in trauma-exposed youth

    Directory of Open Access Journals (Sweden)

    Hilary A. Marusak

    2015-01-01

    Full Text Available Childhood trauma exposure is a potent risk factor for psychopathology. Emerging research suggests that aberrant saliency processing underlies the link between early trauma exposure and later cognitive and socioemotional deficits that are hallmark of several psychiatric disorders. Here, we examine brain and behavioral responses during a face categorization conflict task, and relate these to intrinsic connectivity of the salience network (SN. The results demonstrate a unique pattern of SN dysfunction in youth exposed to trauma (n = 14 relative to comparison youth (n = 19 matched on age, sex, IQ, and sociodemographic risk. We find that trauma-exposed youth are more susceptible to conflict interference and this correlates with higher fronto-insular responses during conflict. Resting-state functional connectivity data collected in the same participants reveal increased connectivity of the insula to SN seed regions that is associated with diminished reward sensitivity, a critical risk/resilience trait following stress. In addition to altered intrinsic connectivity of the SN, we observed altered connectivity between the SN and default mode network (DMN in trauma-exposed youth. These data uncover network-level disruptions in brain organization following one of the strongest predictors of illness, early life trauma, and demonstrate the relevance of observed neural effects for behavior and specific symptom dimensions. SN dysfunction may serve as a diathesis that contributes to illness and negative outcomes following childhood trauma.

  15. A neural circuit model of emotional learning using two pathways with different granularity and speed of information processing.

    Science.gov (United States)

    Murakoshi, Kazushi; Saito, Mayuko

    2009-02-01

    We propose a neural circuit model of emotional learning using two pathways with different granularity and speed of information processing. In order to derive a precise time process, we utilized a spiking model neuron proposed by Izhikevich and spike-timing-dependent synaptic plasticity (STDP) of both excitatory and inhibitory synapses. We conducted computer simulations to evaluate the proposed model. We demonstrate some aspects of emotional learning from the perspective of the time process. The agreement of the results with the previous behavioral experiments suggests that the structure and learning process of the proposed model are appropriate.

  16. Modification of tenascin-R expression following unilateral labyrinthectomy in rats indicates its possible role in neural plasticity of the vestibular neural circuit.

    Science.gov (United States)

    Gaal, Botond; Jóhannesson, Einar Örn; Dattani, Amit; Magyar, Agnes; Wéber, Ildikó; Matesz, Clara

    2015-09-01

    We have previously found that unilateral labyrinthectomy is accompanied by modification of hyaluronan and chondroitin sulfate proteoglycan staining in the lateral vestibular nucleus of rats and the time course of subsequent reorganization of extracellular matrix assembly correlates to the restoration of impaired vestibular function. The tenascin-R has repelling effect on pathfinding during axonal growth/regrowth, and thus inhibits neural circuit repair. By using immunohistochemical method, we studied the modification of tenascin-R expression in the superior, medial, lateral, and descending vestibular nuclei of the rat following unilateral labyrinthectomy. On postoperative day 1, tenascin-R reaction in the perineuronal nets disappeared on the side of labyrinthectomy in the superior, lateral, medial, and rostral part of the descending vestibular nuclei. On survival day 3, the staining intensity of tenascin-R reaction in perineuronal nets recovered on the operated side of the medial vestibular nucleus, whereas it was restored by the time of postoperative day 7 in the superior, lateral and rostral part of the descending vestibular nuclei. The staining intensity of tenascin-R reaction remained unchanged in the caudal part of the descending vestibular nucleus bilaterally. Regional differences in the modification of tenascin-R expression presented here may be associated with different roles of individual vestibular nuclei in the compensatory processes. The decreased expression of the tenascin-R may suggest the extracellular facilitation of plastic modifications in the vestibular neural circuit after lesion of the labyrinthine receptors.

  17. Generating Poetry Title Based on Semantic Relevance with Convolutional Neural Network

    Science.gov (United States)

    Li, Z.; Niu, K.; He, Z. Q.

    2017-09-01

    Several approaches have been proposed to automatically generate Chinese classical poetry (CCP) in the past few years, but automatically generating the title of CCP is still a difficult problem. The difficulties are mainly reflected in two aspects. First, the words used in CCP are very different from modern Chinese words and there are no valid word segmentation tools. Second, the semantic relevance of characters in CCP not only exists in one sentence but also exists between the same positions of adjacent sentences, which is hard to grasp by the traditional text summarization models. In this paper, we propose an encoder-decoder model for generating the title of CCP. Our model encoder is a convolutional neural network (CNN) with two kinds of filters. To capture the commonly used words in one sentence, one kind of filters covers two characters horizontally at each step. The other covers two characters vertically at each step and can grasp the semantic relevance of characters between adjacent sentences. Experimental results show that our model is better than several other related models and can capture the semantic relevance of CCP more accurately.

  18. Task relevance modulates the behavioural and neural effects of sensory predictions.

    Science.gov (United States)

    Auksztulewicz, Ryszard; Friston, Karl J; Nobre, Anna C

    2017-12-01

    The brain is thought to generate internal predictions to optimize behaviour. However, it is unclear whether predictions signalling is an automatic brain function or depends on task demands. Here, we manipulated the spatial/temporal predictability of visual targets, and the relevance of spatial/temporal information provided by auditory cues. We used magnetoencephalography (MEG) to measure participants' brain activity during task performance. Task relevance modulated the influence of predictions on behaviour: spatial/temporal predictability improved spatial/temporal discrimination accuracy, but not vice versa. To explain these effects, we used behavioural responses to estimate subjective predictions under an ideal-observer model. Model-based time-series of predictions and prediction errors (PEs) were associated with dissociable neural responses: predictions correlated with cue-induced beta-band activity in auditory regions and alpha-band activity in visual regions, while stimulus-bound PEs correlated with gamma-band activity in posterior regions. Crucially, task relevance modulated these spectral correlates, suggesting that current goals influence PE and prediction signalling.

  19. Upper Limb Immobilisation: A Neural Plasticity Model with Relevance to Poststroke Motor Rehabilitation.

    Science.gov (United States)

    Furlan, Leonardo; Conforto, Adriana Bastos; Cohen, Leonardo G; Sterr, Annette

    2016-01-01

    Advances in our understanding of the neural plasticity that occurs after hemiparetic stroke have contributed to the formulation of theories of poststroke motor recovery. These theories, in turn, have underpinned contemporary motor rehabilitation strategies for treating motor deficits after stroke, such as upper limb hemiparesis. However, a relative drawback has been that, in general, these strategies are most compatible with the recovery profiles of relatively high-functioning stroke survivors and therefore do not easily translate into benefit to those individuals sustaining low-functioning upper limb hemiparesis, who otherwise have poorer residual function. For these individuals, alternative motor rehabilitation strategies are currently needed. In this paper, we will review upper limb immobilisation studies that have been conducted with healthy adult humans and animals. Then, we will discuss how the findings from these studies could inspire the creation of a neural plasticity model that is likely to be of particular relevance to the context of motor rehabilitation after stroke. For instance, as will be elaborated, such model could contribute to the development of alternative motor rehabilitation strategies for treating poststroke upper limb hemiparesis. The implications of the findings from those immobilisation studies for contemporary motor rehabilitation strategies will also be discussed and perspectives for future research in this arena will be provided as well.

  20. Upper Limb Immobilisation: A Neural Plasticity Model with Relevance to Poststroke Motor Rehabilitation

    Science.gov (United States)

    Furlan, Leonardo; Conforto, Adriana Bastos; Cohen, Leonardo G.; Sterr, Annette

    2016-01-01

    Advances in our understanding of the neural plasticity that occurs after hemiparetic stroke have contributed to the formulation of theories of poststroke motor recovery. These theories, in turn, have underpinned contemporary motor rehabilitation strategies for treating motor deficits after stroke, such as upper limb hemiparesis. However, a relative drawback has been that, in general, these strategies are most compatible with the recovery profiles of relatively high-functioning stroke survivors and therefore do not easily translate into benefit to those individuals sustaining low-functioning upper limb hemiparesis, who otherwise have poorer residual function. For these individuals, alternative motor rehabilitation strategies are currently needed. In this paper, we will review upper limb immobilisation studies that have been conducted with healthy adult humans and animals. Then, we will discuss how the findings from these studies could inspire the creation of a neural plasticity model that is likely to be of particular relevance to the context of motor rehabilitation after stroke. For instance, as will be elaborated, such model could contribute to the development of alternative motor rehabilitation strategies for treating poststroke upper limb hemiparesis. The implications of the findings from those immobilisation studies for contemporary motor rehabilitation strategies will also be discussed and perspectives for future research in this arena will be provided as well. PMID:26843992

  1. Neural representation and clinically relevant moderators of individualised self-criticism in healthy subjects

    Science.gov (United States)

    Schlumpf, Yolanda; Spinelli, Simona; Späti, Jakub; Brakowski, Janis; Quednow, Boris B.; Seifritz, Erich; Grosse Holtforth, Martin

    2014-01-01

    Many people routinely criticise themselves. While self-criticism is largely unproblematic for most individuals, depressed patients exhibit excessive self-critical thinking, which leads to strong negative affects. We used functional magnetic resonance imaging in healthy subjects (N = 20) to investigate neural correlates and possible psychological moderators of self-critical processing. Stimuli consisted of individually selected adjectives of personally negative content and were contrasted with neutral and negative non-self-referential adjectives. We found that confrontation with self-critical material yielded neural activity in regions involved in emotions (anterior insula/hippocampus–amygdala formation) and in anterior and posterior cortical midline structures, which are associated with self-referential and autobiographical memory processing. Furthermore, contrasts revealed an extended network of bilateral frontal brain areas. We suggest that the co-activation of superior and inferior lateral frontal brain regions reflects the recruitment of a frontal top–down pathway, representing cognitive reappraisal strategies for dealing with evoked negative affects. In addition, activation of right superior frontal areas was positively associated with neuroticism and negatively associated with cognitive reappraisal. Although these findings may not be specific to negative stimuli, they support a role for clinically relevant personality traits in successful regulation of emotion during confrontation with self-critical material. PMID:23887820

  2. Upper Limb Immobilisation: A Neural Plasticity Model with Relevance to Poststroke Motor Rehabilitation

    Directory of Open Access Journals (Sweden)

    Leonardo Furlan

    2016-01-01

    Full Text Available Advances in our understanding of the neural plasticity that occurs after hemiparetic stroke have contributed to the formulation of theories of poststroke motor recovery. These theories, in turn, have underpinned contemporary motor rehabilitation strategies for treating motor deficits after stroke, such as upper limb hemiparesis. However, a relative drawback has been that, in general, these strategies are most compatible with the recovery profiles of relatively high-functioning stroke survivors and therefore do not easily translate into benefit to those individuals sustaining low-functioning upper limb hemiparesis, who otherwise have poorer residual function. For these individuals, alternative motor rehabilitation strategies are currently needed. In this paper, we will review upper limb immobilisation studies that have been conducted with healthy adult humans and animals. Then, we will discuss how the findings from these studies could inspire the creation of a neural plasticity model that is likely to be of particular relevance to the context of motor rehabilitation after stroke. For instance, as will be elaborated, such model could contribute to the development of alternative motor rehabilitation strategies for treating poststroke upper limb hemiparesis. The implications of the findings from those immobilisation studies for contemporary motor rehabilitation strategies will also be discussed and perspectives for future research in this arena will be provided as well.

  3. Stability and plasticity in neural encoding of linguistically relevant pitch patterns.

    Science.gov (United States)

    Xie, Zilong; Reetzke, Rachel; Chandrasekaran, Bharath

    2017-03-01

    While lifelong language experience modulates subcortical encoding of pitch patterns, there is emerging evidence that short-term training introduced in adulthood also shapes subcortical pitch encoding. Here we use a cross-language design to examine the stability of language experience-dependent subcortical plasticity over multiple days. We then examine the extent to which behavioral relevance induced by sound-to-category training leads to plastic changes in subcortical pitch encoding in adulthood relative to adolescence, a period of ongoing maturation of subcortical and cortical auditory processing. Frequency-following responses (FFRs), which reflect phase-locked activity from subcortical neural ensembles, were elicited while participants passively listened to pitch patterns reflective of Mandarin tones. In experiment 1 , FFRs were recorded across three consecutive days from native Chinese-speaking ( n = 10) and English-speaking ( n = 10) adults. In experiment 2 , FFRs were recorded from native English-speaking adolescents ( n = 20) and adults ( n = 15) before, during, and immediately after a session of sound-to-category training, as well as a day after training ceased. Experiment 1 demonstrated the stability of language experience-dependent subcortical plasticity in pitch encoding across multiple days of passive exposure to linguistic pitch patterns. In contrast, experiment 2 revealed an enhancement in subcortical pitch encoding that emerged a day after the sound-to-category training, with some developmental differences observed. Taken together, these findings suggest that behavioral relevance is a critical component for the observation of plasticity in the subcortical encoding of pitch. NEW & NOTEWORTHY We examine the timescale of experience-dependent auditory plasticity to linguistically relevant pitch patterns. We find extreme stability in lifelong experience-dependent plasticity. We further demonstrate that subcortical function in adolescents and adults is

  4. Enhanced expression of FNDC5 in human embryonic stem cell-derived neural cells along with relevant embryonic neural tissues.

    Science.gov (United States)

    Ghahrizjani, Fatemeh Ahmadi; Ghaedi, Kamran; Salamian, Ahmad; Tanhaei, Somayeh; Nejati, Alireza Shoaraye; Salehi, Hossein; Nabiuni, Mohammad; Baharvand, Hossein; Nasr-Esfahani, Mohammad Hossein

    2015-02-25

    Availability of human embryonic stem cells (hESCs) has enhanced the capability of basic and clinical research in the context of human neural differentiation. Derivation of neural progenitor (NP) cells from hESCs facilitates the process of human embryonic development through the generation of neuronal subtypes. We have recently indicated that fibronectin type III domain containing 5 protein (FNDC5) expression is required for appropriate neural differentiation of mouse embryonic stem cells (mESCs). Bioinformatics analyses have shown the presence of three isoforms for human FNDC5 mRNA. To differentiate which isoform of FNDC5 is involved in the process of human neural differentiation, we have used hESCs as an in vitro model for neural differentiation by retinoic acid (RA) induction. The hESC line, Royan H5, was differentiated into a neural lineage in defined adherent culture treated by RA and basic fibroblast growth factor (bFGF). We collected all cell types that included hESCs, rosette structures, and neural cells in an attempt to assess the expression of FNDC5 isoforms. There was a contiguous increase in all three FNDC5 isoforms during the neural differentiation process. Furthermore, the highest level of expression of the isoforms was significantly observed in neural cells compared to hESCs and the rosette structures known as neural precursor cells (NPCs). High expression levels of FNDC5 in human fetal brain and spinal cord tissues have suggested the involvement of this gene in neural tube development. Additional research is necessary to determine the major function of FDNC5 in this process. Copyright © 2014 Elsevier B.V. All rights reserved.

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

    Science.gov (United States)

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

    2017-07-01

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

  6. Neural circuits of disgust induced by sexual stimuli in homosexual and heterosexual men: An fMRI study

    Energy Technology Data Exchange (ETDEWEB)

    Zhang Minming [Department of Radiology, Second Affiliated Hospital, College of Medicine, Zhejiang University, Hangzhou (China); Hu Shaohua [Department of Mental Health, First Affiliated Hospital, College of Medicine, Zhejiang University, 79 Qing Chun Road, Hangzhou, Zhejiang Province 310003 (China); Xu Lijuan [National Laboratory of Pattern Recognition, Institute of Automation, Chinese Academy of Sciences, Beijing (China); Wang Qidong [Department of Radiology, First Affiliated Hospital, College of Medicine, Zhejiang University, Hangzhou (China); Xu Xiaojun [Department of Radiology, Second Affiliated Hospital, College of Medicine, Zhejiang University, Hangzhou (China); Wei Erqing [College of Pharmacology, Zhejiang University (China); Yan Leqin [MD Anderson Cancer Center, Virginia Harris Cockrell Cancer Research Center, University of Texas, Austin (United States); Hu Jianbo; Wei Ning; Zhou Weihua; Huang Manli [Department of Mental Health, First Affiliated Hospital, College of Medicine, Zhejiang University, 79 Qing Chun Road, Hangzhou, Zhejiang Province 310003 (China); Xu Yi, E-mail: xuyi61@yahoo.com.cn [Department of Mental Health, First Affiliated Hospital, College of Medicine, Zhejiang University, 79 Qing Chun Road, Hangzhou, Zhejiang Province 310003 (China)

    2011-11-15

    Few studies demonstrated neural circuits related to disgust were influenced by internal sexual orientation in male. Here we used fMRI to study the neural responses to disgust in homosexual and heterosexual men to investigate that issue. Thirty-two healthy male volunteers (sixteen homosexual and sixteen heterosexual) were scanned while viewing alternating blocks of three types of erotic film: heterosexual couples (F-M), male homosexual couples (M-M), and female homosexual couples (F-F) engaged in sexual activity. All the participants rated their level of disgust and sexual arousal as well. The F-F and M-M stimuli induced disgust in homosexual and heterosexual men, respectively. The common activations related to disgusting stimuli included: bilateral frontal gyrus and occipital gyrus, right middle temporal gyrus, left superior temporal gyrus, right cerebellum, and right thalamus. Homosexual men had greater neural responses in the left medial frontal gyrus than did heterosexual men to the sexual disgusting stimuli; in contrast, heterosexual men showed significantly greater activation than homosexual men in the left cuneus. ROI analysis showed that negative correlation were found between the magnitude of MRI signals in the left medial frontal gyrus and scores of disgust in homosexual subjects (p < 0.05). This study indicated that there were regions in common as well as regions specific for each type of erotic stimuli during disgust of homosexual and heterosexual men.

  7. Synaptic plasticity, neural circuits, and the emerging role of altered short-term information processing in schizophrenia.

    Science.gov (United States)

    Crabtree, Gregg W; Gogos, Joseph A

    2014-01-01

    Synaptic plasticity alters the strength of information flow between presynaptic and postsynaptic neurons and thus modifies the likelihood that action potentials in a presynaptic neuron will lead to an action potential in a postsynaptic neuron. As such, synaptic plasticity and pathological changes in synaptic plasticity impact the synaptic computation which controls the information flow through the neural microcircuits responsible for the complex information processing necessary to drive adaptive behaviors. As current theories of neuropsychiatric disease suggest that distinct dysfunctions in neural circuit performance may critically underlie the unique symptoms of these diseases, pathological alterations in synaptic plasticity mechanisms may be fundamental to the disease process. Here we consider mechanisms of both short-term and long-term plasticity of synaptic transmission and their possible roles in information processing by neural microcircuits in both health and disease. As paradigms of neuropsychiatric diseases with strongly implicated risk genes, we discuss the findings in schizophrenia and autism and consider the alterations in synaptic plasticity and network function observed in both human studies and genetic mouse models of these diseases. Together these studies have begun to point toward a likely dominant role of short-term synaptic plasticity alterations in schizophrenia while dysfunction in autism spectrum disorders (ASDs) may be due to a combination of both short-term and long-term synaptic plasticity alterations.

  8. A feed-forward spinal cord glycinergic neural circuit gates mechanical allodynia.

    Science.gov (United States)

    Lu, Yan; Dong, Hailong; Gao, Yandong; Gong, Yuanyuan; Ren, Yingna; Gu, Nan; Zhou, Shudi; Xia, Nan; Sun, Yan-Yan; Ji, Ru-Rong; Xiong, Lize

    2013-09-01

    Neuropathic pain is characterized by mechanical allodynia induced by low-threshold myelinated Aβ-fiber activation. The original gate theory of pain proposes that inhibitory interneurons in the lamina II of the spinal dorsal horn (DH) act as "gate control" units for preventing the interaction between innocuous and nociceptive signals. However, our understanding of the neuronal circuits underlying pain signaling and modulation in the spinal DH is incomplete. Using a rat model, we have shown that the convergence of glycinergic inhibitory and excitatory Aβ-fiber inputs onto PKCγ+ neurons in the superficial DH forms a feed-forward inhibitory circuit that prevents Aβ input from activating the nociceptive pathway. This feed-forward inhibition was suppressed following peripheral nerve injury or glycine blockage, leading to inappropriate induction of action potential outputs in the nociceptive pathway by Aβ-fiber stimulation. Furthermore, spinal blockage of glycinergic synaptic transmission in vivo induced marked mechanical allodynia. Our findings identify a glycinergic feed-forward inhibitory circuit that functions as a gate control to separate the innocuous mechanoreceptive pathway and the nociceptive pathway in the spinal DH. Disruption of this glycinergic inhibitory circuit after peripheral nerve injury has the potential to elicit mechanical allodynia, a cardinal symptom of neuropathic pain.

  9. Analysis of the function and intracellular signal transduction mechanism of secreted semaphorins during neural circuit development

    NARCIS (Netherlands)

    Gunput, R.F.

    2011-01-01

    Our ability to perceive, to act and to remember is a reflection of the elaborate synaptic connections and neuronal circuits that make up the brain. The formation of these connections relies on a series of developmental events including axon growth and guidance, synapse formation and cell death. The

  10. Effects of ion channel noise on neural circuits: an application to the respiratory pattern generator to investigate breathing variability.

    Science.gov (United States)

    Yu, Haitao; Dhingra, Rishi R; Dick, Thomas E; Galán, Roberto F

    2017-01-01

    Neural activity generally displays irregular firing patterns even in circuits with apparently regular outputs, such as motor pattern generators, in which the output frequency fluctuates randomly around a mean value. This "circuit noise" is inherited from the random firing of single neurons, which emerges from stochastic ion channel gating (channel noise), spontaneous neurotransmitter release, and its diffusion and binding to synaptic receptors. Here we demonstrate how to expand conductance-based network models that are originally deterministic to include realistic, physiological noise, focusing on stochastic ion channel gating. We illustrate this procedure with a well-established conductance-based model of the respiratory pattern generator, which allows us to investigate how channel noise affects neural dynamics at the circuit level and, in particular, to understand the relationship between the respiratory pattern and its breath-to-breath variability. We show that as the channel number increases, the duration of inspiration and expiration varies, and so does the coefficient of variation of the breath-to-breath interval, which attains a minimum when the mean duration of expiration slightly exceeds that of inspiration. For small channel numbers, the variability of the expiratory phase dominates over that of the inspiratory phase, and vice versa for large channel numbers. Among the four different cell types in the respiratory pattern generator, pacemaker cells exhibit the highest sensitivity to channel noise. The model shows that suppressing input from the pons leads to longer inspiratory phases, a reduction in breathing frequency, and larger breath-to-breath variability, whereas enhanced input from the raphe nucleus increases breathing frequency without changing its pattern. A major source of noise in neuronal circuits is the "flickering" of ion currents passing through the neurons' membranes (channel noise), which cannot be suppressed experimentally. Computational

  11. A Neural Circuit for Acoustic Navigation combining Heterosynaptic and Non-synaptic Plasticity that learns Stable Trajectories

    DEFF Research Database (Denmark)

    Shaikh, Danish; Manoonpong, Poramate

    2017-01-01

    Reactive spatial robot navigation in goal-directed tasks such as phonotaxis requires generating consistent and stable trajectories towards an acoustic target while avoiding obstacles. High-level goal-directed steering behaviour can steer a robot towards the target by mapping sound direction...... controllers be resolved in a manner that generates consistent and stable robot trajectories? We propose a neural circuit that minimises this conflict by learning sensorimotor mappings as neuronal transfer functions between the perceived sound direction and wheel velocities of a simulated non-holonomic mobile...... robot. These mappings constitute the high-level goal-directed steering behaviour. Sound direction information is obtained from a model of the lizard peripheral auditory system. The parameters of the transfer functions are learned via an online unsupervised correlation learning algorithm through...

  12. Next-generation transgenic mice for optogenetic analysis of neural circuits

    Directory of Open Access Journals (Sweden)

    Brent eAsrican

    2013-11-01

    Full Text Available Here we characterize several new lines of transgenic mice useful for optogenetic analysis of brain circuit function. These mice express optogenetic probes, such as enhanced halorhodopsin or several different versions of channelrhodopsins, behind various neuron-specific promoters. These mice permit photoinhibition or photostimulation both in vitro and in vivo. Our results also reveal the important influence of fluorescent tags on optogenetic probe expression and function in transgenic mice.

  13. Rules and mechanisms for efficient two-stage learning in neural circuits.

    Science.gov (United States)

    Teşileanu, Tiberiu; Ölveczky, Bence; Balasubramanian, Vijay

    2017-04-04

    Trial-and-error learning requires evaluating variable actions and reinforcing successful variants. In songbirds, vocal exploration is induced by LMAN, the output of a basal ganglia-related circuit that also contributes a corrective bias to the vocal output. This bias is gradually consolidated in RA, a motor cortex analogue downstream of LMAN. We develop a new model of such two-stage learning. Using stochastic gradient descent, we derive how the activity in 'tutor' circuits ( e.g., LMAN) should match plasticity mechanisms in 'student' circuits ( e.g., RA) to achieve efficient learning. We further describe a reinforcement learning framework through which the tutor can build its teaching signal. We show that mismatches between the tutor signal and the plasticity mechanism can impair learning. Applied to birdsong, our results predict the temporal structure of the corrective bias from LMAN given a plasticity rule in RA. Our framework can be applied predictively to other paired brain areas showing two-stage learning.

  14. Evolution and analysis of minimal neural circuits for klinotaxis in Caenorhabditis elegans.

    Science.gov (United States)

    Izquierdo, Eduardo J; Lockery, Shawn R

    2010-09-29

    Chemotaxis during sinusoidal locomotion in nematodes captures in simplified form the general problem of how dynamical interactions between the nervous system, body, and environment are exploited in the generation of adaptive behavior. We used an evolutionary algorithm to generate neural networks that exhibit klinotaxis, a common form of chemotaxis in which the direction of locomotion in a chemical gradient closely follows the line of steepest ascent. Sensory inputs and motor outputs of the model networks were constrained to match the inputs and outputs of the Caenorhabditis elegans klinotaxis network. We found that a minimalistic neural network, comprised of an ON-OFF pair of chemosensory neurons and a pair of neck muscle motor neurons, is sufficient to generate realistic klinotaxis behavior. Importantly, emergent properties of model networks reproduced two key experimental observations that they were not designed to fit, suggesting that the model may be operating according to principles similar to those of the biological network. A dynamical systems analysis of 77 evolved networks revealed a novel neural mechanism for spatial orientation behavior. This mechanism provides a testable hypothesis that is likely to accelerate the discovery and analysis of the biological circuitry for chemotaxis in C. elegans.

  15. A multichannel integrated circuit for electrical recording of neural activity, with independent channel programmability.

    Science.gov (United States)

    Mora Lopez, Carolina; Prodanov, Dimiter; Braeken, Dries; Gligorijevic, Ivan; Eberle, Wolfgang; Bartic, Carmen; Puers, Robert; Gielen, Georges

    2012-04-01

    Since a few decades, micro-fabricated neural probes are being used, together with microelectronic interfaces, to get more insight in the activity of neuronal networks. The need for higher temporal and spatial recording resolutions imposes new challenges on the design of integrated neural interfaces with respect to power consumption, data handling and versatility. In this paper, we present an integrated acquisition system for in vitro and in vivo recording of neural activity. The ASIC consists of 16 low-noise, fully-differential input channels with independent programmability of its amplification (from 100 to 6000 V/V) and filtering (1-6000 Hz range) capabilities. Each channel is AC-coupled and implements a fourth-order band-pass filter in order to steeply attenuate out-of-band noise and DC input offsets. The system achieves an input-referred noise density of 37 nV/√Hz, a NEF of 5.1, a CMRR > 60 dB, a THD noise ratios.

  16. Neural circuits underlying mother's voice perception predict social communication abilities in children.

    Science.gov (United States)

    Abrams, Daniel A; Chen, Tianwen; Odriozola, Paola; Cheng, Katherine M; Baker, Amanda E; Padmanabhan, Aarthi; Ryali, Srikanth; Kochalka, John; Feinstein, Carl; Menon, Vinod

    2016-05-31

    The human voice is a critical social cue, and listeners are extremely sensitive to the voices in their environment. One of the most salient voices in a child's life is mother's voice: Infants discriminate their mother's voice from the first days of life, and this stimulus is associated with guiding emotional and social function during development. Little is known regarding the functional circuits that are selectively engaged in children by biologically salient voices such as mother's voice or whether this brain activity is related to children's social communication abilities. We used functional MRI to measure brain activity in 24 healthy children (mean age, 10.2 y) while they attended to brief (social function. Compared to female control voices, mother's voice elicited greater activity in primary auditory regions in the midbrain and cortex; voice-selective superior temporal sulcus (STS); the amygdala, which is crucial for processing of affect; nucleus accumbens and orbitofrontal cortex of the reward circuit; anterior insula and cingulate of the salience network; and a subregion of fusiform gyrus associated with face perception. The strength of brain connectivity between voice-selective STS and reward, affective, salience, memory, and face-processing regions during mother's voice perception predicted social communication skills. Our findings provide a novel neurobiological template for investigation of typical social development as well as clinical disorders, such as autism, in which perception of biologically and socially salient voices may be impaired.

  17. Neural reuse of action perception circuits for language, concepts and communication.

    Science.gov (United States)

    Pulvermüller, Friedemann

    2018-01-01

    Neurocognitive and neurolinguistics theories make explicit statements relating specialized cognitive and linguistic processes to specific brain loci. These linking hypotheses are in need of neurobiological justification and explanation. Recent mathematical models of human language mechanisms constrained by fundamental neuroscience principles and established knowledge about comparative neuroanatomy offer explanations for where, when and how language is processed in the human brain. In these models, network structure and connectivity along with action- and perception-induced correlation of neuronal activity co-determine neurocognitive mechanisms. Language learning leads to the formation of action perception circuits (APCs) with specific distributions across cortical areas. Cognitive and linguistic processes such as speech production, comprehension, verbal working memory and prediction are modelled by activity dynamics in these APCs, and combinatorial and communicative-interactive knowledge is organized in the dynamics within, and connections between APCs. The network models and, in particular, the concept of distributionally-specific circuits, can account for some previously not well understood facts about the cortical 'hubs' for semantic processing and the motor system's role in language understanding and speech sound recognition. A review of experimental data evaluates predictions of the APC model and alternative theories, also providing detailed discussion of some seemingly contradictory findings. Throughout, recent disputes about the role of mirror neurons and grounded cognition in language and communication are assessed critically. Copyright © 2017 The Author. Published by Elsevier Ltd.. All rights reserved.

  18. Normalization of Intrinsic Neural Circuits Governing Tourette's Syndrome Using Cranial Electrotherapy Stimulation.

    Science.gov (United States)

    Qiao, Jianping; Weng, Shenhong; Wang, Pengwei; Long, Jun; Wang, Zhishun

    2015-05-01

    The aim of this study was to investigate the normalization of the intrinsic functional activity and connectivity of TS adolescents before and after the cranial electrotherapy stimulation (CES) with alpha stim device. We performed resting-state functional magnetic resonance imaging on eight adolescents before and after CES with mean age of about nine-years old who had Tourette's syndrome with moderate to severe tics symptom. Independent component analysis (ICA) with hierarchical partner matching method was used to examine the functional connectivity between regions within cortico-striato-thalamo-cortical (CSTC) circuit. Granger causality was used to investigate effective connectivity among these regions detected by ICA. We then performed pattern classification on independent components with significant group differences that served as endophenotype markers to distinguish the adolescents between TS and the normalized ones after CES. Results showed that TS adolescents after CES treatment had stronger functional activity and connectivity in anterior cingulate cortex (ACC), caudate and posterior cingulate cortex while had weaker activity in supplementary motor area within the motor pathway compared with TS before CES. The results suggest that the functional activity and connectivity in motor pathway was suppressed while activities in the control portions within CSTC loop including ACC and caudate were increased in TS adolescents after CES compared with adolescents before CES. The normalization of the balance between motor and control portions of the CSTC circuit may result in the recovery of TS adolescents.

  19. A low-power, low-noise neural-signal amplifier circuit in 90-nm CMOS.

    Science.gov (United States)

    Zarifi, M H; Frounchi, J; Farshchi, S; Judy, J W

    2008-01-01

    A fully-differential low-power low-noise preamplifier for biopotential and neural-recording applications is presented. This design, which has been simulated in a standard 90-nm CMOS process, consumes 30 microW from a 3-V power supply. The simulated integrated input-referred noise is 2.3 microV over 0.1 Hz to 20 kHz. The amplifier also provides an output swing of +/- 0.9 V with a THD of less than 0.1%

  20. Negative emotional distraction on neural circuits for working memory in patients with posttraumatic stress disorder.

    Science.gov (United States)

    Zhang, Jing-na; Xiong, Kun-lining; Qiu, Ming-guo; Zhang, Ye; Xie, Bing; Wang, Jian; Li, Min; Chen, Han; Zhang, Yu; Zhang, Jia-jia

    2013-09-19

    To study the neural mechanism for the impact of negative emotional distraction on working memory in patients with posttraumatic stress disorder (PTSD) resulting from exposure to motor vehicle accidents. Twenty PTSD patients and 20 healthy subjects were recruited. Event-related functional magnetic resonance imaging (fMRI) was used to investigate the effects of negative and neutral distractors on a delayed-response working memory task. All experiments were performed on a 3.0T MRI scanner, and the functional imaging data were analyzed using SPM8 software. The PTSD group showed poorer performance than the control group when the negative distractors were presented during the delay phase of working memory. The functional imaging indicated that, in the presence of negative relative to neutral distractors, the PTSD group showed higher activation in the emotion processing regions, including amygdala, precuneus and fusiform gyrus, but lower activation in the inferior frontal cortex, insula and left supramarginal gyrus than the control group. Based on the results that activation in the PTSD patients in the presence of negative distractors increased in the emotion-related brain regions but decreased in the working memory-related brain regions, we may conclude that the neural basis of working memory is impaired by negative emotion in PTSD patients. © 2013 The Authors. Published by Elsevier B.V. All rights reserved.

  1. Neural circuits in anxiety and stress disorders: a focused review

    Directory of Open Access Journals (Sweden)

    Duval ER

    2015-01-01

    Full Text Available Elizabeth R Duval, Arash Javanbakht, Israel LiberzonDepartment of Psychiatry, University of Michigan Health System, Ann Arbor, MI, USAAbstract: Anxiety and stress disorders are among the most prevalent neuropsychiatric disorders. In recent years, multiple studies have examined brain regions and networks involved in anxiety symptomatology in an effort to better understand the mechanisms involved and to develop more effective treatments. However, much remains unknown regarding the specific abnormalities and interactions between networks of regions underlying anxiety disorder presentations. We examined recent neuroimaging literature that aims to identify neural mechanisms underlying anxiety, searching for patterns of neural dysfunction that might be specific to different anxiety disorder categories. Across different anxiety and stress disorders, patterns of hyperactivation in emotion-generating regions and hypoactivation in prefrontal/regulatory regions are common in the literature. Interestingly, evidence of differential patterns is also emerging, such that within a spectrum of disorders ranging from more fear-based to more anxiety-based, greater involvement of emotion-generating regions is reported in panic disorder and specific phobia, and greater involvement of prefrontal regions is reported in generalized anxiety disorder and posttraumatic stress disorder. We summarize the pertinent literature and suggest areas for continued investigation.Keywords: fear, anxiety, neuroimaging

  2. PDF-1 neuropeptide signaling modulates a neural circuit for mate-searching behavior in C. elegans.

    Science.gov (United States)

    Barrios, Arantza; Ghosh, Rajarshi; Fang, Chunhui; Emmons, Scott W; Barr, Maureen M

    2012-12-01

    Appetitive behaviors require complex decision making that involves the integration of environmental stimuli and physiological needs. C. elegans mate searching is a male-specific exploratory behavior regulated by two competing needs: food and reproductive appetite. We found that the pigment dispersing factor receptor (PDFR-1) modulates the circuit that encodes the male reproductive drive that promotes male exploration following mate deprivation. PDFR-1 and its ligand, PDF-1, stimulated mate searching in the male, but not in the hermaphrodite. pdf-1 was required in the gender-shared interneuron AIM, and the receptor acted in internal and external environment-sensing neurons of the shared nervous system (URY, PQR and PHA) to produce mate-searching behavior. Thus, the pdf-1 and pdfr-1 pathway functions in non-sex-specific neurons to produce a male-specific, goal-oriented exploratory behavior. Our results indicate that secretin neuropeptidergic signaling is involved in regulating motivational internal states.

  3. SEMICONDUCTOR INTEGRATED CIRCUITS: A four-channel microelectronic system for neural signal regeneration

    Science.gov (United States)

    Shushan, Xie; Zhigong, Wang; Xiaoying, Lü; Wenyuan, Li; Haixian, Pan

    2009-12-01

    This paper presents a microelectronic system which is capable of making a signal record and functional electric stimulation of an injured spinal cord. As a requirement of implantable engineering for the regeneration microelectronic system, the system is of low noise, low power, small size and high performance. A front-end circuit and two high performance OPAs (operational amplifiers) have been designed for the system with different functions, and the two OPAs are a low-noise low-power two-stage OPA and a constant-gm RTR input and output OPA. The system has been realized in CSMC 0.5-μm CMOS technology. The test results show that the system satisfies the demands of neuron signal regeneration.

  4. Neural circuits in the brain that are activated when mitigating criminal sentences.

    Science.gov (United States)

    Yamada, Makiko; Camerer, Colin F; Fujie, Saori; Kato, Motoichiro; Matsuda, Tetsuya; Takano, Harumasa; Ito, Hiroshi; Suhara, Tetsuya; Takahashi, Hidehiko

    2012-03-27

    In sentencing guilty defendants, jurors and judges weigh 'mitigating circumstances', which create sympathy for a defendant. Here we use functional magnetic resonance imaging to measure neural activity in ordinary citizens who are potential jurors, as they decide on mitigation of punishment for murder. We found that sympathy activated regions associated with mentalising and moral conflict (dorsomedial prefrontal cortex, precuneus and temporo-parietal junction). Sentencing also activated precuneus and anterior cingulate cortex, suggesting that mitigation is based on negative affective responses to murder, sympathy for mitigating circumstances and cognitive control to choose numerical punishments. Individual differences on the inclination to mitigate, the sentence reduction per unit of judged sympathy, correlated with activity in the right middle insula, an area known to represent interoception of visceral states. These results could help the legal system understand how potential jurors actually decide, and contribute to growing knowledge about whether emotion and cognition are integrated sensibly in difficult judgments.

  5. Role of Amygdala and Hippocampus in the Neural Circuit Subserving Conditioned Defeat in Syrian Hamsters

    Science.gov (United States)

    Markham, Chris M.; Taylor, Stacie L.; Huhman, Kim L.

    2010-01-01

    We examined the roles of the amygdala and hippocampus in the formation of emotionally relevant memories using an ethological model of conditioned fear termed conditioned defeat (CD). Temporary inactivation of the ventral, but not dorsal hippocampus (VH, DH, respectively) using muscimol disrupted the acquisition of CD, whereas pretraining VH…

  6. Altered neural connectivity in excitatory and inhibitory cortical circuits in autism

    Directory of Open Access Journals (Sweden)

    Basilis eZikopoulos

    2013-09-01

    Full Text Available Converging evidence from diverse studies suggests that atypical brain connectivity in autism affects in distinct ways short- and long-range cortical pathways, disrupting neural communication and the balance of excitation and inhibition. This hypothesis is based mostly on functional non-invasive studies that show atypical synchronization and connectivity patterns between cortical areas in children and adults with autism. Indirect methods to study the course and integrity of major brain pathways at low resolution show changes in fractional anisotropy or diffusivity of the white matter in autism. Findings in post-mortem brains of adults with autism provide evidence of changes in the fine structure of axons below prefrontal cortices, which communicate over short- or long-range pathways with other cortices and subcortical structures. Here we focus on evidence of cellular and axon features that likely underlie the changes in short- and long-range communication in autism. We review recent findings of changes in the shape, thickness, and volume of brain areas, cytoarchitecture, neuronal morphology, cellular elements, and structural and neurochemical features of individual axons in the white matter, where pathology is evident even in gross images. We relate cellular and molecular features to imaging and genetic studies that highlight a variety of polymorphisms and epigenetic factors that primarily affect neurite growth and synapse formation and function in autism. We report preliminary findings of changes in autism in the ratio of distinct types of inhibitory neurons in prefrontal cortex, known to shape network dynamics and the balance of excitation and inhibition. Finally we present a model that synthesizes diverse findings by relating them to developmental events, with a goal to identify common processes that perturb development in autism and affect neural communication, reflected in altered patterns of attention, social interactions, and language.

  7. Neural circuit of verbal humor comprehension in schizophrenia - an fMRI study

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    Przemysław Adamczyk

    2017-01-01

    Full Text Available Individuals with schizophrenia exhibit problems with understanding the figurative meaning of language. This study evaluates neural correlates of diminished humor comprehension observed in schizophrenia. The study included chronic schizophrenia (SCH outpatients (n = 20, and sex, age and education level matched healthy controls (n = 20. The fMRI punchline based humor comprehension task consisted of 60 stories of which 20 had funny, 20 nonsensical and 20 neutral (not funny punchlines. After the punchlines were presented, the participants were asked to indicate whether the story was comprehensible and how funny it was. Three contrasts were analyzed in both groups reflecting stages of humor processing: abstract vs neutral stories - incongruity detection; funny vs abstract - incongruity resolution and elaboration; and funny vs neutral – complete humor processing. Additionally, parametric modulation analysis was performed using both subjective ratings separately. Between-group comparisons revealed that the SCH subjects had attenuated activation in the right posterior superior temporal gyrus (BA 41 in case of irresolvable incongruity processing of nonsensical puns; in the left dorsomedial middle and superior frontal gyri (BA 8/9 in case of incongruity resolution and elaboration processing of funny puns; and in the interhemispheric dorsal anterior cingulate cortex (BA 24 in case of complete processing of funny puns. Additionally, during comprehensibility ratings the SCH group showed a suppressed activity in the left dorsomedial middle and superior frontal gyri (BA 8/9 and revealed weaker activation during funniness ratings in the left dorsal anterior cingulate cortex (BA 24. Interestingly, these differences in the SCH group were accompanied behaviorally by a protraction of time in both types of rating responses and by indicating funny punchlines less comprehensible. Summarizing, our results indicate neural substrates of humor comprehension

  8. Neural circuit of verbal humor comprehension in schizophrenia - an fMRI study.

    Science.gov (United States)

    Adamczyk, Przemysław; Wyczesany, Miroslaw; Domagalik, Aleksandra; Daren, Artur; Cepuch, Kamil; Błądziński, Piotr; Cechnicki, Andrzej; Marek, Tadeusz

    2017-01-01

    Individuals with schizophrenia exhibit problems with understanding the figurative meaning of language. This study evaluates neural correlates of diminished humor comprehension observed in schizophrenia. The study included chronic schizophrenia (SCH) outpatients (n = 20), and sex, age and education level matched healthy controls (n = 20). The fMRI punchline based humor comprehension task consisted of 60 stories of which 20 had funny, 20 nonsensical and 20 neutral (not funny) punchlines. After the punchlines were presented, the participants were asked to indicate whether the story was comprehensible and how funny it was. Three contrasts were analyzed in both groups reflecting stages of humor processing: abstract vs neutral stories - incongruity detection; funny vs abstract - incongruity resolution and elaboration; and funny vs neutral - complete humor processing. Additionally, parametric modulation analysis was performed using both subjective ratings separately. Between-group comparisons revealed that the SCH subjects had attenuated activation in the right posterior superior temporal gyrus (BA 41) in case of irresolvable incongruity processing of nonsensical puns; in the left dorsomedial middle and superior frontal gyri (BA 8/9) in case of incongruity resolution and elaboration processing of funny puns; and in the interhemispheric dorsal anterior cingulate cortex (BA 24) in case of complete processing of funny puns. Additionally, during comprehensibility ratings the SCH group showed a suppressed activity in the left dorsomedial middle and superior frontal gyri (BA 8/9) and revealed weaker activation during funniness ratings in the left dorsal anterior cingulate cortex (BA 24). Interestingly, these differences in the SCH group were accompanied behaviorally by a protraction of time in both types of rating responses and by indicating funny punchlines less comprehensible. Summarizing, our results indicate neural substrates of humor comprehension processing

  9. Remediation of Childhood Math Anxiety and Associated Neural Circuits through Cognitive Tutoring

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    Iuculano, Teresa; Chen, Lang

    2015-01-01

    Math anxiety is a negative emotional reaction that is characterized by feelings of stress and anxiety in situations involving mathematical problem solving. High math-anxious individuals tend to avoid situations involving mathematics and are less likely to pursue science, technology, engineering, and math-related careers than those with low math anxiety. Math anxiety during childhood, in particular, has adverse long-term consequences for academic and professional success. Identifying cognitive interventions and brain mechanisms by which math anxiety can be ameliorated in children is therefore critical. Here we investigate whether an intensive 8 week one-to-one cognitive tutoring program designed to improve mathematical skills reduces childhood math anxiety, and we identify the neurobiological mechanisms by which math anxiety can be reduced in affected children. Forty-six children in grade 3, a critical early-onset period for math anxiety, participated in the cognitive tutoring program. High math-anxious children showed a significant reduction in math anxiety after tutoring. Remarkably, tutoring remediated aberrant functional responses and connectivity in emotion-related circuits anchored in the basolateral amygdala. Crucially, children with greater tutoring-induced decreases in amygdala reactivity had larger reductions in math anxiety. Our study demonstrates that sustained exposure to mathematical stimuli can reduce math anxiety and highlights the key role of the amygdala in this process. Our findings are consistent with models of exposure-based therapy for anxiety disorders and have the potential to inform the early treatment of a disability that, if left untreated in childhood, can lead to significant lifelong educational and socioeconomic consequences in affected individuals. SIGNIFICANCE STATEMENT Math anxiety during early childhood has adverse long-term consequences for academic and professional success. It is therefore important to identify ways to alleviate

  10. Remediation of Childhood Math Anxiety and Associated Neural Circuits through Cognitive Tutoring.

    Science.gov (United States)

    Supekar, Kaustubh; Iuculano, Teresa; Chen, Lang; Menon, Vinod

    2015-09-09

    Math anxiety is a negative emotional reaction that is characterized by feelings of stress and anxiety in situations involving mathematical problem solving. High math-anxious individuals tend to avoid situations involving mathematics and are less likely to pursue science, technology, engineering, and math-related careers than those with low math anxiety. Math anxiety during childhood, in particular, has adverse long-term consequences for academic and professional success. Identifying cognitive interventions and brain mechanisms by which math anxiety can be ameliorated in children is therefore critical. Here we investigate whether an intensive 8 week one-to-one cognitive tutoring program designed to improve mathematical skills reduces childhood math anxiety, and we identify the neurobiological mechanisms by which math anxiety can be reduced in affected children. Forty-six children in grade 3, a critical early-onset period for math anxiety, participated in the cognitive tutoring program. High math-anxious children showed a significant reduction in math anxiety after tutoring. Remarkably, tutoring remediated aberrant functional responses and connectivity in emotion-related circuits anchored in the basolateral amygdala. Crucially, children with greater tutoring-induced decreases in amygdala reactivity had larger reductions in math anxiety. Our study demonstrates that sustained exposure to mathematical stimuli can reduce math anxiety and highlights the key role of the amygdala in this process. Our findings are consistent with models of exposure-based therapy for anxiety disorders and have the potential to inform the early treatment of a disability that, if left untreated in childhood, can lead to significant lifelong educational and socioeconomic consequences in affected individuals. Significance statement: Math anxiety during early childhood has adverse long-term consequences for academic and professional success. It is therefore important to identify ways to alleviate

  11. The neural correlates of implicit self-relevant processing in low self-esteem: an ERP study.

    Science.gov (United States)

    Yang, Juan; Guan, Lili; Dedovic, Katarina; Qi, Mingming; Zhang, Qinglin

    2012-08-30

    Previous neuroimaging studies have shown that implicit and explicit processing of self-relevant (schematic) material elicit activity in many of the same brain regions. Electrophysiological studies on the neural processing of explicit self-relevant cues have generally supported the view that P300 is an index of attention to self-relevant stimuli; however, there has been no study to date investigating the temporal course of implicit self-relevant processing. The current study seeks to investigate the time course involved in implicit self-processing by comparing processing of self-relevant with non-self-relevant words while subjects are making a judgment about color of the words in an implicit attention task. Sixteen low self-esteem participants were examined using event-related potentials technology (ERP). We hypothesized that this implicit attention task would involve P2 component rather than the P300 component. Indeed, P2 component has been associated with perceptual analysis and attentional allocation and may be more likely to occur in unconscious conditions such as this task. Results showed that latency of P2 component, which indexes the time required for perceptual analysis, was more prolonged in processing self-relevant words compared to processing non-self-relevant words. Our results suggested that the judgment of the color of the word interfered with automatic processing of self-relevant information and resulted in less efficient processing of self-relevant word. Together with previous ERP studies examining processing of explicit self-relevant cues, these findings suggest that the explicit and the implicit processing of self-relevant information would not elicit the same ERP components. Copyright © 2012 Elsevier B.V. All rights reserved.

  12. Neural bases of food-seeking: affect, arousal and reward in corticostriatolimbic circuits.

    Science.gov (United States)

    Balleine, Bernard W

    2005-12-15

    Recent studies suggest that there are multiple 'reward' or 'reward-like' systems that control food seeking; evidence points to two distinct learning processes and four modulatory processes that contribute to the performance of food-related instrumental actions. The learning processes subserve the acquisition of goal-directed and habitual actions and involve the dorsomedial and dorsolateral striatum, respectively. Access to food can function both to reinforce habits and as a reward or goal for actions. Encoding and retrieving the value of a goal appears to be mediated by distinct processes that, contrary to the somatic marker hypothesis, do not appear to depend on a common mechanism but on emotional and more abstract evaluative processes, respectively. The anticipation of reward on the basis of environmental events exerts a further modulatory influence on food seeking that can be dissociated from that of reward itself; earning a reward and anticipating a reward appear to be distinct processes and have been doubly dissociated at the level of the nucleus accumbens. Furthermore, the excitatory influence of reward-related cues can be both quite specific, based on the identity of the reward anticipated, or more general based on its motivational significance. The influence of these two processes on instrumental actions has also been doubly dissociated at the level of the amygdala. Although the complexity of food seeking provides a hurdle for the treatment of eating disorders, the suggestion that these apparently disparate determinants are functionally integrated within larger neural systems may provide novel approaches to these problems.

  13. Stress-protective neural circuits: not all roads lead through the prefrontal cortex.

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    Christianson, John P; Greenwood, Benjamin N

    2014-01-01

    Exposure to an uncontrollable stressor elicits a constellation of physiological and behavioral sequel in laboratory rats that often reflect aspects of anxiety and other emotional disruptions. We review evidence suggesting that plasticity within the serotonergic dorsal raphe nucleus (DRN) is critical to the expression of uncontrollable stressor-induced anxiety. Specifically, after uncontrollable stressor exposure subsequent anxiogenic stimuli evoke greater 5-HT release in DRN terminal regions including the amygdala and striatum; and pharmacological blockade of postsynaptic 5-HT(2C) receptors in these regions prevents expression of stressor-induced anxiety. Importantly, the controllability of stress, the presence of safety signals, and a history of exercise mitigate the expression of stressor-induced anxiety. These stress-protective factors appear to involve distinct neural substrates; with stressor controllability requiring the medial prefrontal cortex, safety signals the insular cortex and exercise affecting the 5-HT system directly. Knowledge of the distinct yet converging mechanisms underlying these stress-protective factors could provide insight into novel strategies for the treatment and prevention of stress-related psychiatric disorders.

  14. With a little help from my friends: androgens tap BDNF signaling pathways to alter neural circuits.

    Science.gov (United States)

    Ottem, E N; Bailey, D J; Jordan, C L; Breedlove, S M

    2013-06-03

    Gonadal androgens are critical for the development and maintenance of sexually dimorphic regions of the male nervous system, which is critical for male-specific behavior and physiological functioning. In rodents, the motoneurons of the spinal nucleus of the bulbocavernosus (SNB) provide a useful example of a neural system dependent on androgen. Unless rescued by perinatal androgens, the SNB motoneurons will undergo apoptotic cell death. In adulthood, SNB motoneurons remain dependent on androgen, as castration leads to somal atrophy and dendritic retraction. In a second vertebrate model, the zebra finch, androgens are critical for the development of several brain nuclei involved in song production in males. Androgen deprivation during a critical period during postnatal development disrupts song acquisition and dimorphic size-associated nuclei. Mechanisms by which androgens exert masculinizing effects in each model system remain elusive. Recent studies suggest that brain-derived neurotrophic factor (BDNF) may play a role in androgen-dependent masculinization and maintenance of both SNB motoneurons and song nuclei of birds. This review aims to summarize studies demonstrating that BDNF signaling via its tyrosine receptor kinase (TrkB) receptor may work cooperatively with androgens to maintain somal and dendritic morphology of SNB motoneurons. We further describe studies that suggest the cellular origin of BDNF is of particular importance in androgen-dependent regulation of SNB motoneurons. We review evidence that androgens and BDNF may synergistically influence song development and plasticity in bird species. Finally, we provide hypothetical models of mechanisms that may underlie androgen- and BDNF-dependent signaling pathways. Copyright © 2012 IBRO. Published by Elsevier Ltd. All rights reserved.

  15. Nitric oxide in the flocculus works the inhibitory neural circuits after unilateral labyrinthectomy.

    Science.gov (United States)

    Kitahara, T; Takeda, N; Kubo, T; Kiyama, H

    1999-01-09

    We previously reported that nitric oxide (NO) production in the unipolar brush (UB) cells is involved in vestibular compensation [T. Kitahara, N. Takeda, P.C. Emson, T. Kubo, H. Kiyama, Changes in nitric oxide synthase-like immunoreactivities in unipolar brush cells in the rat cerebellar flocculus after unilateral labyrinthectomy, Brain Res. 765 (1997) 1-6]. To further elucidate the role of NO-mediated signaling in flocculus after unilateral labyrinthectomy (UL), we examined UL-induced Fos expression, a marker of neural activity, in vestibular brainstem with continuous floccular infusions of Nomega-nitro-l-arginine methyl ester (l-NAME), an inhibitor of NO synthase (NOS). After UL with floccular l-NAME infusions, Fos expression appeared in bilateral medial vestibular (MVe) and prepositus hypoglossal (PrH) nuclei. After UL with floccular saline infusions, however, Fos expression was observed only in the ipsi-MVe and contra-PrH. Furthermore, it has been revealed that UL with l-NAME infusions caused more severe vestibulo-ocular disturbances than UL with saline infusions at the initial stage [Kitahara et al. Brain Res. 765 (1997) 1-6]. Therefore, it is suggested that UL with floccular l-NAME infusions activates the contra-MVe and ipsi-PrH neurons and causes more severe imbalance between intervestibular nuclear activities at the initial stage. NO-mediated signaling in flocculus could be a possible driving force of the flocculus-mediated inhibition on the contra-MVe and ipsi-PrH at the initial stage of vestibular compensation. Copyright 1999 Elsevier Science B.V.

  16. Enabling functional neural circuit simulations with distributed computing of neuromodulated plasticity

    Directory of Open Access Journals (Sweden)

    Wiebke ePotjans

    2010-11-01

    Full Text Available A major puzzle in the field of computational neuroscience is how to relate system-level learning in higher organisms to synaptic plasticity. Recently, plasticity rules depending not only on pre- and post-synaptic activity but also on a third, non-local neuromodulatory signal have emerged as key candidates to bridge the gap between the macroscopic and the microscopic level of learning. Crucial insights into this topic are expected to be gained from simulations of neural systems, as these allow the simultaneous study of the multiple spatial and temporal scales that are involved in the problem. In particular, synaptic plasticity can be studied during the whole learning process, i.e. on a time scale of minutes to hours and across multiple brain areas. Implementing neuromodulated plasticity in large-scale network simulations where the neuromodulatory signal is dynamically generated by the network itself is challenging, because the network structure is commonly defined purely by the connectivity graph without explicit reference to the embedding of the nodes in physical space. Furthermore, the simulation of networks with realistic connectivity entails the use of distributed computing. A neuromodulated synapse must therefore be informed in an efficient way about the neuromodulatory signal, which is typically generated by a population of neurons located on different machines than either the pre- or post-synaptic neuron. Here, we develop a general framework to solve the problem of implementing neuromodulated plasticity in a time-driven distributed simulation, without reference to a particular implementation language, neuromodulator or neuromodulated plasticity mechanism. We implement our framework in the simulator NEST and demonstrate excellent scaling up to 1024 processors for simulations of a recurrent network incorporating neuromodulated spike-timing dependent plasticity.

  17. Extracting the Behaviorally Relevant Stimulus: Unique Neural Representation of Farnesol, a Component of the Recruitment Pheromone of Bombus terrestris.

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    Martin F Strube-Bloss

    Full Text Available To trigger innate behavior, sensory neural networks are pre-tuned to extract biologically relevant stimuli. Many male-female or insect-plant interactions depend on this phenomenon. Especially communication among individuals within social groups depends on innate behaviors. One example is the efficient recruitment of nest mates by successful bumblebee foragers. Returning foragers release a recruitment pheromone in the nest while they perform a 'dance' behavior to activate unemployed nest mates. A major component of this pheromone is the sesquiterpenoid farnesol. How farnesol is processed and perceived by the olfactory system, has not yet been identified. It is much likely that processing farnesol involves an innate mechanism for the extraction of relevant information to trigger a fast and reliable behavioral response. To test this hypothesis, we used population response analyses of 100 antennal lobe (AL neurons recorded in alive bumblebee workers under repeated stimulation with four behaviorally different, but chemically related odorants (geraniol, citronellol, citronellal and farnesol. The analysis identified a unique neural representation of the recruitment pheromone component compared to the other odorants that are predominantly emitted by flowers. The farnesol induced population activity in the AL allowed a reliable separation of farnesol from all other chemically related odor stimuli we tested. We conclude that the farnesol induced population activity may reflect a predetermined representation within the AL-neural network allowing efficient and fast extraction of a behaviorally relevant stimulus. Furthermore, the results show that population response analyses of multiple single AL-units may provide a powerful tool to identify distinct representations of behaviorally relevant odors.

  18. Extracting the Behaviorally Relevant Stimulus: Unique Neural Representation of Farnesol, a Component of the Recruitment Pheromone of Bombus terrestris.

    Science.gov (United States)

    Strube-Bloss, Martin F; Brown, Austin; Spaethe, Johannes; Schmitt, Thomas; Rössler, Wolfgang

    2015-01-01

    To trigger innate behavior, sensory neural networks are pre-tuned to extract biologically relevant stimuli. Many male-female or insect-plant interactions depend on this phenomenon. Especially communication among individuals within social groups depends on innate behaviors. One example is the efficient recruitment of nest mates by successful bumblebee foragers. Returning foragers release a recruitment pheromone in the nest while they perform a 'dance' behavior to activate unemployed nest mates. A major component of this pheromone is the sesquiterpenoid farnesol. How farnesol is processed and perceived by the olfactory system, has not yet been identified. It is much likely that processing farnesol involves an innate mechanism for the extraction of relevant information to trigger a fast and reliable behavioral response. To test this hypothesis, we used population response analyses of 100 antennal lobe (AL) neurons recorded in alive bumblebee workers under repeated stimulation with four behaviorally different, but chemically related odorants (geraniol, citronellol, citronellal and farnesol). The analysis identified a unique neural representation of the recruitment pheromone component compared to the other odorants that are predominantly emitted by flowers. The farnesol induced population activity in the AL allowed a reliable separation of farnesol from all other chemically related odor stimuli we tested. We conclude that the farnesol induced population activity may reflect a predetermined representation within the AL-neural network allowing efficient and fast extraction of a behaviorally relevant stimulus. Furthermore, the results show that population response analyses of multiple single AL-units may provide a powerful tool to identify distinct representations of behaviorally relevant odors.

  19. Altered behavioral performance and live imaging of circuit-specific neural deficiencies in a zebrafish model for psychomotor retardation.

    Directory of Open Access Journals (Sweden)

    David Zada

    2014-09-01

    Full Text Available The mechanisms and treatment of psychomotor retardation, which includes motor and cognitive impairment, are indefinite. The Allan-Herndon-Dudley syndrome (AHDS is an X-linked psychomotor retardation characterized by delayed development, severe intellectual disability, muscle hypotonia, and spastic paraplegia, in combination with disturbed thyroid hormone (TH parameters. AHDS has been associated with mutations in the monocarboxylate transporter 8 (mct8/slc16a2 gene, which is a TH transporter. In order to determine the pathophysiological mechanisms of AHDS, MCT8 knockout mice were intensively studied. Although these mice faithfully replicated the abnormal serum TH levels, they failed to exhibit the neurological and behavioral symptoms of AHDS patients. Here, we generated an mct8 mutant (mct8-/- zebrafish using zinc-finger nuclease (ZFN-mediated targeted gene editing system. The elimination of MCT8 decreased the expression levels of TH receptors; however, it did not affect the expression of other TH-related genes. Similar to human patients, mct8-/- larvae exhibited neurological and behavioral deficiencies. High-throughput behavioral assays demonstrated that mct8-/- larvae exhibited reduced locomotor activity, altered response to external light and dark transitions and an increase in sleep time. These deficiencies in behavioral performance were associated with altered expression of myelin-related genes and neuron-specific deficiencies in circuit formation. Time-lapse imaging of single-axon arbors and synapses in live mct8-/- larvae revealed a reduction in filopodia dynamics and axon branching in sensory neurons and decreased synaptic density in motor neurons. These phenotypes enable assessment of the therapeutic potential of three TH analogs that can enter the cells in the absence of MCT8. The TH analogs restored the myelin and axon outgrowth deficiencies in mct8-/- larvae. These findings suggest a mechanism by which MCT8 regulates neural circuit

  20. A neural circuit for robust time-to-contact estimation based on primate MST.

    Science.gov (United States)

    Browning, N Andrew

    2012-11-01

    Time-to-contact (TTC) estimation is beneficial for visual navigation. It can be estimated from an image projection, either in a camera or on the retina, by looking at the rate of expansion of an object. When expansion rate (E) is properly defined, TTC = 1/E. Primate dorsal MST cells have receptive field structures suited to the estimation of expansion and TTC. However, the role of MST cells in TTC estimation has been discounted because of large receptive fields, the fact that neither they nor preceding brain areas appear to decompose the motion field to estimate divergence, and a lack of experimental data. This letter demonstrates mathematically that template models of dorsal MST cells can be constructed such that the output of the template match provides an accurate and robust estimate of TTC. The template match extracts the relevant components of the motion field and scales them such that the output of each component of the template match is an estimate of expansion. It then combines these component estimates to provide a mean estimate of expansion across the object. The output of model MST provides a direct measure of TTC. The ViSTARS model of primate visual navigation was updated to incorporate the modified templates. In ViSTARS and in primates, speed is represented as a population code in V1 and MT. A population code for speed complicates TTC estimation from a template match. Results presented in this letter demonstrate that the updated template model of MST accurately codes TTC across a population of model MST cells. We conclude that the updated template model of dorsal MST simultaneously and accurately codes TTC and heading regardless of receptive field size, object size, or motion representation. It is possible that a subpopulation of MST cells in primates represents expansion in this way.

  1. Photonic Integrated Circuit (PIC) Device Structures: Background, Fabrication Ecosystem, Relevance to Space Systems Applications, and Discussion of Related Radiation Effects

    Science.gov (United States)

    Alt, Shannon

    2016-01-01

    Electronic integrated circuits are considered one of the most significant technological advances of the 20th century, with demonstrated impact in their ability to incorporate successively higher numbers transistors and construct electronic devices onto a single CMOS chip. Photonic integrated circuits (PICs) exist as the optical analog to integrated circuits; however, in place of transistors, PICs consist of numerous scaled optical components, including such "building-block" structures as waveguides, MMIs, lasers, and optical ring resonators. The ability to construct electronic and photonic components on a single microsystems platform offers transformative potential for the development of technologies in fields including communications, biomedical device development, autonomous navigation, and chemical and atmospheric sensing. Developing on-chip systems that provide new avenues for integration and replacement of bulk optical and electro-optic components also reduces size, weight, power and cost (SWaP-C) limitations, which are important in the selection of instrumentation for specific flight projects. The number of applications currently emerging for complex photonics systems-particularly in data communications-warrants additional investigations when considering reliability for space systems development. This Body of Knowledge document seeks to provide an overview of existing integrated photonics architectures; the current state of design, development, and fabrication ecosystems in the United States and Europe; and potential space applications, with emphasis given to associated radiation effects and reliability.

  2. Infant cognitive training preshapes learning-relevant prefrontal circuits for adult learning: learning-induced tagging of dendritic spines.

    Science.gov (United States)

    Bock, Joerg; Poeggel, Gerd; Gruss, Michael; Wingenfeld, Katharina; Braun, Katharina

    2014-11-01

    Work in various animal models has demonstrated that cognitive training in infancy has a greater effect on adult cognitive performance than pretraining in adulthood. Since the underlying synaptic mechanisms are unclear, the aim of this study was to test the working hypothesis that associative training "preshapes" synaptic circuits in the developing infant brain and thereby improves learning in adulthood. Using a two-way active avoidance (TWA) paradigm, we found that avoidance training during infancy, even though the infant rats were not capable to learn a successful avoidance strategy, improves avoidance learning in adulthood. On the neuroanatomical level we show here for the first time that infant TWA training in the ventromedial prefrontal cortex suppresses developmental spine formation. In contrast in the lateral orbitofrontal cortex, developmental spine pruning is suppressed, possibly by "tagging" activated synapses, which thereby are protected from being eliminated. Moreover, we demonstrate that infant TWA training alters learning-induced synaptic plasticity in the adult brain. The synaptic and dendritic changes correlate with specific behavioral parameters. Taken together, these results support the working hypothesis that infant cognitive training interferes with developmental reorganization and maturation of dendritic spines and thereby "optimizes" prefrontal neuronal circuits for adult learning. © The Author 2013. Published by Oxford University Press. All rights reserved. For Permissions, please e-mail: journals.permissions@oup.com.

  3. The Use of Modular, Electronic Neuron Simulators for Neural Circuit Construction Produces Learning Gains in an Undergraduate Anatomy and Physiology Course.

    Science.gov (United States)

    Petto, Andrew; Fredin, Zachary; Burdo, Joseph

    2017-01-01

    During the spring of 2016 at the University of Wisconsin-Milwaukee, we implemented a novel educational technology designed to teach undergraduates about the nervous system while allowing them to physically construct their own neural circuits. Modular, electronic neuron simulators called NeuroBytes were used by the students in BIOSCI202 Anatomy and Physiology I, a four-credit course consisting of three hours per week each of lecture and laboratory time. 162 students participated in the laboratory sessions that covered reflexes; 83 in the experimental sections used the NeuroBytes to build a model of the patellar tendon reflex, while 79 in the control sections participated in alternate reflex curricula. To address the question of whether or not the NeuroBytes-based patellar tendon reflex simulation brought about learning gains, the control and experimental group students underwent pre/post testing before and after their laboratory sections. We found that for several of the neuroscience and physiology concepts assessed on the test, the experimental group students had significantly greater declarative learning gains between the pre- and post-test as compared to the control group students. While there are numerous virtual neuroscience education tools available to undergraduate educators, there are relatively few designed to engage students in the basics of electrophysiology and neural circuitry using physical manipulatives, and none to our knowledge that allow them to build circuits from functioning hand-held "neurons."

  4. Multi-array silicon probes with integrated optical fibers: light-assisted perturbation and recording of local neural circuits in the behaving animal.

    Science.gov (United States)

    Royer, Sébastien; Zemelman, Boris V; Barbic, Mladen; Losonczy, Attila; Buzsáki, György; Magee, Jeffrey C

    2010-06-01

    Recordings of large neuronal ensembles and neural stimulation of high spatial and temporal precision are important requisites for studying the real-time dynamics of neural networks. Multiple-shank silicon probes enable large-scale monitoring of individual neurons. Optical stimulation of genetically targeted neurons expressing light-sensitive channels or other fast (milliseconds) actuators offers the means for controlled perturbation of local circuits. Here we describe a method to equip the shanks of silicon probes with micron-scale light guides for allowing the simultaneous use of the two approaches. We then show illustrative examples of how these compact hybrid electrodes can be used in probing local circuits in behaving rats and mice. A key advantage of these devices is the enhanced spatial precision of stimulation that is achieved by delivering light close to the recording sites of the probe. When paired with the expression of light-sensitive actuators within genetically specified neuronal populations, these devices allow the relatively straightforward and interpretable manipulation of network activity.

  5. Neural representation of calling songs and their behavioral relevance in the grasshopper auditory system

    Directory of Open Access Journals (Sweden)

    Gundula eMeckenhäuser

    2014-12-01

    Full Text Available Acoustic communication plays a key role for mate attraction in grasshoppers. Males use songs to advertise themselves to females. Females evaluate the song pattern, a repetitive structure of sound syllables separated by short pauses, to recognize a conspecific male and as proxy to its fitness. In their natural habitat females often receive songs with degraded temporal structure. Perturbations may, for example, result from the overlap with other songs. We studied the response behavior of females to songs that show different signal degradations. A perturbation of an otherwise attractive song at later positions in the syllable diminished the behavioral response, whereas the same perturbation at the onset of a syllable did not affect song attractiveness. We applied naïve Bayes classifiers to the spike trains of identified neurons in the auditory pathway to explore how sensory evidence about the acoustic stimulus and its attractiveness is represented in the neuronal responses. We find that populations of three or more neurons were sufficient to reliably decode the acoustic stimulus and to predict its behavioral relevance from the single-trial integrated firing rate. A simple model of decision making simulates the female response behavior. It computes for each syllable the likelihood for the presence of an attractive song pattern as evidenced by the population firing rate. Integration across syllables allows the likelihood to reach a decision threshold and to elicit the behavioral response. The close match between model performance and animal behavior shows that a spike rate code is sufficient to enable song pattern recognition.

  6. Transport and metabolism at blood-brain interfaces and in neural cells: relevance to bilirubin-induced encephalopathy

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    Silvia eGazzin

    2012-05-01

    Full Text Available Bilirubin, the end-product of heme catabolism, circulates in non pathological plasma mostly as a protein-bound species. When bilirubin concentration builds up, the free fraction of the molecule increases. Unbound bilirubin then diffuses across blood-brain interfaces into the brain, where it accumulates and exerts neurotoxic effects. In this classical view of bilirubin neurotoxicity, blood-brain interfaces act merely as structural barriers impeding the penetration of the pigment-bound carrier protein, and neural cells are considered as passive targets of its toxicity. Yet, the role of blood-brain interfaces in the occurrence of bilirubin encephalopathy appears more complex than being simple barriers to the diffusion of bilirubin, and neural cells such as astrocytes and neurons can play an active role in controlling the balance between the neuroprotective and neurotoxic effects of bilirubin. This article reviews the emerging in vivo and in vitro data showing that transport and metabolic detoxification mechanisms at the blood-brain and blood-CSF barriers may modulate bilirubin flux across both cellular interfaces, and that these protective functions can be affected in chronic hyperbilirubinemia. Then the in vivo and in vitro arguments in favor of the physiological antioxidant function of intracerebral bilirubin are presented, as well as with the potential role of transporters such as ABCC-1 and metabolizing enzymes such as cytochromes P-450 in setting the cerebral cell- and structure-specific toxicity of bilirubin following hyperbilirubinemia. The relevance of these data to the pathophysiology of bilirubin-induced neurological diseases is discussed.

  7. Propofol at Clinically Relevant Concentrations Increases Neuronal Differentiation but Is Not Toxic to Hippocampal Neural Precursor Cells In Vitro

    Science.gov (United States)

    Sall, Jeffrey W.; Stratmann, Greg; Leong, Jason; Woodward, Elliott; Bickler, Philip E.

    2012-01-01

    Background Propofol in the early postnatal period has been shown to cause brain cell death. One proposed mechanism for cognitive dysfunction after anesthesia is alteration of neural stem cell function and neurogenesis. We examined the effect of propofol on neural precursor or stem cells (NPCs) grown in vitro. Methods Hippocampal derived NPCs from postnatal day 2 rats were exposed to propofol or to Diprivan. NPCs were then analyzed for bromodeoxyuridine incorporation to measure proliferation. Cell death was measured by lactate dehydrogenase release. Immunocytochemistry was used to evaluate the expression of neuronal and glial markers in differentiating NPCs exposed to propofol. Results Propofol dose dependently increases the release of lactate dehydrogenase from NPCs under both proliferating and differentiating conditions at supraclinical concentrations (> 7.1μM). Both Diprivan and propofol had the same effect on NPCs. Propofol mediated release of lactate dehydrogenase is not inhibited by blocking the γ-aminobutyric acid type A receptor or extracellular calcium influx and is not mediated by caspase-3/7. Direct γ-aminobutyric acid type A receptor activation did not have the same effect. In differentiating NPCs 6 h of propofol at 2.1 μM increased the number neurons but not glial cells 4 days later. Increased neuronal differentiation was not blocked by Bicuculline. Conclusions Only supraclinical concentrations of propofol or Diprivan kill NPCs in culture by a non-γ-aminobutyric acid type A, noncaspase 3 mechanism. Clinically relevant doses of propofol increase neuronal fate choice by a non-γ-aminobutyric acid type A mechanism. PMID:23001052

  8. A neural circuit transforming temporal periodicity information into a rate-based representation in the mammalian auditory system

    DEFF Research Database (Denmark)

    Dicke, Ulrike; Ewert, Stephan D.; Dau, Torsten

    2007-01-01

    to previous modeling studies, the present circuit does not employ a continuously changing temporal parameter to obtain different best modulation frequencies BMFs of the IC bandpass units. Instead, different BMFs are yielded from varying the number of input units projecting onto different bandpass units...

  9. Neural network modelling and dynamical system theory: are they relevant to study the governing dynamics of association football players?

    Science.gov (United States)

    Dutt-Mazumder, Aviroop; Button, Chris; Robins, Anthony; Bartlett, Roger

    2011-12-01

    Recent studies have explored the organization of player movements in team sports using a range of statistical tools. However, the factors that best explain the performance of association football teams remain elusive. Arguably, this is due to the high-dimensional behavioural outputs that illustrate the complex, evolving configurations typical of team games. According to dynamical system analysts, movement patterns in team sports exhibit nonlinear self-organizing features. Nonlinear processing tools (i.e. Artificial Neural Networks; ANNs) are becoming increasingly popular to investigate the coordination of participants in sports competitions. ANNs are well suited to describing high-dimensional data sets with nonlinear attributes, however, limited information concerning the processes required to apply ANNs exists. This review investigates the relative value of various ANN learning approaches used in sports performance analysis of team sports focusing on potential applications for association football. Sixty-two research sources were summarized and reviewed from electronic literature search engines such as SPORTDiscus, Google Scholar, IEEE Xplore, Scirus, ScienceDirect and Elsevier. Typical ANN learning algorithms can be adapted to perform pattern recognition and pattern classification. Particularly, dimensionality reduction by a Kohonen feature map (KFM) can compress chaotic high-dimensional datasets into low-dimensional relevant information. Such information would be useful for developing effective training drills that should enhance self-organizing coordination among players. We conclude that ANN-based qualitative analysis is a promising approach to understand the dynamical attributes of association football players.

  10. Experimental Analysis of the Input Variables’ Relevance to Forecast Next Day’s Aggregated Electric Demand Using Neural Networks

    Directory of Open Access Journals (Sweden)

    Pablo García

    2013-06-01

    Full Text Available Thanks to the built in intelligence (deployment of new intelligent devices and sensors in places where historically they were not present, the Smart Grid and Microgrid paradigms are able to take advantage from aggregated load forecasting, which opens the door for the implementation of new algorithms to seize this information for optimization and advanced planning. Therefore, accuracy in load forecasts will potentially have a big impact on key operation factors for the future Smart Grid/Microgrid-based energy network like user satisfaction and resource saving, and new methods to achieve an efficient prediction in future energy landscapes (very different from the centralized, big area networks studied so far. This paper proposes different improved models to forecast next day’s aggregated load using artificial neural networks, taking into account the variables that are most relevant for the aggregated. In particular, seven models based on the multilayer perceptron will be proposed, progressively adding input variables after analyzing the influence of climate factors on aggregated load. The results section presents the forecast from the proposed models, obtained from real data.

  11. The development of neural synchrony and large-scale cortical networks during adolescence: relevance for the pathophysiology of schizophrenia and neurodevelopmental hypothesis.

    Science.gov (United States)

    Uhlhaas, Peter J; Singer, Wolf

    2011-05-01

    Recent data from developmental cognitive neuroscience highlight the profound changes in the organization and function of cortical networks during the transition from adolescence to adulthood. While previous studies have focused on the development of gray and white matter, recent evidence suggests that brain maturation during adolescence extends to fundamental changes in the properties of cortical circuits that in turn promote the precise temporal coding of neural activity. In the current article, we will highlight modifications in the amplitude and synchrony of neural oscillations during adolescence that may be crucial for the emergence of cognitive deficits and psychotic symptoms in schizophrenia. Specifically, we will suggest that schizophrenia is associated with impaired parameters of synchronous oscillations that undergo changes during late brain maturation, suggesting an important role of adolescent brain development for the understanding, treatment, and prevention of the disorder. © The Author 2011. Published by Oxford University Press on behalf of the Maryland Psychiatric Research Center. All rights reserved.

  12. A Leptin Analog Locally Produced in the Brain Acts via a Conserved Neural Circuit to Modulate Obesity-Linked Behaviors in Drosophila.

    Science.gov (United States)

    Beshel, Jennifer; Dubnau, Josh; Zhong, Yi

    2017-01-10

    Leptin, a typically adipose-derived "satiety hormone," has a well-established role in weight regulation. Here we describe a functionally conserved model of genetically induced obesity in Drosophila by manipulating the fly leptin analog unpaired 1 (upd1). Unexpectedly, cell-type-specific knockdown reveals upd1 in the brain, not the adipose tissue, mediates obesity-related traits. Disrupting brain-derived upd1 in flies leads to all the hallmarks of mammalian obesity: increased attraction to food cues, increased food intake, and increased weight. These effects are mediated by domeless receptors on neurons expressing Drosophila neuropeptide F, the orexigenic mammalian neuropeptide Y homolog. In vivo two-photon imaging reveals upd1 and domeless inhibit this hedonic signal in fed animals. Manipulations along this central circuit also create hypersensitivity to obesogenic conditions, emphasizing the critical interplay between biological predisposition and environment in overweight and obesity prevalence. We propose adipose- and brain-derived upd/leptin may control differing features of weight regulation through distinct neural circuits. Copyright © 2017 Elsevier Inc. All rights reserved.

  13. Sites of Plasticity in the Neural Circuit Mediating Tentacle Withdrawal in the Snail Helix aspersa: Implications for Behavioral Change and Learning Kinetics

    Science.gov (United States)

    Prescott, Steven A.; Chase, Ronald

    1999-01-01

    The tentacle withdrawal reflex of the snail Helix aspersa exhibits a complex combination of habituation and sensitization consistent with the dual-process theory of plasticity. Habituation, sensitization, or a combination of both were elicited by varying stimulation parameters and lesion condition. Analysis of response plasticity shows that the late phase of the response is selectively enhanced by sensitization, whereas all phases are decreased by habituation. Previous data have shown that tentacle withdrawal is mediated conjointly by parallel monosynaptic and polysynaptic pathways. The former mediates the early phase, whereas the latter mediates the late phase of the response. Plastic loci were identified by stimulating and recording at different points within the neural circuit, in combination with selective lesions. Results indicate that depression occurs at an upstream locus, before circuit divergence, and is therefore expressed in all pathways, whereas facilitation requires downstream facilitatory neurons and is selectively expressed in polysynaptic pathways. Differential expression of plasticity between pathways helps explain the behavioral manifestation of depression and facilitation. A simple mathematical model is used to show how serial positioning of depression and facilitation can explain the kinetics of dual-process learning. These results illustrate how the position of cellular plasticity in the network affects behavioral change and how forms of plasticity can interact to determine the kinetics of the net changes. PMID:10509707

  14. Visual motion imagery neurofeedback based on the hMT+/V5 complex: evidence for a feedback-specific neural circuit involving neocortical and cerebellar regions

    Science.gov (United States)

    Banca, Paula; Sousa, Teresa; Catarina Duarte, Isabel; Castelo-Branco, Miguel

    2015-12-01

    Objective. Current approaches in neurofeedback/brain-computer interface research often focus on identifying, on a subject-by-subject basis, the neural regions that are best suited for self-driven modulation. It is known that the hMT+/V5 complex, an early visual cortical region, is recruited during explicit and implicit motion imagery, in addition to real motion perception. This study tests the feasibility of training healthy volunteers to regulate the level of activation in their hMT+/V5 complex using real-time fMRI neurofeedback and visual motion imagery strategies. Approach. We functionally localized the hMT+/V5 complex to further use as a target region for neurofeedback. An uniform strategy based on motion imagery was used to guide subjects to neuromodulate hMT+/V5. Main results. We found that 15/20 participants achieved successful neurofeedback. This modulation led to the recruitment of a specific network as further assessed by psychophysiological interaction analysis. This specific circuit, including hMT+/V5, putative V6 and medial cerebellum was activated for successful neurofeedback runs. The putamen and anterior insula were recruited for both successful and non-successful runs. Significance. Our findings indicate that hMT+/V5 is a region that can be modulated by focused imagery and that a specific cortico-cerebellar circuit is recruited during visual motion imagery leading to successful neurofeedback. These findings contribute to the debate on the relative potential of extrinsic (sensory) versus intrinsic (default-mode) brain regions in the clinical application of neurofeedback paradigms. This novel circuit might be a good target for future neurofeedback approaches that aim, for example, the training of focused attention in disorders such as ADHD.

  15. Curcumin Alters Neural Plasticity and Viability of Intact Hippocampal Circuits and Attenuates Behavioral Despair and COX-2 Expression in Chronically Stressed Rats.

    Science.gov (United States)

    Choi, Ga-Young; Kim, Hyun-Bum; Hwang, Eun-Sang; Lee, Seok; Kim, Min-Ji; Choi, Ji-Young; Lee, Sung-Ok; Kim, Sang-Seong; Park, Ji-Ho

    2017-01-01

    Curcumin is a major diarylheptanoid component of Curcuma longa with traditional usage for anxiety and depression. It has been known for the anti-inflammatory, antistress, and neurotropic effects. Here we examined curcumin effect in neural plasticity and cell viability. 60-channel multielectrode array was applied on organotypic hippocampal slice cultures (OHSCs) to monitor the effect of 10 μM curcumin in long-term depression (LTD) through low-frequency stimulation (LFS) to the Schaffer collaterals and commissural pathways. Cell viability was assayed by propidium iodide uptake test in OHSCs. In addition, the influence of oral curcumin administration on rat behavior was assessed with the forced swim test (FST). Finally, protein expression levels of brain-derived neurotrophic factor (BDNF) and cyclooxygenase-2 (COX-2) were measured by Western blot in chronically stressed rats. Our results demonstrated that 10 μM curcumin attenuated LTD and reduced cell death. It also recovered the behavior immobility of FST, rescued the attenuated BDNF expression, and inhibited the enhancement of COX-2 expression in stressed animals. These findings indicate that curcumin can enhance postsynaptic electrical reactivity and cell viability in intact neural circuits with antidepressant-like effects, possibly through the upregulation of BDNF and reduction of inflammatory factors in the brain.

  16. Curcumin Alters Neural Plasticity and Viability of Intact Hippocampal Circuits and Attenuates Behavioral Despair and COX-2 Expression in Chronically Stressed Rats

    Directory of Open Access Journals (Sweden)

    Ga-Young Choi

    2017-01-01

    Full Text Available Curcumin is a major diarylheptanoid component of Curcuma longa with traditional usage for anxiety and depression. It has been known for the anti-inflammatory, antistress, and neurotropic effects. Here we examined curcumin effect in neural plasticity and cell viability. 60-channel multielectrode array was applied on organotypic hippocampal slice cultures (OHSCs to monitor the effect of 10 μM curcumin in long-term depression (LTD through low-frequency stimulation (LFS to the Schaffer collaterals and commissural pathways. Cell viability was assayed by propidium iodide uptake test in OHSCs. In addition, the influence of oral curcumin administration on rat behavior was assessed with the forced swim test (FST. Finally, protein expression levels of brain-derived neurotrophic factor (BDNF and cyclooxygenase-2 (COX-2 were measured by Western blot in chronically stressed rats. Our results demonstrated that 10 μM curcumin attenuated LTD and reduced cell death. It also recovered the behavior immobility of FST, rescued the attenuated BDNF expression, and inhibited the enhancement of COX-2 expression in stressed animals. These findings indicate that curcumin can enhance postsynaptic electrical reactivity and cell viability in intact neural circuits with antidepressant-like effects, possibly through the upregulation of BDNF and reduction of inflammatory factors in the brain.

  17. Defining biotypes for depression and anxiety based on large-scale circuit dysfunction: a theoretical review of the evidence and future directions for clinical translation.

    Science.gov (United States)

    Williams, Leanne M

    2017-01-01

    Complex emotional, cognitive and self-reflective functions rely on the activation and connectivity of large-scale neural circuits. These circuits offer a relevant scale of focus for conceptualizing a taxonomy for depression and anxiety based on specific profiles (or biotypes) of neural circuit dysfunction. Here, the theoretical review first outlines the current consensus as to what constitutes the organization of large-scale circuits in the human brain identified using parcellation and meta-analysis. The focus is on neural circuits implicated in resting reflection (default mode), detection of "salience," affective processing ("threat" and "reward"), "attention," and "cognitive control." Next, the current evidence regarding which type of dysfunctions in these circuits characterize depression and anxiety disorders is reviewed, with an emphasis on published meta-analyses and reviews of circuit dysfunctions that have been identified in at least two well-powered case:control studies. Grounded in the review of these topics, a conceptual framework is proposed for considering neural circuit-defined "biotypes." In this framework, biotypes are defined by profiles of extent of dysfunction on each large-scale circuit. The clinical implications of a biotype approach for guiding classification and treatment of depression and anxiety is considered. Future research directions will develop the validity and clinical utility of a neural circuit biotype model that spans diagnostic categories and helps to translate neuroscience into clinical practice in the real world. © 2016 Wiley Periodicals, Inc.

  18. Forgetting the best when predicting the worst: Preliminary observations on neural circuit function in adolescent social anxiety

    Directory of Open Access Journals (Sweden)

    Johanna M. Jarcho

    2015-06-01

    Full Text Available Social anxiety disorder typically begins in adolescence, a sensitive period for brain development, when increased complexity and salience of peer relationships requires novel forms of social learning. Disordered social learning in adolescence may explain how brain dysfunction promotes social anxiety. Socially anxious adolescents (n = 15 and adults (n = 19 and non-anxious adolescents (n = 24 and adults (n = 32 predicted, then received, social feedback from high and low-value peers while undergoing functional magnetic resonance imaging (fMRI. A surprise recall task assessed memory biases for feedback. Neural correlates of social evaluation prediction errors (PEs were assessed by comparing engagement to expected and unexpected positive and negative feedback. For socially anxious adolescents, but not adults or healthy participants of either age group, PEs elicited heightened striatal activity and negative fronto-striatal functional connectivity. This occurred selectively to unexpected positive feedback from high-value peers and corresponded with impaired memory for social feedback. While impaired memory also occurred in socially-anxious adults, this impairment was unrelated to brain-based PE activity. Thus, social anxiety in adolescence may relate to altered neural correlates of PEs that contribute to impaired learning about social feedback. Small samples necessitate replication. Nevertheless, results suggest that the relationship between learning and fronto-striatal function may attenuate as development progresses.

  19. Conflict Resolution as Near-Threshold Decision-Making: A Spiking Neural Circuit Model with Two-Stage Competition for Antisaccadic Task.

    Science.gov (United States)

    Lo, Chung-Chuan; Wang, Xiao-Jing

    2016-08-01

    Automatic responses enable us to react quickly and effortlessly, but they often need to be inhibited so that an alternative, voluntary action can take place. To investigate the brain mechanism of controlled behavior, we investigated a biologically-based network model of spiking neurons for inhibitory control. In contrast to a simple race between pro- versus anti-response, our model incorporates a sensorimotor remapping module, and an action-selection module endowed with a "Stop" process through tonic inhibition. Both are under the modulation of rule-dependent control. We tested the model by applying it to the well known antisaccade task in which one must suppress the urge to look toward a visual target that suddenly appears, and shift the gaze diametrically away from the target instead. We found that the two-stage competition is crucial for reproducing the complex behavior and neuronal activity observed in the antisaccade task across multiple brain regions. Notably, our model demonstrates two types of errors: fast and slow. Fast errors result from failing to inhibit the quick automatic responses and therefore exhibit very short response times. Slow errors, in contrast, are due to incorrect decisions in the remapping process and exhibit long response times comparable to those of correct antisaccade responses. The model thus reveals a circuit mechanism for the empirically observed slow errors and broad distributions of erroneous response times in antisaccade. Our work suggests that selecting between competing automatic and voluntary actions in behavioral control can be understood in terms of near-threshold decision-making, sharing a common recurrent (attractor) neural circuit mechanism with discrimination in perception.

  20. Emergence of task-dependent representations in working memory circuits

    Directory of Open Access Journals (Sweden)

    Cristina eSavin

    2014-05-01

    Full Text Available A wealth of experimental evidence suggests that working memory circuits preferentially represent information that is behaviorally relevant. Still, we are missing a mechanistic account of how these representations come about. Here we provide a simple explanation for a range of experimental findings, in light of prefrontal circuits adapting to task constraints by reward-dependent learning. In particular, we model a neural network shaped by reward-modulated spike-timing dependent plasticity (r-STDP and homeostatic plasticity (intrinsic excitability and synaptic scaling. We show that the experimentally-observed neural representations naturally emerge in an initially unstructured circuit as it learns to solve several working memory tasks. These results point to a critical, and previously unappreciated, role for reward-dependent learning in shaping prefrontal cortex activity.

  1. The interaction of bayesian priors and sensory data and its neural circuit implementation in visually guided movement.

    Science.gov (United States)

    Yang, Jin; Lee, Joonyeol; Lisberger, Stephen G

    2012-12-05

    Sensory-motor behavior results from a complex interaction of noisy sensory data with priors based on recent experience. By varying the stimulus form and contrast for the initiation of smooth pursuit eye movements in monkeys, we show that visual motion inputs compete with two independent priors: one prior biases eye speed toward zero; the other prior attracts eye direction according to the past several days' history of target directions. The priors bias the speed and direction of the initiation of pursuit for the weak sensory data provided by the motion of a low-contrast sine wave grating. However, the priors have relatively little effect on pursuit speed and direction when the visual stimulus arises from the coherent motion of a high-contrast patch of dots. For any given stimulus form, the mean and variance of eye speed covary in the initiation of pursuit, as expected for signal-dependent noise. This relationship suggests that pursuit implements a trade-off between movement accuracy and variation, reducing both when the sensory signals are noisy. The tradeoff is implemented as a competition of sensory data and priors that follows the rules of Bayesian estimation. Computer simulations show that the priors can be understood as direction-specific control of the strength of visual-motor transmission, and can be implemented in a neural-network model that makes testable predictions about the population response in the smooth eye movement region of the frontal eye fields.

  2. The Physics of Decision Making:. Stochastic Differential Equations as Models for Neural Dynamics and Evidence Accumulation in Cortical Circuits

    Science.gov (United States)

    Holmes, Philip; Eckhoff, Philip; Wong-Lin, K. F.; Bogacz, Rafal; Zacksenhouse, Miriam; Cohen, Jonathan D.

    2010-03-01

    We describe how drift-diffusion (DD) processes - systems familiar in physics - can be used to model evidence accumulation and decision-making in two-alternative, forced choice tasks. We sketch the derivation of these stochastic differential equations from biophysically-detailed models of spiking neurons. DD processes are also continuum limits of the sequential probability ratio test and are therefore optimal in the sense that they deliver decisions of specified accuracy in the shortest possible time. This leaves open the critical balance of accuracy and speed. Using the DD model, we derive a speed-accuracy tradeoff that optimizes reward rate for a simple perceptual decision task, compare human performance with this benchmark, and discuss possible reasons for prevalent sub-optimality, focussing on the question of uncertain estimates of key parameters. We present an alternative theory of robust decisions that allows for uncertainty, and show that its predictions provide better fits to experimental data than a more prevalent account that emphasises a commitment to accuracy. The article illustrates how mathematical models can illuminate the neural basis of cognitive processes.

  3. The interaction of Bayesian priors and sensory data and its neural circuit implementation in visually-guided movement

    Science.gov (United States)

    Yang, Jin; Lee, Joonyeol; Lisberger, Stephen G.

    2012-01-01

    Sensory-motor behavior results from a complex interaction of noisy sensory data with priors based on recent experience. By varying the stimulus form and contrast for the initiation of smooth pursuit eye movements in monkeys, we show that visual motion inputs compete with two independent priors: one prior biases eye speed toward zero; the other prior attracts eye direction according to the past several days’ history of target directions. The priors bias the speed and direction of the initiation of pursuit for the weak sensory data provided by the motion of a low-contrast sine wave grating. However, the priors have relatively little effect on pursuit speed and direction when the visual stimulus arises from the coherent motion of a high-contrast patch of dots. For any given stimulus form, the mean and variance of eye speed co-vary in the initiation of pursuit, as expected for signal-dependent noise. This relationship suggests that pursuit implements a trade-off between movement accuracy and variation, reducing both when the sensory signals are noisy. The tradeoff is implemented as a competition of sensory data and priors that follows the rules of Bayesian estimation. Computer simulations show that the priors can be understood as direction specific control of the strength of visual-motor transmission, and can be implemented in a neural-network model that makes testable predictions about the population response in the smooth eye movement region of the frontal eye fields. PMID:23223286

  4. Dynamic Effects of Self-Relevance and Task on the Neural Processing of Emotional Words in Context.

    Science.gov (United States)

    Fields, Eric C; Kuperberg, Gina R

    2015-01-01

    We used event-related potentials (ERPs) to examine the interactions between task, emotion, and contextual self-relevance on processing words in social vignettes. Participants read scenarios that were in either third person (other-relevant) or second person (self-relevant) and we recorded ERPs to a neutral, pleasant, or unpleasant critical word. In a previously reported study (Fields and Kuperberg, 2012) with these stimuli, participants were tasked with producing a third sentence continuing the scenario. We observed a larger LPC to emotional words than neutral words in both the self-relevant and other-relevant scenarios, but this effect was smaller in the self-relevant scenarios because the LPC was larger on the neutral words (i.e., a larger LPC to self-relevant than other-relevant neutral words). In the present work, participants simply answered comprehension questions that did not refer to the emotional aspects of the scenario. Here we observed quite a different pattern of interaction between self-relevance and emotion: the LPC was larger to emotional vs. neutral words in the self-relevant scenarios only, and there was no effect of self-relevance on neutral words. Taken together, these findings suggest that the LPC reflects a dynamic interaction between specific task demands, the emotional properties of a stimulus, and contextual self-relevance. We conclude by discussing implications and future directions for a functional theory of the emotional LPC.

  5. Dynamic effects of self-relevance and task on the neural processing of emotional words in context

    Directory of Open Access Journals (Sweden)

    Eric C. Fields

    2016-01-01

    Full Text Available We used event-related potentials (ERPs to examine the interactions between task, emotion, and contextual self-relevance on processing words in social vignettes. Participants read scenarios that were in either third person (other-relevant or second person (self-relevant and we recorded ERPs to a neutral, pleasant, or unpleasant critical word. In a previously reported study (Fields & Kuperberg, 2012 with these stimuli, participants were tasked with producing a third sentence continuing the scenario. We observed a larger LPC to emotional words than neutral words in both the self-relevant and other-relevant scenarios, but this effect was smaller in the self-relevant scenarios because the LPC was larger on the neutral words (i.e., a larger LPC to self-relevant than other-relevant neutral words. In the present work, participants simply answered comprehension questions that did not refer to the emotional aspects of the scenario. Here we observed quite a different pattern of interaction between self-relevance and emotion: the LPC was larger to emotional versus neutral words in the self-relevant scenarios only, and there was no effect of self-relevance on neutral words. Taken together, these findings suggest that the LPC reflects a dynamic interaction between specific task demands, the emotional properties of a stimulus, and contextual self-relevance. We conclude by discussing implications and future directions for a functional theory of the emotional LPC.

  6. Memristor-based neural networks

    Science.gov (United States)

    Thomas, Andy

    2013-03-01

    The synapse is a crucial element in biological neural networks, but a simple electronic equivalent has been absent. This complicates the development of hardware that imitates biological architectures in the nervous system. Now, the recent progress in the experimental realization of memristive devices has renewed interest in artificial neural networks. The resistance of a memristive system depends on its past states and exactly this functionality can be used to mimic the synaptic connections in a (human) brain. After a short introduction to memristors, we present and explain the relevant mechanisms in a biological neural network, such as long-term potentiation and spike time-dependent plasticity, and determine the minimal requirements for an artificial neural network. We review the implementations of these processes using basic electric circuits and more complex mechanisms that either imitate biological systems or could act as a model system for them.

  7. Dynamic effects of self-relevance and task on the neural processing of emotional words in context

    OpenAIRE

    Fields, Eric C.; Kuperberg, Gina R.

    2016-01-01

    We used event-related potentials (ERPs) to examine the interactions between task, emotion, and contextual self-relevance on processing words in social vignettes. Participants read scenarios that were in either third person (other-relevant) or second person (self-relevant) and we recorded ERPs to a neutral, pleasant, or unpleasant critical word. In a previously reported study (Fields & Kuperberg, 2012) with these stimuli, participants were tasked with producing a third sentence continuing the ...

  8. Dynamic Effects of Self-Relevance and Task on the Neural Processing of Emotional Words in Context

    OpenAIRE

    Fields, Eric C.; Kuperberg, Gina R.

    2016-01-01

    We used event-related potentials (ERPs) to examine the interactions between task, emotion, and contextual self-relevance on processing words in social vignettes. Participants read scenarios that were in either third person (other-relevant) or second person (self-relevant) and we recorded ERPs to a neutral, pleasant, or unpleasant critical word. In a previously reported study (Fields and Kuperberg, 2012) with these stimuli, participants were tasked with producing a third sentence continuing th...

  9. A Neural Relevance Model for Feature Extraction from Hyperspectral Images, and Its Application in the Wavelet Domain

    Science.gov (United States)

    2006-08-01

    Neural Networks I, pages 117-124, New York, Jull 1988. [20] Stanley C. Ahalt, Ashok K. Krishnamurthy, Prakoon Chen, and Douglas E. Melton . Competitive...SUBMITTED IN PARTIAL FULFILLMENT OF THE REQUIREMENTS FOR THE DEGREE Doctor of Philosophy APPROVED, THESIS COMMITTEE: Dr . Erzs~bet Mer~nyi, Chair...Research Professor of Electrical and Computer Engineering Dr . Richard C. Baraniuk Victor E. Cameron Professor of Electrical and Computer Engineering S

  10. Measuring circuits

    CERN Document Server

    Graf, Rudolf F

    1996-01-01

    This series of circuits provides designers with a quick source for measuring circuits. Why waste time paging through huge encyclopedias when you can choose the topic you need and select any of the specialized circuits sorted by application?This book in the series has 250-300 practical, ready-to-use circuit designs, with schematics and brief explanations of circuit operation. The original source for each circuit is listed in an appendix, making it easy to obtain additional information.Ready-to-use circuits.Grouped by application for easy look-up.Circuit source listings

  11. Oscillator circuits

    CERN Document Server

    Graf, Rudolf F

    1996-01-01

    This series of circuits provides designers with a quick source for oscillator circuits. Why waste time paging through huge encyclopedias when you can choose the topic you need and select any of the specialized circuits sorted by application?This book in the series has 250-300 practical, ready-to-use circuit designs, with schematics and brief explanations of circuit operation. The original source for each circuit is listed in an appendix, making it easy to obtain additional information.Ready-to-use circuits.Grouped by application for easy look-up.Circuit source listing

  12. Driver circuit

    Science.gov (United States)

    Matsumoto, Raymond T. (Inventor); Higashi, Stanley T. (Inventor)

    1976-01-01

    A driver circuit which has low power requirements, a relatively small number of components and provides flexibility in output voltage setting. The driver circuit comprises, essentially, two portions which are selectively activated by the application of input signals. The output signal is determined by which of the two circuit portions is activated. While each of the two circuit portions operates in a manner similar to silicon controlled rectifiers (SCR), the circuit portions are on only when an input signal is supplied thereto.

  13. Deriving amplification factors from simple site parameters using generalized regression neural networks: implications for relevant site proxies

    Science.gov (United States)

    Boudghene Stambouli, Ahmed; Zendagui, Djawad; Bard, Pierre-Yves; Derras, Boumédiène

    2017-07-01

    Most modern seismic codes account for site effects using an amplification factor (AF) that modifies the rock acceleration response spectra in relation to a "site condition proxy," i.e., a parameter related to the velocity profile at the site under consideration. Therefore, for practical purposes, it is interesting to identify the site parameters that best control the frequency-dependent shape of the AF. The goal of the present study is to provide a quantitative assessment of the performance of various site condition proxies to predict the main AF features, including the often used short- and mid-period amplification factors, Fa and Fv, proposed by Borcherdt (in Earthq Spectra 10:617-653, 1994). In this context, the linear, viscoelastic responses of a set of 858 actual soil columns from Japan, the USA, and Europe are computed for a set of 14 real accelerograms with varying frequency contents. The correlation between the corresponding site-specific average amplification factors and several site proxies (considered alone or as multiple combinations) is analyzed using the generalized regression neural network (GRNN). The performance of each site proxy combination is assessed through the variance reduction with respect to the initial amplification factor variability of the 858 profiles. Both the whole period range and specific short- and mid-period ranges associated with the Borcherdt factors Fa and Fv are considered. The actual amplification factor of an arbitrary soil profile is found to be satisfactorily approximated with a limited number of site proxies (4-6). As the usual code practice implies a lower number of site proxies (generally one, sometimes two), a sensitivity analysis is conducted to identify the "best performing" site parameters. The best one is the overall velocity contrast between underlying bedrock and minimum velocity in the soil column. Because these are the most difficult and expensive parameters to measure, especially for thick deposits, other

  14. Recent advances in neural recording microsystems.

    Science.gov (United States)

    Gosselin, Benoit

    2011-01-01

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

  15. Recent Advances in Neural Recording Microsystems

    Directory of Open Access Journals (Sweden)

    Benoit Gosselin

    2011-04-01

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

  16. Brain-machine interface circuits and systems

    CERN Document Server

    Zjajo, Amir

    2016-01-01

    This book provides a complete overview of significant design challenges in respect to circuit miniaturization and power reduction of the neural recording system, along with circuit topologies, architecture trends, and (post-silicon) circuit optimization algorithms. The introduced novel circuits for signal conditioning, quantization, and classification, as well as system configurations focus on optimized power-per-area performance, from the spatial resolution (i.e. number of channels), feasible wireless data bandwidth and information quality to the delivered power of implantable system.

  17. Deep learning relevance

    DEFF Research Database (Denmark)

    Lioma, Christina; Larsen, Birger; Petersen, Casper

    2016-01-01

    train a Recurrent Neural Network (RNN) on existing relevant information to that query. We then use the RNN to "deep learn" a single, synthetic, and we assume, relevant document for that query. We design a crowdsourcing experiment to assess how relevant the "deep learned" document is, compared...... to existing relevant documents. Users are shown a query and four wordclouds (of three existing relevant documents and our deep learned synthetic document). The synthetic document is ranked on average most relevant of all....

  18. A Voltage Mode Memristor Bridge Synaptic Circuit with Memristor Emulators

    Directory of Open Access Journals (Sweden)

    Leon Chua

    2012-03-01

    Full Text Available A memristor bridge neural circuit which is able to perform signed synaptic weighting was proposed in our previous study, where the synaptic operation was verified via software simulation of the mathematical model of the HP memristor. This study is an extension of the previous work advancing toward the circuit implementation where the architecture of the memristor bridge synapse is built with memristor emulator circuits. In addition, a simple neural network which performs both synaptic weighting and summation is built by combining memristor emulators-based synapses and differential amplifier circuits. The feasibility of the memristor bridge neural circuit is verified via SPICE simulations.

  19. Refining the Role of 5-HT in Postnatal Development of Brain Circuits

    Directory of Open Access Journals (Sweden)

    Anne Teissier

    2017-05-01

    Full Text Available Changing serotonin (5-hydroxytryptamine, 5-HT brain levels during critical periods in development has long-lasting effects on brain function, particularly on later anxiety/depression-related behaviors in adulthood. A large part of the known developmental effects of 5-HT occur during critical periods of postnatal life, when activity-dependent mechanisms remodel neural circuits. This was first demonstrated for the maturation of sensory brain maps in the barrel cortex and the visual system. More recently this has been extended to the 5-HT raphe circuits themselves and to limbic circuits. Recent studies overviewed here used new genetic models in mice and rats and combined physiological and structural approaches to provide new insights on the cellular and molecular mechanisms controlled by 5-HT during late stages of neural circuit maturation in the raphe projections, the somatosensory cortex and the visual system. Similar mechanisms appear to be also involved in the maturation of limbic circuits such as prefrontal circuits. The latter are of particular relevance to understand the impact of transient 5-HT dysfunction during postnatal life on psychiatric illnesses and emotional disorders in adult life.

  20. Tunable low energy, compact and high performance neuromorphic circuit for spike-based synaptic plasticity.

    Directory of Open Access Journals (Sweden)

    Mostafa Rahimi Azghadi

    Full Text Available Cortical circuits in the brain have long been recognised for their information processing capabilities and have been studied both experimentally and theoretically via spiking neural networks. Neuromorphic engineers are primarily concerned with translating the computational capabilities of biological cortical circuits, using the Spiking Neural Network (SNN paradigm, into in silico applications that can mimic the behaviour and capabilities of real biological circuits/systems. These capabilities include low power consumption, compactness, and relevant dynamics. In this paper, we propose a new accelerated-time circuit that has several advantages over its previous neuromorphic counterparts in terms of compactness, power consumption, and capability to mimic the outcomes of biological experiments. The presented circuit simulation results demonstrate that, in comparing the new circuit to previous published synaptic plasticity circuits, reduced silicon area and lower energy consumption for processing each spike is achieved. In addition, it can be tuned in order to closely mimic the outcomes of various spike timing- and rate-based synaptic plasticity experiments. The proposed circuit is also investigated and compared to other designs in terms of tolerance to mismatch and process variation. Monte Carlo simulation results show that the proposed design is much more stable than its previous counterparts in terms of vulnerability to transistor mismatch, which is a significant challenge in analog neuromorphic design. All these features make the proposed design an ideal circuit for use in large scale SNNs, which aim at implementing neuromorphic systems with an inherent capability that can adapt to a continuously changing environment, thus leading to systems with significant learning and computational abilities.

  1. Neuromorphic Silicon Neuron Circuits

    Science.gov (United States)

    Indiveri, Giacomo; Linares-Barranco, Bernabé; Hamilton, Tara Julia; van Schaik, André; Etienne-Cummings, Ralph; Delbruck, Tobi; Liu, Shih-Chii; Dudek, Piotr; Häfliger, Philipp; Renaud, Sylvie; Schemmel, Johannes; Cauwenberghs, Gert; Arthur, John; Hynna, Kai; Folowosele, Fopefolu; Saighi, Sylvain; Serrano-Gotarredona, Teresa; Wijekoon, Jayawan; Wang, Yingxue; Boahen, Kwabena

    2011-01-01

    Hardware implementations of spiking neurons can be extremely useful for a large variety of applications, ranging from high-speed modeling of large-scale neural systems to real-time behaving systems, to bidirectional brain–machine interfaces. The specific circuit solutions used to implement silicon neurons depend on the application requirements. In this paper we describe the most common building blocks and techniques used to implement these circuits, and present an overview of a wide range of neuromorphic silicon neurons, which implement different computational models, ranging from biophysically realistic and conductance-based Hodgkin–Huxley models to bi-dimensional generalized adaptive integrate and fire models. We compare the different design methodologies used for each silicon neuron design described, and demonstrate their features with experimental results, measured from a wide range of fabricated VLSI chips. PMID:21747754

  2. Neuromorphic silicon neuron circuits

    Directory of Open Access Journals (Sweden)

    Giacomo eIndiveri

    2011-05-01

    Full Text Available Hardware implementations of spiking neurons can be extremely useful for a large variety of applications, ranging from high-speed modeling of large-scale neural systems to real-time behaving systems, to bidirectional brain-machine interfaces. The specific circuit solutions used to implement silicon neurons depend on the application requirements. In this paper we describe the most common building blocks and techniques used to implement these circuits, and present an overview of a wide range of neuromorphic silicon neurons, which implement different computational models, ranging from biophysically realistic and conductance based Hodgkin-Huxley models to bi-dimensional generalized adaptive Integrate and Fire models. We compare the different design methodologies used for each silicon neuron design described, and demonstrate their features with experimental results, measured from a wide range of fabricated VLSI chips.

  3. Neural reflexes in inflammation and immunity

    National Research Council Canada - National Science Library

    Andersson, Ulf; Tracey, Kevin J

    2012-01-01

    .... Development of advanced neurophysiological and immunological techniques recently enabled the study of reflex neural circuits that maintain immunological homeostasis, and are essential for health in mammals...

  4. Frontolimbic Neural Circuit Changes in Emotional Processing and Inhibitory Control Associated With Clinical Improvement Following Transference-Focused Psychotherapy in Borderline Personality Disorder

    Science.gov (United States)

    Perez, David L.; Vago, David R.; Pan, Hong; Root, James; Tuescher, Oliver; Fuchs, Benjamin H.; Leung, Lorene; Epstein, Jane; Cain, Nicole M.; Clarkin, John F.; Lenzenweger, Mark F.; Kernberg, Otto F.; Levy, Kenneth N.; Silbersweig, David A.; Stern, Emily

    2015-01-01

    Aim Borderline personality disorder (BPD) is characterized by self-regulation deficits, including impulsivity and affective lability. Transference-Focused Psychotherapy (TFP) is an evidence-based treatment proven to reduce symptoms across multiple cognitive-emotional domains in BPD. This pilot study aims to investigate neural activation associated with, and predictive of, clinical improvement in emotional and behavioral regulation in BPD following TFP. Methods BPD subjects (N=10) were scanned pre- and post-TFP treatment using a within-subjects design. A disorder-specific emotional-linguistic go/no-go fMRI paradigm was used to probe the interaction between negative emotional processing and inhibitory control. Results Analyses demonstrated significant treatment-related effects with relative increased dorsal prefrontal (dorsal anterior cingulate, dorsolateral prefrontal, and frontopolar cortices) activation, and relative decreased ventrolateral prefrontal cortex and hippocampal activation following treatment. Clinical improvement in constraint correlated positively with relative increased left dorsal anterior cingulate cortex activation. Clinical improvement in affective lability correlated positively with left posterior-medial orbitofrontal cortex/ventral striatum activation, and negatively with right amygdala/parahippocampal activation. Post-treatment improvements in constraint were predicted by pre-treatment right dorsal anterior cingulate cortex hypoactivation, and pre-treatment left posterior-medial orbitofrontal cortex/ventral striatum hypoactivation predicted improvements in affective lability. Conclusions These preliminary findings demonstrate potential TFP-associated alterations in frontolimbic circuitry and begin to identify neural mechanisms associated with a psychodynamically-oriented psychotherapy. PMID:26289141

  5. Frontolimbic neural circuit changes in emotional processing and inhibitory control associated with clinical improvement following transference-focused psychotherapy in borderline personality disorder.

    Science.gov (United States)

    Perez, David L; Vago, David R; Pan, Hong; Root, James; Tuescher, Oliver; Fuchs, Benjamin H; Leung, Lorene; Epstein, Jane; Cain, Nicole M; Clarkin, John F; Lenzenweger, Mark F; Kernberg, Otto F; Levy, Kenneth N; Silbersweig, David A; Stern, Emily

    2016-01-01

    Borderline personality disorder (BPD) is characterized by self-regulation deficits, including impulsivity and affective lability. Transference-focused psychotherapy (TFP) is an evidence-based treatment proven to reduce symptoms across multiple cognitive-emotional domains in BPD. This pilot study aimed to investigate neural activation associated with, and predictive of, clinical improvement in emotional and behavioral regulation in BPD following TFP. BPD subjects (n = 10) were scanned pre- and post-TFP treatment using a within-subjects design. A disorder-specific emotional-linguistic go/no-go functional magnetic resonance imaging paradigm was used to probe the interaction between negative emotional processing and inhibitory control. Analyses demonstrated significant treatment-related effects with relative increased dorsal prefrontal (dorsal anterior cingulate, dorsolateral prefrontal, and frontopolar cortices) activation, and relative decreased ventrolateral prefrontal cortex and hippocampal activation following treatment. Clinical improvement in constraint correlated positively with relative increased left dorsal anterior cingulate cortex activation. Clinical improvement in affective lability correlated positively with left posterior-medial orbitofrontal cortex/ventral striatum activation, and negatively with right amygdala/parahippocampal activation. Post-treatment improvements in constraint were predicted by pre-treatment right dorsal anterior cingulate cortex hypoactivation, and pre-treatment left posterior-medial orbitofrontal cortex/ventral striatum hypoactivation predicted improvements in affective lability. These preliminary findings demonstrate potential TFP-associated alterations in frontolimbic circuitry and begin to identify neural mechanisms associated with a psychodynamically oriented psychotherapy. © 2015 The Authors. Psychiatry and Clinical Neurosciences © 2015 Japanese Society of Psychiatry and Neurology.

  6. Affective Circuits

    DEFF Research Database (Denmark)

    to the intersecting streams of goods, people, ideas, and money as they circulate between African migrants and their kin who remain back home. They also show the complex ways that emotions become entangled in these exchanges. Examining how these circuits operate in domains of social life ranging from child fosterage...... to binational marriages, from coming-of-age to healing and religious rituals, the book also registers the tremendous impact of state officials, laws, and policies on migrant experience. Together these essays paint an especially vivid portrait of new forms of kinship at a time of both intense mobility and ever...

  7. Can modular psychological concepts like affect and emotion be assigned to a distinct subset of regional neural circuits?. Comment on "The quartet theory of human emotions: An integrative and neurofunctional model" by S. Koelsch et al.

    Science.gov (United States)

    Fehr, Thorsten; Herrmann, Manfred

    2015-06-01

    The proposed Quartet Theory of Human Emotions by Koelsch and co-workers [11] adumbrates evidence from various scientific sources to integrate and assign the psychological concepts of 'affect' and 'emotion' to four brain circuits or to four neuronal core systems for affect-processing in the brain. The authors differentiate between affect and emotion and assign several facultative, or to say modular, psychological domains and principles of information processing, such as learning and memory, antecedents of affective activity, emotion satiation, cognitive complexity, subjective quality feelings, degree of conscious appraisal, to different affect systems. Furthermore, they relate orbito-frontal brain structures to moral affects as uniquely human, and the hippocampus to attachment-related affects. An additional feature of the theory describes 'emotional effector-systems' for motor-related processes (e.g., emotion-related actions), physiological arousal, attention and memory that are assumed to be cross-linked with the four proposed affect systems. Thus, higher principles of emotional information processing, but also modular affect-related issues, such as moral and attachment related affects, are thought to be handled by these four different physiological sub-systems that are on the other side assumed to be highly interwoven at both physiological and functional levels. The authors also state that the proposed sub-systems have many features in common, such as the selection and modulation of biological processes related to behaviour, perception, attention and memory. The latter aspect challenges an ongoing discussion about the mind-body problem: To which degree do the proposed sub-systems 'sufficiently' cover the processing of complex modular or facultative emotional/affective and/or cognitive phenomena? There are current models and scientific positions that almost completely reject the idea that modular psychological phenomena are handled by a distinct selection of

  8. LOGIC CIRCUIT

    Science.gov (United States)

    Strong, G.H.; Faught, M.L.

    1963-12-24

    A device for safety rod counting in a nuclear reactor is described. A Wheatstone bridge circuit is adapted to prevent de-energizing the hopper coils of a ball backup system if safety rods, sufficient in total control effect, properly enter the reactor core to effect shut down. A plurality of resistances form one arm of the bridge, each resistance being associated with a particular safety rod and weighted in value according to the control effect of the particular safety rod. Switching means are used to switch each of the resistances in and out of the bridge circuit responsive to the presence of a particular safety rod in its effective position in the reactor core and responsive to the attainment of a predetermined velocity by a particular safety rod enroute to its effective position. The bridge is unbalanced in one direction during normal reactor operation prior to the generation of a scram signal and the switching means and resistances are adapted to unbalance the bridge in the opposite direction if the safety rods produce a predetermined amount of control effect in response to the scram signal. The bridge unbalance reversal is then utilized to prevent the actuation of the ball backup system, or, conversely, a failure of the safety rods to produce the predetermined effect produces no unbalance reversal and the ball backup system is actuated. (AEC)

  9. From circuits to behaviour in the amygdala

    Science.gov (United States)

    Janak, Patricia H.; Tye, Kay M.

    2015-01-01

    The amygdala has long been associated with emotion and motivation, playing an essential part in processing both fearful and rewarding environmental stimuli. How can a single structure be crucial for such different functions? With recent technological advances that allow for causal investigations of specific neural circuit elements, we can now begin to map the complex anatomical connections of the amygdala onto behavioural function. Understanding how the amygdala contributes to a wide array of behaviours requires the study of distinct amygdala circuits. PMID:25592533

  10. Digital Optical Circuit Technology

    Science.gov (United States)

    Dove, B. L. (Editor)

    1985-01-01

    The Proceedings for the 48th Meeting of the AGARD Avionics Panel contain the 18 papers presented a Technical Evaluation Report, and discussions that followed the presentations of papers. Seven papers were presented in the session devoted to optical bistability. Optical logic was addressed by three papers. The session on sources, modulators and demodulators presented three papers. Five papers were given in the final session on all optical systems. The purpose of this Specialists' Meeting was to present the research and development status of digital optical circuit technology and to examine its relevance in the broad context of digital processing, communication, radar, avionics and flight control systems implementation.

  11. Controllable circuit

    DEFF Research Database (Denmark)

    2010-01-01

    signal. The control unit comprises a first signal processing unit, a second signal processing unit, and a combiner unit. The first signal processing unit has an output and is supplied with a first carrier signal and an input signal. The second signal processing unit has an output and is supplied...... with a second carrier signal and the input signal. The combiner unit is connected to the first and second signal processing units combining the outputs of the first and the second signal processing units to form a signal representative of the control signal......A switch-mode power circuit comprises a controllable element and a control unit. The controllable element is configured to control a current in response to a control signal supplied to the controllable element. The control unit is connected to the controllable element and provides the control...

  12. Real-time cerebellar neuroprosthetic system based on a spiking neural network model of motor learning.

    Science.gov (United States)

    Xu, Tao; Xiao, Na; Zhai, Xiaolong; Kwan Chan, Pak; Tin, Chung

    2018-02-01

    Damage to the brain, as a result of various medical conditions, impacts the everyday life of patients and there is still no complete cure to neurological disorders. Neuroprostheses that can functionally replace the damaged neural circuit have recently emerged as a possible solution to these problems. Here we describe the development of a real-time cerebellar neuroprosthetic system to substitute neural function in cerebellar circuitry for learning delay eyeblink conditioning (DEC). The system was empowered by a biologically realistic spiking neural network (SNN) model of the cerebellar neural circuit, which considers the neuronal population and anatomical connectivity of the network. The model simulated synaptic plasticity critical for learning DEC. This SNN model was carefully implemented on a field programmable gate array (FPGA) platform for real-time simulation. This hardware system was interfaced in in vivo experiments with anesthetized rats and it used neural spikes recorded online from the animal to learn and trigger conditioned eyeblink in the animal during training. This rat-FPGA hybrid system was able to process neuronal spikes in real-time with an embedded cerebellum model of ~10 000 neurons and reproduce learning of DEC with different inter-stimulus intervals. Our results validated that the system performance is physiologically relevant at both the neural (firing pattern) and behavioral (eyeblink pattern) levels. This integrated system provides the sufficient computation power for mimicking the cerebellar circuit in real-time. The system interacts with the biological system naturally at the spike level and can be generalized for including other neural components (neuron types and plasticity) and neural functions for potential neuroprosthetic applications.

  13. Real-time cerebellar neuroprosthetic system based on a spiking neural network model of motor learning

    Science.gov (United States)

    Xu, Tao; Xiao, Na; Zhai, Xiaolong; Chan, Pak Kwan; Tin, Chung

    2018-02-01

    Objective. Damage to the brain, as a result of various medical conditions, impacts the everyday life of patients and there is still no complete cure to neurological disorders. Neuroprostheses that can functionally replace the damaged neural circuit have recently emerged as a possible solution to these problems. Here we describe the development of a real-time cerebellar neuroprosthetic system to substitute neural function in cerebellar circuitry for learning delay eyeblink conditioning (DEC). Approach. The system was empowered by a biologically realistic spiking neural network (SNN) model of the cerebellar neural circuit, which considers the neuronal population and anatomical connectivity of the network. The model simulated synaptic plasticity critical for learning DEC. This SNN model was carefully implemented on a field programmable gate array (FPGA) platform for real-time simulation. This hardware system was interfaced in in vivo experiments with anesthetized rats and it used neural spikes recorded online from the animal to learn and trigger conditioned eyeblink in the animal during training. Main results. This rat-FPGA hybrid system was able to process neuronal spikes in real-time with an embedded cerebellum model of ~10 000 neurons and reproduce learning of DEC with different inter-stimulus intervals. Our results validated that the system performance is physiologically relevant at both the neural (firing pattern) and behavioral (eyeblink pattern) levels. Significance. This integrated system provides the sufficient computation power for mimicking the cerebellar circuit in real-time. The system interacts with the biological system naturally at the spike level and can be generalized for including other neural components (neuron types and plasticity) and neural functions for potential neuroprosthetic applications.

  14. Analog circuit design designing dynamic circuit response

    CERN Document Server

    Feucht, Dennis

    2010-01-01

    This second volume, Designing Dynamic Circuit Response builds upon the first volume Designing Amplifier Circuits by extending coverage to include reactances and their time- and frequency-related behavioral consequences.

  15. Analog circuit design designing waveform processing circuits

    CERN Document Server

    Feucht, Dennis

    2010-01-01

    The fourth volume in the set Designing Waveform-Processing Circuits builds on the previous 3 volumes and presents a variety of analog non-amplifier circuits, including voltage references, current sources, filters, hysteresis switches and oscilloscope trigger and sweep circuitry, function generation, absolute-value circuits, and peak detectors.

  16. NeuralWISP: A Wirelessly Powered Neural Interface With 1-m Range.

    Science.gov (United States)

    Yeager, D J; Holleman, J; Prasad, R; Smith, J R; Otis, B P

    2009-12-01

    We present the NeuralWISP, a wireless neural interface operating from far-field radio-frequency RF energy. The NeuralWISP is compatible with commercial RF identification readers and operates at a range up to 1 m. It includes a custom low-noise, low-power amplifier integrated circuit for processing the neural signal and an analog spike detection circuit for reducing digital computational requirements and communications bandwidth. Our system monitors the neural signal and periodically transmits the spike density in a user-programmable time window. The entire system draws an average 20 muA from the harvested 1.8-V supply.

  17. Equivalent Quantum Circuits

    OpenAIRE

    Garcia-Escartin, Juan Carlos; Chamorro-Posada, Pedro

    2011-01-01

    Quantum algorithms and protocols are often presented as quantum circuits for a better understanding. We give a list of equivalence rules which can help in the analysis and design of quantum circuits. As example applications we study quantum teleportation and dense coding protocols in terms of a simple XOR swapping circuit and give an intuitive picture of a basic gate teleportation circuit.

  18. Universal Quantum Circuits

    OpenAIRE

    Bera, Debajyoti; Fenner, Stephen; Green, Frederic; Homer, Steve

    2008-01-01

    We define and construct efficient depth-universal and almost-size-universal quantum circuits. Such circuits can be viewed as general-purpose simulators for central classes of quantum circuits and can be used to capture the computational power of the circuit class being simulated. For depth we construct universal circuits whose depth is the same order as the circuits being simulated. For size, there is a log factor blow-up in the universal circuits constructed here. We prove that this construc...

  19. Circuit analysis for dummies

    CERN Document Server

    Santiago, John

    2013-01-01

    Circuits overloaded from electric circuit analysis? Many universities require that students pursuing a degree in electrical or computer engineering take an Electric Circuit Analysis course to determine who will ""make the cut"" and continue in the degree program. Circuit Analysis For Dummies will help these students to better understand electric circuit analysis by presenting the information in an effective and straightforward manner. Circuit Analysis For Dummies gives you clear-cut information about the topics covered in an electric circuit analysis courses to help

  20. Solid-state circuits

    CERN Document Server

    Pridham, G J

    2013-01-01

    Solid-State Circuits provides an introduction to the theory and practice underlying solid-state circuits, laying particular emphasis on field effect transistors and integrated circuits. Topics range from construction and characteristics of semiconductor devices to rectification and power supplies, low-frequency amplifiers, sine- and square-wave oscillators, and high-frequency effects and circuits. Black-box equivalent circuits of bipolar transistors, physical equivalent circuits of bipolar transistors, and equivalent circuits of field effect transistors are also covered. This volume is divided

  1. Feature-selective Attention in Frontoparietal Cortex: Multivoxel Codes Adjust to Prioritize Task-relevant Information.

    Science.gov (United States)

    Jackson, Jade; Rich, Anina N; Williams, Mark A; Woolgar, Alexandra

    2017-02-01

    Human cognition is characterized by astounding flexibility, enabling us to select appropriate information according to the objectives of our current task. A circuit of frontal and parietal brain regions, often referred to as the frontoparietal attention network or multiple-demand (MD) regions, are believed to play a fundamental role in this flexibility. There is evidence that these regions dynamically adjust their responses to selectively process information that is currently relevant for behavior, as proposed by the "adaptive coding hypothesis" [Duncan, J. An adaptive coding model of neural function in prefrontal cortex. Nature Reviews Neuroscience, 2, 820-829, 2001]. Could this provide a neural mechanism for feature-selective attention, the process by which we preferentially process one feature of a stimulus over another? We used multivariate pattern analysis of fMRI data during a perceptually challenging categorization task to investigate whether the representation of visual object features in the MD regions flexibly adjusts according to task relevance. Participants were trained to categorize visually similar novel objects along two orthogonal stimulus dimensions (length/orientation) and performed short alternating blocks in which only one of these dimensions was relevant. We found that multivoxel patterns of activation in the MD regions encoded the task-relevant distinctions more strongly than the task-irrelevant distinctions: The MD regions discriminated between stimuli of different lengths when length was relevant and between the same objects according to orientation when orientation was relevant. The data suggest a flexible neural system that adjusts its representation of visual objects to preferentially encode stimulus features that are currently relevant for behavior, providing a neural mechanism for feature-selective attention.

  2. Small-signal neural models and their applications.

    Science.gov (United States)

    Basu, Arindam

    2012-02-01

    This paper introduces the use of the concept of small-signal analysis, commonly used in circuit design, for understanding neural models. We show that neural models, varying in complexity from Hodgkin-Huxley to integrate and fire have similar small-signal models when their corresponding differential equations are close to the same bifurcation with respect to input current. Three applications of small-signal neural models are shown. First, some of the properties of cortical neurons described by Izhikevich are explained intuitively through small-signal analysis. Second, we use small-signal models for deriving parameters for a simple neural model (such as resonate and fire) from a more complicated but biophysically relevant one like Morris-Lecar. We show similarity in the subthreshold behavior of the simple and complicated model when they are close to a Hopf bifurcation and a saddle-node bifurcation. Hence, this is useful to correctly tune simple neural models for large-scale cortical simulations. Finaly, the biasing regime of a silicon ion channel is derived by comparing its small-signal model with a Hodgkin-Huxley-type model.

  3. The circuit designer's companion

    CERN Document Server

    Williams, Tim

    1991-01-01

    The Circuit Designer's Companion covers the theoretical aspects and practices in analogue and digital circuit design. Electronic circuit design involves designing a circuit that will fulfill its specified function and designing the same circuit so that every production model of it will fulfill its specified function, and no other undesired and unspecified function.This book is composed of nine chapters and starts with a review of the concept of grounding, wiring, and printed circuits. The subsequent chapters deal with the passive and active components of circuitry design. These topics are foll

  4. Electronic devices and circuits

    CERN Document Server

    Pridham, Gordon John

    1972-01-01

    Electronic Devices and Circuits, Volume 3 provides a comprehensive account on electronic devices and circuits and includes introductory network theory and physics. The physics of semiconductor devices is described, along with field effect transistors, small-signal equivalent circuits of bipolar transistors, and integrated circuits. Linear and non-linear circuits as well as logic circuits are also considered. This volume is comprised of 12 chapters and begins with an analysis of the use of Laplace transforms for analysis of filter networks, followed by a discussion on the physical properties of

  5. Intuitive analog circuit design

    CERN Document Server

    Thompson, Marc

    2013-01-01

    Intuitive Analog Circuit Design outlines ways of thinking about analog circuits and systems that let you develop a feel for what a good, working analog circuit design should be. This book reflects author Marc Thompson's 30 years of experience designing analog and power electronics circuits and teaching graduate-level analog circuit design, and is the ideal reference for anyone who needs a straightforward introduction to the subject. In this book, Dr. Thompson describes intuitive and ""back-of-the-envelope"" techniques for designing and analyzing analog circuits, including transistor amplifi

  6. Deep learning with coherent nanophotonic circuits

    Science.gov (United States)

    Shen, Yichen; Harris, Nicholas C.; Skirlo, Scott; Prabhu, Mihika; Baehr-Jones, Tom; Hochberg, Michael; Sun, Xin; Zhao, Shijie; Larochelle, Hugo; Englund, Dirk; Soljačić, Marin

    2017-07-01

    Artificial neural networks are computational network models inspired by signal processing in the brain. These models have dramatically improved performance for many machine-learning tasks, including speech and image recognition. However, today's computing hardware is inefficient at implementing neural networks, in large part because much of it was designed for von Neumann computing schemes. Significant effort has been made towards developing electronic architectures tuned to implement artificial neural networks that exhibit improved computational speed and accuracy. Here, we propose a new architecture for a fully optical neural network that, in principle, could offer an enhancement in computational speed and power efficiency over state-of-the-art electronics for conventional inference tasks. We experimentally demonstrate the essential part of the concept using a programmable nanophotonic processor featuring a cascaded array of 56 programmable Mach-Zehnder interferometers in a silicon photonic integrated circuit and show its utility for vowel recognition.

  7. Memristor Circuits and Systems

    KAUST Repository

    Zidan, Mohammed A.

    2015-05-01

    resistive-based memory systems and neural computing. For gateless arrays, we present multiport array structure and readout technique, which for the first time introduces a closed-form solution for the challenging crossbar sneak-paths problem. Moreover, a new adaptive threshold readout methodology is proposed, which employs the memory hierarchy locality property in order to improve the access time to the memristor crossbar. Another fast readout technique based on binary counters is presented for locality-less crossbar systems. On the other hand, for gated arrays, we present new readout technique and circuitry that combines the advantages of the gated and gateless memristor arrays, namely the high-density and low-power consumption. In general, the presented structures and readout methodologies empower much faster and power efficient access to the high-density memristive crossbar, compared to other works presented in the literature. Finally, at the circuit level, we propose novel reactance-less oscillators based on memristor devices, which find promising applications in embedded systems and bio-inspired computing. Altogether, we believe that our contributions to the emerging technology help to push it to the next level, shortening the path towards better futuristic computing systems.

  8. The Emergence of a Circuit Model for Addiction.

    Science.gov (United States)

    Lüscher, Christian

    2016-07-08

    Addiction is a disease of altered behavior. Addicts use drugs compulsively and will continue to do so despite negative consequences. Even after prolonged periods of abstinence, addicts are at risk of relapse, particularly when cues evoke memories that are associated with drug use. Rodent models mimic many of the core components of addiction, from the initial drug reinforcement to cue-associated relapse and continued drug intake despite negative consequences. Rodent models have also enabled unprecedented mechanistic insight into addiction, revealing plasticity of glutamatergic synaptic transmission evoked by the strong activation of mesolimbic dopamine-a defining feature of all addictive drugs-as a neural substrate for these drug-adaptive behaviors. Cell type-specific optogenetic manipulations have allowed both identification of the relevant circuits and design of protocols to reverse drug-evoked plasticity and to establish links of causality with drug-adaptive behaviors. The emergence of a circuit model for addiction will open the door for novel therapies, such as deep brain stimulation.

  9. A guide to printed circuit board design

    CERN Document Server

    Hamilton, Charles

    1984-01-01

    A Guide to Printed Circuit Board Design discusses the basic design principles of printed circuit board (PCB). The book consists of nine chapters; each chapter provides both text discussion and illustration relevant to the topic being discussed. Chapter 1 talks about understanding the circuit diagram, and Chapter 2 covers how to compile component information file. Chapter 3 deals with the design layout, while Chapter 4 talks about preparing the master artworks. The book also covers generating computer aided design (CAD) master patterns, and then discusses how to prepare the production drawing a

  10. Electric circuits essentials

    CERN Document Server

    REA, Editors of

    2012-01-01

    REA's Essentials provide quick and easy access to critical information in a variety of different fields, ranging from the most basic to the most advanced. As its name implies, these concise, comprehensive study guides summarize the essentials of the field covered. Essentials are helpful when preparing for exams, doing homework and will remain a lasting reference source for students, teachers, and professionals. Electric Circuits I includes units, notation, resistive circuits, experimental laws, transient circuits, network theorems, techniques of circuit analysis, sinusoidal analysis, polyph

  11. Classical circuit theory

    CERN Document Server

    Wing, Omar

    2008-01-01

    Starting with the basic principles of circuits, this book derives their analytic properties in both the time and frequency domains. It develops an algorithmic method to design common and uncommon types of circuits, such as prototype filters, lumped delay lines, constant phase difference circuits, and delay equalizers.

  12. Signal sampling circuit

    NARCIS (Netherlands)

    Louwsma, S.M.; Vertregt, Maarten

    2011-01-01

    A sampling circuit for sampling a signal is disclosed. The sampling circuit comprises a plurality of sampling channels adapted to sample the signal in time-multiplexed fashion, each sampling channel comprising a respective track-and-hold circuit connected to a respective analogue to digital

  13. Signal sampling circuit

    NARCIS (Netherlands)

    Louwsma, S.M.; Vertregt, Maarten

    2010-01-01

    A sampling circuit for sampling a signal is disclosed. The sampling circuit comprises a plurality of sampling channels adapted to sample the signal in time-multiplexed fashion, each sampling channel comprising a respective track-and-hold circuit connected to a respective analogue to digital

  14. Piezoelectric drive circuit

    Science.gov (United States)

    Treu, Jr., Charles A.

    1999-08-31

    A piezoelectric motor drive circuit is provided which utilizes the piezoelectric elements as oscillators and a Meacham half-bridge approach to develop feedback from the motor ground circuit to produce a signal to drive amplifiers to power the motor. The circuit automatically compensates for shifts in harmonic frequency of the piezoelectric elements due to pressure and temperature changes.

  15. Exact Threshold Circuits

    DEFF Research Database (Denmark)

    Hansen, Kristoffer Arnsfelt; Podolskii, Vladimir V.

    2010-01-01

    with the well-studied corresponding hierarchies defined using ordinary threshold gates. A major open problem in Boolean circuit complexity is to provide an explicit super-polynomial lower bound for depth two threshold circuits. We identify the class of depth two exact threshold circuits as a natural subclass...

  16. Load testing circuit

    DEFF Research Database (Denmark)

    2009-01-01

    A load testing circuit a circuit tests the load impedance of a load connected to an amplifier. The load impedance includes a first terminal and a second terminal, the load testing circuit comprising a signal generator providing a test signal of a defined bandwidth to the first terminal of the load...

  17. Short-circuit logic

    NARCIS (Netherlands)

    Bergstra, J.A.; Ponse, A.

    2010-01-01

    Short-circuit evaluation denotes the semantics of propositional connectives in which the second argument is only evaluated if the first argument does not suffice to determine the value of the expression. In programming, short-circuit evaluation is widely used. A short-circuit logic is a variant of

  18. An adaptive neural mechanism for acoustic motion perception with varying sparsity

    DEFF Research Database (Denmark)

    Shaikh, Danish; Manoonpong, Poramate

    2017-01-01

    Biological motion-sensitive neural circuits are quite adept in perceiving the relative motion of a relevant stimulus. Motion perception is a fundamental ability in neural sensory processing and crucial in target tracking tasks. Tracking a stimulus entails the ability to perceive its motion, i.......e. extracting information about its direction and velocity. Here we focus on auditory motion perception of sound stimuli, which is poorly understood as compared to its visual counterpart. In earlier work we have developed a bio-inspired neural learning mechanism for acoustic motion perception. The mechanism...... be occluded by artefacts in the environment, such as an escaping prey momentarily disappearing behind a cover of trees. This article extends the earlier work by presenting a comparative investigation of auditory motion perception for unoccluded and occluded tonal sound stimuli with a frequency of 2.2 k...

  19. Deciphering the Cognitive and Neural Mechanisms Underlying ...

    International Development Research Centre (IDRC) Digital Library (Canada)

    Deciphering the Cognitive and Neural Mechanisms Underlying Auditory Learning. This project seeks to understand the brain mechanisms necessary for people to learn to perceive sounds. Neural circuits and learning. The research team will test people with and without musical training to evaluate their capacity to learn ...

  20. Neural Plasticity in Speech Acquisition and Learning

    Science.gov (United States)

    Zhang, Yang; Wang, Yue

    2007-01-01

    Neural plasticity in speech acquisition and learning is concerned with the timeline trajectory and the mechanisms of experience-driven changes in the neural circuits that support or disrupt linguistic function. In this selective review, we discuss the role of phonetic learning in language acquisition, the "critical period" of learning, the agents…

  1. Hypothalamic survival circuits: blueprints for purposive behaviors.

    Science.gov (United States)

    Sternson, Scott M

    2013-03-06

    Neural processes that direct an animal's actions toward environmental goals are critical elements for understanding behavior. The hypothalamus is closely associated with motivated behaviors required for survival and reproduction. Intense feeding, drinking, aggressive, and sexual behaviors can be produced by a simple neuronal stimulus applied to discrete hypothalamic regions. What can these "evoked behaviors" teach us about the neural processes that determine behavioral intent and intensity? Small populations of neurons sufficient to evoke a complex motivated behavior may be used as entry points to identify circuits that energize and direct behavior to specific goals. Here, I review recent applications of molecular genetic, optogenetic, and pharmacogenetic approaches that overcome previous limitations for analyzing anatomically complex hypothalamic circuits and their interactions with the rest of the brain. These new tools have the potential to bridge the gaps between neurobiological and psychological thinking about the mechanisms of complex motivated behavior. Copyright © 2013 Elsevier Inc. All rights reserved.

  2. Rett syndrome: genes, synapses, circuits and therapeutics

    Directory of Open Access Journals (Sweden)

    Abhishek eBanerjee

    2012-05-01

    Full Text Available Development of the nervous system proceeds through a set of complex checkpoints which arise from a combination of sequential gene expression and early neural activity sculpted by the environment. Genetic and environmental insults lead to neurodevelopmental disorders which encompass a large group of diseases that result from anatomical and physiological abnormalities during maturation and development of brain circuits. Rett syndrome (RTT is a postnatal neurological disorder of genetic origin, caused by mutations in the X-linked gene MECP2. It features neuropsychiatric abnormalities like motor dysfunctions and mild to severe cognitive impairment. This review discusses several key questions and attempts to evaluate recently developed animal models, cell-type specific function of MeCP2, defects in neural circuit plasticity and possible therapeutic strategies. Finally, we also discuss how genes, proteins and overlapping signaling pathways affect the molecular etiology of apparently unrelated neuropsychiatric disorders, an understanding of which can offer novel therapeutic strategies.

  3. Feedback in analog circuits

    CERN Document Server

    Ochoa, Agustin

    2016-01-01

    This book describes a consistent and direct methodology to the analysis and design of analog circuits with particular application to circuits containing feedback. The analysis and design of circuits containing feedback is generally presented by either following a series of examples where each circuit is simplified through the use of insight or experience (someone else’s), or a complete nodal-matrix analysis generating lots of algebra. Neither of these approaches leads to gaining insight into the design process easily. The author develops a systematic approach to circuit analysis, the Driving Point Impedance and Signal Flow Graphs (DPI/SFG) method that does not require a-priori insight to the circuit being considered and results in factored analysis supporting the design function. This approach enables designers to account fully for loading and the bi-directional nature of elements both in the feedback path and in the amplifier itself, properties many times assumed negligible and ignored. Feedback circuits a...

  4. Neural network applications

    Science.gov (United States)

    Padgett, Mary L.; Desai, Utpal; Roppel, T.A.; White, Charles R.

    1993-01-01

    A design procedure is suggested for neural networks which accommodates the inclusion of such knowledge-based systems techniques as fuzzy logic and pairwise comparisons. The use of these procedures in the design of applications combines qualitative and quantitative factors with empirical data to yield a model with justifiable design and parameter selection procedures. The procedure is especially relevant to areas of back-propagation neural network design which are highly responsive to the use of precisely recorded expert knowledge.

  5. Identification of Relevant Phytochemical Constituents for Characterization and Authentication of Tomatoes by General Linear Model Linked to Automatic Interaction Detection (GLM-AID and Artificial Neural Network Models (ANNs.

    Directory of Open Access Journals (Sweden)

    Marcos Hernández Suárez

    Full Text Available There are a large number of tomato cultivars with a wide range of morphological, chemical, nutritional and sensorial characteristics. Many factors are known to affect the nutrient content of tomato cultivars. A complete understanding of the effect of these factors would require an exhaustive experimental design, multidisciplinary scientific approach and a suitable statistical method. Some multivariate analytical techniques such as Principal Component Analysis (PCA or Factor Analysis (FA have been widely applied in order to search for patterns in the behaviour and reduce the dimensionality of a data set by a new set of uncorrelated latent variables. However, in some cases it is not useful to replace the original variables with these latent variables. In this study, Automatic Interaction Detection (AID algorithm and Artificial Neural Network (ANN models were applied as alternative to the PCA, AF and other multivariate analytical techniques in order to identify the relevant phytochemical constituents for characterization and authentication of tomatoes. To prove the feasibility of AID algorithm and ANN models to achieve the purpose of this study, both methods were applied on a data set with twenty five chemical parameters analysed on 167 tomato samples from Tenerife (Spain. Each tomato sample was defined by three factors: cultivar, agricultural practice and harvest date. General Linear Model linked to AID (GLM-AID tree-structured was organized into 3 levels according to the number of factors. p-Coumaric acid was the compound the allowed to distinguish the tomato samples according to the day of harvest. More than one chemical parameter was necessary to distinguish among different agricultural practices and among the tomato cultivars. Several ANN models, with 25 and 10 input variables, for the prediction of cultivar, agricultural practice and harvest date, were developed. Finally, the models with 10 input variables were chosen with fit's goodness

  6. Identification of Relevant Phytochemical Constituents for Characterization and Authentication of Tomatoes by General Linear Model Linked to Automatic Interaction Detection (GLM-AID) and Artificial Neural Network Models (ANNs).

    Science.gov (United States)

    Hernández Suárez, Marcos; Astray Dopazo, Gonzalo; Larios López, Dina; Espinosa, Francisco

    2015-01-01

    There are a large number of tomato cultivars with a wide range of morphological, chemical, nutritional and sensorial characteristics. Many factors are known to affect the nutrient content of tomato cultivars. A complete understanding of the effect of these factors would require an exhaustive experimental design, multidisciplinary scientific approach and a suitable statistical method. Some multivariate analytical techniques such as Principal Component Analysis (PCA) or Factor Analysis (FA) have been widely applied in order to search for patterns in the behaviour and reduce the dimensionality of a data set by a new set of uncorrelated latent variables. However, in some cases it is not useful to replace the original variables with these latent variables. In this study, Automatic Interaction Detection (AID) algorithm and Artificial Neural Network (ANN) models were applied as alternative to the PCA, AF and other multivariate analytical techniques in order to identify the relevant phytochemical constituents for characterization and authentication of tomatoes. To prove the feasibility of AID algorithm and ANN models to achieve the purpose of this study, both methods were applied on a data set with twenty five chemical parameters analysed on 167 tomato samples from Tenerife (Spain). Each tomato sample was defined by three factors: cultivar, agricultural practice and harvest date. General Linear Model linked to AID (GLM-AID) tree-structured was organized into 3 levels according to the number of factors. p-Coumaric acid was the compound the allowed to distinguish the tomato samples according to the day of harvest. More than one chemical parameter was necessary to distinguish among different agricultural practices and among the tomato cultivars. Several ANN models, with 25 and 10 input variables, for the prediction of cultivar, agricultural practice and harvest date, were developed. Finally, the models with 10 input variables were chosen with fit's goodness between 44 and 100

  7. Optimal neural computations require analog processors

    Energy Technology Data Exchange (ETDEWEB)

    Beiu, V.

    1998-12-31

    This paper discusses some of the limitations of hardware implementations of neural networks. The authors start by presenting neural structures and their biological inspirations, while mentioning the simplifications leading to artificial neural networks. Further, the focus will be on hardware imposed constraints. They will present recent results for three different alternatives of parallel implementations of neural networks: digital circuits, threshold gate circuits, and analog circuits. The area and the delay will be related to the neurons` fan-in and to the precision of their synaptic weights. The main conclusion is that hardware-efficient solutions require analog computations, and suggests the following two alternatives: (i) cope with the limitations imposed by silicon, by speeding up the computation of the elementary silicon neurons; (2) investigate solutions which would allow the use of the third dimension (e.g. using optical interconnections).

  8. Artificial Neural Network with Hardware Training and Hardware Refresh

    Science.gov (United States)

    Duong, Tuan A. (Inventor)

    2003-01-01

    A neural network circuit is provided having a plurality of circuits capable of charge storage. Also provided is a plurality of circuits each coupled to at least one of the plurality of charge storage circuits and constructed to generate an output in accordance with a neuron transfer function. Each of a plurality of circuits is coupled to one of the plurality of neuron transfer function circuits and constructed to generate a derivative of the output. A weight update circuit updates the charge storage circuits based upon output from the plurality of transfer function circuits and output from the plurality of derivative circuits. In preferred embodiments, separate training and validation networks share the same set of charge storage circuits and may operate concurrently. The validation network has a separate transfer function circuits each being coupled to the charge storage circuits so as to replicate the training network s coupling of the plurality of charge storage to the plurality of transfer function circuits. The plurality of transfer function circuits may be constructed each having a transconductance amplifier providing differential currents combined to provide an output in accordance with a transfer function. The derivative circuits may have a circuit constructed to generate a biased differential currents combined so as to provide the derivative of the transfer function.

  9. Electric circuits and signals

    CERN Document Server

    Sabah, Nassir H

    2007-01-01

    Circuit Variables and Elements Overview Learning Objectives Electric Current Voltage Electric Power and Energy Assigned Positive Directions Active and Passive Circuit Elements Voltage and Current Sources The Resistor The Capacitor The Inductor Concluding Remarks Summary of Main Concepts and Results Learning Outcomes Supplementary Topics on CD Problems and Exercises Basic Circuit Connections and Laws Overview Learning Objectives Circuit Terminology Kirchhoff's Laws Voltage Division and Series Connection of Resistors Current Division and Parallel Connection of Resistors D-Y Transformation Source Equivalence and Transformation Reduced-Voltage Supply Summary of Main Concepts and Results Learning Outcomes Supplementary Topics and Examples on CD Problems and Exercises Basic Analysis of Resistive Circuits Overview Learning Objectives Number of Independent Circuit Equations Node-Voltage Analysis Special Considerations in Node-Voltage Analysis Mesh-Current Analysis Special Conside...

  10. Analog circuits cookbook

    CERN Document Server

    Hickman, Ian

    2013-01-01

    Analog Circuits Cookbook presents articles about advanced circuit techniques, components and concepts, useful IC for analog signal processing in the audio range, direct digital synthesis, and ingenious video op-amp. The book also includes articles about amplitude measurements on RF signals, linear optical imager, power supplies and devices, and RF circuits and techniques. Professionals and students of electrical engineering will find the book informative and useful.

  11. Analog circuit design

    CERN Document Server

    Dobkin, Bob

    2012-01-01

    Analog circuit and system design today is more essential than ever before. With the growth of digital systems, wireless communications, complex industrial and automotive systems, designers are being challenged to develop sophisticated analog solutions. This comprehensive source book of circuit design solutions aids engineers with elegant and practical design techniques that focus on common analog challenges. The book's in-depth application examples provide insight into circuit design and application solutions that you can apply in today's demanding designs. <

  12. Regenerative feedback resonant circuit

    Science.gov (United States)

    Jones, A. Mark; Kelly, James F.; McCloy, John S.; McMakin, Douglas L.

    2014-09-02

    A regenerative feedback resonant circuit for measuring a transient response in a loop is disclosed. The circuit includes an amplifier for generating a signal in the loop. The circuit further includes a resonator having a resonant cavity and a material located within the cavity. The signal sent into the resonator produces a resonant frequency. A variation of the resonant frequency due to perturbations in electromagnetic properties of the material is measured.

  13. Quantum Memristors with Superconducting Circuits.

    Science.gov (United States)

    Salmilehto, J; Deppe, F; Di Ventra, M; Sanz, M; Solano, E

    2017-02-14

    Memristors are resistive elements retaining information of their past dynamics. They have garnered substantial interest due to their potential for representing a paradigm change in electronics, information processing and unconventional computing. Given the advent of quantum technologies, a design for a quantum memristor with superconducting circuits may be envisaged. Along these lines, we introduce such a quantum device whose memristive behavior arises from quasiparticle-induced tunneling when supercurrents are cancelled. For realistic parameters, we find that the relevant hysteretic behavior may be observed using current state-of-the-art measurements of the phase-driven tunneling current. Finally, we develop suitable methods to quantify memory retention in the system.

  14. CMOS circuits manual

    CERN Document Server

    Marston, R M

    1995-01-01

    CMOS Circuits Manual is a user's guide for CMOS. The book emphasizes the practical aspects of CMOS and provides circuits, tables, and graphs to further relate the fundamentals with the applications. The text first discusses the basic principles and characteristics of the CMOS devices. The succeeding chapters detail the types of CMOS IC, including simple inverter, gate and logic ICs and circuits, and complex counters and decoders. The last chapter presents a miscellaneous collection of two dozen useful CMOS circuits. The book will be useful to researchers and professionals who employ CMOS circu

  15. Circuits and filters handbook

    CERN Document Server

    Chen, Wai-Kai

    2003-01-01

    A bestseller in its first edition, The Circuits and Filters Handbook has been thoroughly updated to provide the most current, most comprehensive information available in both the classical and emerging fields of circuits and filters, both analog and digital. This edition contains 29 new chapters, with significant additions in the areas of computer-aided design, circuit simulation, VLSI circuits, design automation, and active and digital filters. It will undoubtedly take its place as the engineer's first choice in looking for solutions to problems encountered in the design, analysis, and behavi

  16. Nanoscale Microelectronic Circuit Development

    Science.gov (United States)

    2011-06-17

    Project 3: Low-Power All-Digital Chip-to-Chip Interface Circuits by Pavan Kumar Hanumolu (OSU) CDADIC Project 4: Nanoscale Clock and Data Recovery...CDADIC Project 3: Low-Power All-Digital Chip-to-Chip Interface Circuits by Pavan Kumar Hanumolu (OSU) CDADIC Project 6: Stochastic and Passive A/D...Area 3: Reconfigurable Mixed-Signal Circuits CDADIC Project 3: Low-Power All-Digital Chip-to-Chip Interface Circuits by Pavan Kumar Hanumolu (OSU

  17. Timergenerator circuits manual

    CERN Document Server

    Marston, R M

    2013-01-01

    Timer/Generator Circuits Manual is an 11-chapter text that deals mainly with waveform generator techniques and circuits. Each chapter starts with an explanation of the basic principles of its subject followed by a wide range of practical circuit designs. This work presents a total of over 300 practical circuits, diagrams, and tables.Chapter 1 outlines the basic principles and the different types of generator. Chapters 2 to 9 deal with a specific type of waveform generator, including sine, square, triangular, sawtooth, and special waveform generators pulse. These chapters also include pulse gen

  18. Electronic devices and circuits

    CERN Document Server

    Pridham, Gordon John

    1968-01-01

    Electronic Devices and Circuits, Volume 1 deals with the design and applications of electronic devices and circuits such as passive components, diodes, triodes and transistors, rectification and power supplies, amplifying circuits, electronic instruments, and oscillators. These topics are supported with introductory network theory and physics. This volume is comprised of nine chapters and begins by explaining the operation of resistive, inductive, and capacitive elements in direct and alternating current circuits. The theory for some of the expressions quoted in later chapters is presented. Th

  19. Security electronics circuits manual

    CERN Document Server

    MARSTON, R M

    1998-01-01

    Security Electronics Circuits Manual is an invaluable guide for engineers and technicians in the security industry. It will also prove to be a useful guide for students and experimenters, as well as providing experienced amateurs and DIY enthusiasts with numerous ideas to protect their homes, businesses and properties.As with all Ray Marston's Circuits Manuals, the style is easy-to-read and non-mathematical, with the emphasis firmly on practical applications, circuits and design ideas. The ICs and other devices used in the practical circuits are modestly priced and readily available ty

  20. MOS integrated circuit design

    CERN Document Server

    Wolfendale, E

    2013-01-01

    MOS Integral Circuit Design aims to help in the design of integrated circuits, especially large-scale ones, using MOS Technology through teaching of techniques, practical applications, and examples. The book covers topics such as design equation and process parameters; MOS static and dynamic circuits; logic design techniques, system partitioning, and layout techniques. Also featured are computer aids such as logic simulation and mask layout, as well as examples on simple MOS design. The text is recommended for electrical engineers who would like to know how to use MOS for integral circuit desi

  1. FOXP2 and the role of cortico-basal ganglia circuits in speech and language evolution.

    Science.gov (United States)

    Enard, Wolfgang

    2011-06-01

    A reduced dosage of the transcription factor FOXP2 leads to speech and language impairments probably owing to deficits in cortical and subcortical neural circuits. Based on evolutionary sequence analysis it has been proposed that the two amino acid substitutions that occurred on the human lineage have been positively selected. Here I review recent studies investigating the functional consequences of these two substitutions and discuss how these first endeavors to study human brain evolution can be interpreted in the context of speech and language evolution. Mice carrying the two substitutions in their endogenous Foxp2 gene show specific alterations in dopamine levels, striatal synaptic plasticity and neuronal morphology. Mice carrying only one functional Foxp2, show additional and partly opposite effects suggesting that FOXP2 has contributed to tuning cortico-basal ganglia circuits during human evolution. Evidence from human and songbird studies suggest that this could have been relevant during language acquisition or vocal learning, respectively. FOXP2 could have contributed to the evolution of human speech and language by adapting cortico-basal ganglia circuits. More generally the recent studies allow careful optimism that aspects of human brain evolution can be investigated in model systems such as the mouse. Copyright © 2011 Elsevier Ltd. All rights reserved.

  2. Offset cancelling circuit

    NARCIS (Netherlands)

    Wiegerink, Remco J.; Seevinck, Evert; de Jager, Wim

    1989-01-01

    A monolithic offset cancelling circuit to reduce the offset voltage at an integrated audio-amplifier output is described. This offset voltage is detected using a low-pass filter with a very large time constant for which only one small on-chip capacitor is needed. The circuit was realized with a

  3. Synchronizing Hyperchaotic Circuits

    DEFF Research Database (Denmark)

    Tamasevicius, Arunas; Cenys, Antanas; Namajunas, Audrius

    1997-01-01

    Regarding possible applications to secure communications the technique of synchronizing hyperchaotic circuits with a single dynamical variable is discussed. Several specific examples including the fourth-order circuits with two positive Lyapunov exponents as well as the oscillator with a delay line...

  4. A Virtual Circuits Lab

    Science.gov (United States)

    Vick, Matthew E.

    2010-01-01

    The University of Colorado's Physics Education Technology (PhET) website offers free, high-quality simulations of many physics experiments that can be used in the classroom. The Circuit Construction Kit, for example, allows students to safely and constructively play with circuit components while learning the mathematics behind many circuit…

  5. CMOS analog circuit design

    CERN Document Server

    Allen, Phillip E

    1987-01-01

    This text presents the principles and techniques for designing analog circuits to be implemented in a CMOS technology. The level is appropriate for seniors and graduate students familiar with basic electronics, including biasing, modeling, circuit analysis, and some familiarity with frequency response. Students learn the methodology of analog integrated circuit design through a hierarchically-oriented approach to the subject that provides thorough background and practical guidance for designing CMOS analog circuits, including modeling, simulation, and testing. The authors' vast industrial experience and knowledge is reflected in the circuits, techniques, and principles presented. They even identify the many common pitfalls that lie in the path of the beginning designer--expert advice from veteran designers. The text mixes the academic and practical viewpoints in a treatment that is neither superficial nor overly detailed, providing the perfect balance.

  6. Adolescent gain in positive valence of a socially relevant stimulus: engagement of the mesocorticolimbic reward circuitry.

    Science.gov (United States)

    Bell, Margaret R; De Lorme, Kayla C; Figueira, Rayson J; Kashy, Deborah A; Sisk, Cheryl L

    2013-02-01

    A successful transition from childhood to adulthood requires adolescent maturation of social information processing. The neurobiological underpinnings of this maturational process remain elusive. This research employed the male Syrian hamster as a tractable animal model for investigating the neural circuitry involved in this critical transition. In this species, adult and juvenile males display different behavioral and neural responses to vaginal secretions, which contain pheromones essential for expression of sexual behavior in adulthood. These studies tested the hypothesis that vaginal secretions acquire positive valence over adolescent development via remodeling of neural circuits underlying sexual reward. Sexually naïve adult, but not juvenile, hamsters showed a conditioned place preference for vaginal secretions. Differences in behavioral response to vaginal secretions between juveniles and adults correlated with a difference in the vaginal secretion-induced neural activation pattern in mesocorticolimbic reward circuitry. Fos immunoreactivity increased in response to vaginal secretions in the medial amygdala and ventral tegmental dopaminergic cells of both juvenile and adult males. However, only in adults was there a Fos response to vaginal secretions in non-dopaminergic cells in interfascicular ventral tegmental area, nucleus accumbens core and infralimbic medial prefrontal cortex. These results demonstrate that a socially relevant chemosensory stimulus acquires the status of an unconditioned reward during adolescence, and that this adolescent gain in social reward is correlated with experience-independent engagement of specific cell groups in reward circuitry. © 2012 Federation of European Neuroscience Societies and Blackwell Publishing Ltd.

  7. [Glutamate signaling and neural plasticity].

    Science.gov (United States)

    Watanabe, Masahiko

    2013-07-01

    Proper functioning of the nervous system relies on the precise formation of neural circuits during development. At birth, neurons have redundant synaptic connections not only to their proper targets but also to other neighboring cells. Then, functional neural circuits are formed during early postnatal development by the selective strengthening of necessary synapses and weakening of surplus connections. Synaptic connections are also modified so that projection fields of active afferents expand at the expense of lesser ones. We have studied the molecular mechanisms underlying these activity-dependent prunings and the plasticity of synaptic circuitry using gene-engineered mice defective in the glutamatergic signaling system. NMDA-type glutamate receptors are critically involved in the establishment of the somatosensory pathway ascending from the brainstem trigeminal nucleus to the somatosensory cortex. Without NMDA receptors, whisker-related patterning fails to develop, whereas lesion-induced plasticity occurs normally during the critical period. In contrast, mice lacking the glutamate transporters GLAST or GLT1 are selectively impaired in the lesion-induced critical plasticity of cortical barrels, although whisker-related patterning itself develops normally. In the developing cerebellum, multiple climbing fibers initially innervating given Purkinje cells are eliminated one by one until mono-innervation is achieved. In this pruning process, P/Q-type Ca2+ channels expressed on Purkinje cells are critically involved by the selective strengthening of single main climbing fibers against other lesser afferents. Therefore, the activation of glutamate receptors that leads to an activity-dependent increase in the intracellular Ca2+ concentration plays a key role in the pruning of immature synaptic circuits into functional circuits. On the other hand, glutamate transporters appear to control activity-dependent plasticity among afferent fields, presumably through adjusting

  8. Hysteresis in a quantized superfluid `atomtronic' circuit

    Science.gov (United States)

    Eckel, Stephen; Lee, Jeffrey G.; Jendrzejewski, Fred; Murray, Noel; Clark, Charles W.; Lobb, Christopher J.; Phillips, William D.; Edwards, Mark; Campbell, Gretchen K.

    2014-02-01

    Atomtronics is an emerging interdisciplinary field that seeks to develop new functional methods by creating devices and circuits where ultracold atoms, often superfluids, have a role analogous to that of electrons in electronics. Hysteresis is widely used in electronic circuits--it is routinely observed in superconducting circuits and is essential in radio-frequency superconducting quantum interference devices. Furthermore, it is as fundamental to superfluidity (and superconductivity) as quantized persistent currents, critical velocity and Josephson effects. Nevertheless, despite multiple theoretical predictions, hysteresis has not been previously observed in any superfluid, atomic-gas Bose-Einstein condensate. Here we directly detect hysteresis between quantized circulation states in an atomtronic circuit formed from a ring of superfluid Bose-Einstein condensate obstructed by a rotating weak link (a region of low atomic density). This contrasts with previous experiments on superfluid liquid helium where hysteresis was observed directly in systems in which the quantization of flow could not be observed, and indirectly in systems that showed quantized flow. Our techniques allow us to tune the size of the hysteresis loop and to consider the fundamental excitations that accompany hysteresis. The results suggest that the relevant excitations involved in hysteresis are vortices, and indicate that dissipation has an important role in the dynamics. Controlled hysteresis in atomtronic circuits may prove to be a crucial feature for the development of practical devices, just as it has in electronic circuits such as memories, digital noise filters (for example Schmitt triggers) and magnetometers (for example superconducting quantum interference devices).

  9. Approximate circuits for increased reliability

    Science.gov (United States)

    Hamlet, Jason R.; Mayo, Jackson R.

    2015-08-18

    Embodiments of the invention describe a Boolean circuit having a voter circuit and a plurality of approximate circuits each based, at least in part, on a reference circuit. The approximate circuits are each to generate one or more output signals based on values of received input signals. The voter circuit is to receive the one or more output signals generated by each of the approximate circuits, and is to output one or more signals corresponding to a majority value of the received signals. At least some of the approximate circuits are to generate an output value different than the reference circuit for one or more input signal values; however, for each possible input signal value, the majority values of the one or more output signals generated by the approximate circuits and received by the voter circuit correspond to output signal result values of the reference circuit.

  10. Approximate circuits for increased reliability

    Energy Technology Data Exchange (ETDEWEB)

    Hamlet, Jason R.; Mayo, Jackson R.

    2015-12-22

    Embodiments of the invention describe a Boolean circuit having a voter circuit and a plurality of approximate circuits each based, at least in part, on a reference circuit. The approximate circuits are each to generate one or more output signals based on values of received input signals. The voter circuit is to receive the one or more output signals generated by each of the approximate circuits, and is to output one or more signals corresponding to a majority value of the received signals. At least some of the approximate circuits are to generate an output value different than the reference circuit for one or more input signal values; however, for each possible input signal value, the majority values of the one or more output signals generated by the approximate circuits and received by the voter circuit correspond to output signal result values of the reference circuit.

  11. Troubleshooting analog circuits

    CERN Document Server

    Pease, Robert A

    1991-01-01

    Troubleshooting Analog Circuits is a guidebook for solving product or process related problems in analog circuits. The book also provides advice in selecting equipment, preventing problems, and general tips. The coverage of the book includes the philosophy of troubleshooting; the modes of failure of various components; and preventive measures. The text also deals with the active components of analog circuits, including diodes and rectifiers, optically coupled devices, solar cells, and batteries. The book will be of great use to both students and practitioners of electronics engineering. Other

  12. Circuit analysis with Multisim

    CERN Document Server

    Baez-Lopez, David

    2011-01-01

    This book is concerned with circuit simulation using National Instruments Multisim. It focuses on the use and comprehension of the working techniques for electrical and electronic circuit simulation. The first chapters are devoted to basic circuit analysis.It starts by describing in detail how to perform a DC analysis using only resistors and independent and controlled sources. Then, it introduces capacitors and inductors to make a transient analysis. In the case of transient analysis, it is possible to have an initial condition either in the capacitor voltage or in the inductor current, or bo

  13. Optoelectronics circuits manual

    CERN Document Server

    Marston, R M

    2013-01-01

    Optoelectronics Circuits Manual covers the basic principles and characteristics of the best known types of optoelectronic devices, as well as the practical applications of many of these optoelectronic devices. The book describes LED display circuits and LED dot- and bar-graph circuits and discusses the applications of seven-segment displays, light-sensitive devices, optocouplers, and a variety of brightness control techniques. The text also tackles infrared light-beam alarms and multichannel remote control systems. The book provides practical user information and circuitry and illustrations.

  14. Plasmonic Nanoguides and Circuits

    CERN Document Server

    Bozhevolnyi, Sergey

    2008-01-01

    Modern communication systems dealing with huge amounts of data at ever increasing speed try to utilize the best aspects of electronic and optical circuits. Electronic circuits are tiny but their operation speed is limited, whereas optical circuits are extremely fast but their sizes are limited by diffraction. Waveguide components utilizing surface plasmon (SP) modes were found to combine the huge optical bandwidth and compactness of electronics, and plasmonics thereby began to be considered as the next chip-scale technology. In this book, the authors concentrate on the SP waveguide configurati

  15. Modern TTL circuits manual

    CERN Document Server

    Marston, R M

    2013-01-01

    Modern TTL Circuits Manual provides an introduction to the basic principles of Transistor-Transistor Logic (TTL). This book outlines the major features of the 74 series of integrated circuits (ICs) and introduces the various sub-groups of the TTL family.Organized into seven chapters, this book begins with an overview of the basics of digital ICs. This text then examines the symbology and mathematics of digital logic. Other chapters consider a variety of topics, including waveform generator circuitry, clocked flip-flop and counter circuits, special counter/dividers, registers, data latches, com

  16. Circadian Control of the Estrogenic Circuits Regulating GnRH Secretion and the Preovulatory Luteinizing Hormone Surge

    Directory of Open Access Journals (Sweden)

    Lance J Kriegsfeld

    2012-05-01

    Full Text Available Female reproduction requires the precise temporal organization of interacting, estradiol-sensitive neural circuits that converge to optimally drive hypothalamo-pituitary-gonadal (HPG axis functioning. In mammals, the master circadian pacemaker in the suprachaismatic nucleus (SCN of the anterior hypothalamus coordinates reproductively-relevant neuroendocrine events necessary to maximize reproductive success. Likewise, in species where periods of fertility are brief, circadian oversight of reproductive function ensures that estradiol-dependent increases in sexual motivation coincide with ovulation. Across species, including humans, disruptions to circadian timing (e.g., through rotating shift work, night shift work, poor sleep hygiene lead to pronounced deficits in ovulation and fecundity. Despite the well-established roles for the circadian system in female reproductive functioning, the specific neural circuits and neurochemical mediators underlying these interactions are not fully understood. Most work to date has focused on the direct and indirect communication from the SCN to the GnRH system in control of the preovulatory LH surge. However, the same clock genes underlying circadian rhythms at the cellular level in SCN cells are also common to target cell populations of the SCN, including the GnRH neuronal network. Exploring the means by which the master clock synergizes with subordinate clocks in GnRH cells and its upstream modulatory systems represents an exciting opportunity to further understand the role of endogenous timing systems in female reproduction. Herein we provide an overview of the state of knowledge regarding interactions between the circadian timing system and estradiol-sensitive neural circuits driving GnRH secretion and the preovulatory LH surge.

  17. Fractional Hopfield Neural Networks: Fractional Dynamic Associative Recurrent Neural Networks.

    Science.gov (United States)

    Pu, Yi-Fei; Yi, Zhang; Zhou, Ji-Liu

    2017-10-01

    This paper mainly discusses a novel conceptual framework: fractional Hopfield neural networks (FHNN). As is commonly known, fractional calculus has been incorporated into artificial neural networks, mainly because of its long-term memory and nonlocality. Some researchers have made interesting attempts at fractional neural networks and gained competitive advantages over integer-order neural networks. Therefore, it is naturally makes one ponder how to generalize the first-order Hopfield neural networks to the fractional-order ones, and how to implement FHNN by means of fractional calculus. We propose to introduce a novel mathematical method: fractional calculus to implement FHNN. First, we implement fractor in the form of an analog circuit. Second, we implement FHNN by utilizing fractor and the fractional steepest descent approach, construct its Lyapunov function, and further analyze its attractors. Third, we perform experiments to analyze the stability and convergence of FHNN, and further discuss its applications to the defense against chip cloning attacks for anticounterfeiting. The main contribution of our work is to propose FHNN in the form of an analog circuit by utilizing a fractor and the fractional steepest descent approach, construct its Lyapunov function, prove its Lyapunov stability, analyze its attractors, and apply FHNN to the defense against chip cloning attacks for anticounterfeiting. A significant advantage of FHNN is that its attractors essentially relate to the neuron's fractional order. FHNN possesses the fractional-order-stability and fractional-order-sensitivity characteristics.

  18. Circuitry for a Wireless Microsystem for Neural Recording Microprobes

    National Research Council Canada - National Science Library

    Yu, Hao

    2001-01-01

    .... Recorded neural signals are amplified, multiplexed, digitized using a 2nd order sigma-delta modulator, and then transmitted to the outside world by an on-chip transmitter, The circuit is designed using a standard...

  19. Quantum circuits for cryptanalysis

    Science.gov (United States)

    Amento, Brittanney Jaclyn

    Finite fields of the form F2 m play an important role in coding theory and cryptography. We show that the choice of how to represent the elements of these fields can have a significant impact on the resource requirements for quantum arithmetic. In particular, we show how the Gaussian normal basis representations and "ghost-bit basis" representations can be used to implement inverters with a quantum circuit of depth O(mlog(m)). To the best of our knowledge, this is the first construction with subquadratic depth reported in the literature. Our quantum circuit for the computation of multiplicative inverses is based on the Itoh-Tsujii algorithm which exploits the property that, in a normal basis representation, squaring corresponds to a permutation of the coefficients. We give resource estimates for the resulting quantum circuit for inversion over binary fields F2 m based on an elementary gate set that is useful for fault-tolerant implementation. Elliptic curves over finite fields F2 m play a prominent role in modern cryptography. Published quantum algorithms dealing with such curves build on a short Weierstrass form in combination with affine or projective coordinates. In this thesis we show that changing the curve representation allows a substantial reduction in the number of T-gates needed to implement the curve arithmetic. As a tool, we present a quantum circuit for computing multiplicative inverses in F2m in depth O(m log m) using a polynomial basis representation, which may be of independent interest. Finally, we change our focus from the design of circuits which aim at attacking computational assumptions on asymmetric cryptographic algorithms to the design of a circuit attacking a symmetric cryptographic algorithm. We consider a block cipher, SERPENT, and our design of a quantum circuit implementing this cipher to be used for a key attack using Grover's algorithm as in [18]. This quantum circuit is essential for understanding the complexity of Grover's algorithm.

  20. On the SCTC-OCTC Method for the Analysis and Design of Circuits

    Science.gov (United States)

    Salvatori, S.; Conte, G.

    2009-01-01

    This paper discusses guidelines that emphasize the relevance of short-circuit- and open-circuit-time constant (SCTC and OCTC, respectively) methods in the analysis and design of electronic amplifiers. It is demonstrated that it is only necessary to grasp a few concepts in order to understand that the two short- and open-circuit cases fall into a…

  1. Color Coding of Circuit Quantities in Introductory Circuit Analysis Instruction

    Science.gov (United States)

    Reisslein, Jana; Johnson, Amy M.; Reisslein, Martin

    2015-01-01

    Learning the analysis of electrical circuits represented by circuit diagrams is often challenging for novice students. An open research question in electrical circuit analysis instruction is whether color coding of the mathematical symbols (variables) that denote electrical quantities can improve circuit analysis learning. The present study…

  2. Integrated Circuits for Analog Signal Processing

    CERN Document Server

    2013-01-01

      This book presents theory, design methods and novel applications for integrated circuits for analog signal processing.  The discussion covers a wide variety of active devices, active elements and amplifiers, working in voltage mode, current mode and mixed mode.  This includes voltage operational amplifiers, current operational amplifiers, operational transconductance amplifiers, operational transresistance amplifiers, current conveyors, current differencing transconductance amplifiers, etc.  Design methods and challenges posed by nanometer technology are discussed and applications described, including signal amplification, filtering, data acquisition systems such as neural recording, sensor conditioning such as biomedical implants, actuator conditioning, noise generators, oscillators, mixers, etc.   Presents analysis and synthesis methods to generate all circuit topologies from which the designer can select the best one for the desired application; Includes design guidelines for active devices/elements...

  3. Integral dose delivered to normal brain with conventional intensity-modulated radiotherapy (IMRT) and helical tomotherapy IMRT during partial brain radiotherapy for high-grade gliomas with and without selective sparing of the hippocampus, limbic circuit and neural stem cell compartment.

    Science.gov (United States)

    Marsh, James C; Ziel, G Ellis; Diaz, Aidnag Z; Wendt, Julie A; Gobole, Rohit; Turian, Julius V

    2013-06-01

    We compared integral dose with uninvolved brain (IDbrain ) during partial brain radiotherapy (PBRT) for high-grade glioma patients using helical tomotherapy (HT) and seven field traditional inverse-planned intensity-modulated radiotherapy (IMRT) with and without selective sparing (SPA) of contralateral hippocampus, neural stem cell compartment (NSC) and limbic circuit. We prepared four PBRT treatment plans for four patients with high-grade gliomas (60 Gy in 30 fractions delivered to planning treatment volume (PTV60Gy)). For all plans, a structure denoted 'uninvolved brain' was created, which included all brain tissue not part of PTV or standard (STD) organs at risk (OAR). No dosimetric constraints were included for uninvolved brain. Selective SPA plans were prepared with IMRT and HT; contralateral hippocampus, NSC and limbic circuit were contoured; and dosimetric constraints were entered for these structures without compromising dose to PTV or STD OAR. We compared V100 and D95 for PTV46Gy and PTV60Gy, and IDbrain for all plans. There were no significant differences in V100 and D95 for PTV46Gy and PTV60Gy. IDbrain was lower in traditional IMRT versus HT plans for STD and SPA plans (mean IDbrain 23.64 Gy vs. 28 Gy and 18.7 Gy vs. 24.5 Gy, respectively) and in SPA versus STD plans both with IMRT and HT (18.7 Gy vs. 23.64 Gy and 24.5 Gy vs. 28 Gy, respectively). In the setting of PBRT for high-grade gliomas, IMRT reduces IDbrain compared with HT with or without selective SPA of contralateral hippocampus, limbic circuit and NSC, and the use of selective SPA reduces IDbrain compared with STD PBRT delivered with either traditional IMRT or HT. © 2013 The Authors. Journal of Medical Imaging and Radiation Oncology © 2013 The Royal Australian and New Zealand College of Radiologists.

  4. Activity-dependent neural plasticity from bench to bedside.

    Science.gov (United States)

    Ganguly, Karunesh; Poo, Mu-Ming

    2013-10-30

    Much progress has been made in understanding how behavioral experience and neural activity can modify the structure and function of neural circuits during development and in the adult brain. Studies of physiological and molecular mechanisms underlying activity-dependent plasticity in animal models have suggested potential therapeutic approaches for a wide range of brain disorders in humans. Physiological and electrical stimulations as well as plasticity-modifying molecular agents may facilitate functional recovery by selectively enhancing existing neural circuits or promoting the formation of new functional circuits. Here, we review the advances in basic studies of neural plasticity mechanisms in developing and adult nervous systems and current clinical treatments that harness neural plasticity, and we offer perspectives on future development of plasticity-based therapy. Copyright © 2013 Elsevier Inc. All rights reserved.

  5. Neural plasticity after spinal cord injury.

    Science.gov (United States)

    Liu, Jian; Yang, Xiaoyu; Jiang, Lianying; Wang, Chunxin; Yang, Maoguang

    2012-02-15

    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. The results showed that synaptic reorganization, axonal sprouting, and neurogenesis are critical factors for neural circuit reconstruction. Directed functional exercise, neurotrophic factor and transplantation of nerve-derived and non-nerve-derived tissues and cells can effectively ameliorate functional disturbances caused by spinal cord injury and improve quality of life for patients.

  6. GABAergic circuit dysfunctions in neurodevelopmental disorders

    Directory of Open Access Journals (Sweden)

    Bidisha eChattopadhyaya

    2012-05-01

    Full Text Available GABAergic interneurons control neuronal excitability, integration, and plasticity. Further, they regulate the generation of temporal synchrony and oscillatory behavior among networks of pyramidal neurons. Such oscillations within and across neural systems are believed to serve various complex functions, such as perception, movement initiation, and memory. Alterations in the development of GABAergic circuits have been implicated in various brain diseases with neurodevelopmental origin. Here, we highlight recent studies suggesting a role for alterations of GABA transmission in the pathophysiology of two neurodevelopmental diseases, schizophrenia and autism. We further discuss how manipulations of GABA signaling may be used for novel therapeutic interventions.

  7. Characteristic and intermingled neocortical circuits encode different visual object discriminations.

    Science.gov (United States)

    Zhang, Guo-Rong; Zhao, Hua; Cook, Nathan; Svestka, Michael; Choi, Eui M; Jan, Mary; Cook, Robert G; Geller, Alfred I

    2017-07-28

    Synaptic plasticity and neural network theories hypothesize that the essential information for advanced cognitive tasks is encoded in specific circuits and neurons within distributed neocortical networks. However, these circuits are incompletely characterized, and we do not know if a specific discrimination is encoded in characteristic circuits among multiple animals. Here, we determined the spatial distribution of active neurons for a circuit that encodes some of the essential information for a cognitive task. We genetically activated protein kinase C pathways in several hundred spatially-grouped glutamatergic and GABAergic neurons in rat postrhinal cortex, a multimodal associative area that is part of a distributed circuit that encodes visual object discriminations. We previously established that this intervention enhances accuracy for specific discriminations. Moreover, the genetically-modified, local circuit in POR cortex encodes some of the essential information, and this local circuit is preferentially activated during performance, as shown by activity-dependent gene imaging. Here, we mapped the positions of the active neurons, which revealed that two image sets are encoded in characteristic and different circuits. While characteristic circuits are known to process sensory information, in sensory areas, this is the first demonstration that characteristic circuits encode specific discriminations, in a multimodal associative area. Further, the circuits encoding the two image sets are intermingled, and likely overlapping, enabling efficient encoding. Consistent with reconsolidation theories, intermingled and overlapping encoding could facilitate formation of associations between related discriminations, including visually similar discriminations or discriminations learned at the same time or place. Copyright © 2017 Elsevier B.V. All rights reserved.

  8. Respiratory circuits: function, mechanisms, topology, and pathology.

    Science.gov (United States)

    Mironov, Sergej

    2009-04-01

    Neuroscientists have long sought to understand how circuits in the nervous system are organized to generate the precise neural outputs that underlie particular behaviors. Recent studies deepened our understanding of the mechanisms responsible for the generation of the rhythmic output for breathing. Here, the author focuses on issues that are pertinent for the respiratory network and considers its organization and how it derives the functional output. The author discusses pacemaker and network mechanisms of rhythm generation, which are now combined into a novel concept of emergent network activity due to coherent excitation of pacemaker groups. He discusses subcellular basis of this hypothesis and possible mechanisms of synchronization within respiratory network. These new findings in respiratory neuroscience are further applied to explain modifications in breathing during hypoxia and possible origins of respiratory disorders that may be acquired during neural development and aging.

  9. Vibration Damping Circuit Card Assembly

    Science.gov (United States)

    Hunt, Ronald Allen (Inventor)

    2016-01-01

    A vibration damping circuit card assembly includes a populated circuit card having a mass M. A closed metal container is coupled to a surface of the populated circuit card at approximately a geometric center of the populated circuit card. Tungsten balls fill approximately 90% of the metal container with a collective mass of the tungsten balls being approximately (0.07) M.

  10. Advanced models of neural networks nonlinear dynamics and stochasticity in biological neurons

    CERN Document Server

    Rigatos, Gerasimos G

    2015-01-01

    This book provides a complete study on neural structures exhibiting nonlinear and stochastic dynamics, elaborating on neural dynamics by introducing advanced models of neural networks. It overviews the main findings in the modelling of neural dynamics in terms of electrical circuits and examines their stability properties with the use of dynamical systems theory. It is suitable for researchers and postgraduate students engaged with neural networks and dynamical systems theory.

  11. Neuromorphic Silicon Neuron Circuits

    National Research Council Canada - National Science Library

    Indiveri, Giacomo; Linares-Barranco, Bernabé; Hamilton, Tara Julia; Schaik, André van; Etienne-Cummings, Ralph; Delbruck, Tobi; Liu, Shih-Chii; Dudek, Piotr; Häfliger, Philipp; Renaud, Sylvie; Schemmel, Johannes; Cauwenberghs, Gert; Arthur, John; Hynna, Kai; Folowosele, Fopefolu; Saighi, Sylvain; Serrano-Gotarredona, Teresa; Wijekoon, Jayawan; Wang, Yingxue; Boahen, Kwabena

    2011-01-01

    Hardware implementations of spiking neurons can be extremely useful for a large variety of applications, ranging from high-speed modeling of large-scale neural systems to real-time behaving systems...

  12. Enabling complex genetic circuits to respond to extrinsic environmental signals.

    Science.gov (United States)

    Hoynes-O'Connor, Allison; Shopera, Tatenda; Hinman, Kristina; Creamer, John Philip; Moon, Tae Seok

    2017-07-01

    Genetic circuits have the potential to improve a broad range of metabolic engineering processes and address a variety of medical and environmental challenges. However, in order to engineer genetic circuits that can meet the needs of these real-world applications, genetic sensors that respond to relevant extrinsic and intrinsic signals must be implemented in complex genetic circuits. In this work, we construct the first AND and NAND gates that respond to temperature and pH, two signals that have relevance in a variety of real-world applications. A previously identified pH-responsive promoter and a temperature-responsive promoter were extracted from the E. coli genome, characterized, and modified to suit the needs of the genetic circuits. These promoters were combined with components of the type III secretion system in Salmonella typhimurium and used to construct a set of AND gates with up to 23-fold change. Next, an antisense RNA was integrated into the circuit architecture to invert the logic of the AND gate and generate a set of NAND gates with up to 1168-fold change. These circuits provide the first demonstration of complex pH- and temperature-responsive genetic circuits, and lay the groundwork for the use of similar circuits in real-world applications. Biotechnol. Bioeng. 2017;114: 1626-1631. © 2017 Wiley Periodicals, Inc. © 2017 Wiley Periodicals, Inc.

  13. Offset cancelling circuit

    OpenAIRE

    Wiegerink, Remco J.; Seevinck, Evert; de Jager, Wim

    1989-01-01

    A monolithic offset cancelling circuit to reduce the offset voltage at an integrated audio-amplifier output is described. This offset voltage is detected using a low-pass filter with a very large time constant for which only one small on-chip capacitor is needed. The circuit was realized with a bipolar cell-based semicustom array. Measurements have shown that a -3-dB bandwidth below 5 Hz can be realized with a capacitor value of 50 pF. The resulting offset voltage at the audio-amplifier outpu...

  14. Primer printed circuit boards

    CERN Document Server

    Argyle, Andrew

    2009-01-01

    Step-by-step instructions for making your own PCBs at home. Making your own printed circuit board (PCB) might seem a daunting task, but once you master the steps, it's easy to attain professional-looking results. Printed circuit boards, which connect chips and other components, are what make almost all modern electronic devices possible. PCBs are made from sheets of fiberglass clad with copper, usually in multiplelayers. Cut a computer motherboard in two, for instance, and you'll often see five or more differently patterned layers. Making boards at home is relatively easy

  15. Electronic circuits fundamentals & applications

    CERN Document Server

    Tooley, Mike

    2015-01-01

    Electronics explained in one volume, using both theoretical and practical applications.New chapter on Raspberry PiCompanion website contains free electronic tools to aid learning for students and a question bank for lecturersPractical investigations and questions within each chapter help reinforce learning Mike Tooley provides all the information required to get to grips with the fundamentals of electronics, detailing the underpinning knowledge necessary to appreciate the operation of a wide range of electronic circuits, including amplifiers, logic circuits, power supplies and oscillators. The

  16. Electrical Circuit Tester

    Science.gov (United States)

    Love, Frank

    2006-04-18

    An electrical circuit testing device is provided, comprising a case, a digital voltage level testing circuit with a display means, a switch to initiate measurement using the device, a non-shorting switching means for selecting pre-determined electrical wiring configurations to be tested in an outlet, a terminal block, a five-pole electrical plug mounted on the case surface and a set of adapters that can be used for various multiple-pronged electrical outlet configurations for voltages from 100 600 VAC from 50 100 Hz.

  17. Circuit design for reliability

    CERN Document Server

    Cao, Yu; Wirth, Gilson

    2015-01-01

    This book presents physical understanding, modeling and simulation, on-chip characterization, layout solutions, and design techniques that are effective to enhance the reliability of various circuit units.  The authors provide readers with techniques for state of the art and future technologies, ranging from technology modeling, fault detection and analysis, circuit hardening, and reliability management. Provides comprehensive review on various reliability mechanisms at sub-45nm nodes; Describes practical modeling and characterization techniques for reliability; Includes thorough presentation of robust design techniques for major VLSI design units; Promotes physical understanding with first-principle simulations.

  18. Neural Plasticity and Neurorehabilitation: Teaching the New Brain Old Tricks

    Science.gov (United States)

    Kleim, Jeffrey A.

    2011-01-01

    Following brain injury or disease there are widespread biochemical, anatomical and physiological changes that result in what might be considered a new, very different brain. This adapted brain is forced to reacquire behaviors lost as a result of the injury or disease and relies on neural plasticity within the residual neural circuits. The same…

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

    Science.gov (United States)

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

    2017-08-01

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

  20. Power amplifier circuit

    NARCIS (Netherlands)

    Takeya, Hideaki; Nauta, Bram

    2015-01-01

    PROBLEM TO BE SOLVED: To provide a power amplifier circuit which has high power efficiency while suppressing a fluctuation of output power relatively to a fluctuation of a power supply voltage in a high-efficiency switching amplifier which operates in a radio frequency band.SOLUTION: A duty ratio

  1. "Printed-circuit" rectenna

    Science.gov (United States)

    Dickinson, R. M.

    1977-01-01

    Rectifying antenna is less bulky structure for absorbing transmitted microwave power and converting it into electrical current. Printed-circuit approach, using microstrip technology and circularly polarized antenna, makes polarization orientation unimportant and allows much smaller arrays for given performance. Innovation is particularly useful with proposed electric vehicles powered by beam microwaves.

  2. Superconducting Quantum Circuits

    NARCIS (Netherlands)

    Majer, J.B.

    2002-01-01

    This thesis describes a number of experiments with superconducting cir- cuits containing small Josephson junctions. The circuits are made out of aluminum islands which are interconnected with a very thin insulating alu- minum oxide layer. The connections form a Josephson junction. The current trough

  3. ESD analog circuits and design

    CERN Document Server

    Voldman, Steven H

    2014-01-01

    A comprehensive and in-depth review of analog circuit layout, schematic architecture, device, power network and ESD design This book will provide a balanced overview of analog circuit design layout, analog circuit schematic development, architecture of chips, and ESD design.  It will start at an introductory level and will bring the reader right up to the state-of-the-art. Two critical design aspects for analog and power integrated circuits are combined. The first design aspect covers analog circuit design techniques to achieve the desired circuit performance. The second and main aspect pres

  4. Track Circuit Fault Diagnosis Method based on Least Squares Support Vector

    Science.gov (United States)

    Cao, Yan; Sun, Fengru

    2018-01-01

    In order to improve the troubleshooting efficiency and accuracy of the track circuit, track circuit fault diagnosis method was researched. Firstly, the least squares support vector machine was applied to design the multi-fault classifier of the track circuit, and then the measured track data as training samples was used to verify the feasibility of the methods. Finally, the results based on BP neural network fault diagnosis methods and the methods used in this paper were compared. Results shows that the track fault classifier based on least squares support vector machine can effectively achieve the five track circuit fault diagnosis with less computing time.

  5. Artificial immune system algorithm in VLSI circuit configuration

    Science.gov (United States)

    Mansor, Mohd. Asyraf; Sathasivam, Saratha; Kasihmuddin, Mohd Shareduwan Mohd

    2017-08-01

    In artificial intelligence, the artificial immune system is a robust bio-inspired heuristic method, extensively used in solving many constraint optimization problems, anomaly detection, and pattern recognition. This paper discusses the implementation and performance of artificial immune system (AIS) algorithm integrated with Hopfield neural networks for VLSI circuit configuration based on 3-Satisfiability problems. Specifically, we emphasized on the clonal selection technique in our binary artificial immune system algorithm. We restrict our logic construction to 3-Satisfiability (3-SAT) clauses in order to outfit with the transistor configuration in VLSI circuit. The core impetus of this research is to find an ideal hybrid model to assist in the VLSI circuit configuration. In this paper, we compared the artificial immune system (AIS) algorithm (HNN-3SATAIS) with the brute force algorithm incorporated with Hopfield neural network (HNN-3SATBF). Microsoft Visual C++ 2013 was used as a platform for training, simulating and validating the performances of the proposed network. The results depict that the HNN-3SATAIS outperformed HNN-3SATBF in terms of circuit accuracy and CPU time. Thus, HNN-3SATAIS can be used to detect an early error in the VLSI circuit design.

  6. Mapping of topological quantum circuits to physical hardware.

    Science.gov (United States)

    Paler, Alexandru; Devitt, Simon J; Nemoto, Kae; Polian, Ilia

    2014-04-11

    Topological quantum computation is a promising technique to achieve large-scale, error-corrected computation. Quantum hardware is used to create a large, 3-dimensional lattice of entangled qubits while performing computation requires strategic measurement in accordance with a topological circuit specification. The specification is a geometric structure that defines encoded information and fault-tolerant operations. The compilation of a topological circuit is one important aspect of programming a quantum computer, another is the mapping of the topological circuit into the operations performed by the hardware. Each qubit has to be controlled, and measurement results are needed to propagate encoded quantum information from input to output. In this work, we introduce an algorithm for mapping an topological circuit to the operations needed by the physical hardware. We determine the control commands for each qubit in the computer and the relevant measurements that are needed to track information as it moves through the circuit.

  7. Error Mitigation for Short-Depth Quantum Circuits

    Science.gov (United States)

    Temme, Kristan; Bravyi, Sergey; Gambetta, Jay M.

    2017-11-01

    Two schemes are presented that mitigate the effect of errors and decoherence in short-depth quantum circuits. The size of the circuits for which these techniques can be applied is limited by the rate at which the errors in the computation are introduced. Near-term applications of early quantum devices, such as quantum simulations, rely on accurate estimates of expectation values to become relevant. Decoherence and gate errors lead to wrong estimates of the expectation values of observables used to evaluate the noisy circuit. The two schemes we discuss are deliberately simple and do not require additional qubit resources, so to be as practically relevant in current experiments as possible. The first method, extrapolation to the zero noise limit, subsequently cancels powers of the noise perturbations by an application of Richardson's deferred approach to the limit. The second method cancels errors by resampling randomized circuits according to a quasiprobability distribution.

  8. Synaptic Scaling in Combination with many Generic Plasticity Mechanisms Stabilizes Circuit Connectivity

    Directory of Open Access Journals (Sweden)

    Christian eTetzlaff

    2011-11-01

    Full Text Available Synaptic scaling is a slow process that modifies synapses, keeping the firing rate of neural circuits in specific regimes. Together with other processes, such as conventional synaptic plasticity in the form of long term depression and potentiation, this changes the synaptic patterns in a network, ensuring diverse, functionally relevant, stable and input-dependent connectivity. How synaptic patterns are generated and stabilized, however, is largely unknown. Here we formally describe and analyze synaptic scaling based on results from experimental studies and demonstrate that the combination of different conventional plasticity mechanisms and synaptic scaling provides a powerful general framework for regulating network connectivity. In addition, we design several simple models, which reproduce experimentally observed synaptic distributions as well as the observed synaptic modifications during sustained activity changes. These models predict that the combination of plasticity with scaling generates globally stable, input-controlled synaptic patterns, also in recurrent networks. Thus, in combination with other forms of plasticity, synaptic scaling can robustly yield neuronal circuits with high synaptic diversity, which potentially allows in a more robust way for the dynamic storage of complex activation patterns. This mechanism is even more pronounced when considering networks with a realistic degree of inhibition. This, could be the basis for the learning of structured behavior even in initially random networks.

  9. Synaptic Scaling in Combination with Many Generic Plasticity Mechanisms Stabilizes Circuit Connectivity

    Science.gov (United States)

    Tetzlaff, Christian; Kolodziejski, Christoph; Timme, Marc; Wörgötter, Florentin

    2011-01-01

    Synaptic scaling is a slow process that modifies synapses, keeping the firing rate of neural circuits in specific regimes. Together with other processes, such as conventional synaptic plasticity in the form of long term depression and potentiation, synaptic scaling changes the synaptic patterns in a network, ensuring diverse, functionally relevant, stable, and input-dependent connectivity. How synaptic patterns are generated and stabilized, however, is largely unknown. Here we formally describe and analyze synaptic scaling based on results from experimental studies and demonstrate that the combination of different conventional plasticity mechanisms and synaptic scaling provides a powerful general framework for regulating network connectivity. In addition, we design several simple models that reproduce experimentally observed synaptic distributions as well as the observed synaptic modifications during sustained activity changes. These models predict that the combination of plasticity with scaling generates globally stable, input-controlled synaptic patterns, also in recurrent networks. Thus, in combination with other forms of plasticity, synaptic scaling can robustly yield neuronal circuits with high synaptic diversity, which potentially enables robust dynamic storage of complex activation patterns. This mechanism is even more pronounced when considering networks with a realistic degree of inhibition. Synaptic scaling combined with plasticity could thus be the basis for learning structured behavior even in initially random networks. PMID:22203799

  10. Computer model of a reverberant and parallel circuit coupling

    Science.gov (United States)

    Kalil, Camila de Andrade; de Castro, Maria Clícia Stelling; Cortez, Célia Martins

    2017-11-01

    The objective of the present study was to deepen the knowledge about the functioning of the neural circuits by implementing a signal transmission model using the Graph Theory in a small network of neurons composed of an interconnected reverberant and parallel circuit, in order to investigate the processing of the signals in each of them and the effects on the output of the network. For this, a program was developed in C language and simulations were done using neurophysiological data obtained in the literature.

  11. James Wenceslaus Papez, His Circuit, and Emotion.

    Science.gov (United States)

    Bhattacharyya, Kalyan B

    2017-01-01

    James Papez worked on the anatomical substrates of emotion and described a circuit, mainly composed of the hippocampus, thalamus and cingulum, and published his observations in 1937. However, such an idea existed before him, as evidenced by the rudimentary indications from Paul Broca, and Paul MacLean added some other structures like, septum, amygdala, and hypothalamus in its ambit and called it the limbic system. Paul Ivan Yakovlev, proposed a circuit which also referred to orbitofrontal, insular, anterior temporal lobe, and other nuclei of thalamus. Further works hinted at cerebellar projections into this system and the clinical picture of aggression, arousal and positive feeding responses with stimulation of cerebellar nuclei, attests its possible role. Finally, the work of Heinrich Klüver and Paul Bucy of the United States of America on ablating the temporal lobes and amygdala and the resultant behaviour of the animals, almost incontrovertibly adduced evidence for the operation of a neural circuitry in the genesis of emotion. Additionally, Papez circuit may also be concerned with memory and damage to its various components in Parkinson's disease, Alzheimer's disease, Korsakoff's syndrome, semantic dementia, and global amnesia, where cognitive disturbance is almost universal, lends credence to its putative role.

  12. Lactate Detection in Tumor Cell Cultures Using Organic Transistor Circuits.

    Science.gov (United States)

    Braendlein, Marcel; Pappa, Anna-Maria; Ferro, Marc; Lopresti, Alexia; Acquaviva, Claire; Mamessier, Emilie; Malliaras, George G; Owens, Róisín M

    2017-04-01

    A biosensing platform based on an organic transistor circuit for metabolite detection in highly complex biological media is introduced. The sensor circuit provides inherent background subtraction allowing for highly specific, sensitive lactate detection in tumor cell cultures. The proposed sensing platform paves the way toward rapid, label-free, and cost-effective clinically relevant in vitro diagnostic tools. © 2017 WILEY-VCH Verlag GmbH & Co. KGaA, Weinheim.

  13. Reducing energy with asynchronous circuits

    OpenAIRE

    Rivas Barragan, Daniel

    2012-01-01

    Reducing energy consumption using asynchronous circuits. The elastic clocks approach has been implemented along with a closed-feedback loop in order to achieve a lower energy consumption along with more reliability in integrated circuits.

  14. Diode, transistor & fet circuits manual

    CERN Document Server

    Marston, R M

    2013-01-01

    Diode, Transistor and FET Circuits Manual is a handbook of circuits based on discrete semiconductor components such as diodes, transistors, and FETS. The book also includes diagrams and practical circuits. The book describes basic and special diode characteristics, heat wave-rectifier circuits, transformers, filter capacitors, and rectifier ratings. The text also presents practical applications of associated devices, for example, zeners, varicaps, photodiodes, or LEDs, as well as it describes bipolar transistor characteristics. The transistor can be used in three basic amplifier configuration

  15. Development of a computational model on the neural activity patterns of a visual working memory in a hierarchical feedforward Network

    Science.gov (United States)

    An, Soyoung; Choi, Woochul; Paik, Se-Bum

    2015-11-01

    Understanding the mechanism of information processing in the human brain remains a unique challenge because the nonlinear interactions between the neurons in the network are extremely complex and because controlling every relevant parameter during an experiment is difficult. Therefore, a simulation using simplified computational models may be an effective approach. In the present study, we developed a general model of neural networks that can simulate nonlinear activity patterns in the hierarchical structure of a neural network system. To test our model, we first examined whether our simulation could match the previously-observed nonlinear features of neural activity patterns. Next, we performed a psychophysics experiment for a simple visual working memory task to evaluate whether the model could predict the performance of human subjects. Our studies show that the model is capable of reproducing the relationship between memory load and performance and may contribute, in part, to our understanding of how the structure of neural circuits can determine the nonlinear neural activity patterns in the human brain.

  16. Circuit Bodging : Atari Punk Console

    NARCIS (Netherlands)

    Allen, B.

    2009-01-01

    Circuit bodging is back! Maxwell is proud to present small, simple, but ultimately lovable little circuits to build for your own, personal pleasure. In this edition we are featuring: The Atari Punk Console. The Atari Punk Console (or APC) is a 555 timer IC based noise maker circuit. The original was

  17. Synthetic in vitro transcription circuits.

    Science.gov (United States)

    Weitz, Maximilian; Simmel, Friedrich C

    2012-01-01

    With the help of only two enzymes--an RNA polymerase and a ribonuclease--reduced versions of transcriptional regulatory circuits can be implemented in vitro. These circuits enable the emulation of naturally occurring biochemical networks, the exploration of biological circuit design principles and the biochemical implementation of powerful computational models.

  18. High voltage MOSFET switching circuit

    Science.gov (United States)

    McEwan, Thomas E.

    1994-01-01

    The problem of source lead inductance in a MOSFET switching circuit is compensated for by adding an inductor to the gate circuit. The gate circuit inductor produces an inductive spike which counters the source lead inductive drop to produce a rectangular drive voltage waveform at the internal gate-source terminals of the MOSFET.

  19. Quantum-circuit refrigerator

    Science.gov (United States)

    Tan, Kuan Yen; Partanen, Matti; Lake, Russell E.; Govenius, Joonas; Masuda, Shumpei; Möttönen, Mikko

    2017-05-01

    Quantum technology promises revolutionizing applications in information processing, communications, sensing and modelling. However, efficient on-demand cooling of the functional quantum degrees of freedom remains challenging in many solid-state implementations, such as superconducting circuits. Here we demonstrate direct cooling of a superconducting resonator mode using voltage-controllable electron tunnelling in a nanoscale refrigerator. This result is revealed by a decreased electron temperature at a resonator-coupled probe resistor, even for an elevated electron temperature at the refrigerator. Our conclusions are verified by control experiments and by a good quantitative agreement between theory and experimental observations at various operation voltages and bath temperatures. In the future, we aim to remove spurious dissipation introduced by our refrigerator and to decrease the operational temperature. Such an ideal quantum-circuit refrigerator has potential applications in the initialization of quantum electric devices. In the superconducting quantum computer, for example, fast and accurate reset of the quantum memory is needed.

  20. Quantum-circuit refrigerator

    Science.gov (United States)

    Tan, Kuan Yen; Partanen, Matti; Lake, Russell E.; Govenius, Joonas; Masuda, Shumpei; Möttönen, Mikko

    2017-01-01

    Quantum technology promises revolutionizing applications in information processing, communications, sensing and modelling. However, efficient on-demand cooling of the functional quantum degrees of freedom remains challenging in many solid-state implementations, such as superconducting circuits. Here we demonstrate direct cooling of a superconducting resonator mode using voltage-controllable electron tunnelling in a nanoscale refrigerator. This result is revealed by a decreased electron temperature at a resonator-coupled probe resistor, even for an elevated electron temperature at the refrigerator. Our conclusions are verified by control experiments and by a good quantitative agreement between theory and experimental observations at various operation voltages and bath temperatures. In the future, we aim to remove spurious dissipation introduced by our refrigerator and to decrease the operational temperature. Such an ideal quantum-circuit refrigerator has potential applications in the initialization of quantum electric devices. In the superconducting quantum computer, for example, fast and accurate reset of the quantum memory is needed. PMID:28480900

  1. Integrated Circuit Immunity

    Science.gov (United States)

    Sketoe, J. G.; Clark, Anthony

    2000-01-01

    This paper presents a DOD E3 program overview on integrated circuit immunity. The topics include: 1) EMI Immunity Testing; 2) Threshold Definition; 3) Bias Tee Function; 4) Bias Tee Calibration Set-Up; 5) EDM Test Figure; 6) EMI Immunity Levels; 7) NAND vs. and Gate Immunity; 8) TTL vs. LS Immunity Levels; 9) TP vs. OC Immunity Levels; 10) 7805 Volt Reg Immunity; and 11) Seventies Chip Set. This paper is presented in viewgraph form.

  2. Cartography of serotonergic circuits.

    Science.gov (United States)

    Sparta, Dennis R; Stuber, Garret D

    2014-08-06

    Serotonin is an essential neuromodulator, but the precise circuit connectivity that regulates serotonergic neurons has not been well defined. Using rabies virus tracing strategies Weissbourd et al. (2014) and Pollak Dorocic et al. (2014) in this issue of Neuron and Ogawa et al. (2014) in Cell Reports provide a comprehensive map of the inputs to serotonergic neurons, highlighting the complexity and diversity of potential upstream cellular regulators. Copyright © 2014 Elsevier Inc. All rights reserved.

  3. Changes to the shuttle circuits

    CERN Multimedia

    GS Department

    2011-01-01

    To fit with passengers expectation, there will be some changes to the shuttle circuits as from Monday 10 October. See details on http://cern.ch/ShuttleService (on line on 7 October). Circuit No. 5 is cancelled as circuit No. 1 also stops at Bldg. 33. In order to guarantee shorter travel times, circuit No. 1 will circulate on Meyrin site only and circuit No. 2, with departures from Bldg. 33 and 500, on Prévessin site only. Site Services Section

  4. From imitation to meaning: circuit plasticity and the acquisition of a primitive semantics.

    Directory of Open Access Journals (Sweden)

    Ricardo R Garcia

    2014-08-01

    Full Text Available The capacity for language is arguably the most remarkable innovation of the human brain. A relatively recent interpretation prescribes that part of the language-related circuits were co-opted from circuitry involved in hand control –the mirror neuron system, involved both in the perception and in the execution of voluntary grasping actions. A less radical view is that in early humans, communication was opportunistic and multimodal, using signs, vocalizations or whatever means available to transmit social information. However, one point that is not yet clear under either perspective is how learned communication acquired a semantic property thereby allowing us to name objects and eventually describe our surrounding environment. Here we suggest a scenario involving both manual gestures and learned vocalizations that led to the development of a primitive form of conventionalized reference. This proposal is based on comparative evidence gathered from other species and on neurolinguistic evidence in humans, which points to a crucial role for vocal learning in the early development of language. Firstly, the capacity to direct the attention of others to a common object may have been crucial for developing a consensual referential system. Pointing, which is a ritualized grasping gesture, may have been crucial to this end. Vocalizations also served to generate joint attention among conversants, especially when combined with gaze direction. Another contributing element was the development of pantomimic actions resembling events or animals. In conjunction with this mimicry, the development of plastic neural circuits that support complex, learned vocalizations was probably a significant factor in the evolution of conventionalized semantics in our species. Thus, vocal imitations of sounds, as in onomatopoeias (words whose sound resembles their meaning, are possibly supported by mirror system circuits, and may have been relevant in the acquisition of early

  5. From imitation to meaning: circuit plasticity and the acquisition of a conventionalized semantics.

    Science.gov (United States)

    García, Ricardo R; Zamorano, Francisco; Aboitiz, Francisco

    2014-01-01

    The capacity for language is arguably the most remarkable innovation of the human brain. A relatively recent interpretation prescribes that part of the language-related circuits were co-opted from circuitry involved in hand control-the mirror neuron system (MNS), involved both in the perception and in the execution of voluntary grasping actions. A less radical view is that in early humans, communication was opportunistic and multimodal, using signs, vocalizations or whatever means available to transmit social information. However, one point that is not yet clear under either perspective is how learned communication acquired a semantic property thereby allowing us to name objects and eventually describe our surrounding environment. Here we suggest a scenario involving both manual gestures and learned vocalizations that led to the development of a primitive form of conventionalized reference. This proposal is based on comparative evidence gathered from other species and on neurolinguistic evidence in humans, which points to a crucial role for vocal learning in the early development of language. Firstly, the capacity to direct the attention of others to a common object may have been crucial for developing a consensual referential system. Pointing, which is a ritualized grasping gesture, may have been crucial to this end. Vocalizations also served to generate joint attention among conversants, especially when combined with gaze direction. Another contributing element was the development of pantomimic actions resembling events or animals. In conjunction with this mimicry, the development of plastic neural circuits that support complex, learned vocalizations was probably a significant factor in the evolution of conventionalized semantics in our species. Thus, vocal imitations of sounds, as in onomatopoeias (words whose sound resembles their meaning), are possibly supported by mirror system circuits, and may have been relevant in the acquisition of early meanings.

  6. Trading speed and accuracy by coding time: a coupled-circuit cortical model.

    Directory of Open Access Journals (Sweden)

    Dominic Standage

    2013-04-01

    Full Text Available Our actions take place in space and time, but despite the role of time in decision theory and the growing acknowledgement that the encoding of time is crucial to behaviour, few studies have considered the interactions between neural codes for objects in space and for elapsed time during perceptual decisions. The speed-accuracy trade-off (SAT provides a window into spatiotemporal interactions. Our hypothesis is that temporal coding determines the rate at which spatial evidence is integrated, controlling the SAT by gain modulation. Here, we propose that local cortical circuits are inherently suited to the relevant spatial and temporal coding. In simulations of an interval estimation task, we use a generic local-circuit model to encode time by 'climbing' activity, seen in cortex during tasks with a timing requirement. The model is a network of simulated pyramidal cells and inhibitory interneurons, connected by conductance synapses. A simple learning rule enables the network to quickly produce new interval estimates, which show signature characteristics of estimates by experimental subjects. Analysis of network dynamics formally characterizes this generic, local-circuit timing mechanism. In simulations of a perceptual decision task, we couple two such networks. Network function is determined only by spatial selectivity and NMDA receptor conductance strength; all other parameters are identical. To trade speed and accuracy, the timing network simply learns longer or shorter intervals, driving the rate of downstream decision processing by spatially non-selective input, an established form of gain modulation. Like the timing network's interval estimates, decision times show signature characteristics of those by experimental subjects. Overall, we propose, demonstrate and analyse a generic mechanism for timing, a generic mechanism for modulation of decision processing by temporal codes, and we make predictions for experimental verification.

  7. Power system with an integrated lubrication circuit

    Science.gov (United States)

    Hoff, Brian D [East Peoria, IL; Akasam, Sivaprasad [Peoria, IL; Algrain, Marcelo C [Peoria, IL; Johnson, Kris W [Washington, IL; Lane, William H [Chillicothe, IL

    2009-11-10

    A power system includes an engine having a first lubrication circuit and at least one auxiliary power unit having a second lubrication circuit. The first lubrication circuit is in fluid communication with the second lubrication circuit.

  8. Reversible gates and circuits descriptions

    Science.gov (United States)

    Gracki, Krzystof

    2017-08-01

    This paper presents basic methods of reversible circuit description. To design reversible circuit a set of gates has to be chosen. Most popular libraries are composed of three types of gates so called CNT gates (Control, NOT and Toffoli). The gate indexing method presented in this paper is based on the CNT gates set. It introduces a uniform indexing of the gates used during synthesis process of reversible circuits. The paper is organized as follows. Section 1 recalls basic concepts of reversible logic. In Section 2 and 3 a graphical representation of the reversible gates and circuits is described. Section 4 describes proposed uniform NCT gates indexing. The presented gate indexing method provides gate numbering scheme independent of lines number of the designed circuit. The solution for a circuit consisting of smaller number of lines is a subset of solution for a larger circuit.

  9. A Core Circuit Module for Cost/Benefit Decision

    Directory of Open Access Journals (Sweden)

    Keiko eHirayama

    2012-08-01

    Full Text Available A simple circuit for cost-benefit decision derived from behavioral and neural studies of the predatory sea-slug Pleurobranchaea may closely resemble that upon which the more complex valuation and decision processes of the social vertebrates are built. The neuronal natures of the pathways in the connectionist model comprise classic central pattern generators, bipolar switch mechanisms, and neuromodulatory state regulation. Marked potential exists for exploring more complex neuroeconomic behavior by appending appropriate circuitry in simulo.

  10. Evolvable synthetic neural system

    Science.gov (United States)

    Curtis, Steven A. (Inventor)

    2009-01-01

    An evolvable synthetic neural system includes an evolvable neural interface operably coupled to at least one neural basis function. Each neural basis function includes an evolvable neural interface operably coupled to a heuristic neural system to perform high-level functions and an autonomic neural system to perform low-level functions. In some embodiments, the evolvable synthetic neural system is operably coupled to one or more evolvable synthetic neural systems in a hierarchy.

  11. Development of a Novel Test Method for On-Demand Internal Short Circuit in a Li-Ion Cell (Presentation)

    Energy Technology Data Exchange (ETDEWEB)

    Keyser, M.; Long, D.; Jung, Y. S.; Pesaran, A.; Darcy, E.; McCarthy, B.; Patrick, L.; Kruger, C.

    2011-01-01

    This presentation describes a cell-level test method that simulates an emergent internal short circuit, produces consistent and reproducible test results, can establish the locations and temperatures/power/SOC conditions where an internal short circuit will result in thermal runaway, and provides relevant data to validate internal short circuit models.

  12. Encoding of fear learning and memory in distributed neuronal circuits.

    Science.gov (United States)

    Herry, Cyril; Johansen, Joshua P

    2014-12-01

    How sensory information is transformed by learning into adaptive behaviors is a fundamental question in neuroscience. Studies of auditory fear conditioning have revealed much about the formation and expression of emotional memories and have provided important insights into this question. Classical work focused on the amygdala as a central structure for fear conditioning. Recent advances, however, have identified new circuits and neural coding strategies mediating fear learning and the expression of fear behaviors. One area of research has identified key brain regions and neuronal coding mechanisms that regulate the formation, specificity and strength of fear memories. Other work has discovered critical circuits and neuronal dynamics by which fear memories are expressed through a medial prefrontal cortex pathway and coordinated activity across interconnected brain regions. Here we review these recent advances alongside prior work to provide a working model of the extended circuits and neuronal coding mechanisms mediating fear learning and memory.

  13. Three dimensional living neural networks

    Science.gov (United States)

    Linnenberger, Anna; McLeod, Robert R.; Basta, Tamara; Stowell, Michael H. B.

    2015-08-01

    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.

  14. Central neural pathways for thermoregulation

    Science.gov (United States)

    Morrison, Shaun F.; Nakamura, Kazuhiro

    2010-01-01

    Central neural circuits orchestrate a homeostatic repertoire to maintain body temperature during environmental temperature challenges and to alter body temperature during the inflammatory response. This review summarizes the functional organization of the neural pathways through which cutaneous thermal receptors alter thermoregulatory effectors: the cutaneous circulation for heat loss, the brown adipose tissue, skeletal muscle and heart for thermogenesis and species-dependent mechanisms (sweating, panting and saliva spreading) for evaporative heat loss. These effectors are regulated by parallel but distinct, effector-specific neural pathways that share a common peripheral thermal sensory input. The thermal afferent circuits include cutaneous thermal receptors, spinal dorsal horn neurons and lateral parabrachial nucleus neurons projecting to the preoptic area to influence warm-sensitive, inhibitory output neurons which control thermogenesis-promoting neurons in the dorsomedial hypothalamus that project to premotor neurons in the rostral ventromedial medulla, including the raphe pallidus, that descend to provide the excitation necessary to drive thermogenic thermal effectors. A distinct population of warm-sensitive preoptic neurons controls heat loss through an inhibitory input to raphe pallidus neurons controlling cutaneous vasoconstriction. PMID:21196160

  15. Mapping a complete neural population in the retina.

    Science.gov (United States)

    Marre, Olivier; Amodei, Dario; Deshmukh, Nikhil; Sadeghi, Kolia; Soo, Frederick; Holy, Timothy E; Berry, Michael J

    2012-10-24

    Recording simultaneously from essentially all of the relevant neurons in a local circuit is crucial to understand how they collectively represent information. Here we show that the combination of a large, dense multielectrode array and a novel, mostly automated spike-sorting algorithm allowed us to record simultaneously from a highly overlapping population of >200 ganglion cells in the salamander retina. By combining these methods with labeling and imaging, we showed that up to 95% of the ganglion cells over the area of the array were recorded. By measuring the coverage of visual space by the receptive fields of the recorded cells, we concluded that our technique captured a neural population that forms an essentially complete representation of a region of visual space. This completeness allowed us to determine the spatial layout of different cell types as well as identify a novel group of ganglion cells that responded reliably to a set of naturalistic and artificial stimuli but had no measurable receptive field. Thus, our method allows unprecedented access to the complete neural representation of visual information, a crucial step for the understanding of population coding in sensory systems.

  16. History of winning remodels thalamo-PFC circuit to reinforce social dominance.

    Science.gov (United States)

    Zhou, Tingting; Zhu, Hong; Fan, Zhengxiao; Wang, Fei; Chen, Yang; Liang, Hexing; Yang, Zhongfei; Zhang, Lu; Lin, Longnian; Zhan, Yang; Wang, Zheng; Hu, Hailan

    2017-07-14

    Mental strength and history of winning play an important role in the determination of social dominance. However, the neural circuits mediating these intrinsic and extrinsic factors have remained unclear. Working in mice, we identified a dorsomedial prefrontal cortex (dmPFC) neural population showing "effort"-related firing during moment-to-moment competition in the dominance tube test. Activation or inhibition of the dmPFC induces instant winning or losing, respectively. In vivo optogenetic-based long-term potentiation and depression experiments establish that the mediodorsal thalamic input to the dmPFC mediates long-lasting changes in the social dominance status that are affected by history of winning. The same neural circuit also underlies transfer of dominance between different social contests. These results provide a framework for understanding the circuit basis of adaptive and pathological social behaviors. Copyright © 2017, American Association for the Advancement of Science.

  17. Complex-Valued Neural Networks

    CERN Document Server

    Hirose, Akira

    2012-01-01

    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...

  18. Optoelectronics circuits manual

    CERN Document Server

    Marston, R M

    1999-01-01

    This manual is a useful single-volume guide specifically aimed at the practical design engineer, technician, and experimenter, as well as the electronics student and amateur. It deals with the subject in an easy to read, down to earth, and non-mathematical yet comprehensive manner, explaining the basic principles and characteristics of the best known devices, and presenting the reader with many practical applications and over 200 circuits. Most of the ICs and other devices used are inexpensive and readily available types, with universally recognised type numbers.The second edition

  19. Photonic Integrated Circuits

    Science.gov (United States)

    Krainak, Michael; Merritt, Scott

    2016-01-01

    Integrated photonics generally is the integration of multiple lithographically defined photonic and electronic components and devices (e.g. lasers, detectors, waveguides passive structures, modulators, electronic control and optical interconnects) on a single platform with nanometer-scale feature sizes. The development of photonic integrated circuits permits size, weight, power and cost reductions for spacecraft microprocessors, optical communication, processor buses, advanced data processing, and integrated optic science instrument optical systems, subsystems and components. This is particularly critical for small spacecraft platforms. We will give an overview of some NASA applications for integrated photonics.

  20. Integrated circuit cell library

    Science.gov (United States)

    Whitaker, Sterling R. (Inventor); Miles, Lowell H. (Inventor)

    2005-01-01

    According to the invention, an ASIC cell library for use in creation of custom integrated circuits is disclosed. The ASIC cell library includes some first cells and some second cells. Each of the second cells includes two or more kernel cells. The ASIC cell library is at least 5% comprised of second cells. In various embodiments, the ASIC cell library could be 10% or more, 20% or more, 30% or more, 40% or more, 50% or more, 60% or more, 70% or more, 80% or more, 90% or more, or 95% or more comprised of second cells.

  1. Electronics circuits and systems

    CERN Document Server

    Bishop, Owen

    2007-01-01

    The material in Electronics - Circuits and Systems is a truly up-to-date textbook, with coverage carefully matched to the electronics units of the 2007 BTEC National Engineering and the latest AS and A Level specifications in Electronics from AQA, OCR and WJEC. The material has been organized with a logical learning progression, making it ideal for a wide range of pre-degree courses in electronics. The approach is student-centred and includes: numerous examples and activities; web research topics; Self Test features, highlighted key facts, formulae and definitions. Each chapter ends with a set

  2. Electronics circuits and systems

    CERN Document Server

    Bishop, Owen

    2011-01-01

    The material in Electronics - Circuits and Systems is a truly up-to-date textbook, with coverage carefully matched to the electronics units of the 2007 BTEC National Engineering and the latest AS and A Level specifications in Electronics from AQA, OCR and WJEC. The material has been organized with a logical learning progression, making it ideal for a wide range of pre-degree courses in electronics. The approach is student-centred and includes: numerous examples and activities; web research topics; Self Test features, highlighted key facts, formulae and definitions. Ea

  3. Linear integrated circuits

    CERN Document Server

    Carr, Joseph

    1996-01-01

    The linear IC market is large and growing, as is the demand for well trained technicians and engineers who understand how these devices work and how to apply them. Linear Integrated Circuits provides in-depth coverage of the devices and their operation, but not at the expense of practical applications in which linear devices figure prominently. This book is written for a wide readership from FE and first degree students, to hobbyists and professionals.Chapter 1 offers a general introduction that will provide students with the foundations of linear IC technology. From chapter 2 onwa

  4. Electric circuits problem solver

    CERN Document Server

    REA, Editors of

    2012-01-01

    Each Problem Solver is an insightful and essential study and solution guide chock-full of clear, concise problem-solving gems. All your questions can be found in one convenient source from one of the most trusted names in reference solution guides. More useful, more practical, and more informative, these study aids are the best review books and textbook companions available. Nothing remotely as comprehensive or as helpful exists in their subject anywhere. Perfect for undergraduate and graduate studies.Here in this highly useful reference is the finest overview of electric circuits currently av

  5. Digital Optical Circuit Technology.

    Science.gov (United States)

    1985-03-01

    avait donc pour but de dresser un bilan des recherches; et des raisations intiEressant la technologie des circuits optiques et d󈨁udier leurs...experiment. 3. EXPERIMENTAL WAVEGUIDE DEVICE Experiments were performed using carbon disulphide, CS2 , as the nonlinear medium. CS2 has a high non- linear...x 1.60- 1.595- S1.590 15514 16 18 20 22 24 26 28 Temperature (I C) FIGURE 5 REFRACTIVE INDEX OF CARBON DISULPHIDE AT 1 .O6um AS A FUNCTION OF

  6. Optically controllable molecular logic circuits

    Energy Technology Data Exchange (ETDEWEB)

    Nishimura, Takahiro, E-mail: t-nishimura@ist.osaka-u.ac.jp; Fujii, Ryo; Ogura, Yusuke; Tanida, Jun [Graduate School of Information Science and Technology, Osaka University, 1-5 Yamadaoka, Suita, Osaka 565-0871 (Japan)

    2015-07-06

    Molecular logic circuits represent a promising technology for observation and manipulation of biological systems at the molecular level. However, the implementation of molecular logic circuits for temporal and programmable operation remains challenging. In this paper, we demonstrate an optically controllable logic circuit that uses fluorescence resonance energy transfer (FRET) for signaling. The FRET-based signaling process is modulated by both molecular and optical inputs. Based on the distance dependence of FRET, the FRET pathways required to execute molecular logic operations are formed on a DNA nanostructure as a circuit based on its molecular inputs. In addition, the FRET pathways on the DNA nanostructure are controlled optically, using photoswitching fluorescent molecules to instruct the execution of the desired operation and the related timings. The behavior of the circuit can thus be controlled using external optical signals. As an example, a molecular logic circuit capable of executing two different logic operations was studied. The circuit contains functional DNAs and a DNA scaffold to construct two FRET routes for executing Input 1 AND Input 2 and Input 1 AND NOT Input 3 operations on molecular inputs. The circuit produced the correct outputs with all possible combinations of the inputs by following the light signals. Moreover, the operation execution timings were controlled based on light irradiation and the circuit responded to time-dependent inputs. The experimental results demonstrate that the circuit changes the output for the required operations following the input of temporal light signals.

  7. Behavioral and neural plasticity caused by early social experiences: the case of the honeybee.

    Science.gov (United States)

    Arenas, Andrés; Ramírez, Gabriela P; Balbuena, María Sol; Farina, Walter M

    2013-01-01

    Cognitive experiences during the early stages of life play an important role in shaping future behavior. Behavioral and neural long-term changes after early sensory and associative experiences have been recently reported in the honeybee. This invertebrate is an excellent model for assessing the role of precocious experiences on later behavior due to its extraordinarily tuned division of labor based on age polyethism. These studies are mainly focused on the role and importance of experiences occurred during the first days of the adult lifespan, their impact on foraging decisions, and their contribution to coordinate food gathering. Odor-rewarded experiences during the first days of honeybee adulthood alter the responsiveness to sucrose, making young hive bees more sensitive to assess gustatory features about the nectar brought back to the hive and affecting the dynamic of the food transfers and the propagation of food-related information within the colony. Early olfactory experiences lead to stable and long-term associative memories that can be successfully recalled after many days, even at foraging ages. Also they improve memorizing of new associative learning events later in life. The establishment of early memories promotes stable reorganization of the olfactory circuits inducing structural and functional changes in the antennal lobe (AL). Early rewarded experiences have relevant consequences at the social level too, biasing dance and trophallaxis partner choice and affecting recruitment. Here, we revised recent results in bees' physiology, behavior, and sociobiology to depict how the early experiences affect their cognition abilities and neural-related circuits.

  8. Moving towards causality in attention-deficit hyperactivity disorder: overview of neural and genetic mechanisms

    Science.gov (United States)

    Gallo, Eduardo F; Posner, Jonathan

    2016-01-01

    Attention-deficit hyperactivity disorder (ADHD) is a neurodevelopmental disorder characterised by developmentally inappropriate levels of inattention and hyperactivity or impulsivity. The heterogeneity of its clinical manifestations and the differential responses to treatment and varied prognoses have long suggested myriad underlying causes. Over the past decade, clinical and basic research efforts have uncovered many behavioural and neurobiological alterations associated with ADHD, from genes to higher order neural networks. Here, we review the neurobiology of ADHD by focusing on neural circuits implicated in the disorder and discuss how abnormalities in circuitry relate to symptom presentation and treatment. We summarise the literature on genetic variants that are potentially related to the development of ADHD, and how these, in turn, might affect circuit function and relevant behaviours. Whether these underlying neurobiological factors are causally related to symptom presentation remains unresolved. Therefore, we assess efforts aimed at disentangling issues of causality, and showcase the shifting research landscape towards endophenotype refinement in clinical and preclinical settings. Furthermore, we review approaches being developed to understand the neurobiological underpinnings of this complex disorder including the use of animal models, neuromodulation, and pharmaco-imaging studies. PMID:27183902

  9. Neural Mechanisms of Conceptual Relations

    Science.gov (United States)

    Lewis, Gwyneth A.

    2017-01-01

    An over-arching goal in neurolinguistic research is to characterize the neural bases of semantic representation. A particularly relevant goal concerns whether we represent features and events (a) together in a generalized semantic hub or (b) separately in distinct but complementary systems. While the left anterior temporal lobe (ATL) is strongly…

  10. Noise in biological circuits.

    Science.gov (United States)

    Simpson, Michael L; Cox, Chris D; Allen, Michael S; McCollum, James M; Dar, Roy D; Karig, David K; Cooke, John F

    2009-01-01

    Noise biology focuses on the sources, processing, and biological consequences of the inherent stochastic fluctuations in molecular transitions or interactions that control cellular behavior. These fluctuations are especially pronounced in small systems where the magnitudes of the fluctuations approach or exceed the mean value of the molecular population. Noise biology is an essential component of nanomedicine where the communication of information is across a boundary that separates small synthetic and biological systems that are bound by their size to reside in environments of large fluctuations. Here we review the fundamentals of the computational, analytical, and experimental approaches to noise biology. We review results that show that the competition between the benefits of low noise and those of low population has resulted in the evolution of genetic system architectures that produce an uneven distribution of stochasticity across the molecular components of cells and, in some cases, use noise to drive biological function. We review the exact and approximate approaches to gene circuit noise analysis and simulation, and review many of the key experimental results obtained using flow cytometry and time-lapse fluorescent microscopy. In addition, we consider the probative value of noise with a discussion of using measured noise properties to elucidate the structure and function of the underlying gene circuit. We conclude with a discussion of the frontiers of and significant future challenges for noise biology. (c) 2009 John Wiley & Sons, Inc.

  11. Determining Changes in Neural Circuits in Tuberous Sclerosis

    Science.gov (United States)

    2013-05-01

    Washington Headquarters Services, Directorate for Information Operations and Reports (0704-0188), 1215 Jefferson Davis Highway, Suite 1204, Arlington, VA...Tsc1fl/+ or Gbx2CreER;R26tdTomato;Tsc1fl/+ males with Tsc1fl/+ females. The morning (0900) of the day a vaginal plug was detected was designated as...dsRed+) projections could be used to track entire axonal bundles en route to the deep cortical layers in more lateral sections (Fig. 3F). Finally, by P7

  12. Homeostatic synaptic plasticity: from single synapses to neural circuits.

    OpenAIRE

    Vitureira, Nathalia; Letellier, Mathieu; Goda, Yukiko

    2012-01-01

    Homeostatic synaptic plasticity remains an enigmatic form of synaptic plasticity. Increasing interest on the topic has fuelled a surge of recent studies that have identified key molecular players and the signaling pathways involved. However, the new findings also highlight our lack of knowledge concerning some of the basic properties of homeostatic synaptic plasticity. In this review we address how homeostatic mechanisms balance synaptic strengths between the presynaptic and the postsynaptic ...

  13. Neural circuit rewiring: insights from DD synapse remodeling.

    Science.gov (United States)

    Kurup, Naina; Jin, Yishi

    2016-01-01

    Nervous systems exhibit many forms of neuronal plasticity during growth, learning and memory consolidation, as well as in response to injury. Such plasticity can occur across entire nervous systems as with the case of insect metamorphosis, in individual classes of neurons, or even at the level of a single neuron. A striking example of neuronal plasticity in C. elegans is the synaptic rewiring of the GABAergic Dorsal D-type motor neurons during larval development, termed DD remodeling. DD remodeling entails multi-step coordination to concurrently eliminate pre-existing synapses and form new synapses on different neurites, without changing the overall morphology of the neuron. This mini-review focuses on recent advances in understanding the cellular and molecular mechanisms driving DD remodeling.

  14. Fiberless multicolor neural optoelectrode for in vivo circuit analysis

    National Research Council Canada - National Science Library

    Kampasi, Komal; Stark, Eran; Seymour, John; Na, Kyounghwan; Winful, Herbert G; Buzsáki, György; Wise, Kensall D; Yoon, Euisik

    2016-01-01

    ... recording electrical data from those neurons. Here, we present the first fiber-less optoelectrode with a monolithically integrated optical waveguide mixer that can deliver multicolor light at a common waveguide port to achieve multicolor...

  15. Arithmetic circuits for DSP applications

    CERN Document Server

    Stouraitis, Thanos

    2017-01-01

    Arithmetic Circuits for DSP Applications is a complete resource on arithmetic circuits for digital signal processing (DSP). It covers the key concepts, designs and developments of different types of arithmetic circuits, which can be used for improving the efficiency of implementation of a multitude of DSP applications. Each chapter includes various applications of the respective class of arithmetic circuits along with information on the future scope of research. Written for students, engineers, and researchers in electrical and computer engineering, this comprehensive text offers a clear understanding of different types of arithmetic circuits used for digital signal processing applications. The text includes contributions from noted researchers on a wide range of topics, including a review o circuits used in implementing basic operations like additions and multiplications; distributed arithmetic as a technique for the multiplier-less implementation of inner products for DSP applications; discussions on look ...

  16. Integrated circuit cooled turbine blade

    Energy Technology Data Exchange (ETDEWEB)

    Lee, Ching-Pang; Jiang, Nan; Um, Jae Y.; Holloman, Harry; Koester, Steven

    2017-08-29

    A turbine rotor blade includes at least two integrated cooling circuits that are formed within the blade that include a leading edge circuit having a first cavity and a second cavity and a trailing edge circuit that includes at least a third cavity located aft of the second cavity. The trailing edge circuit flows aft with at least two substantially 180-degree turns at the tip end and the root end of the blade providing at least a penultimate cavity and a last cavity. The last cavity is located along a trailing edge of the blade. A tip axial cooling channel connects to the first cavity of the leading edge circuit and the penultimate cavity of the trailing edge circuit. At least one crossover hole connects the penultimate cavity to the last cavity substantially near the tip end of the blade.

  17. Automated Design of Quantum Circuits

    Science.gov (United States)

    Williams, Colin P.; Gray, Alexander G.

    2000-01-01

    In order to design a quantum circuit that performs a desired quantum computation, it is necessary to find a decomposition of the unitary matrix that represents that computation in terms of a sequence of quantum gate operations. To date, such designs have either been found by hand or by exhaustive enumeration of all possible circuit topologies. In this paper we propose an automated approach to quantum circuit design using search heuristics based on principles abstracted from evolutionary genetics, i.e. using a genetic programming algorithm adapted specially for this problem. We demonstrate the method on the task of discovering quantum circuit designs for quantum teleportation. We show that to find a given known circuit design (one which was hand-crafted by a human), the method considers roughly an order of magnitude fewer designs than naive enumeration. In addition, the method finds novel circuit designs superior to those previously known.

  18. Neural Control of the Lower Urinary Tract

    Science.gov (United States)

    de Groat, William C.; Griffiths, Derek; Yoshimura, Naoki

    2015-01-01

    This article summarizes anatomical, neurophysiological, pharmacological, and brain imaging studies in humans and animals that have provided insights into the neural circuitry and neurotransmitter mechanisms controlling the lower urinary tract. The functions of the lower urinary tract to store and periodically eliminate urine are regulated by a complex neural control system in the brain, spinal cord, and peripheral autonomic ganglia that coordinates the activity of smooth and striated muscles of the bladder and urethral outlet. The neural control of micturition is organized as a hierarchical system in which spinal storage mechanisms are in turn regulated by circuitry in the rostral brain stem that initiates reflex voiding. Input from the forebrain triggers voluntary voiding by modulating the brain stem circuitry. Many neural circuits controlling the lower urinary tract exhibit switch-like patterns of activity that turn on and off in an all-or-none manner. The major component of the micturition switching circuit is a spinobulbospinal parasympathetic reflex pathway that has essential connections in the periaqueductal gray and pontine micturition center. A computer model of this circuit that mimics the switching functions of the bladder and urethra at the onset of micturition is described. Micturition occurs involuntarily in infants and young children until the age of 3 to 5 years, after which it is regulated voluntarily. Diseases or injuries of the nervous system in adults can cause the re-emergence of involuntary micturition, leading to urinary incontinence. Neuroplasticity underlying these developmental and pathological changes in voiding function is discussed. PMID:25589273

  19. Clock generators for SOC processors circuits and architectures

    CERN Document Server

    Fahim, Amr

    2004-01-01

    This book explores the design of fully-integrated frequency synthesizers suitable for system-on-a-chip (SOC) processors. The text takes a more global design perspective in jointly examining the design space at the circuit level as well as at the architectural level. The comprehensive coverage includes summary chapters on circuit theory as well as feedback control theory relevant to the operation of phase locked loops (PLLs). On the circuit level, the discussion includes low-voltage analog design in deep submicron digital CMOS processes, effects of supply noise, substrate noise, as well device noise. On the architectural level, the discussion includes PLL analysis using continuous-time as well as discrete-time models, linear and nonlinear effects of PLL performance, and detailed analysis of locking behavior. The book provides numerous real world applications, as well as practical rules-of-thumb for modern designers to use at the system, architectural, as well as the circuit level.

  20. Why relevance theory is relevant for lexicography

    DEFF Research Database (Denmark)

    Bothma, Theo; Tarp, Sven

    2014-01-01

    This article starts by providing a brief summary of relevance theory in information science in relation to the function theory of lexicography, explaining the different types of relevance, viz. objective system relevance and the subjective types of relevance, i.e. topical, cognitive, situational...... that is very important for lexicography as well as for information science, viz. functional relevance. Since all lexicographic work is ultimately aimed at satisfying users’ information needs, the article then discusses why the lexicographer should take note of all these types of relevance when planning a new...... dictionary project, identifying new tasks and responsibilities of the modern lexicographer. The article furthermore discusses how relevance theory impacts on teaching dictionary culture and reference skills. By integrating insights from lexicography and information science, the article contributes to new...

  1. Synthetic biology: integrated gene circuits.

    Science.gov (United States)

    Nandagopal, Nagarajan; Elowitz, Michael B

    2011-09-02

    A major goal of synthetic biology is to develop a deeper understanding of biological design principles from the bottom up, by building circuits and studying their behavior in cells. Investigators initially sought to design circuits "from scratch" that functioned as independently as possible from the underlying cellular system. More recently, researchers have begun to develop a new generation of synthetic circuits that integrate more closely with endogenous cellular processes. These approaches are providing fundamental insights into the regulatory architecture, dynamics, and evolution of genetic circuits and enabling new levels of control across diverse biological systems.

  2. Unstable oscillators based hyperchaotic circuit

    DEFF Research Database (Denmark)

    Murali, K.; Tamasevicius, A.; G. Mykolaitis, A.

    1999-01-01

    A simple 4th order hyperchaotic circuit with unstable oscillators is described. The circuit contains two negative impedance converters, two inductors, two capacitors, a linear resistor and a diode. The Lyapunov exponents are presented to confirm hyperchaotic nature of the oscillations in the circ......A simple 4th order hyperchaotic circuit with unstable oscillators is described. The circuit contains two negative impedance converters, two inductors, two capacitors, a linear resistor and a diode. The Lyapunov exponents are presented to confirm hyperchaotic nature of the oscillations...

  3. Mechanisms of hierarchical reinforcement learning in cortico-striatal circuits 2: evidence from fMRI.

    Science.gov (United States)

    Badre, David; Frank, Michael J

    2012-03-01

    The frontal lobes may be organized hierarchically such that more rostral frontal regions modulate cognitive control operations in caudal regions. In our companion paper (Frank MJ, Badre D. 2011. Mechanisms of hierarchical reinforcement learning in corticostriatal circuits I: computational analysis. 22:509-526), we provide novel neural circuit and algorithmic models of hierarchical cognitive control in cortico-striatal circuits. Here, we test key model predictions using functional magnetic resonance imaging (fMRI). Our neural circuit model proposes that contextual representations in rostral frontal cortex influence the striatal gating of contextual representations in caudal frontal cortex. Reinforcement learning operates at each level, such that the system adaptively learns to gate higher order contextual information into rostral regions. Our algorithmic Bayesian "mixture of experts" model captures the key computations of this neural model and provides trial-by-trial estimates of the learner's latent hypothesis states. In the present paper, we used these quantitative estimates to reanalyze fMRI data from a hierarchical reinforcement learning task reported in Badre D, Kayser AS, D'Esposito M. 2010. Frontal cortex and the discovery of abstract action rules. Neuron. 66:315--326. Results validate key predictions of the models and provide evidence for an individual cortico-striatal circuit for reinforcement learning of hierarchical structure at a specific level of policy abstraction. These findings are initially consistent with the proposal that hierarchical control in frontal cortex may emerge from interactions among nested cortico-striatal circuits at different levels of abstraction.

  4. Neural networks and perceptual learning

    Science.gov (United States)

    Tsodyks, Misha; Gilbert, Charles

    2005-01-01

    Sensory perception is a learned trait. The brain strategies we use to perceive the world are constantly modified by experience. With practice, we subconsciously become better at identifying familiar objects or distinguishing fine details in our environment. Current theoretical models simulate some properties of perceptual learning, but neglect the underlying cortical circuits. Future neural network models must incorporate the top-down alteration of cortical function by expectation or perceptual tasks. These newly found dynamic processes are challenging earlier views of static and feedforward processing of sensory information. PMID:15483598

  5. SpikingLab: modelling agents controlled by Spiking Neural Networks in Netlogo.

    Science.gov (United States)

    Jimenez-Romero, Cristian; Johnson, Jeffrey

    2017-01-01

    The scientific interest attracted by Spiking Neural Networks (SNN) has lead to the development of tools for the simulation and study of neuronal dynamics ranging from phenomenological models to the more sophisticated and biologically accurate Hodgkin-and-Huxley-based and multi-compartmental models. However, despite the multiple features offered by neural modelling tools, their integration with environments for the simulation of robots and agents can be challenging and time consuming. The implementation of artificial neural circuits to control robots generally involves the following tasks: (1) understanding the simulation tools, (2) creating the neural circuit in the neural simulator, (3) linking the simulated neural circuit with the environment of the agent and (4) programming the appropriate interface in the robot or agent to use the neural controller. The accomplishment of the above-mentioned tasks can be challenging, especially for undergraduate students or novice researchers. This paper presents an alternative tool which facilitates the simulation of simple SNN circuits using the multi-agent simulation and the programming environment Netlogo (educational software that simplifies the study and experimentation of complex systems). The engine proposed and implemented in Netlogo for the simulation of a functional model of SNN is a simplification of integrate and fire (I&F) models. The characteristics of the engine (including neuronal dynamics, STDP learning and synaptic delay) are demonstrated through the implementation of an agent representing an artificial insect controlled by a simple neural circuit. The setup of the experiment and its outcomes are described in this work.

  6. Wireless Communication Electronics Introduction to RF Circuits and Design Techniques

    CERN Document Server

    Sobot, Robert

    2012-01-01

    This book is intended for senior undergraduate and graduate students as well as practicing engineers who are involved in design and analysis of radio frequency (RF) circuits.  Detailed tutorials are included on all major topics required to understand fundamental principles behind both the main sub-circuits required to design an RF transceiver and the whole communication system. Starting with review of fundamental principles in electromagnetic (EM) transmission and signal propagation, through detailed practical analysis of RF amplifier, mixer, modulator, demodulator, and oscillator circuit topologies, all the way to the system communication theory behind the RF transceiver operation, this book systematically covers all relevant aspects in a way that is suitable for a single semester university level course.   Offers readers a complete, self-sufficient tutorial style textbook; Includes all relevant topics required to study and design an RF receiver in a consistent, coherent way with appropriate depth for a on...

  7. Neural reuse: a fundamental organizational principle of the brain.

    Science.gov (United States)

    Anderson, Michael L

    2010-08-01

    An emerging class of theories concerning the functional structure of the brain takes the reuse of neural circuitry for various cognitive purposes to be a central organizational principle. According to these theories, it is quite common for neural circuits established for one purpose to be exapted (exploited, recycled, redeployed) during evolution or normal development, and be put to different uses, often without losing their original functions. Neural reuse theories thus differ from the usual understanding of the role of neural plasticity (which is, after all, a kind of reuse) in brain organization along the following lines: According to neural reuse, circuits can continue to acquire new uses after an initial or original function is established; the acquisition of new uses need not involve unusual circumstances such as injury or loss of established function; and the acquisition of a new use need not involve (much) local change to circuit structure (e.g., it might involve only the establishment of functional connections to new neural partners). Thus, neural reuse theories offer a distinct perspective on several topics of general interest, such as: the evolution and development of the brain, including (for instance) the evolutionary-developmental pathway supporting primate tool use and human language; the degree of modularity in brain organization; the degree of localization of cognitive function; and the cortical parcellation problem and the prospects (and proper methods to employ) for function to structure mapping. The idea also has some practical implications in the areas of rehabilitative medicine and machine interface design.

  8. A dishwasher for circuits

    CERN Multimedia

    Rosaria Marraffino

    2014-01-01

    You have always been told that electronic devices fear water. However, at the Surface Mount Devices (SMD) Workshop here at CERN all the electronic assemblies are cleaned with a machine that looks like a… dishwasher.   The circuit dishwasher. Credit: Clara Nellist.  If you think the image above shows a dishwasher, you wouldn’t be completely wrong. Apart from the fact that the whole pumping system and the case itself are made entirely from stainless steel and chemical resistant materials, and the fact that it washes electrical boards instead of dishes… it works exactly like a dishwasher. It’s a professional machine (mainly used in the pharmaceutical industry) designed to clean everything that can be washed with a water-based chemical soap. This type of treatment increases the lifetime of the electronic boards and therefore the LHC's reliability by preventing corrosion problems in the severe radiation and ozone environment of the LHC tunn...

  9. Modeling cortical circuits.

    Energy Technology Data Exchange (ETDEWEB)

    Rohrer, Brandon Robinson; Rothganger, Fredrick H.; Verzi, Stephen J.; Xavier, Patrick Gordon

    2010-09-01

    The neocortex is perhaps the highest region of the human brain, where audio and visual perception takes place along with many important cognitive functions. An important research goal is to describe the mechanisms implemented by the neocortex. There is an apparent regularity in the structure of the neocortex [Brodmann 1909, Mountcastle 1957] which may help simplify this task. The work reported here addresses the problem of how to describe the putative repeated units ('cortical circuits') in a manner that is easily understood and manipulated, with the long-term goal of developing a mathematical and algorithmic description of their function. The approach is to reduce each algorithm to an enhanced perceptron-like structure and describe its computation using difference equations. We organize this algorithmic processing into larger structures based on physiological observations, and implement key modeling concepts in software which runs on parallel computing hardware.

  10. Basic electronic circuits

    CERN Document Server

    Buckley, P M

    1980-01-01

    In the past, the teaching of electricity and electronics has more often than not been carried out from a theoretical and often highly academic standpoint. Fundamentals and basic concepts have often been presented with no indication of their practical appli­ cations, and all too frequently they have been illustrated by artificially contrived laboratory experiments bearing little relationship to the outside world. The course comes in the form of fourteen fairly open-ended constructional experiments or projects. Each experiment has associated with it a construction exercise and an explanation. The basic idea behind this dual presentation is that the student can embark on each circuit following only the briefest possible instructions and that an open-ended approach is thereby not prejudiced by an initial lengthy encounter with the theory behind the project; this being a sure way to dampen enthusiasm at the outset. As the investigation progresses, questions inevitably arise. Descriptions of the phenomena encounte...

  11. Pattern recognition via synchronization in phase-locked loop neural networks.

    Science.gov (United States)

    Hoppensteadt, F C; Izhikevich, E M

    2000-01-01

    We propose a novel architecture of an oscillatory neural network that consists of phase-locked loop (PLL) circuits. It stores and retrieves complex oscillatory patterns as synchronized states with appropriate phase relations between neurons.

  12. [Robustness analysis of adaptive neural network model based on spike timing-dependent plasticity].

    Science.gov (United States)

    Chen, Yunzhi; Xu, Guizhi; Zhou, Qian; Guo, Miaomiao; Guo, Lei; Wan, Xiaowei

    2015-02-01

    To explore the self-organization robustness of the biological neural network, and thus to provide new ideas and methods for the electromagnetic bionic protection, we studied both the information transmission mechanism of neural network and spike timing-dependent plasticity (STDP) mechanism, and then investigated the relationship between synaptic plastic and adaptive characteristic of biology. Then a feedforward neural network with the Izhikevich model and the STDP mechanism was constructed, and the adaptive robust capacity of the network was analyzed. Simulation results showed that the neural network based on STDP mechanism had good rubustness capacity, and this characteristics is closely related to the STDP mechanisms. Based on this simulation work, the cell circuit with neurons and synaptic circuit which can simulate the information processing mechanisms of biological nervous system will be further built, then the electronic circuits with adaptive robustness will be designed based on the cell circuit.

  13. Two-photon imaging and analysis of neural network dynamics

    Science.gov (United States)

    Lütcke, Henry; Helmchen, Fritjof

    2011-08-01

    The glow of a starry night sky, the smell of a freshly brewed cup of coffee or the sound of ocean waves breaking on the beach are representations of the physical world that have been created by the dynamic interactions of thousands of neurons in our brains. How the brain mediates perceptions, creates thoughts, stores memories and initiates actions remains one of the most profound puzzles in biology, if not all of science. A key to a mechanistic understanding of how the nervous system works is the ability to measure and analyze the dynamics of neuronal networks in the living organism in the context of sensory stimulation and behavior. Dynamic brain properties have been fairly well characterized on the microscopic level of individual neurons and on the macroscopic level of whole brain areas largely with the help of various electrophysiological techniques. However, our understanding of the mesoscopic level comprising local populations of hundreds to thousands of neurons (so-called 'microcircuits') remains comparably poor. Predominantly, this has been due to the technical difficulties involved in recording from large networks of neurons with single-cell spatial resolution and near-millisecond temporal resolution in the brain of living animals. In recent years, two-photon microscopy has emerged as a technique which meets many of these requirements and thus has become the method of choice for the interrogation of local neural circuits. Here, we review the state-of-research in the field of two-photon imaging of neuronal populations, covering the topics of microscope technology, suitable fluorescent indicator dyes, staining techniques, and in particular analysis techniques for extracting relevant information from the fluorescence data. We expect that functional analysis of neural networks using two-photon imaging will help to decipher fundamental operational principles of neural microcircuits.

  14. Two-photon imaging and analysis of neural network dynamics

    Energy Technology Data Exchange (ETDEWEB)

    Luetcke, Henry; Helmchen, Fritjof [Brain Research Institute, University of Zurich, Winterthurerstrasse 190, CH-8057 Zurich (Switzerland)

    2011-08-15

    The glow of a starry night sky, the smell of a freshly brewed cup of coffee or the sound of ocean waves breaking on the beach are representations of the physical world that have been created by the dynamic interactions of thousands of neurons in our brains. How the brain mediates perceptions, creates thoughts, stores memories and initiates actions remains one of the most profound puzzles in biology, if not all of science. A key to a mechanistic understanding of how the nervous system works is the ability to measure and analyze the dynamics of neuronal networks in the living organism in the context of sensory stimulation and behavior. Dynamic brain properties have been fairly well characterized on the microscopic level of individual neurons and on the macroscopic level of whole brain areas largely with the help of various electrophysiological techniques. However, our understanding of the mesoscopic level comprising local populations of hundreds to thousands of neurons (so-called 'microcircuits') remains comparably poor. Predominantly, this has been due to the technical difficulties involved in recording from large networks of neurons with single-cell spatial resolution and near-millisecond temporal resolution in the brain of living animals. In recent years, two-photon microscopy has emerged as a technique which meets many of these requirements and thus has become the method of choice for the interrogation of local neural circuits. Here, we review the state-of-research in the field of two-photon imaging of neuronal populations, covering the topics of microscope technology, suitable fluorescent indicator dyes, staining techniques, and in particular analysis techniques for extracting relevant information from the fluorescence data. We expect that functional analysis of neural networks using two-photon imaging will help to decipher fundamental operational principles of neural microcircuits.

  15. Degenerate coding in neural systems.

    Science.gov (United States)

    Leonardo, Anthony

    2005-11-01

    When the dimensionality of a neural circuit is substantially larger than the dimensionality of the variable it encodes, many different degenerate network states can produce the same output. In this review I will discuss three different neural systems that are linked by this theme. The pyloric network of the lobster, the song control system of the zebra finch, and the odor encoding system of the locust, while different in design, all contain degeneracies between their internal parameters and the outputs they encode. Indeed, although the dynamics of song generation and odor identification are quite different, computationally, odor recognition can be thought of as running the song generation circuitry backwards. In both of these systems, degeneracy plays a vital role in mapping a sparse neural representation devoid of correlations onto external stimuli (odors or song structure) that are strongly correlated. I argue that degeneracy between input and output states is an inherent feature of many neural systems, which can be exploited as a fault-tolerant method of reliably learning, generating, and discriminating closely related patterns.

  16. Digital circuits using universal logic gates

    Science.gov (United States)

    Whitaker, Sterling R. (Inventor); Miles, Lowell H. (Inventor); Cameron, Eric G. (Inventor); Donohoe, Gregory W. (Inventor); Gambles, Jody W. (Inventor)

    2004-01-01

    According to the invention, a digital circuit design embodied in at least one of a structural netlist, a behavioral netlist, a hardware description language netlist, a full-custom ASIC, a semi-custom ASIC, an IP core, an integrated circuit, a hybrid of chips, one or more masks, a FPGA, and a circuit card assembly is disclosed. The digital circuit design includes first and second sub-circuits. The first sub-circuits comprise a first percentage of the digital circuit design and the second sub-circuits comprise a second percentage of the digital circuit design. Each of the second sub-circuits is substantially comprised of one or more kernel circuits. The kernel circuits are comprised of selection circuits. The second percentage is at least 5%. In various embodiments, the second percentage could be at least 10%, 20%, 30%, 40%, 50%, 60%, 70%, 80%, 90%, or 95%.

  17. Enhancement of Linear Circuit Program

    DEFF Research Database (Denmark)

    Gaunholt, Hans; Dabu, Mihaela; Beldiman, Octavian

    1996-01-01

    In this report a preliminary user friendly interface has been added to the LCP2 program making it possible to describe an electronic circuit by actually drawing the circuit on the screen. Component values and other options and parameters can easily be set by the aid of the interface. The interface...

  18. Compact Circuit Preprocesses Accelerometer Output

    Science.gov (United States)

    Bozeman, Richard J., Jr.

    1993-01-01

    Compact electronic circuit transfers dc power to, and preprocesses ac output of, accelerometer and associated preamplifier. Incorporated into accelerometer case during initial fabrication or retrofit onto commercial accelerometer. Made of commercial integrated circuits and other conventional components; made smaller by use of micrologic and surface-mount technology.

  19. Comminution circuits for compact itabirites

    Directory of Open Access Journals (Sweden)

    Pedro Ferreira Pinto

    Full Text Available Abstract In the beneficiation of compact Itabirites, crushing and grinding account for major operational and capital costs. As such, the study and development of comminution circuits have a fundamental importance for feasibility and optimization of compact Itabirite beneficiation. This work makes a comparison between comminution circuits for compact Itabirites from the Iron Quadrangle. The circuits developed are: a crushing and ball mill circuit (CB, a SAG mill and ball mill circuit (SAB and a single stage SAG mill circuit (SSSAG. For the SAB circuit, the use of pebble crushing is analyzed (SABC. An industrial circuit for 25 million tons of run of mine was developed for each route from tests on a pilot scale (grinding and industrial scale. The energy consumption obtained for grinding in the pilot tests was compared with that reported by Donda and Bond. The SSSAG route had the lowest energy consumption, 11.8kWh/t and the SAB route had the highest energy consumption, 15.8kWh/t. The CB and SABC routes had a similar energy consumption of 14.4 kWh/t and 14.5 kWh/t respectively.

  20. Striatal circuits as a common node for autism pathophysiology

    Directory of Open Access Journals (Sweden)

    Marc Vincent Fuccillo

    2016-02-01

    Full Text Available Autism spectrum disorders (ASD are characterized by two seemingly unrelated symptom domains – deficits in social interactions and restrictive, repetitive patterns of behavioral output. Whether the diverse nature of ASD symptomatology represents distributed dysfunction of brain networks or abnormalities within specific neural circuits is unclear. Striatal dysfunction is postulated to underlie the repetitive motor behaviors seen in ASD, and neurological and brain-imaging studies have supported this assumption. However, as our appreciation of striatal function expands to include regulation of behavioral flexibility, motivational state, goal-directed learning, and attention, we consider whether alterations in striatal physiology are a central node mediating a range of autism-associated behaviors, including social and cognitive deficits that are hallmarks of the disease. This review investigates multiple genetic mouse models of ASD to explore whether abnormalities in striatal circuits constitute a common pathophysiological mechanism in the development of autism-related behaviors. Despite the heterogeneity of genetic insult investigated, numerous genetic ASD models display alterations in the structure and function of striatal circuits, as well as abnormal behaviors including repetitive grooming, stereotypic motor routines, deficits in social interaction and decision-making. Comparative analysis in rodents provides a unique opportunity to leverage growing genetic association data to reveal canonical neural circuits whose dysfunction directly contributes to discrete aspects of ASD symptomatology. The description of such circuits could provide both organizing principles for understanding the complex genetic etiology of ASD as well as novel treatment routes. Furthermore, this focus on striatal mechanisms of behavioral regulation may also prove useful for exploring the pathogenesis of other neuropsychiatric diseases, which display overlapping behavioral

  1. A carbon-fiber electrode array for long-term neural recording.

    Science.gov (United States)

    Guitchounts, Grigori; Markowitz, Jeffrey E; Liberti, William A; Gardner, Timothy J

    2013-08-01

    Chronic neural recording in behaving animals is an essential method for studies of neural circuit function. However, stable recordings from small, densely packed neurons remains challenging, particularly over time-scales relevant for learning. We describe an assembly method for a 16-channel electrode array consisting of carbon fibers (Carbon fiber arrays were tested in HVC (used as a proper name), a song motor nucleus, of singing zebra finches where individual neurons discharge with temporally precise patterns. Previous reports of activity in this population of neurons have required the use of high impedance electrodes on movable microdrives. Here, the carbon fiber electrodes provided stable multi-unit recordings over time-scales of months. Spike-sorting indicated that the multi-unit signals were dominated by one, or a small number of cells. Stable firing patterns during singing confirmed the stability of these clusters over time-scales of months. In addition, from a total of 10 surgeries, 16 projection neurons were found. This cell type is characterized by sparse stereotyped firing patterns, providing unambiguous confirmation of single cell recordings. Carbon fiber electrode bundles may provide a scalable solution for long-term neural recordings of densely packed neurons.

  2. Reward-based training of recurrent neural networks for cognitive and value-based tasks

    Science.gov (United States)

    Song, H Francis; Yang, Guangyu R; Wang, Xiao-Jing

    2017-01-01

    Trained neural network models, which exhibit features of neural activity recorded from behaving animals, may provide insights into the circuit mechanisms of cognitive functions through systematic analysis of network activity and connectivity. However, in contrast to the graded error signals commonly used to train networks through supervised learning, animals learn from reward feedback on definite actions through reinforcement learning. Reward maximization is particularly relevant when optimal behavior depends on an animal’s internal judgment of confidence or subjective preferences. Here, we implement reward-based training of recurrent neural networks in which a value network guides learning by using the activity of the decision network to predict future reward. We show that such models capture behavioral and electrophysiological findings from well-known experimental paradigms. Our work provides a unified framework for investigating diverse cognitive and value-based computations, and predicts a role for value representation that is essential for learning, but not executing, a task. DOI: http://dx.doi.org/10.7554/eLife.21492.001 PMID:28084991

  3. On the neural networks of empathy: A principal component analysis of an fMRI study

    Directory of Open Access Journals (Sweden)

    Wittsack Hans-Jörg

    2008-09-01

    Full Text Available Abstract Background Human emotional expressions serve an important communicatory role allowing the rapid transmission of valence information among individuals. We aimed at exploring the neural networks mediating the recognition of and empathy with human facial expressions of emotion. Methods A principal component analysis was applied to event-related functional magnetic imaging (fMRI data of 14 right-handed healthy volunteers (29 +/- 6 years. During scanning, subjects viewed happy, sad and neutral face expressions in the following conditions: emotion recognition, empathizing with emotion, and a control condition of simple object detection. Functionally relevant principal components (PCs were identified by planned comparisons at an alpha level of p Results Four PCs revealed significant differences in variance patterns of the conditions, thereby revealing distinct neural networks: mediating facial identification (PC 1, identification of an expressed emotion (PC 2, attention to an expressed emotion (PC 12, and sense of an emotional state (PC 27. Conclusion Our findings further the notion that the appraisal of human facial expressions involves multiple neural circuits that process highly differentiated cognitive aspects of emotion.

  4. Optics in neural computation

    Science.gov (United States)

    Levene, Michael John

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

  5. Photodiode circuits for retinal prostheses.

    Science.gov (United States)

    Loudin, J D; Cogan, S F; Mathieson, K; Sher, A; Palanker, D V

    2011-10-01

    Photodiode circuits show promise for the development of high-resolution retinal prostheses. While several of these systems have been constructed and some even implanted in humans, existing descriptions of the complex optoelectronic interaction between light, photodiode, and the electrode/electrolyte load are limited. This study examines this interaction in depth with theoretical calculations and experimental measurements. Actively biased photoconductive and passive photovoltaic circuits are investigated, with the photovoltaic circuits consisting of one or more diodes connected in series, and the photoconductive circuits consisting of a single diode in series with a pulsed bias voltage. Circuit behavior and charge injection levels were markedly different for platinum and sputtered iridium-oxide film (SIROF) electrodes. Photovoltaic circuits were able to deliver 0.038 mC/cm(2) (0.75 nC/phase) per photodiode with 50- μm platinum electrodes, and 0.54-mC/cm(2) (11 nC/phase) per photodiode with 50-μ m SIROF electrodes driven with 0.5-ms pulses of light at 25 Hz. The same pulses applied to photoconductive circuits with the same electrodes were able to deliver charge injections as high as 0.38 and 7.6 mC/cm(2) (7.5 and 150 nC/phase), respectively. We demonstrate photovoltaic stimulation of rabbit retina in-vitro, with 0.5-ms pulses of 905-nm light using peak irradiance of 1 mW/mm(2). Based on the experimental data, we derive electrochemical and optical safety limits for pixel density and charge injection in various circuits. While photoconductive circuits offer smaller pixels, photovoltaic systems do not require an external bias voltage. Both classes of circuits show promise for the development of high-resolution optoelectronic retinal prostheses.

  6. Rapid three dimensional two photon neural population scanning.

    Science.gov (United States)

    Schuck, Renaud; Quicke, Peter; Copeland, Caroline; Garasto, Stefania; Annecchino, Luca A; Hwang, June Kyu; Schultz, Simon R

    2015-08-01

    Recording the activity of neural populations at high sampling rates is a fundamental requirement for understanding computation in neural circuits. Two photon microscopy provides one promising approach towards this. However, neural circuits are three dimensional, and functional imaging in two dimensions fails to capture the 3D nature of neural dynamics. Electrically tunable lenses (ETLs) provide a simple and cheap method to extend laser scanning microscopy into the relatively unexploited third dimension. We have therefore incorporated them into our Adaptive Spiral Scanning (SSA) algorithm, which calculates kinematically efficient scanning strategies using radially modulated spiral paths. We characterised the response of the ETL, incorporated its dynamics using MATLAB models of the SSA algorithm and tested the models on populations of Izhikevich neurons of varying size and density. From this, we show that our algorithms can theoretically at least achieve sampling rates of 36.2Hz compared to 21.6Hz previously reported for 3D scanning techniques.

  7. Inherently stochastic spiking neurons for probabilistic neural computation

    KAUST Repository

    Al-Shedivat, Maruan

    2015-04-01

    Neuromorphic engineering aims to design hardware that efficiently mimics neural circuitry and provides the means for emulating and studying neural systems. In this paper, we propose a new memristor-based neuron circuit that uniquely complements the scope of neuron implementations and follows the stochastic spike response model (SRM), which plays a cornerstone role in spike-based probabilistic algorithms. We demonstrate that the switching of the memristor is akin to the stochastic firing of the SRM. Our analysis and simulations show that the proposed neuron circuit satisfies a neural computability condition that enables probabilistic neural sampling and spike-based Bayesian learning and inference. Our findings constitute an important step towards memristive, scalable and efficient stochastic neuromorphic platforms. © 2015 IEEE.

  8. Neural Networks

    Directory of Open Access Journals (Sweden)

    Schwindling Jerome

    2010-04-01

    Full Text Available This course presents an overview of the concepts of the neural networks and their aplication in the framework of High energy physics analyses. After a brief introduction on the concept of neural networks, the concept is explained in the frame of neuro-biology, introducing the concept of multi-layer perceptron, learning and their use as data classifer. The concept is then presented in a second part using in more details the mathematical approach focussing on typical use cases faced in particle physics. Finally, the last part presents the best way to use such statistical tools in view of event classifers, putting the emphasis on the setup of the multi-layer perceptron. The full article (15 p. corresponding to this lecture is written in french and is provided in the proceedings of the book SOS 2008.

  9. An overview of Bayesian methods for neural spike train analysis.

    Science.gov (United States)

    Chen, Zhe

    2013-01-01

    Neural spike train analysis is an important task in computational neuroscience which aims to understand neural mechanisms and gain insights into neural circuits. With the advancement of multielectrode recording and imaging technologies, it has become increasingly demanding to develop statistical tools for analyzing large neuronal ensemble spike activity. Here we present a tutorial overview of Bayesian methods and their representative applications in neural spike train analysis, at both single neuron and population levels. On the theoretical side, we focus on various approximate Bayesian inference techniques as applied to latent state and parameter estimation. On the application side, the topics include spike sorting, tuning curve estimation, neural encoding and decoding, deconvolution of spike trains from calcium imaging signals, and inference of neuronal functional connectivity and synchrony. Some research challenges and opportunities for neural spike train analysis are discussed.

  10. An Overview of Bayesian Methods for Neural Spike Train Analysis

    Directory of Open Access Journals (Sweden)

    Zhe Chen

    2013-01-01

    Full Text Available Neural spike train analysis is an important task in computational neuroscience which aims to understand neural mechanisms and gain insights into neural circuits. With the advancement of multielectrode recording and imaging technologies, it has become increasingly demanding to develop statistical tools for analyzing large neuronal ensemble spike activity. Here we present a tutorial overview of Bayesian methods and their representative applications in neural spike train analysis, at both single neuron and population levels. On the theoretical side, we focus on various approximate Bayesian inference techniques as applied to latent state and parameter estimation. On the application side, the topics include spike sorting, tuning curve estimation, neural encoding and decoding, deconvolution of spike trains from calcium imaging signals, and inference of neuronal functional connectivity and synchrony. Some research challenges and opportunities for neural spike train analysis are discussed.

  11. A canonical neural mechanism for behavioral variability

    Science.gov (United States)

    Darshan, Ran; Wood, William E.; Peters, Susan; Leblois, Arthur; Hansel, David

    2017-05-01

    The ability to generate variable movements is essential for learning and adjusting complex behaviours. This variability has been linked to the temporal irregularity of neuronal activity in the central nervous system. However, how neuronal irregularity actually translates into behavioural variability is unclear. Here we combine modelling, electrophysiological and behavioural studies to address this issue. We demonstrate that a model circuit comprising topographically organized and strongly recurrent neural networks can autonomously generate irregular motor behaviours. Simultaneous recordings of neurons in singing finches reveal that neural correlations increase across the circuit driving song variability, in agreement with the model predictions. Analysing behavioural data, we find remarkable similarities in the babbling statistics of 5-6-month-old human infants and juveniles from three songbird species and show that our model naturally accounts for these `universal' statistics.

  12. A 2.1 μW/channel current-mode integrated neural recording interface

    NARCIS (Netherlands)

    Zjajo, A.; van Leuken, T.G.R.M.

    2016-01-01

    In this paper, we present a neural recording interface circuit for biomedical implantable devices, which includes low-noise signal amplification, band-pass filtering, and current-mode successive approximation A/D signal conversion. The integrated interface circuit is realized in a 65 nm CMOS

  13. Power amplifier circuits for functional electrical stimulation systems

    Directory of Open Access Journals (Sweden)

    Delmar Carvalho de Souza

    Full Text Available Abstract Introduction: Functional electrical stimulation (FES is a technique that has been successfully employed in rehabilitation treatment to mitigate problems after spinal cord injury (SCI. One of the most relevant modules in a typical FES system is the power or output amplifier stage, which is responsible for the application of voltage or current pulses of proper intensity to the biological tissue, applied noninvasively via electrodes, placed on the skin surface or inside the muscular tissue, closer to the nervous fibers. The goals of this paper are to describe and discuss about the main power output designs usually employed in transcutaneous functional electrical stimulators as well as safety precautions taken to protect patients. Methods A systematic review investigated the circuits of papers published in IEEE Xplore and ScienceDirect databases from 2000 to 2016. The query terms were “((FES or Functional electric stimulator and (circuit or design” with 274 papers retrieved from IEEE Xplore and 29 from ScienceDirect. After the application of exclusion criteria the amount of papers decreased to 9 and 2 from IEEE Xplore and ScienceDirect, respectively. One paper was inserted in the results as a technological contribution to the field. Therefore, 12 papers presented power stage circuits suitable to stimulate great muscles. Discussion The retrieved results presented relevant circuits with different electronic strategies and circuit components. Some of them considered patient safety strategies or aimed to preserve muscle homeostasis such as biphasic current application, which prevents charge accumulation in stimulated tissues as well as circuits that dealt with electrical impedance variation to keep the electrode-tissue interface within an electrochemical safe regime. The investigation revealed a predominance of design strategies using operational amplifiers in power circuits, current outputs, and safety methods to reduce risks of electrical

  14. Signal transfer within a cultured asymmetric cortical neuron circuit

    Science.gov (United States)

    Isomura, Takuya; Shimba, Kenta; Takayama, Yuzo; Takeuchi, Akimasa; Kotani, Kiyoshi; Jimbo, Yasuhiko

    2015-12-01

    Objective. Simplified neuronal circuits are required for investigating information representation in nervous systems and for validating theoretical neural network models. Here, we developed patterned neuronal circuits using micro fabricated devices, comprising a micro-well array bonded to a microelectrode-array substrate. Approach. The micro-well array consisted of micrometre-scale wells connected by tunnels, all contained within a silicone slab called a micro-chamber. The design of the micro-chamber confined somata to the wells and allowed axons to grow through the tunnels bidirectionally but with a designed, unidirectional bias. We guided axons into the point of the arrow structure where one of the two tunnel entrances is located, making that the preferred direction. Main results. When rat cortical neurons were cultured in the wells, their axons grew through the tunnels and connected to neurons in adjoining wells. Unidirectional burst transfers and other asymmetric signal-propagation phenomena were observed via the substrate-embedded electrodes. Seventy-nine percent of burst transfers were in the forward direction. We also observed rapid propagation of activity from sites of local electrical stimulation, and significant effects of inhibitory synapse blockade on bursting activity. Significance. These results suggest that this simple, substrate-controlled neuronal circuit can be applied to develop in vitro models of the function of cortical microcircuits or deep neural networks, better to elucidate the laws governing the dynamics of neuronal networks.

  15. Variational integrators for electric circuits

    Energy Technology Data Exchange (ETDEWEB)

    Ober-Blöbaum, Sina, E-mail: sinaob@math.upb.de [Computational Dynamics and Optimal Control, University of Paderborn (Germany); Tao, Molei [Courant Institute of Mathematical Sciences, New York University (United States); Cheng, Mulin [Applied and Computational Mathematics, California Institute of Technology (United States); Owhadi, Houman; Marsden, Jerrold E. [Control and Dynamical Systems, California Institute of Technology (United States); Applied and Computational Mathematics, California Institute of Technology (United States)

    2013-06-01

    In this contribution, we develop a variational integrator for the simulation of (stochastic and multiscale) electric circuits. When considering the dynamics of an electric circuit, one is faced with three special situations: 1. The system involves external (control) forcing through external (controlled) voltage sources and resistors. 2. The system is constrained via the Kirchhoff current (KCL) and voltage laws (KVL). 3. The Lagrangian is degenerate. Based on a geometric setting, an appropriate variational formulation is presented to model the circuit from which the equations of motion are derived. A time-discrete variational formulation provides an iteration scheme for the simulation of the electric circuit. Dependent on the discretization, the intrinsic degeneracy of the system can be canceled for the discrete variational scheme. In this way, a variational integrator is constructed that gains several advantages compared to standard integration tools for circuits; in particular, a comparison to BDF methods (which are usually the method of choice for the simulation of electric circuits) shows that even for simple LCR circuits, a better energy behavior and frequency spectrum preservation can be observed using the developed variational integrator.

  16. Experimental Device for Learning of Logical Circuit Design using Integrated Circuits

    OpenAIRE

    石橋, 孝昭

    2012-01-01

    This paper presents an experimental device for learning of logical circuit design using integrated circuits and breadboards. The experimental device can be made at a low cost and can be used for many subjects such as logical circuits, computer engineering, basic electricity, electrical circuits and electronic circuits. The proposed device is effective to learn the logical circuits than the usual lecture.

  17. 30 CFR 77.800 - High-voltage circuits; circuit breakers.

    Science.gov (United States)

    2010-07-01

    ... 30 Mineral Resources 1 2010-07-01 2010-07-01 false High-voltage circuits; circuit breakers. 77.800... COAL MINES Surface High-Voltage Distribution § 77.800 High-voltage circuits; circuit breakers. High-voltage circuits supplying power to portable or mobile equipment shall be protected by suitable circuit...

  18. Durability evaluation method for contact component interconnections in printed circuit boards under thermal loads

    Science.gov (United States)

    Azin, Anton; Zhukov, Andrey A.; Ponomarev, Sergey A.; Ponomarev, Sergey V.

    2017-11-01

    In designing sophisticated printed circuit boards, required evaluation of the product life cycle is relevant in terms of presumably applied load conditions during operation. The paper describes the durability evaluation method of printed circuit board components with contact output such as ball grid array (BGA) and pitch grid array (PGA) under thermal loads. Experiment data and numerical simulation results of soldered connections have been obtained. This method is demonstrated by a practical application example-evaluating of printed circuit board durability under cyclic thermal loads. The application of proposed method for printed circuit boards would make it possible to predict the service life of these designed products.

  19. Neural Network Solves "Traveling-Salesman" Problem

    Science.gov (United States)

    Thakoor, Anilkumar P.; Moopenn, Alexander W.

    1990-01-01

    Experimental electronic neural network solves "traveling-salesman" problem. Plans round trip of minimum distance among N cities, visiting every city once and only once (without backtracking). This problem is paradigm of many problems of global optimization (e.g., routing or allocation of resources) occuring in industry, business, and government. Applied to large number of cities (or resources), circuits of this kind expected to solve problem faster and more cheaply.

  20. Wireless power transfer and data communication for neural implants case study : epilepsy monitoring

    CERN Document Server

    Yilmaz, Gürkan

    2017-01-01

    This book presents new circuits and systems for implantable biomedical applications targeting neural recording. The authors describe a system design adapted to conform to the requirements of an epilepsy monitoring system. Throughout the book, these requirements are reflected in terms of implant size, power consumption, and data rate. In addition to theoretical background which explains the relevant technical challenges, the authors provide practical, step-by-step solutions to these problems. Readers will gain understanding of the numerical values in such a system, enabling projections for feasibility of new projects. Provides complete, system-level perspective for implantable batteryless biomedical system; Extends design example to implementation and long term in-vitro validation; Discusses system design concerns regarding wireless power transmission and wireless data communication, particularly for systems in which both are performed on the same channel/frequency; Presents fully-integrated, implantable syste...

  1. The Maplin electronic circuits handbook

    CERN Document Server

    Tooley, Michael

    1990-01-01

    The Maplin Electronic Circuits Handbook provides pertinent data, formula, explanation, practical guidance, theory and practical guidance in the design, testing, and construction of electronic circuits. This book discusses the developments in electronics technology techniques.Organized into 11 chapters, this book begins with an overview of the common types of passive component. This text then provides the reader with sufficient information to make a correct selection of passive components for use in the circuits. Other chapters consider the various types of the most commonly used semiconductor

  2. Mapping patterns of depression-related brain regions with cytochrome oxidase histochemistry: relevance of animal affective systems to human disorders, with a focus on resilience to adverse events.

    Science.gov (United States)

    Harro, Jaanus; Kanarik, Margus; Matrov, Denis; Panksepp, Jaak

    2011-10-01

    The search for novel antidepressants may be facilitated by pre-clinical animal models that relay on specific neural circuit and related neurochemical endpoint measures, which are anchored in concrete neuro-anatomical and functional neural-network analyzes. One of the most important initial considerations must be which regions of the brain are candidates for the maladaptive response to depressogenic challenges. Consideration of persistent differences or changes in the activity of cerebral networks can be achieved by mapping oxidative metabolism in ethologically or pathogenetically relevant animal models. Cytochrome oxidase histochemistry is a technique suitable to detect regional long-term brain activity changes relative to control conditions and has been used in a variety of animal models. This work is summarized and indicates that major changes occur mainly in subcortical areas, highlighting specific brain regions where some alterations in regional oxidative metabolism may represent adaptive changes to depressogenic adverse life events, while others may reflect failures of adaptation. Many of these changes in oxidative metabolism may depend upon the integrity of serotonergic neurotransmission, and occur in several brain regions shown by other techniques to be involved in endogenous affective circuits that control emotional behaviors as well as related higher brain regions that integrate learning and cognitive information processing. These brain regions appear as primary targets for further identification of endophenotypes specific to affective disorders. Copyright © 2011 Elsevier Ltd. All rights reserved.

  3. Digital integrated circuit design using Verilog and SystemVerilog

    CERN Document Server

    Mehler, Ronald W

    2014-01-01

    For those with a basic understanding of digital design, this book teaches the essential skills to design digital integrated circuits using Verilog and the relevant extensions of SystemVerilog. In addition to covering the syntax of Verilog and SystemVerilog, the author provides an appreciation of design challenges and solutions for producing working circuits. The book covers not only the syntax and limitations of HDL coding, but deals extensively with design problems such as partitioning and synchronization, helping you to produce designs that are not only logically correct, but will actually

  4. Non-invasive neural stimulation

    Science.gov (United States)

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

    2017-05-01

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

  5. Neural networks and applications tutorial

    Science.gov (United States)

    Guyon, I.

    1991-09-01

    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.

  6. Sociability Deficits and Altered Amygdala Circuits in Mice Lacking Pcdh10, an Autism Associated Gene.

    Science.gov (United States)

    Schoch, Hannah; Kreibich, Arati S; Ferri, Sarah L; White, Rachel S; Bohorquez, Dominique; Banerjee, Anamika; Port, Russell G; Dow, Holly C; Cordero, Lucero; Pallathra, Ashley A; Kim, Hyong; Li, Hongzhe; Bilker, Warren B; Hirano, Shinji; Schultz, Robert T; Borgmann-Winter, Karin; Hahn, Chang-Gyu; Feldmeyer, Dirk; Carlson, Gregory C; Abel, Ted; Brodkin, Edward S

    2017-02-01

    Behavioral symptoms in individuals with autism spectrum disorder (ASD) have been attributed to abnormal neuronal connectivity, but the molecular bases of these behavioral and brain phenotypes are largely unknown. Human genetic studies have implicated PCDH10, a member of the δ2 subfamily of nonclustered protocadherin genes, in ASD. PCDH10 expression is enriched in the basolateral amygdala, a brain region implicated in the social deficits of ASD. Previous reports indicate that Pcdh10 plays a role in axon outgrowth and glutamatergic synapse elimination, but its roles in social behaviors and amygdala neuronal connectivity are unknown. We hypothesized that haploinsufficiency of Pcdh10 would reduce social approach behavior and alter the structure and function of amygdala circuits. Mice lacking one copy of Pcdh10 (Pcdh10 +/- ) and wild-type littermates were assessed for social approach and other behaviors. The lateral/basolateral amygdala was assessed for dendritic spine number and morphology, and amygdala circuit function was studied using voltage-sensitive dye imaging. Expression of Pcdh10 and N-methyl-D-aspartate receptor (NMDAR) subunits was assessed in postsynaptic density fractions of the amygdala. Male Pcdh10 +/- mice have reduced social approach behavior, as well as impaired gamma synchronization, abnormal spine morphology, and reduced levels of NMDAR subunits in the amygdala. Social approach deficits in Pcdh10 +/- male mice were rescued with acute treatment with the NMDAR partial agonist d-cycloserine. Our studies reveal that male Pcdh10 +/- mice have synaptic and behavioral deficits, and establish Pcdh10 +/- mice as a novel genetic model for investigating neural circuitry and behavioral changes relevant to ASD. Copyright © 2016 Society of Biological Psychiatry. Published by Elsevier Inc. All rights reserved.

  7. Imaging the neural circuitry and chemical control of aggressive motivation

    Directory of Open Access Journals (Sweden)

    Blanchard D Caroline

    2008-11-01

    Full Text Available Abstract Background With the advent of functional magnetic resonance imaging (fMRI in awake animals it is possible to resolve patterns of neuronal activity across the entire brain with high spatial and temporal resolution. Synchronized changes in neuronal activity across multiple brain areas can be viewed as functional neuroanatomical circuits coordinating the thoughts, memories and emotions for particular behaviors. To this end, fMRI in conscious rats combined with 3D computational analysis was used to identifying the putative distributed neural circuit involved in aggressive motivation and how this circuit is affected by drugs that block aggressive behavior. Results To trigger aggressive motivation, male rats were presented with their female cage mate plus a novel male intruder in the bore of the magnet during image acquisition. As expected, brain areas previously identified as critical in the organization and expression of aggressive behavior were activated, e.g., lateral hypothalamus, medial basal amygdala. Unexpected was the intense activation of the forebrain cortex and anterior thalamic nuclei. Oral administration of a selective vasopressin V1a receptor antagonist SRX251 or the selective serotonin reuptake inhibitor fluoxetine, drugs that block aggressive behavior, both caused a general suppression of the distributed neural circuit involved in aggressive motivation. However, the effect of SRX251, but not fluoxetine, was specific to aggression as brain activation in response to a novel sexually receptive female was unaffected. Conclusion The putative neural circuit of aggressive motivation identified with fMRI includes neural substrates contributing to emotional expression (i.e. cortical and medial amygdala, BNST, lateral hypothalamus, emotional experience (i.e. hippocampus, forebrain cortex, anterior cingulate, retrosplenial cortex and the anterior thalamic nuclei that bridge the motor and cognitive components of aggressive responding

  8. Learning sequential control in a Neural Blackboard Architecture for in situ concept reasoning

    NARCIS (Netherlands)

    van der Velde, Frank; van der Velde, Frank; Besold, Tarek R.; Lamb, Luis; Serafini, Luciano; Tabor, Whitney

    2016-01-01

    Simulations are presented and discussed of learning sequential control in a Neural Blackboard Architecture (NBA) for in situ concept-based reasoning. Sequential control is learned in a reservoir network, consisting of columns with neural circuits. This allows the reservoir to control the dynamics of

  9. Circuit design on plastic foils

    CERN Document Server

    Raiteri, Daniele; Roermund, Arthur H M

    2015-01-01

    This book illustrates a variety of circuit designs on plastic foils and provides all the information needed to undertake successful designs in large-area electronics.  The authors demonstrate architectural, circuit, layout, and device solutions and explain the reasons and the creative process behind each. Readers will learn how to keep under control large-area technologies and achieve robust, reliable circuit designs that can face the challenges imposed by low-cost low-temperature high-throughput manufacturing.   • Discusses implications of problems associated with large-area electronics and compares them to standard silicon; • Provides the basis for understanding physics and modeling of disordered material; • Includes guidelines to quickly setup the basic CAD tools enabling efficient and reliable designs; • Illustrates practical solutions to cope with hard/soft faults, variability, mismatch, aging and bias stress at architecture, circuit, layout, and device levels.

  10. Circuit Mechanisms Governing Local vs. Global Motion Processing in Mouse Visual Cortex

    DEFF Research Database (Denmark)

    Rasmussen, Rune; Yonehara, Keisuke

    2017-01-01

    literature on global motion processing based on works in primates and mice. Lastly, we propose what types of experiments could illuminate what circuit mechanisms are governing cortical global visual motion processing. We propose that PDS cells in mouse visual cortex appear as the perfect arena...... for delineating and solving how individual sensory features extracted by neural circuits in peripheral brain areas are integrated to build our rich cohesive sensory experiences.......A withstanding question in neuroscience is how neural circuits encode representations and perceptions of the external world. A particularly well-defined visual computation is the representation of global object motion by pattern direction-selective (PDS) cells from convergence of motion of local...

  11. Direction-Selective Circuits Shape Noise to Ensure a Precise Population Code.

    Science.gov (United States)

    Zylberberg, Joel; Cafaro, Jon; Turner, Maxwell H; Shea-Brown, Eric; Rieke, Fred

    2016-01-20

    Neural responses are noisy, and circuit structure can correlate this noise across neurons. Theoretical studies show that noise correlations can have diverse effects on population coding, but these studies rarely explore stimulus dependence of noise correlations. Here, we show that noise correlations in responses of ON-OFF direction-selective retinal ganglion cells are strongly stimulus dependent, and we uncover the circuit mechanisms producing this stimulus dependence. A population model based on these mechanistic studies shows that stimulus-dependent noise correlations improve the encoding of motion direction 2-fold compared to independent noise. This work demonstrates a mechanism by which a neural circuit effectively shapes its signal and noise in concert, minimizing corruption of signal by noise. Finally, we generalize our findings beyond direction coding in the retina and show that stimulus-dependent correlations will generally enhance information coding in populations of diversely tuned neurons. Copyright © 2016 Elsevier Inc. All rights reserved.

  12. Behavioral synthesis of asynchronous circuits

    DEFF Research Database (Denmark)

    Nielsen, Sune Fallgaard

    2005-01-01

    is idle. This reduces unnecessary switching activity in the individual functional units and therefore the energy consumption of the entire circuit. A collection of behavioral synthesis algorithms have been developed allowing the designer to perform time and power constrained design space exploration....... The datapath and control architecture is then expressed in the Balsa-language, and using syntax directed compilation a corresponding handshake circuit implementation (and eventually a layout) is produced....

  13. Neural Tube Defects

    Science.gov (United States)

    ... vitamin, before and during pregnancy prevents most neural tube defects. Neural tube defects are usually diagnosed before the infant is ... or imaging tests. There is no cure for neural tube defects. The nerve damage and loss of function ...

  14. Mechanisms of Long Non-Coding RNAs in the Assembly and Plasticity of Neural Circuitry.

    Science.gov (United States)

    Wang, Andi; Wang, Junbao; Liu, Ying; Zhou, Yan

    2017-01-01

    The mechanisms underlying development processes and functional dynamics of neural circuits are far from understood. Long non-coding RNAs (lncRNAs) have emerged as essential players in defining identities of neural cells, and in modulating neural activities. In this review, we summarized latest advances concerning roles and mechanisms of lncRNAs in assembly, maintenance and plasticity of neural circuitry, as well as lncRNAs' implications in neurological disorders. We also discussed technical advances and challenges in studying functions and mechanisms of lncRNAs in neural circuitry. Finally, we proposed that lncRNA studies would advance our understanding on how neural circuits develop and function in physiology and disease conditions.

  15. Receiver Gain Modulation Circuit

    Science.gov (United States)

    Jones, Hollis; Racette, Paul; Walker, David; Gu, Dazhen

    2011-01-01

    A receiver gain modulation circuit (RGMC) was developed that modulates the power gain of the output of a radiometer receiver with a test signal. As the radiometer receiver switches between calibration noise references, the test signal is mixed with the calibrated noise and thus produces an ensemble set of measurements from which ensemble statistical analysis can be used to extract statistical information about the test signal. The RGMC is an enabling technology of the ensemble detector. As a key component for achieving ensemble detection and analysis, the RGMC has broad aeronautical and space applications. The RGMC can be used to test and develop new calibration algorithms, for example, to detect gain anomalies, and/or correct for slow drifts that affect climate-quality measurements over an accelerated time scale. A generalized approach to analyzing radiometer system designs yields a mathematical treatment of noise reference measurements in calibration algorithms. By treating the measurements from the different noise references as ensemble samples of the receiver state, i.e. receiver gain, a quantitative description of the non-stationary properties of the underlying receiver fluctuations can be derived. Excellent agreement has been obtained between model calculations and radiometric measurements. The mathematical formulation is equivalent to modulating the gain of a stable receiver with an externally generated signal and is the basis for ensemble detection and analysis (EDA). The concept of generating ensemble data sets using an ensemble detector is similar to the ensemble data sets generated as part of ensemble empirical mode decomposition (EEMD) with exception of a key distinguishing factor. EEMD adds noise to the signal under study whereas EDA mixes the signal with calibrated noise. It is mixing with calibrated noise that permits the measurement of temporal-functional variability of uncertainty in the underlying process. The RGMC permits the evaluation of EDA by

  16. Disrupted reward circuits is associated with cognitive deficits and depression severity in major depressive disorder.

    Science.gov (United States)

    Gong, Liang; Yin, Yingying; He, Cancan; Ye, Qing; Bai, Feng; Yuan, Yonggui; Zhang, Haisan; Lv, Luxian; Zhang, Hongxing; Xie, Chunming; Zhang, Zhijun

    2017-01-01

    Neuroimaging studies have demonstrated that major depressive disorder (MDD) patients show blunted activity responses to reward-related tasks. However, whether abnormal reward circuits affect cognition and depression in MDD patients remains unclear. Seventy-five drug-naive MDD patients and 42 cognitively normal (CN) subjects underwent a resting-state functional magnetic resonance imaging scan. The bilateral nucleus accumbens (NAc) were selected as seeds to construct reward circuits across all subjects. A multivariate linear regression analysis was employed to investigate the neural substrates of cognitive function and depression severity on the reward circuits in MDD patients. The common pathway underlying cognitive deficits and depression was identified with conjunction analysis. Compared with CN subjects, MDD patients showed decreased reward network connectivity that was primarily located in the prefrontal-striatal regions. Importantly, distinct and common neural pathways underlying cognition and depression were identified, implying the independent and synergistic effects of cognitive deficits and depression severity on reward circuits. This study demonstrated that disrupted topological organization within reward circuits was significantly associated with cognitive deficits and depression severity in MDD patients. These findings suggest that in addition to antidepressant treatment, normalized reward circuits should be a focus and a target for improving depression and cognitive deficits in MDD patients. Copyright © 2016 Elsevier Ltd. All rights reserved.

  17. An integrator circuit in cerebellar cortex.

    Science.gov (United States)

    Maex, Reinoud; Steuber, Volker

    2013-09-01

    The brain builds dynamic models of the body and the outside world to predict the consequences of actions and stimuli. A well-known example is the oculomotor integrator, which anticipates the position-dependent elasticity forces acting on the eye ball by mathematically integrating over time oculomotor velocity commands. Many models of neural integration have been proposed, based on feedback excitation, lateral inhibition or intrinsic neuronal nonlinearities. We report here that a computational model of the cerebellar cortex, a structure thought to implement dynamic models, reveals a hitherto unrecognized integrator circuit. In this model, comprising Purkinje cells, molecular layer interneurons and parallel fibres, Purkinje cells were able to generate responses lasting more than 10 s, to which both neuronal and network mechanisms contributed. Activation of the somatic fast sodium current by subthreshold voltage fluctuations was able to maintain pulse-evoked graded persistent activity, whereas lateral inhibition among Purkinje cells via recurrent axon collaterals further prolonged the responses to step and sine wave stimulation. The responses of Purkinje cells decayed with a time-constant whose value depended on their baseline spike rate, with integration vanishing at low ( 30 per s). The model predicts that the apparently fast circuit of the cerebellar cortex may control the timing of slow processes without having to rely on sensory feedback. Thus, the cerebellar cortex may contain an adaptive temporal integrator, with the sensitivity of integration to the baseline spike rate offering a potential mechanism of plasticity of the response time-constant. © 2013 Federation of European Neuroscience Societies and John Wiley & Sons Ltd.

  18. RF and microwave integrated circuit development technology, packaging and testing

    CERN Document Server

    Gamand, Patrice; Kelma, Christophe

    2018-01-01

    RF and Microwave Integrated Circuit Development bridges the gap between existing literature, which focus mainly on the 'front-end' part of a product development (system, architecture, design techniques), by providing the reader with an insight into the 'back-end' part of product development. In addition, the authors provide practical answers and solutions regarding the choice of technology, the packaging solutions and the effects on the performance on the circuit and to the industrial testing strategy. It will also discuss future trends and challenges and includes case studies to illustrate examples. * Offers an overview of the challenges in RF/microwave product design * Provides practical answers to packaging issues and evaluates its effect on the performance of the circuit * Includes industrial testing strategies * Examines relevant RF MIC technologies and the factors which affect the choice of technology for a particular application, e.g. technical performance and cost * Discusses future trends and challen...

  19. Astrocyte regulation of sleep circuits: experimental and modeling perspectives

    Directory of Open Access Journals (Sweden)

    Tommaso eFellin

    2012-08-01

    Full Text Available Integrated within neural circuits, astrocytes have recently been shown to modulate brain rhythms thought to mediate sleep function. Experimental evidence suggests that local impact of astrocytes on single synapses translates into global modulation of neuronal networks and behavior. We discuss these findings in the context of current conceptual models of sleep generation and function, each of which have historically focused on neural mechanisms. We highlight the implications and the challenges introduced by these results from a conceptual and computational perspective. We further provide modeling directions on how these data might extend our knowledge of astrocytic properties and sleep function. Given our evolving understanding of how local cellular activities during sleep lead to functional outcomes for the brain, further mechanistic and theoretical understanding of astrocytic contribution to these dynamics will undoubtedly be of great basic and translational benefit.

  20. Noise-Reduction Circuit For Imaging Photodetectors

    Science.gov (United States)

    Ramirez, Luis J.; Pain, Bedabrata; Staller, Craig; Hickok, Roger W.

    1995-01-01

    Developmental correlated-triple-sampling circuit suppresses capacitor reset noise and attenuates low frequency noise in integrated-and-sampled circuits of multiplexed photodiode arrays. Noise reduction circuit part of Visible and Infrared Mapping Spectrometer (VIMS) instrument to fly aboard Cassini spacecraft to explore Saturn and its moons. Modified versions of circuit also useful for reducing noise in terrestrial photosensor instruments.

  1. Multi-Layer E-Textile Circuits

    Science.gov (United States)

    Dunne, Lucy E.; Bibeau, Kaila; Mulligan, Lucie; Frith, Ashton; Simon, Cory

    2012-01-01

    Stitched e-textile circuits facilitate wearable, flexible, comfortable wearable technology. However, while stitched methods of e-textile circuits are common, multi-layer circuit creation remains a challenge. Here, we present methods of stitched multi-layer circuit creation using accessible tools and techniques.

  2. The neural basis of the speed-accuracy tradeoff

    NARCIS (Netherlands)

    Bogacz, R.; Wagenmakers, E.J.; Forstmann, B.U.; Nieuwenhuis, S.

    2010-01-01

    In many situations, decision makers need to negotiate between the competing demands of response speed and response accuracy, a dilemma generally known as the speed-accuracy tradeoff (SAT). Despite the ubiquity of SAT, the question of how neural decision circuits implement SAT has received little

  3. [Neural repair].

    Science.gov (United States)

    Kitada, Masaaki; Dezawa, Mari

    2008-05-01

    Recent progress of stem cell biology gives us the hope for neural repair. We have established methods to specifically induce functional Schwann cells and neurons from bone marrow stromal cells (MSCs). The effectiveness of these induced cells was evaluated by grafting them either into peripheral nerve injury, spinal cord injury, or Parkinson' s disease animal models. MSCs-derived Schwann cells supported axonal regeneration and re-constructed myelin to facilitate the functional recovery in peripheral and spinal cord injury. MSCs-derived dopaminergic neurons integrated into host striatum and contributed to behavioral repair. In this review, we introduce the differentiation potential of MSCs and finally discuss about their benefits and drawbacks of these induction systems for cell-based therapy in neuro-traumatic and neuro-degenerative diseases.

  4. Automated Cell Synthesis of Analog Integrated Circuit Layout Anasyn.

    Science.gov (United States)

    Stanojevich, Bob Srbislav

    This thesis describes a novel model to automate cell generation for the design of analog integrated circuits and the conclusions about important features that such automation should include. This research represents the first attempt to address this problem by analyzing relevant issues of what constitutes an analog cell and how a technique can be implemented to generate these cells automatically. Our motivation for doing this is the critical limitations to circuit performance which arise from cell design. This thesis defines unique construction properties for the layout of some commonly used analog circuit topologies or cells. This thesis defines the physical layout of analog circuit cells beyond simple geometrical description. Each cell is an independent object that can be interfaced and communicated with. This thesis has extended the concept of an analog cell even further by incorporating synthesis rules into the cell definition. These rules are used to dynamically construct the optimized layout that will satisfy many of the options encountered in actual analog circuit design such as area, matching, tolerance, element rationing and parasitic components. This model can construct complex geometric shapes such as common-centroids, waffles, interdigitated, cascode etc. that are optimized at device level with the precise models for parasitic components. Furthermore, Object-Oriented implementation used in this thesis allow for easy integration of this work into other CAD tools. To demonstrate the feasibility and correctness of the ideas described in this thesis, a CAD tool ANASYN has been written. To test and demonstrate the utility and the performance developed, a variety of test cells have been generated. Data presented clearly demonstrate the uniqueness, flexibility, and precision of the analog circuit layout cells implemented in this research thesis. In addition, one test chip and one design chip have been laid out using cells generated by ANASYN and fabricated at

  5. Neonatal ghrelin programs development of hypothalamic feeding circuits

    Science.gov (United States)

    Steculorum, Sophie M.; Collden, Gustav; Coupe, Berengere; Croizier, Sophie; Lockie, Sarah; Andrews, Zane B.; Jarosch, Florian; Klussmann, Sven; Bouret, Sebastien G.

    2015-01-01

    A complex neural network regulates body weight and energy balance, and dysfunction in the communication between the gut and this neural network is associated with metabolic diseases, such as obesity. The stomach-derived hormone ghrelin stimulates appetite through interactions with neurons in the arcuate nucleus of the hypothalamus (ARH). Here, we evaluated the physiological and neurobiological contribution of ghrelin during development by specifically blocking ghrelin action during early postnatal development in mice. Ghrelin blockade in neonatal mice resulted in enhanced ARH neural projections and long-term metabolic effects, including increased body weight, visceral fat, and blood glucose levels and decreased leptin sensitivity. In addition, chronic administration of ghrelin during postnatal life impaired the normal development of ARH projections and caused metabolic dysfunction. Consistent with these observations, direct exposure of postnatal ARH neuronal explants to ghrelin blunted axonal growth and blocked the neurotrophic effect of the adipocyte-derived hormone leptin. Moreover, chronic ghrelin exposure in neonatal mice also attenuated leptin-induced STAT3 signaling in ARH neurons. Collectively, these data reveal that ghrelin plays an inhibitory role in the development of hypothalamic neural circuits and suggest that proper expression of ghrelin during neonatal life is pivotal for lifelong metabolic regulation. PMID:25607843

  6. Bioluminescent bioreporter integrated circuits (BBICs)

    Science.gov (United States)

    Simpson, Michael L.; Sayler, Gary S.; Nivens, David; Ripp, Steve; Paulus, Michael J.; Jellison, Gerald E.

    1998-07-01

    As the workhorse of the integrated circuit (IC) industry, the capabilities of CMOS have been expanded well beyond the original applications. The full spectrum of analog circuits from switched-capacitor filters to microwave circuit blocks, and from general-purpose operational amplifiers to sub- nanosecond analog timing circuits for nuclear physics experiments have been implemented in CMOS. This technology has also made in-roads into the growing area of monolithic sensors with devices such as active-pixel sensors and other electro-optical detection devices. While many of the processes used for MEMS fabrication are not compatible with the CMOS IC process, depositing a sensor material onto a previously fabricated CMOS circuit can create a very useful category of sensors. In this work we report a chemical sensor composed of bioluminescent bioreporters (genetically engineered bacteria) deposited onto a micro-luminometer fabricated in a standard CMOS IC process. The bioreporter used for this work emitted 490-nm light when exposed to toluene. This luminescence was detected by the micro- luminometer giving an indication of the concentration of toluene. Other bioluminescent bioreporters sensitive to explosives, mercury, and other organic chemicals and heavy metals have been reported. These could be incorporated (individually or in combination) with the micro-luminometer reported here to form a variety of chemical sensors.

  7. Circuits regulating pleasure and happiness in major depression.

    Science.gov (United States)

    Loonen, A J M; Ivanova, S A

    2016-02-01

    The introduction of selective serotonin reuptake inhibitors has gradually changed the borders of the major depression disease class. Anhedonia was considered a cardinal symptom of endogenous depression, but the potential of selective serotonin reuptake inhibitors to treat anxiety disorders has increased the relevance of stress-induced morbidity. This shift has led to an important heterogeneity of current major depressive disorder. The complexity can be disentangled by postulating the existence of two different but mutually interacting neuronal circuits regulating the intensity of anhedonia (lack of pleasure) and dysphoria (lack of happiness). These circuits are functionally dominated by partly closed limbic (regulating misery-fleeing behaviour) and extrapyramidal (regulating reward-seeking behaviour) cortico-striato-thalamo-cortical (CSTC) circuits. The re-entry circuits include the shell and core parts of the accumbens nucleus, respectively. Pleasure can be considered to result from finding relief from the hypermotivation to exhibit rewarding behaviour, and happiness from finding relief from negative or conflicting circumstances. Hyperactivity of the extrapyramidal CSTC circuit results in craving, whereas hyperactivity of the limbic system results in dysphoria. Copyright © 2015 The Authors. Published by Elsevier Ltd.. All rights reserved.

  8. Architecture Analysis of an FPGA-Based Hopfield Neural Network

    Directory of Open Access Journals (Sweden)

    Miguel Angelo de Abreu de Sousa

    2014-01-01

    Full Text Available Interconnections between electronic circuits and neural computation have been a strongly researched topic in the machine learning field in order to approach several practical requirements, including decreasing training and operation times in high performance applications and reducing cost, size, and energy consumption for autonomous or embedded developments. Field programmable gate array (FPGA hardware shows some inherent features typically associated with neural networks, such as, parallel processing, modular executions, and dynamic adaptation, and works on different types of FPGA-based neural networks were presented in recent years. This paper aims to address different aspects of architectural characteristics analysis on a Hopfield Neural Network implemented in FPGA, such as maximum operating frequency and chip-area occupancy according to the network capacity. Also, the FPGA implementation methodology, which does not employ multipliers in the architecture developed for the Hopfield neural model, is presented, in detail.

  9. Instrumentation and test gear circuits manual

    CERN Document Server

    Marston, R M

    2013-01-01

    Instrumentation and Test Gear Circuits Manual provides diagrams, graphs, tables, and discussions of several types of practical circuits. The practical circuits covered in this book include attenuators, bridges, scope trace doublers, timebases, and digital frequency meters. Chapter 1 discusses the basic instrumentation and test gear principles. Chapter 2 deals with the design of passive attenuators, and Chapter 3 with passive and active filter circuits. The subsequent chapters tackle 'bridge' circuits, analogue and digital metering techniques and circuitry, signal and waveform generation, and p

  10. Mapping sensory circuits by anterograde trans-synaptic transfer of recombinant rabies virus

    Science.gov (United States)

    Zampieri, Niccolò; Jessell, Thomas M.; Murray, Andrew J.

    2014-01-01

    Summary Primary sensory neurons convey information from the external world to relay circuits within the central nervous system (CNS), but the identity and organization of the neurons that process incoming sensory information remains sketchy. Within the CNS viral tracing techniques that rely on retrograde trans-synaptic transfer provide a powerful tool for delineating circuit organization. Viral tracing of the circuits engaged by primary sensory neurons has, however, been hampered by the absence of a genetically tractable anterograde transfer system. In this study we demonstrate that rabies virus can infect sensory neurons in the somatosensory system, is subject to anterograde trans-synaptic transfer from primary sensory to spinal target neurons, and can delineate output connectivity with third-order neurons. Anterograde trans-synaptic transfer is a feature shared by other classes of primary sensory neurons, permitting the identification and potentially the manipulation of neural circuits processing sensory feedback within the mammalian CNS. PMID:24486087

  11. SMN is required for sensory-motor circuit function in Drosophila

    Science.gov (United States)

    Imlach, Wendy L.; Beck, Erin S.; Choi, Ben Jiwon; Lotti, Francesco; Pellizzoni, Livio; McCabe, Brian D.

    2012-01-01

    Summary Spinal muscular atrophy (SMA) is a lethal human disease characterized by motor neuron dysfunction and muscle deterioration due to depletion of the ubiquitous Survival Motor Neuron (SMN) protein. Drosophila SMN mutants have reduced muscle size and defective locomotion, motor rhythm and motor neuron neurotransmission. Unexpectedly, restoration of SMN in either muscles or motor neurons did not alter these phenotypes. Instead, SMN must be expressed in proprioceptive neurons and interneurons in the motor circuit to non-autonomously correct defects in motor neurons and muscles. SMN depletion disrupts the motor system subsequent to circuit development and can be mimicked by the inhibition of motor network function. Furthermore, increasing motor circuit excitability by genetic or pharmacological inhibition of K+ channels can correct SMN-dependent phenotypes. These results establish sensory-motor circuit dysfunction as the origin of motor system deficits in this SMA model and suggest that enhancement of motor neural network activity could ameliorate the disease. PMID:23063130

  12. 30 CFR 75.800 - High-voltage circuits; circuit breakers.

    Science.gov (United States)

    2010-07-01

    ... 30 Mineral Resources 1 2010-07-01 2010-07-01 false High-voltage circuits; circuit breakers. 75.800... SAFETY AND HEALTH MANDATORY SAFETY STANDARDS-UNDERGROUND COAL MINES Underground High-Voltage Distribution § 75.800 High-voltage circuits; circuit breakers. High-voltage circuits entering the underground area...

  13. Abnormal neural activation patterns underlying working memory impairment in chronic phencyclidine-treated mice.

    Directory of Open Access Journals (Sweden)

    Yosefu Arime

    Full Text Available Working memory impairment is a hallmark feature of schizophrenia and is thought be caused by dysfunctions in the prefrontal cortex (PFC and associated brain regions. However, the neural circuit anomalies underlying this impairment are poorly understood. The aim of this study is to assess working memory performance in the chronic phencyclidine (PCP mouse model of schizophrenia, and to identify the neural substrates of working memory. To address this issue, we conducted the following experiments for mice after withdrawal from chronic administration (14 days of either saline or PCP (10 mg/kg: (1 a discrete paired-trial variable-delay task in T-maze to assess working memory, and (2 brain-wide c-Fos mapping to identify activated brain regions relevant to this task performance either 90 min or 0 min after the completion of the task, with each time point examined under working memory effort and basal conditions. Correct responses in the test phase of the task were significantly reduced across delays (5, 15, and 30 s in chronic PCP-treated mice compared with chronic saline-treated controls, suggesting delay-independent impairments in working memory in the PCP group. In layer 2-3 of the prelimbic cortex, the number of working memory effort-elicited c-Fos+ cells was significantly higher in the chronic PCP group than in the chronic saline group. The main effect of working memory effort relative to basal conditions was to induce significantly increased c-Fos+ cells in the other layers of prelimbic cortex and the anterior cingulate and infralimbic cortex regardless of the different chronic regimens. Conversely, this working memory effort had a negative effect (fewer c-Fos+ cells in the ventral hippocampus. These results shed light on some putative neural networks relevant to working memory impairments in mice chronically treated with PCP, and emphasize the importance of the layer 2-3 of the prelimbic cortex of the PFC.

  14. Abnormal neural activation patterns underlying working memory impairment in chronic phencyclidine-treated mice.

    Science.gov (United States)

    Arime, Yosefu; Akiyama, Kazufumi

    2017-01-01

    Working memory impairment is a hallmark feature of schizophrenia and is thought be caused by dysfunctions in the prefrontal cortex (PFC) and associated brain regions. However, the neural circuit anomalies underlying this impairment are poorly understood. The aim of this study is to assess working memory performance in the chronic phencyclidine (PCP) mouse model of schizophrenia, and to identify the neural substrates of working memory. To address this issue, we conducted the following experiments for mice after withdrawal from chronic administration (14 days) of either saline or PCP (10 mg/kg): (1) a discrete paired-trial variable-delay task in T-maze to assess working memory, and (2) brain-wide c-Fos mapping to identify activated brain regions relevant to this task performance either 90 min or 0 min after the completion of the task, with each time point examined under working memory effort and basal conditions. Correct responses in the test phase of the task were significantly reduced across delays (5, 15, and 30 s) in chronic PCP-treated mice compared with chronic saline-treated controls, suggesting delay-independent impairments in working memory in the PCP group. In layer 2-3 of the prelimbic cortex, the number of working memory effort-elicited c-Fos+ cells was significantly higher in the chronic PCP group than in the chronic saline group. The main effect of working memory effort relative to basal conditions was to induce significantly increased c-Fos+ cells in the other layers of prelimbic cortex and the anterior cingulate and infralimbic cortex regardless of the different chronic regimens. Conversely, this working memory effort had a negative effect (fewer c-Fos+ cells) in the ventral hippocampus. These results shed light on some putative neural networks relevant to working memory impairments in mice chronically treated with PCP, and emphasize the importance of the layer 2-3 of the prelimbic cortex of the PFC.

  15. Neural substrates of the interaction of emotional stimulus processing and motor inhibitory control: an emotional linguistic go/no-go fMRI study.

    Science.gov (United States)

    Goldstein, Martin; Brendel, Gary; Tuescher, Oliver; Pan, Hong; Epstein, Jane; Beutel, Manfred; Yang, Yihong; Thomas, Katherine; Levy, Kenneth; Silverman, Michael; Clarkin, Jonathon; Posner, Michael; Kernberg, Otto; Stern, Emily; Silbersweig, David

    2007-07-01

    Neural substrates of behavioral inhibitory control have been probed in a variety of animal model, physiologic, behavioral, and imaging studies, many emphasizing the role of prefrontal circuits. Likewise, the neurocircuitry of emotion has been investigated from a variety of perspectives. Recently, neural mechanisms mediating the interaction of emotion and behavioral regulation have become the focus of intense study. To further define neurocircuitry specifically underlying the interaction between emotional processing and response inhibition, we developed an emotional linguistic go/no-go fMRI paradigm with a factorial block design which joins explicit inhibitory task demand (i.e., go or no-go) with task-unrelated incidental emotional stimulus valence manipulation, to probe the modulation of the former by the latter. In this study of normal subjects focusing on negative emotional processing, we hypothesized activity changes in specific frontal neocortical and limbic regions reflecting modulation of response inhibition by negative stimulus processing. We observed common fronto-limbic activations (including orbitofrontal cortical and amygdalar components) associated with the interaction of emotional stimulus processing and response suppression. Further, we found a distributed cortico-limbic network to be a candidate neural substrate for the interaction of negative valence-specific processing and inhibitory task demand. These findings have implications for elucidating neural mechanisms of emotional modulation of behavioral control, with relevance to a variety of neuropsychiatric disease states marked by behavioral dysregulation within the context of negative emotional processing.

  16. Medical image analysis with artificial neural networks.

    Science.gov (United States)

    Jiang, J; Trundle, P; Ren, J

    2010-12-01

    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. Copyright © 2010 Elsevier Ltd. All rights reserved.

  17. Neural plasticity in pancreatitis and pancreatic cancer.

    Science.gov (United States)

    Demir, Ihsan Ekin; Friess, Helmut; Ceyhan, Güralp O

    2015-11-01

    Pancreatic nerves undergo prominent alterations during the evolution and progression of human chronic pancreatitis and pancreatic cancer. Intrapancreatic nerves increase in size (neural hypertrophy) and number (increased neural density). The proportion of autonomic and sensory fibres (neural remodelling) is switched, and are infiltrated by perineural inflammatory cells (pancreatic neuritis) or invaded by pancreatic cancer cells (neural invasion). These neuropathic alterations also correlate with neuropathic pain. Instead of being mere histopathological manifestations of disease progression, pancreatic neural plasticity synergizes with the enhanced excitability of sensory neurons, with Schwann cell recruitment toward cancer and with central nervous system alterations. These alterations maintain a bidirectional interaction between nerves and non-neural pancreatic cells, as demonstrated by tissue and neural damage inducing neuropathic pain, and activated neurons releasing mediators that modulate inflammation and cancer growth. Owing to the prognostic effects of pain and neural invasion in pancreatic cancer, dissecting the mechanism of pancreatic neuroplasticity holds major translational relevance. However, current in vivo models of pancreatic cancer and chronic pancreatitis contain many discrepancies from human disease that overshadow their translational value. The present Review discusses novel possibilities for mechanistically uncovering the role of the nervous system in pancreatic disease progression.

  18. Circuit modeling for electromagnetic compatibility

    CERN Document Server

    Darney, Ian B

    2013-01-01

    Very simply, electromagnetic interference (EMI) costs money, reduces profits, and generally wreaks havoc for circuit designers in all industries. This book shows how the analytic tools of circuit theory can be used to simulate the coupling of interference into, and out of, any signal link in the system being reviewed. The technique is simple, systematic and accurate. It enables the design of any equipment to be tailored to meet EMC requirements. Every electronic system consists of a number of functional modules interconnected by signal links and power supply lines. Electromagnetic interference

  19. Embedded systems circuits and programming

    CERN Document Server

    Sanchez, Julio

    2012-01-01

    During the development of an engineered product, developers often need to create an embedded system--a prototype--that demonstrates the operation/function of the device and proves its viability. Offering practical tools for the development and prototyping phases, Embedded Systems Circuits and Programming provides a tutorial on microcontroller programming and the basics of embedded design. The book focuses on several development tools and resources: Standard and off-the-shelf components, such as input/output devices, integrated circuits, motors, and programmable microcontrollers The implementat

  20. Simplified design of filter circuits

    CERN Document Server

    Lenk, John

    1999-01-01

    Simplified Design of Filter Circuits, the eighth book in this popular series, is a step-by-step guide to designing filters using off-the-shelf ICs. The book starts with the basic operating principles of filters and common applications, then moves on to describe how to design circuits by using and modifying chips available on the market today. Lenk's emphasis is on practical, simplified approaches to solving design problems.Contains practical designs using off-the-shelf ICsStraightforward, no-nonsense approachHighly illustrated with manufacturer's data sheets

  1. Programming languages for circuit design.

    Science.gov (United States)

    Pedersen, Michael; Yordanov, Boyan

    2015-01-01

    This chapter provides an overview of a programming language for Genetic Engineering of Cells (GEC). A GEC program specifies a genetic circuit at a high level of abstraction through constraints on otherwise unspecified DNA parts. The GEC compiler then selects parts which satisfy the constraints from a given parts database. GEC further provides more conventional programming language constructs for abstraction, e.g., through modularity. The GEC language and compiler is available through a Web tool which also provides functionality, e.g., for simulation of designed circuits.

  2. Brains--Computers--Machines: Neural Engineering in Science Classrooms

    Science.gov (United States)

    Chudler, Eric H.; Bergsman, Kristen Clapper

    2016-01-01

    Neural engineering is an emerging field of high relevance to students, teachers, and the general public. This feature presents online resources that educators and scientists can use to introduce students to neural engineering and to integrate core ideas from the life sciences, physical sciences, social sciences, computer science, and engineering…

  3. Neural evidence for cultural differences in the valuation of positive facial expressions.

    Science.gov (United States)

    Park, BoKyung; Tsai, Jeanne L; Chim, Louise; Blevins, Elizabeth; Knutson, Brian

    2016-02-01

    European Americans value excitement more and calm less than Chinese. Within cultures, European Americans value excited and calm states similarly, whereas Chinese value calm more than excited states. To examine how these cultural differences influence people's immediate responses to excited vs calm facial expressions, we combined a facial rating task with functional magnetic resonance imaging. During scanning, European American (n = 19) and Chinese (n = 19) females viewed and rated faces that varied by expression (excited, calm), ethnicity (White, Asian) and gender (male, female). As predicted, European Americans showed greater activity in circuits associated with affect and reward (bilateral ventral striatum, left caudate) while viewing excited vs calm expressions than did Chinese. Within cultures, European Americans responded to excited vs calm expressions similarly, whereas Chinese showed greater activity in these circuits in response to calm vs excited expressions regardless of targets' ethnicity or gender. Across cultural groups, greater ventral striatal activity while viewing excited vs. calm expressions predicted greater preference for excited vs calm expressions months later. These findings provide neural evidence that people find viewing the specific positive facial expressions valued by their cultures to be rewarding and relevant. © The Author (2015). Published by Oxford University Press. For Permissions, please email: journals.permissions@oup.com.

  4. Relevance Matrices in LVQ

    NARCIS (Netherlands)

    Schneider, Petra; Biehl, Michael; Hammer, Barbara; Verleysen, Michel

    2007-01-01

    We propose a new matrix learning scheme to extend Generalized Relevance Learning Vector Quantization (GRLVQ). By introducing a full matrix of relevance factors in the distance measure, correlations between different features and their importance for the classification scheme can be taken into

  5. Seeding neural progenitor cells on silicon-based neural probes.

    Science.gov (United States)

    Azemi, Erdrin; Gobbel, Glenn T; Cui, Xinyan Tracy

    2010-09-01

    Chronically implanted neural electrode arrays have the potential to be used as neural prostheses in patients with various neurological disorders. While these electrodes perform well in acute recordings, they often fail to function reliably in clinically relevant chronic settings because of glial encapsulation and the loss of neurons. Surface modification of these implants may provide a means of improving their biocompatibility and integration within host brain tissue. The authors proposed a method of improving the brain-implant interface by seeding the implant's surface with a layer of neural progenitor cells (NPCs) derived from adult murine subependyma. Neural progenitor cells may reduce the foreign body reaction by presenting a tissue-friendly surface and repair implant-induced injury and inflammation by releasing neurotrophic factors. In this study, the authors evaluated the growth and differentiation of NPCs on laminin-immobilized probe surfaces and explored the potential impact on transplant survival of these cells. Laminin protein was successfully immobilized on the silicon surface via covalent binding using silane chemistry. The growth, adhesion, and differentiation of NPCs expressing green fluorescent protein (GFP) on laminin-modified silicon surfaces were characterized in vitro by using immunocytochemical techniques. Shear forces were applied to NPC cultures in growth medium to evaluate their shearing properties. In addition, neural probes seeded with GFP-labeled NPCs cultured in growth medium for 14 days were implanted in murine cortex. The authors assessed the adhesion properties of these cells during implantation conditions. Moreover, the tissue response around NPC-seeded implants was observed after 1 and 7 days postimplantation. Significantly improved NPC attachment and growth was found on the laminin-immobilized surface compared with an unmodified control before and after shear force application. The NPCs grown on the laminin-immobilized surface

  6. Complex-valued Neural Networks

    Science.gov (United States)

    Hirose, Akira

    This paper reviews the features and applications of complex-valued neural networks (CVNNs). First we list the present application fields, and describe the advantages of the CVNNs in two application examples, namely, an adaptive plastic-landmine visualization system and an optical frequency-domain-multiplexed learning logic circuit. Then we briefly discuss the features of complex number itself to find that the phase rotation is the most significant concept, which is very useful in processing the information related to wave phenomena such as lightwave and electromagnetic wave. The CVNNs will also be an indispensable framework of the future microelectronic information-processing hardware where the quantum electron wave plays the principal role.

  7. Short-Circuit Characterization of 10 kV 10A 4H-SiC MOSFET

    DEFF Research Database (Denmark)

    Eni, Emanuel-Petre; Beczkowski, Szymon; Munk-Nielsen, Stig

    2016-01-01

    The short-circuit capability of a power device is highly relevant for converter design and fault protection. In this paper a 10kV 10A 4H-SiC MOSFET is characterized and its short circuit withstand capability is studied and analyzed at 6 kV DC-link voltage. The test setup for this study is also in...

  8. Integrated Circuit Stellar Magnitude Simulator

    Science.gov (United States)

    Blackburn, James A.

    1978-01-01

    Describes an electronic circuit which can be used to demonstrate the stellar magnitude scale. Six rectangular light-emitting diodes with independently adjustable duty cycles represent stars of magnitudes 1 through 6. Experimentally verifies the logarithmic response of the eye. (Author/GA)

  9. A Low Noise Electronic Circuit

    NARCIS (Netherlands)

    Annema, Anne J.; Leenaerts, Dominicus M.W.; de Vreede, Petrus W.H.

    2002-01-01

    An electronic circuit, which can be used as a Low Noise Amplifier (LNA), comprises two complementary Field Effect Transistors (M1, M2; M5, M6), each having a gate, a source and a drain. The gates are connected together as a common input terminal, and the drains are connected together as a

  10. Invention of the Integrated Circuit

    Indian Academy of Sciences (India)

    Home; Journals; Resonance – Journal of Science Education; Volume 17; Issue 11. Invention of the Integrated Circuit. Jack S Kilby. Classics Volume 17 Issue 11 November 2012 pp 1100-1115. Fulltext. Click here to view fulltext PDF. Permanent link: http://www.ias.ac.in/article/fulltext/reso/017/11/1100-1115 ...

  11. Development of CMOS integrated circuits

    Science.gov (United States)

    Bertino, F.; Feller, A.; Greenhouse, J.; Lombardi, T.; Merriam, A.; Noto, R.; Ozga, S.; Pryor, R.; Ramondetta, P.; Smith, A.

    1979-01-01

    Report documents life cycles of two custom CMOS integrated circuits: (1) 4-bit multiplexed register with shift left and shift right capabilities, and (2) dual 4-bit registers. Cycles described include conception as logic diagrams through design, fabrication, testing, and delivery.

  12. Data assimilation with Chua's circuit

    Indian Academy of Sciences (India)

    noise and observational frequency, using both simulated observations and data obtained from an experimental realization of a commonly used low-dimensional dynamical system, namely, Chua circuit, in both the periodic as well as the chaotic regime. Keywords. Synchronization; ensemble Kalman filter; data assimilation.

  13. Circuit design for RF transceivers

    CERN Document Server

    Leenaerts, Domine; Vaucher, Cicero S

    2007-01-01

    Second edition of this successful 2001 RF Circuit Design book, has been updated, latest technology reviews have been added as well as several actual case studies. Due to the authors being active in industry as well as academia, this should prove to be an essential guide on RF Transceiver Design for students and engineers.

  14. Parallel circuit simulation on supercomputers

    Energy Technology Data Exchange (ETDEWEB)

    Saleh, R.A.; Gallivan, K.A. (Illinois Univ., Urbana, IL (USA). Center for Supercomputing Research and Development); Chang, M.C. (Texas Instruments, Inc., Dallas, TX (USA)); Hajj, I.N.; Trick, T.N. (Illinois Univ., Urbana, IL (USA). Coordinated Science Lab.); Smart, D. (Semiconductor Div., Analog Devices, Wilmington, MA (US))

    1989-12-01

    Circuit simulation is a very time-consuming and numerically intensive application, especially when the problem size is large as in the case of VLSI circuits. To improve the performance of circuit simulators without sacrificing accuracy, a variety of parallel processing algorithms have been investigated due to the recent availability of a number of commercial multiprocessor machines. In this paper, research in the field of parallel circuit simulation is surveyed and the ongoing research in this area at the University of Illinois is described. Both standard and relaxation-based approaches are considered. In particular, the forms of parallelism available within the direct method approach, used in programs such as SPICE2 and SLATE, and within the relaxation-based approaches, such as waveform relaxation, iterated timing analysis, and waveform-relaxation-Newton, are described. The specific implementation issues addressed here are primarily related to general-purpose multiprocessors with a shared-memory architecture having a limited number of processors, although many of the comments also apply to a number of other architectures.

  15. Designing analog circuits in CMOS

    NARCIS (Netherlands)

    Annema, Anne J.; Nauta, Bram; van Langevelde, Ronald; Tuinhout, Hans

    2004-01-01

    The evolution in CMOS technology dictated by Moore's Law is clearly beneficial for designers of digital circuits, but it presents difficult challenges, such as lowered nominal supply voltages, for their peers in the analog world who want to keep pace with this rapid progression. This article

  16. Clocking Scheme for Switched-Capacitor Circuits

    DEFF Research Database (Denmark)

    Steensgaard-Madsen, Jesper

    1998-01-01

    A novel clocking scheme for switched-capacitor (SC) circuits is presented. It can enhance the understanding of SC circuits and the errors caused by MOSFET (MOS) switches. Charge errors, and techniques to make SC circuits less sensitive to them are discussed.......A novel clocking scheme for switched-capacitor (SC) circuits is presented. It can enhance the understanding of SC circuits and the errors caused by MOSFET (MOS) switches. Charge errors, and techniques to make SC circuits less sensitive to them are discussed....

  17. Advanced circuit simulation using Multisim workbench

    CERN Document Server

    Báez-López, David; Cervantes-Villagómez, Ofelia Delfina

    2012-01-01

    Multisim is now the de facto standard for circuit simulation. It is a SPICE-based circuit simulator which combines analog, discrete-time, and mixed-mode circuits. In addition, it is the only simulator which incorporates microcontroller simulation in the same environment. It also includes a tool for printed circuit board design.Advanced Circuit Simulation Using Multisim Workbench is a companion book to Circuit Analysis Using Multisim, published by Morgan & Claypool in 2011. This new book covers advanced analyses and the creation of models and subcircuits. It also includes coverage of transmissi

  18. Digital circuit boards mach 1 GHz

    CERN Document Server

    Morrison, Ralph

    2012-01-01

    A unique, practical approach to the design of high-speed digital circuit boards The demand for ever-faster digital circuit designs is beginning to render the circuit theory used by engineers ineffective. Digital Circuit Boards presents an alternative to the circuit theory approach, emphasizing energy flow rather than just signal interconnection to explain logic circuit behavior. The book shows how treating design in terms of transmission lines will ensure that the logic will function, addressing both storage and movement of electrical energy on these lines. It cove

  19. High performance integer arithmetic circuit design on FPGA architecture, implementation and design automation

    CERN Document Server

    Palchaudhuri, Ayan

    2016-01-01

    This book describes the optimized implementations of several arithmetic datapath, controlpath and pseudorandom sequence generator circuits for realization of high performance arithmetic circuits targeted towards a specific family of the high-end Field Programmable Gate Arrays (FPGAs). It explores regular, modular, cascadable, and bit-sliced architectures of these circuits, by directly instantiating the target FPGA-specific primitives in the HDL. Every proposed architecture is justified with detailed mathematical analyses. Simultaneously, constrained placement of the circuit building blocks is performed, by placing the logically related hardware primitives in close proximity to one another by supplying relevant placement constraints in the Xilinx proprietary “User Constraints File”. The book covers the implementation of a GUI-based CAD tool named FlexiCore integrated with the Xilinx Integrated Software Environment (ISE) for design automation of platform-specific high-performance arithmetic circuits from us...

  20. Behavioral and neural plasticity caused by early social experiences: the case of the honeybee

    Directory of Open Access Journals (Sweden)

    Andrés eArenas

    2013-08-01

    Full Text Available Cognitive experiences during the early stages of life play an important role in shaping future behavior. Behavioral and neural long-term changes after early sensory and associative experiences have been recently reported in the honeybee. This invertebrate is an excellent model for assessing the role of precocious experiences on later behavior due to its extraordinarily tuned division of labor based on age polyethism. These studies are mainly focused on the role and importance of experiences occurred during the first days of the adult lifespan, their impact on foraging decisions and their contribution to coordinate food gathering. Odor-rewarded experiences during the first days of honeybee adulthood alter the responsiveness to sucrose, making young hive bees more sensitive to assess gustatory features about the nectar brought back to the hive and affecting the dynamic of the food transfers and the propagation of food-related information within the colony as well. Early olfactory experiences lead to stable and long-term associative memories that can be successfully recalled after many days, even at foraging ages. Also they improve memorizing of new associative learning events later in life. The establishment of early memories promotes stable reorganization of the olfactory circuits inducing structural and functional changes in the antennal lobe. Early rewarded experiences have relevant consequences at the social level too, biasing dance and trophallaxis partner choice and affecting recruitment. Here, we revised recent results in bees´ physiology, behavior and sociobiology to depict how the early experiences affect their cognition abilities and neural-related circuits.