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Sample records for active neural circuits

  1. An Activity for Demonstrating the Concept of a Neural Circuit

    Kreiner, David S.

    2012-01-01

    College students in two sections of a general psychology course participated in a demonstration of a simple neural circuit. The activity was based on a neural circuit that Jeffress proposed for localizing sounds. Students in one section responded to a questionnaire prior to participating in the activity, while students in the other section…

  2. Genetic control of active neural circuits

    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.

  3. Tools for Resolving Functional Activity and Connectivity within Intact Neural Circuits

    Jennings, Joshua H.; Stuber, Garret D.

    2014-01-01

    Mammalian neural circuits are sophisticated biological systems that choreograph behavioral processes vital for survival. While the inherent complexity of discrete neural circuits has proven difficult to decipher, many parallel methodological developments promise to help delineate the function and connectivity of molecularly defined neural circuits. Here, we review recent technological advances designed to precisely monitor and manipulate neural circuit activity. We propose a holistic, multifa...

  4. Activity-dependent modulation of neural circuit synaptic connectivity

    Tessier, Charles R.; Kendal Broadie

    2009-01-01

    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 circ...

  5. Activity-dependent modulation of neural circuit synaptic connectivity

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

    Caleb Andrew Doll; Kendal eBroadie

    2014-01-01

    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 mechanism...

  7. Demultiplexer circuit for neural stimulation

    Wessendorf, Kurt O; Okandan, Murat; Pearson, Sean

    2012-10-09

    A demultiplexer circuit is disclosed which can be used with a conventional neural stimulator to extend the number of electrodes which can be activated. The demultiplexer circuit, which is formed on a semiconductor substrate containing a power supply that provides all the dc electrical power for operation of the circuit, includes digital latches that receive and store addressing information from the neural stimulator one bit at a time. This addressing information is used to program one or more 1:2.sup.N demultiplexers in the demultiplexer circuit which then route neural stimulation signals from the neural stimulator to an electrode array which is connected to the outputs of the 1:2.sup.N demultiplexer. The demultiplexer circuit allows the number of individual electrodes in the electrode array to be increased by a factor of 2.sup.N with N generally being in a range of 2-4.

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

    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. Auto-programmable impulse neural circuits

    Watula, D.; Meador, J.

    1990-01-01

    Impulse neural networks use pulse trains to communicate neuron activation levels. Impulse neural circuits emulate natural neurons at a more detailed level than that typically employed by contemporary neural network implementation methods. An impulse neural circuit which realizes short term memory dynamics is presented. The operation of that circuit is then characterized in terms of pulse frequency modulated signals. Both fixed and programmable synapse circuits for realizing long term memory are also described. The implementation of a simple and useful unsupervised learning law is then presented. The implementation of a differential Hebbian learning rule for a specific mean-frequency signal interpretation is shown to have a straightforward implementation using digital combinational logic with a variation of a previously developed programmable synapse circuit. This circuit is expected to be exploited for simple and straightforward implementation of future auto-adaptive neural circuits.

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

    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.

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

    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.

  12. Classes of feedforward neural networks and their circuit complexity

    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 well-studied hierarchy of boolean circuits. Results cover both classes of sigmoid activation function networks and linear threshold networks. This provides a much needed theoretical basis for the stu...

  13. Genetic dissection of GABAergic neural circuits in mouse neocortex

    Taniguchi, Hiroki

    2014-01-01

    Diverse and flexible cortical functions rely on the ability of neural circuits to perform multiple types of neuronal computations. GABAergic inhibitory interneurons significantly contribute to this task by regulating the balance of activity, synaptic integration, spiking, synchrony, and oscillation in a neural ensemble. GABAergic interneurons display a high degree of cellular diversity in morphology, physiology, connectivity, and gene expression. A considerable number of subtypes of GABAergic...

  14. Genetic dissection of GABAergic neural circuits in mouse neocortex

    Hiroki Taniguchi

    2014-01-01

    Diverse and flexible cortical functions rely on the ability of neural circuits to perform multiple types of neuronal computations. GABAergic inhibitory interneurons significantly contribute to this task by regulating the balance of activity, synaptic integration, spiking, synchrony, and oscillation in a neural ensemble. GABAergic interneruons display a high degree of cellular diversity in morphology, physiology, connectivity, and gene expression. A considerable number of subtypes of GABAer...

  15. Neurotrophin regulation of neural circuit development and function.

    Park, Hyungju; Poo, Mu-ming

    2013-01-01

    Brain-derived neurotrophic factor (BDNF)--a member of a small family of secreted proteins that includes nerve growth factor, neurotrophin 3 and neurotrophin 4--has emerged as a key regulator of neural circuit development and function. The expression, secretion and actions of BDNF are directly controlled by neural activity, and secreted BDNF is capable of mediating many activity-dependent processes in the mammalian brain, including neuronal differentiation and growth, synapse formation and plasticity, and higher cognitive functions. This Review summarizes some of the recent progress in understanding the cellular and molecular mechanisms underlying neurotrophin regulation of neural circuits. The focus of the article is on BDNF, as this is the most widely expressed and studied neurotrophin in the mammalian brain. PMID:23254191

  16. Electronic circuits modeling using artificial neural networks

    Andrejević Miona V.

    2003-01-01

    Full Text Available In this paper artificial neural networks (ANN are applied to modeling of electronic circuits. ANNs are used for application of the black-box modeling concept in the time domain. Modeling process is described, so the topology of the ANN, the testing signal used for excitation, together with the complexity of ANN are considered. The procedure is first exemplified in modeling of resistive circuits. MOS transistor, as a four-terminal device, is modeled. Then nonlinear negative resistive characteristic is modeled in order to be used as a piece-wise linear resistor in Chua's circuit. Examples of modeling nonlinear dynamic circuits are given encompassing a variety of modeling problems. A nonlinear circuit containing quartz oscillator is considered for modeling. Verification of the concept is performed by verifying the ability of the model to generalize i.e. to create acceptable responses to excitations not used during training. Implementation of these models within a behavioral simulator is exemplified. Every model is implemented in realistic surrounding in order to show its interaction, and of course, its usage and purpose.

  17. Tic disorders: neural circuits, neurochemistry, and neuroimmunology.

    Harris, Kendra; Singer, Harvey S

    2006-08-01

    The neuroanatomy and neurochemistry underlying tic disorders are thought to involve corticostriatothalamocortical circuits and dysregulation of their component neurotransmitter systems. Tourette syndrome is a tic disorder that begins in childhood and follows a waxing and waning course of tic severity. Although it is generally believed to have a genetic component, its etiology has not been fully elucidated. The clinical entity pediatric autoimmune neuropsychiatric disorders associated with streptococcal infection (PANDAS) has led some to suggest that the pathophysiology of tics in some individuals might involve a postinfectious autoimmune component. We review the neural circuits and neurochemistry of Tourette syndrome and evaluate the evidence for and against a role for autoimmunity in the expression of tics. PMID:16970869

  18. Stable chaos in fluctuation driven neural circuits

    Highlights: • Nonlinear instabilities in fluctuation driven (balanced) neural circuits are studied. • Balanced networks display chaos and stable phases at different post-synaptic widths. • Linear instabilities coexists with nonlinear ones in the chaotic regime. • Erratic motion appears also in linearly stable phase due to stable chaos. - Abstract: We study the dynamical stability of pulse coupled networks of leaky integrate-and-fire neurons against infinitesimal and finite perturbations. In particular, we compare mean versus fluctuations driven networks, the former (latter) is realized by considering purely excitatory (inhibitory) sparse neural circuits. In the excitatory case the instabilities of the system can be completely captured by an usual linear stability (Lyapunov) analysis, whereas the inhibitory networks can display the coexistence of linear and nonlinear instabilities. The nonlinear effects are associated to finite amplitude instabilities, which have been characterized in terms of suitable indicators. For inhibitory coupling one observes a transition from chaotic to non chaotic dynamics by decreasing the pulse-width. For sufficiently fast synapses the system, despite showing an erratic evolution, is linearly stable, thus representing a prototypical example of stable chaos

  19. Genetic dissection of GABAergic neural circuits in mouse neocortex

    Hiroki Taniguchi

    2014-01-01

    Full Text Available Diverse and flexible cortical functions rely on the ability of neural circuits to perform multiple types of neuronal computations. GABAergic inhibitory interneurons significantly contribute to this task by regulating the balance of activity, synaptic integration, spiking, synchrony, and oscillation in a neural ensemble. GABAergic interneruons display a high degree of cellular diversity in morphology, physiology, connectivity, and gene expression. A considerable number of subtypes of GABAergic interneurons diversify modes of cortical inhibition, enabling various types of information processing in the cortex. Thus, comprehensively understanding fate specification, circuit assembly and physiological function of GABAergic interneurons is a key to elucidate the principles of cortical wiring and function. Recent advances in genetically encoded molecular tools have made a breakthrough to systematically study cortical circuitry at the molecular, cellular, circuit, and whole animal levels. However, the biggest obstacle to fully applying the power of these to analysis of GABAergic circuits was that there were no efficient and reliable methods to express them in subtypes of GABAergic interneurons. Here, I first summarize cortical interneuron diversity and current understanding of mechanisms, by which distinct classes of GABAergic interneurons are generated. I then review recent development in genetically encoded molecular tools for neural circuit research, and genetic targeting of GABAergic interneuron subtypes, particulary focusing on our recent effort to develop and characterize Cre/CreER knockin lines. Finally, I highlight recent success in genetic targeting of chandelier cells (ChCs, the most unique and distinct GABAergic interneuron subtype, and discuss what kind of questions need to be addressed to understand development and function of cortical inhibitory circuits.

  20. Noise Delays Bifurcation in a Positively Coupled Neural Circuit

    Gutkin, Boris; Hely, Tim; Jost, Juergen

    2000-01-01

    We report a noise induced delay of bifurcation in a simple pulse-coupled neural circuit. We study the behavior of two neural oscillators, each individually governed by saddle-node dynamics, with reciprocal excitatory synaptic connections. In the deterministic circuit, the synaptic current amplitude acts as a control parameter to move the circuit from a mono-stable regime through a bifurcation into a bistable regime. In this regime stable sustained anti-phase oscillations in both neurons coexi...

  1. Grand Research Plan for Neural Circuits of Emotion and Memory-Current status of neural circuit studies in China

    Yuan-Gui Zhu; He-Qi Cao; Er-Dan Dong

    2013-01-01

    During recent years,major advances have been made in neuroscience,i.e.,asynchronous release,three-dimensional structural data sets,saliency maps,magnesium in brain research,and new functional roles of long non-coding RNAs.Especially,the development of optogenetic technology provides access to important information about relevant neural circuits by allowing the activation of specific neurons in awake mammals and directly observing the resulting behavior.The Grand Research Plan for Neural Circuits of Emotion and Memory was launched by the National Natural Science Foundation of China.It takes emotion and memory as its main objects,making the best use of cutting-edge technologies from medical science,life science and information science.In this paper,we outline the current status of neural circuit studies in China and the technologies and methodologies being applied,as well as studies related to the impairments of emotion and memory.In this phase,we are making efforts to repair the current deficiencies by making adjustments,mainly involving four aspects of core scientific issues to investigate these circuits at multiple levels.Five research directions have been taken to solve important scientific problems while the Grand Research Plan is implemented.Future research into this area will be multimodal,incorporating a range of methods and sciences into each project.Addressing these issues will ensure a bright future,major discoveries,and a higher level of treatment for all affected by debilitating brain illnesses.

  2. A neural circuit for angular velocity computation.

    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. PMID:21228902

  3. A neural circuit for angular velocity computation

    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.

  4. A neuromime system for neural circuit analysis.

    Mitchell, C E; Friesen, W O

    1981-01-01

    A system of electronic analog neurons (neuromimes) for modeling the activity in small neuronal networks is described. The system consists of sixteen analogs that simulate the integrative neuronal properties at the axon hillock and sixty-four analogs that serve to simulate synaptic interactions. The neuromime properties are based on a potential model incorporating the following properties: membrane potential, threshold, refractory period, adaptation, post-inhibitory rebound, accommodation and pacemaker potential. Use of matrix switch boards provides for convenient interconnection of the neuromime elements, allowing the construction of even complex circuits. PMID:7236753

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

    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...

  6. The neural circuit basis of learning

    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

  7. FUZZY NEURAL NETWORK FOR OBJECT IDENTIFICATION ON INTEGRATED CIRCUIT LAYOUTS

    Doudkin, A. A.

    2016-01-01

    Fuzzy neural network model based on neocognitron is proposed to identify layout objects on images of topological layers of integrated circuits. Testing of the model on images of real chip layouts was showed a highеr degree of identification of the proposed neural network in comparison to base neocognitron.

  8. Diagnostic Neural Network Systems for the Electronic Circuits

    Neural Networks is one of the most important artificial intelligent approaches for solving the diagnostic processes. This research concerns with uses the neural networks for diagnosis of the electronic circuits. Modern electronic systems contain both the analog and digital circuits. But, diagnosis of the analog circuits suffers from great complexity due to their nonlinearity. To overcome this problem, the proposed system introduces a diagnostic system that uses the neural network to diagnose both the digital and analog circuits. So, it can face the new requirements for the modern electronic systems. A fault dictionary method was implemented in the system. Experimental results are presented on three electronic systems. They are: artificial kidney, wireless network and personal computer systems. The proposed system has improved the performance of the diagnostic systems when applied for these practical cases

  9. Analog VLSI neural network integrated circuits

    Kub, F. J.; Moon, K. K.; Just, E. A.

    1991-01-01

    Two analog very large scale integration (VLSI) vector matrix multiplier integrated circuit chips were designed, fabricated, and partially tested. They can perform both vector-matrix and matrix-matrix multiplication operations at high speeds. The 32 by 32 vector-matrix multiplier chip and the 128 by 64 vector-matrix multiplier chip were designed to perform 300 million and 3 billion multiplications per second, respectively. An additional circuit that has been developed is a continuous-time adaptive learning circuit. The performance achieved thus far for this circuit is an adaptivity of 28 dB at 300 KHz and 11 dB at 15 MHz. This circuit has demonstrated greater than two orders of magnitude higher frequency of operation than any previous adaptive learning circuit.

  10. Genetic identification of a neural circuit that suppresses appetite.

    Carter, Matthew E; Soden, Marta E; Zweifel, Larry S; Palmiter, Richard D

    2013-11-01

    Appetite suppression occurs after a meal and in conditions when it is unfavourable to eat, such as during illness or exposure to toxins. A brain region proposed to play a role in appetite suppression is the parabrachial nucleus, a heterogeneous population of neurons surrounding the superior cerebellar peduncle in the brainstem. The parabrachial nucleus is thought to mediate the suppression of appetite induced by the anorectic hormones amylin and cholecystokinin, as well as by lithium chloride and lipopolysaccharide, compounds that mimic the effects of toxic foods and bacterial infections, respectively. Hyperactivity of the parabrachial nucleus is also thought to cause starvation after ablation of orexigenic agouti-related peptide neurons in adult mice. However, the identities of neurons in the parabrachial nucleus that regulate feeding are unknown, as are the functionally relevant downstream projections. Here we identify calcitonin gene-related peptide-expressing neurons in the outer external lateral subdivision of the parabrachial nucleus that project to the laterocapsular division of the central nucleus of the amygdala as forming a functionally important circuit for suppressing appetite. Using genetically encoded anatomical, optogenetic and pharmacogenetic tools, we demonstrate that activation of these neurons projecting to the central nucleus of the amygdala suppresses appetite. In contrast, inhibition of these neurons increases food intake in circumstances when mice do not normally eat and prevents starvation in adult mice whose agouti-related peptide neurons are ablated. Taken together, our data demonstrate that this neural circuit from the parabrachial nucleus to the central nucleus of the amygdala mediates appetite suppression in conditions when it is unfavourable to eat. This neural circuit may provide targets for therapeutic intervention to overcome or promote appetite. PMID:24121436

  11. Two-photon holographic optogenetics of neural circuits (Conference Presentation)

    Yang, Weijian; Carrillo-Reid, Luis; Peterka, Darcy S.; Yuste, Rafael

    2016-03-01

    Optical manipulation of in vivo neural circuits with cellular resolution could be important for understanding cortical function. Despite recent progress, simultaneous optogenetic activation with cellular precision has either been limited to 2D planes, or a very small numbers of neurons over a limited volume. Here we demonstrate a novel paradigm for simultaneous 3D activation using a low repetition rate pulse-amplified fiber laser system and a spatial light modulator (SLM) to project 3D holographic excitation patterns on the cortex of mice in vivo for targeted volumetric 3D photoactivation. This method is compatible with two-photon imaging, and enables the simultaneous activation of multiple cells in 3D, using red-shifted opsins, such as C1V1 or ReaChR, while simultaneously imaging GFP-based sensors such as GCaMP6. This all-optical imaging and 3D manipulation approach achieves simultaneous reading and writing of cortical activity, and should be a powerful tool for the study of neuronal circuits.

  12. Sleep quality and neural circuit function supporting emotion regulation

    Minkel Jared D

    2012-12-01

    Full Text Available Abstract Background Recent laboratory studies employing an extended sleep deprivation model have mapped sleep-related changes in behavior onto functional alterations in specific brain regions supporting emotion, suggesting possible biological mechanisms for an association between sleep difficulties and deficits in emotion regulation. However, it is not yet known if similar behavioral and neural changes are associated with the more modest variability in sleep observed in daily life. Methods We examined relationships between sleep and neural circuitry of emotion using the Pittsburgh Sleep Quality Index and fMRI data from a widely used emotion regulation task focusing on cognitive reappraisal of negative emotional stimuli in an unselected sample of 97 adult volunteers (48 women; mean age 42.78±7.37 years, range 30–54 years old. Results Emotion regulation was associated with greater activation in clusters located in the dorsomedial prefrontal cortex (dmPFC, left dorsolateral prefrontal cortex (dlPFC, and inferior parietal cortex. Only one subscale from the Pittsburgh Sleep Quality Index, use of sleep medications, was related to BOLD responses in the dmPFC and dlPFC during cognitive reappraisal. Use of sleep medications predicted lesser BOLD responses during reappraisal, but other aspects of sleep, including sleep duration and subjective sleep quality, were not related to neural activation in this paradigm. Conclusions The relatively modest variability in sleep that is common in the general community is unlikely to cause significant disruption in neural circuits supporting reactivity or regulation by cognitive reappraisal of negative emotion. Use of sleep medication however, may influence emotion regulation circuitry, but additional studies are necessary to determine if such use plays a causal role in altering emotional responses.

  13. Fully integrated circuit chip of microelectronic neural bridge

    Nerve tracts interruption is one of the major reasons for dysfunction after spiral cord injury. The microelectronic neural bridge is a method to restore function of interrupted neural pathways, by making use of microelectronic chips to bypass the injured nerve tracts. A low-power fully integrated microelectronic neural bridge chip is designed, using CSMC 0.5-μm CMOS technology. The structure and the key points in the circuit design will be introduced in detail. In order to meet the requirement for implantation, the circuit was modified to avoid the use of off-chip components, and fully monolithic integration is achieved. The operating voltage of the circuit is ±2.5 V, and the chip area is 1.21 × 1.18 mm2. According to the characteristic of neural signal, the time-domain method is used in testing. The pass bandwidth of the microelectronic neural bridge system covers the whole frequency range of the neural signal, power consumption is 4.33 mW, and the gain is adjustable. The design goals are achieved. (semiconductor integrated circuits)

  14. Synchrony and neural coding in cerebellar circuits

    Abigail L Person

    2012-12-01

    Full Text Available The cerebellum regulates complex movements and is also implicated in cognitive tasks, and cerebellar dysfunction is consequently associated not only with movement disorders, but also with conditions like autism and dyslexia. How information is encoded by specific cerebellar firing patterns remains debated, however. A central question is how the cerebellar cortex transmits its integrated output to the cerebellar nuclei via GABAergic synapses from Purkinje neurons. Possible answers come from accumulating evidence that subsets of Purkinje cells synchronize their firing during behaviors that require the cerebellum. Consistent with models predicting that coherent activity of inhibitory networks has the capacity to dictate firing patterns of target neurons, recent experimental work supports the idea that inhibitory synchrony may regulate the response of cerebellar nuclear cells to Purkinje inputs, owing to the interplay between unusually fast inhibitory synaptic responses and high rates of intrinsic activity. Data from multiple laboratories lead to a working hypothesis that synchronous inhibitory input from Purkinje cells can set the timing and rate of action potentials produced by cerebellar nuclear cells, thereby relaying information out of the cerebellum. If so, then changing spatiotemporal patterns of Purkinje activity would allow different subsets of inhibitory neurons to control cerebellar output at different times. Here we explore the evidence for and against the idea that a synchrony code defines, at least in part, the input-output function between the cerebellar cortex and nuclei. We consider the literature on the existence of simple spike synchrony, convergence of Purkinje neurons onto nuclear neurons, and intrinsic properties of nuclear neurons that contribute to responses to inhibition. Finally, we discuss factors that may disrupt or modulate a synchrony code and describe the potential contributions of inhibitory synchrony to other motor

  15. Computational Aspects of Feedback in Neural Circuits

    Wolfgang Maass; Prashant Joshi; Sontag, Eduardo D.

    2007-01-01

    It has previously been shown that generic cortical microcircuit models can perform complex real-time computations on continuous input streams, provided that these computations can be carried out with a rapidly fading memory. We investigate the computational capability of such circuits in the more realistic case where not only readout neurons, but in addition a few neurons within the circuit, have been trained for specific tasks. This is essentially equivalent to the case where the output of t...

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

    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...... suitable learning algorithm -- a continuous-time version of a temporal differential Hebbian learning algorithm for pulsed neural systems with non-linear synapses -- as well as circuits for the electronic implementation. Measurements from an experimental CMOS chip are presented. Finally, we use our test...... chip to solve simple classical conditioning tasks, thus verifying the design methodologies put forward in the paper....

  17. Immune Cells Exploit a Neural Circuit to Enter the CNS

    Kevin J Tracey

    2012-01-01

    Multiple sclerosis (MS) is associated with the appearance of autoreactive T cells in the central nervous system. Using a mouse model of MS, Arima et al. now show that this attack begins at a specific spinal cord location. T cell entry into the CNS is regulated by a reflex neural circuit originating from leg muscle contractions.

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

    Chang Hao Chen; Sio Hang Pun; Peng Un Mak; Vai, Mang I.; Achim Klug; 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 micropipett...

  19. Implementing neural architectures using analog VLSI circuits

    Maher, Mary Ann C.; DeWeerth, Stephen P.; Mahowald, Misha A.; Mead, Carver A.

    1989-01-01

    Analog very large-scale integrated (VLSI) technology can be used not only to study and simulate biological systems, but also to emulate them in designing artificial sensory systems. A methodology for building these systems in CMOS VLSI technology has been developed using analog micropower circuit elements that can be hierarchically combined. Using this methodology, experimental VLSI chips of visual and motor subsystems have been designed and fabricated. These chips exhibit behavior similar to...

  20. Neural circuit mechanisms of short-term memory

    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.

  1. TrakEM2 software for neural circuit reconstruction.

    Albert Cardona

    Full Text Available A key challenge in neuroscience is the expeditious reconstruction of neuronal circuits. For model systems such as Drosophila and C. elegans, the limiting step is no longer the acquisition of imagery but the extraction of the circuit from images. For this purpose, we designed a software application, TrakEM2, that addresses the systematic reconstruction of neuronal circuits from large electron microscopical and optical image volumes. We address the challenges of image volume composition from individual, deformed images; of the reconstruction of neuronal arbors and annotation of synapses with fast manual and semi-automatic methods; and the management of large collections of both images and annotations. The output is a neural circuit of 3d arbors and synapses, encoded in NeuroML and other formats, ready for analysis.

  2. Micropower circuits for bidirectional wireless telemetry in neural recording applications.

    Neihart, Nathan M; Harrison, Reid R

    2005-11-01

    State-of-the art neural recording systems require electronics allowing for transcutaneous, bidirectional data transfer. As these circuits will be implanted near the brain, they must be small and low power. We have developed micropower integrated circuits for recovering clock and data signals over a transcutaneous power link. The data recovery circuit produces a digital data signal from an ac power waveform that has been amplitude modulated. We have also developed an FM transmitter with the lowest power dissipation reported for biosignal telemetry. The FM transmitter consists of a low-noise biopotential amplifier and a voltage controlled oscillator used to transmit amplified neural signals at a frequency near 433 MHz. All circuits were fabricated in a standard 0.5-microm CMOS VLSI process. The resulting chip is powered through a wireless inductive link. The power consumption of the clock and data recovery circuits is measured to be 129 microW; the power consumption of the transmitter is measured to be 465 microW when using an external surface mount inductor. Using a parasitic antenna less than 2 mm long, a received power level was measured to be -59.73 dBm at a distance of one meter. PMID:16285399

  3. Chaotic phenomena in Josephson circuits coupled quantum cellular neural networks

    Wang Sen; Cai Li; Li Qin; Wu Gang

    2007-01-01

    In this paper the nonlinear dynamical behaviour of a quantum cellular neural network (QCNN) by coupling Josephson circuits was investigated and it was shown that the QCNN using only two of them can cause the onset of chaotic oscillation. The theoretical analysis and simulation for the two Josephson-circuits-coupled QCNN have been done by using the amplitude and phase as state variables. The complex chaotic behaviours can be observed and then proved by calculating Lyapunov exponents. The study provides valuable information about QCNNs for future application in high-parallel signal processing and novel chaotic generators.

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

    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.

  5. Neural Networks Integrated Circuit for Biomimetics MEMS Microrobot

    Ken Saito; Kazuaki Maezumi; Yuka Naito; Tomohiro Hidaka; Kei Iwata; Yuki Okane; Hirozumi Oku; Minami Takato; Fumio Uchikoba

    2014-01-01

    In this paper, we will propose the neural networks integrated circuit (NNIC) which is the driving waveform generator of the 4.0, 2.7, 2.5 mm, width, length, height in size biomimetics microelectromechanical systems (MEMS) microrobot. The microrobot was made from silicon wafer fabricated by micro fabrication technology. The mechanical system of the robot was equipped with small size rotary type actuators, link mechanisms and six legs to realize the ant-like switching behavior. The NNIC generat...

  6. Derivation of Neural Circuits from the Similarity Matching Principle

    Pehlevan, Cengiz; Chklovskii, Dmitri

    Our brains analyze high-dimensional datasets streamed by our sensory organs in multiple stages. Sensory cortices, for example, perform tasks like dimensionality reduction, sparse feature discovery and clustering. To model these tasks we pursue an approach analogous to use of action principles in physics and propose a new family of objective functions based on the principle of similarity matching. From these objective functions we derive online distributed algorithms that can be implemented by biological neural networks resembling cortical circuits. Our networks can adapt to changes in the number of latent dimensions or the number of clusters in the input dataset. Furthermore, we formulate minimax optimization problems from which we derive online algorithms with two classes of neurons identified with principal neurons and interneurons in biological circuits. In addition to bearing resemblance to biological circuits, our algorithms are competitive for Big Data applications.

  7. Stochastic interpolation model of the medial superior olive neural circuit.

    Sanda, Pavel; Marsalek, Petr

    2012-01-24

    This article presents a stochastic model of binaural hearing in the medial superior olive (MSO) circuit. This model is a variant of the slope encoding models. First, a general framework is developed describing the elementary neural operations realized on spike trains in individual parts of the circuit and how the neurons converging onto the MSO are connected. Random delay, coincidence detection of spikes, divergence and convergence of spike trains are operations implemented by the following modules: spike generator, jitter generator, and coincidence detector. Subsequent processing of spike trains computes the sound azimuth in the circuit. The circuit parameters that influence efficiency of slope encoding are studied. In order to measure the overall circuit performance the concept of an ideal observer is used instead of a detailed model of higher relays in the auditory pathway. This makes it possible to bridge the gap between psychophysical observations in humans and recordings taken of small rodents. Most of the results are obtained through numerical simulations of the model. PMID:21920505

  8. X-ray microscopy for neural circuit reconstruction

    Mizutani, Haruo; Takagi, Toshihisa [Science Integration Program, University of Tokyo, Chiba (Japan); Takeda, Yoshihiro; Momose, Atsushi [Department of Advanced Materials Science, University of Tokyo, Chiba (Japan); Takeuchi, Akihisa, E-mail: mizutani@dpc.scint.u-tokyo.ac.j [Japan Synchrotron Radiation Research Institute/SPring-8, Hyogo (Japan)

    2009-09-01

    Neural circuits in the central nervous system build our various higher brain functions. However, little is known about mechanisms underlying neuronal information processing in the brain. Anatomical graph structures of real neural networks will provide us with fundamental views to elucidate them. We aim at developing a three-dimensional atlas of neural circuits using high resolution hard X-ray microscopy by synchrotron radiation. We stained neurons of a complete brain from a mouse by the Golgi-Cox method. The heavy metals used in our procedure enhanced X-ray absorption and phase contrast. 3D images of fibriform axons and dendrites of various neurons were reconstructed by back projection. X-ray microscopy with a Talbot interferometer demonstrated finer histological structures of pyramidal neurons in the hippocampus and the cerebral cortex. This observation probably serves as a foundation for achieving a mammalian Connectome Project (identifying complete wiring diagrams of the brain) with X-ray nano-tomography in the near future.

  9. X-ray microscopy for neural circuit reconstruction

    Neural circuits in the central nervous system build our various higher brain functions. However, little is known about mechanisms underlying neuronal information processing in the brain. Anatomical graph structures of real neural networks will provide us with fundamental views to elucidate them. We aim at developing a three-dimensional atlas of neural circuits using high resolution hard X-ray microscopy by synchrotron radiation. We stained neurons of a complete brain from a mouse by the Golgi-Cox method. The heavy metals used in our procedure enhanced X-ray absorption and phase contrast. 3D images of fibriform axons and dendrites of various neurons were reconstructed by back projection. X-ray microscopy with a Talbot interferometer demonstrated finer histological structures of pyramidal neurons in the hippocampus and the cerebral cortex. This observation probably serves as a foundation for achieving a mammalian Connectome Project (identifying complete wiring diagrams of the brain) with X-ray nano-tomography in the near future.

  10. Precision psychiatry: a neural circuit taxonomy for depression and anxiety.

    Williams, Leanne M

    2016-05-01

    Although there have been tremendous advances in the understanding of human dysfunctions in the brain circuitry for self-reflection, emotion, and cognitive control, a brain-based taxonomy for mental disease is still lacking. As a result, these advances have not been translated into actionable clinical tools, and the language of brain circuits has not been incorporated into training programmes. To address this gap, I present this synthesis of published work, with a focus on functional imaging of circuit dysfunctions across the spectrum of mood and anxiety disorders. This synthesis provides the foundation for a taxonomy of putative types of dysfunction, which cuts across traditional diagnostic boundaries for depression and anxiety and includes instead distinct types of neural circuit dysfunction that together reflect the heterogeneity of depression and anxiety. This taxonomy is suited to specifying symptoms in terms of underlying neural dysfunction at the individual level and is intended as the foundation for building mechanistic research and ultimately guiding clinical practice. PMID:27150382

  11. Oscillation-induced signal transmission and gating in neural circuits.

    Jahnke, Sven; Memmesheimer, Raoul-Martin; Timme, Marc

    2014-12-01

    Reliable signal transmission constitutes a key requirement for neural circuit function. The propagation of synchronous pulse packets through recurrent circuits is hypothesized to be one robust form of signal transmission and has been extensively studied in computational and theoretical works. Yet, although external or internally generated oscillations are ubiquitous across neural systems, their influence on such signal propagation is unclear. Here we systematically investigate the impact of oscillations on propagating synchrony. We find that for standard, additive couplings and a net excitatory effect of oscillations, robust propagation of synchrony is enabled in less prominent feed-forward structures than in systems without oscillations. In the presence of non-additive coupling (as mediated by fast dendritic spikes), even balanced oscillatory inputs may enable robust propagation. Here, emerging resonances create complex locking patterns between oscillations and spike synchrony. Interestingly, these resonances make the circuits capable of selecting specific pathways for signal transmission. Oscillations may thus promote reliable transmission and, in co-action with dendritic nonlinearities, provide a mechanism for information processing by selectively gating and routing of signals. Our results are of particular interest for the interpretation of sharp wave/ripple complexes in the hippocampus, where previously learned spike patterns are replayed in conjunction with global high-frequency oscillations. We suggest that the oscillations may serve to stabilize the replay. PMID:25503492

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

    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. PMID:24183023

  13. Enhancement of synchronization in a hybrid neural circuit by spike timing dependent plasticity

    Nowotny, Thomas; Zhigulin, Valentin P.; Selverston, Allan I; Abarbanel, Henry D.I.; Rabinovich, Mikhail I.

    2003-01-01

    Synchronization of neural activity is fundamental for many functions of the brain. We demonstrate that spike-timing dependent plasticity (STDP) enhances synchronization (entrainment) in a hybrid circuit composed of a spike generator, a dynamic clamp emulating an excitatory plastic synapse, and a chemically isolated neuron from the Aplysia abdominal ganglion. Fixed-phase entrainment of the Aplysia neuron to the spike generator is possible for a much wider range of frequency ratios and is more ...

  14. Communication in Neural Circuits: Tools, Opportunities, and Challenges.

    Lerner, Talia N; Ye, Li; Deisseroth, Karl

    2016-03-10

    Communication, the effective delivery of information, is fundamental to life across all scales and species. Nervous systems (by necessity) may be most specifically adapted among biological tissues for high rate and complexity of information transmitted, and thus, the properties of neural tissue and principles of its organization into circuits may illuminate capabilities and limitations of biological communication. Here, we consider recent developments in tools for studying neural circuits with particular attention to defining neuronal cell types by input and output information streams-i.e., by how they communicate. Complementing approaches that define cell types by virtue of genetic promoter/enhancer properties, this communication-based approach to defining cell types operationally by input/output (I/O) relationships links structure and function, resolves difficulties associated with single-genetic-feature definitions, leverages technology for observing and testing significance of precisely these I/O relationships in intact brains, and maps onto processes through which behavior may be adapted during development, experience, and evolution. PMID:26967281

  15. Neural circuits mediating olfactory-driven behavior in fish

    Florence Kermen

    2013-04-01

    Full Text Available 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.

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

    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.

  17. PCSIM: a parallel simulation environment for neural circuits fully integrated with Python

    Dejan Pecevski; Thomas Natschläger; Klaus Schuch

    2009-01-01

    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...

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

    Pecevski, Dejan; Natschläger, Thomas; Schuch, Klaus

    2009-01-01

    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 f...

  19. Neural Networks Integrated Circuit for Biomimetics MEMS Microrobot

    Ken Saito

    2014-06-01

    Full Text Available In this paper, we will propose the neural networks integrated circuit (NNIC which is the driving waveform generator of the 4.0, 2.7, 2.5 mm, width, length, height in size biomimetics microelectromechanical systems (MEMS microrobot. The microrobot was made from silicon wafer fabricated by micro fabrication technology. The mechanical system of the robot was equipped with small size rotary type actuators, link mechanisms and six legs to realize the ant-like switching behavior. The NNIC generates the driving waveform using synchronization phenomena such as biological neural networks. The driving waveform can operate the actuators of the MEMS microrobot directly. Therefore, the NNIC bare chip realizes the robot control without using any software programs or A/D converters. The microrobot performed forward and backward locomotion, and also changes direction by inputting an external single trigger pulse. The locomotion speed of the microrobot was 26.4 mm/min when the step width was 0.88 mm. The power consumption of the system was 250 mWh when the room temperature was 298 K.

  20. Shaping Neural Circuits by High Order Synaptic Interactions

    Ravid Tannenbaum, Neta; Burak, Yoram

    2016-01-01

    Spike timing dependent plasticity (STDP) is believed to play an important role in shaping the structure of neural circuits. Here we show that STDP generates effective interactions between synapses of different neurons, which were neglected in previous theoretical treatments, and can be described as a sum over contributions from structural motifs. These interactions can have a pivotal influence on the connectivity patterns that emerge under the influence of STDP. In particular, we consider two highly ordered forms of structure: wide synfire chains, in which groups of neurons project to each other sequentially, and self connected assemblies. We show that high order synaptic interactions can enable the formation of both structures, depending on the form of the STDP function and the time course of synaptic currents. Furthermore, within a certain regime of biophysical parameters, emergence of the ordered connectivity occurs robustly and autonomously in a stochastic network of spiking neurons, without a need to expose the neural network to structured inputs during learning. PMID:27517461

  1. Extracellular space preservation aids the connectomic analysis of neural circuits

    Pallotto, Marta; Watkins, Paul V; Fubara, Boma; Singer, Joshua H; Briggman, Kevin L

    2015-01-01

    Dense connectomic mapping of neuronal circuits is limited by the time and effort required to analyze 3D electron microscopy (EM) datasets. Algorithms designed to automate image segmentation suffer from substantial error rates and require significant manual error correction. Any improvement in segmentation error rates would therefore directly reduce the time required to analyze 3D EM data. We explored preserving extracellular space (ECS) during chemical tissue fixation to improve the ability to segment neurites and to identify synaptic contacts. ECS preserved tissue is easier to segment using machine learning algorithms, leading to significantly reduced error rates. In addition, we observed that electrical synapses are readily identified in ECS preserved tissue. Finally, we determined that antibodies penetrate deep into ECS preserved tissue with only minimal permeabilization, thereby enabling correlated light microscopy (LM) and EM studies. We conclude that preservation of ECS benefits multiple aspects of the connectomic analysis of neural circuits. DOI: http://dx.doi.org/10.7554/eLife.08206.001 PMID:26650352

  2. Functional neuroanatomy of anxiety: a neural circuit perspective.

    Etkin, Amit

    2010-01-01

    Anxiety is a commonly experienced subjective state that can have both adaptive and maladaptive properties. Clinical disorders of anxiety are likewise also common, and range widely in their symptomatology and consequences for the individual. Cognitive neuroscience has provided an increasingly sophisticated understanding of the processes underlying normal human emotion, and its disruption or dysregulation in clinical anxiety disorders. In this chapter, I review functional neuroimaging studies of emotion in healthy and anxiety-disordered populations. A limbic-medial prefrontal circuit is emphasized and an information processing model is proposed for the processing of negative emotion. Data on negative emotion processing in a variety of anxiety disorders are presented and integrated within an understanding of the functions of elements within the limbic-medial prefrontal circuit. These data suggest that anxiety disorders may be usefully conceptualized as differentially affecting emotional reactivity and regulatory processes--functions that involve different neurobiological mechanisms. While the neural bases of several anxiety disorders are increasingly better understood, advances have lagged significantly behind in others. Nonetheless, the conceptual framework provided by convergent findings in studies of emotional processing in normative and anxiety-disordered populations promises to yield continued insights and nuances, and will likely provide useful information in the search for etiology and novel treatments. PMID:21309113

  3. Lag Synchronization of Switched Neural Networks via Neural Activation Function and Applications in Image Encryption.

    Wen, Shiping; Zeng, Zhigang; Huang, Tingwen; Meng, Qinggang; Yao, Wei

    2015-07-01

    This paper investigates the problem of global exponential lag synchronization of a class of switched neural networks with time-varying delays via neural activation function and applications in image encryption. The controller is dependent on the output of the system in the case of packed circuits, since it is hard to measure the inner state of the circuits. Thus, it is critical to design the controller based on the neuron activation function. Comparing the results, in this paper, with the existing ones shows that we improve and generalize the results derived in the previous literature. Several examples are also given to illustrate the effectiveness and potential applications in image encryption. PMID:25594985

  4. Active components for integrated plasmonic circuits

    Krasavin, A.V.; Bolger, P.M.; Zayats, A.V.;

    2009-01-01

    We present a comprehensive study of highly efficient and compact passive and active components for integrated plasmonic circuit based on dielectric-loaded surface plasmon polariton waveguides.......We present a comprehensive study of highly efficient and compact passive and active components for integrated plasmonic circuit based on dielectric-loaded surface plasmon polariton waveguides....

  5. Technologies for imaging neural activity in large volumes.

    Ji, Na; Freeman, Jeremy; Smith, Spencer L

    2016-08-26

    Neural circuitry has evolved to form distributed networks that act dynamically across large volumes. Conventional microscopy collects data from individual planes and cannot sample circuitry across large volumes at the temporal resolution relevant to neural circuit function and behaviors. Here we review emerging technologies for rapid volume imaging of neural circuitry. We focus on two critical challenges: the inertia of optical systems, which limits image speed, and aberrations, which restrict the image volume. Optical sampling time must be long enough to ensure high-fidelity measurements, but optimized sampling strategies and point-spread function engineering can facilitate rapid volume imaging of neural activity within this constraint. We also discuss new computational strategies for processing and analyzing volume imaging data of increasing size and complexity. Together, optical and computational advances are providing a broader view of neural circuit dynamics and helping elucidate how brain regions work in concert to support behavior. PMID:27571194

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

    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. PMID:23825209

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

    Sher, A. [Santa Cruz Institute for Particle Physics, University of California, Santa Cruz, CA (United States)], E-mail: sasha@scipp.ucsc.edu; Chichilnisky, E.J. [Systems Neurobiology, Salk Institute, La Jolla, CA (United States); Dabrowski, W. [AGH University of Science and Technology, Cracow (Poland); Grillo, A.A.; Grivich, M. [Santa Cruz Institute for Particle Physics, University of California, Santa Cruz, CA (United States); Gunning, D. [University of Glasgow, Glasgow (United Kingdom); Hottowy, P. [AGH University of Science and Technology, Cracow (Poland); Kachiguine, S.; Litke, A.M. [Santa Cruz Institute for Particle Physics, University of California, Santa Cruz, CA (United States); Mathieson, K. [University of Glasgow, Glasgow (United Kingdom); Petrusca, D. [Santa Cruz Institute for Particle Physics, University of California, Santa Cruz, CA (United States)

    2007-09-01

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

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

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

  9. Feature evaluation and extraction based on neural network in analog circuit fault diagnosis

    Yuan Haiying; Chen Guangju; Xie Yongle

    2007-01-01

    Choosing the right characteristic parameter is the key to fault diagnosis in analog circuit.The feature evaluation and extraction methods based on neural network are presented.Parameter evaluation of circuit features is realized by training results from neural network; the superior nonlinear mapping capability is competent for extracting fault features which are normalized and compressed subsequently.The complex classification problem on fault pattern recognition in analog circuit is transferred into feature processing stage by feature extraction based on neural network effectively, which improves the diagnosis efficiency.A fault diagnosis illustration validated this method.

  10. [Synapse elimination and functional neural circuit formation in the cerebellum].

    Kano, Masanobu

    2013-06-01

    Neuronal connections are initially redundant, but unnecessary connections are eliminated subsequently during postnatal development. This process, known as 'synapse elimination', is thought to be crucial for establishing functionally mature neural circuits. The climbing fiber (CF) to the Purkinje cell (PC) synapse in the cerebellum is a representative model of synapse elimination. We disclose that one-to-one connection from CF to PC is established through four distinct phases: (1) strengthening of a single CF among multiple CFs in each PC at P3-P7, (2) translocation of a single strengthened CF to PC dendrites from around P9, and (3) early phase (P7 to around P11) and (4) late phase (around P12 to P17) of elimination of weak CF synapses from PC somata. Mice with PC-selective deletion of P/Q-type voltage-dependent Ca2+ channel (VDCC) exhibit severe defects in strengthening of single CFs, dendritic translocation of single CFs and CF elimination from P7. In contrast, mice with a mutation of a single allele for the GABA-synthesizing enzyme GAD67 have a selective impairment of CF elimination from P10 due to reduced inhibition and elevated Ca2+ influx to PC somata. Thus, regulation of Ca2+ influx to PCs is crucial for the four phases of CF synapse elimination. PMID:25069248

  11. The universal fuzzy logical framework of neural circuits and its application in modeling primary visual cortex

    2008-01-01

    Analytical study of large-scale nonlinear neural circuits is a difficult task. Here we analyze the function of neural systems by probing the fuzzy logical framework of the neural cells’ dynamical equations. Al- though there is a close relation between the theories of fuzzy logical systems and neural systems and many papers investigate this subject, most investigations focus on finding new functions of neural systems by hybridizing fuzzy logical and neural system. In this paper, the fuzzy logical framework of neural cells is used to understand the nonlinear dynamic attributes of a common neural system by abstracting the fuzzy logical framework of a neural cell. Our analysis enables the educated design of network models for classes of computation. As an example, a recurrent network model of the primary visual cortex has been built and tested using this approach.

  12. EM-based optimization of microwave circuits using artificial neural networks: the state of the art

    Rayas-Sánchez, José E.

    2004-01-01

    This paper reviews the current state-of-the-art in electromagnetic (EM)-based design and optimization of microwave circuits using artificial neural networks (ANNs). Measurement-based design of microwave circuits using ANNs is also reviewed. The conventional microwave neural optimization approach is surveyed, along with typical enhancing techniques, such as segmentation, decomposition, hierarchy, design of experiments and clusterization. Innovative strategies for ANN-based design exploiting...

  13. Nonlocal mechanism for cluster synchronization in neural circuits

    Kanter, I.; Kopelowitz, E.; Vardi, R.; Zigzag, M.; Kinzel, W.; Abeles, M.; Cohen, D.

    2011-03-01

    The interplay between the topology of cortical circuits and synchronized activity modes in distinct cortical areas is a key enigma in neuroscience. We present a new nonlocal mechanism governing the periodic activity mode: the greatest common divisor (GCD) of network loops. For a stimulus to one node, the network splits into GCD-clusters in which cluster neurons are in zero-lag synchronization. For complex external stimuli, the number of clusters can be any common divisor. The synchronized mode and the transients to synchronization pinpoint the type of external stimuli. The findings, supported by an information mixing argument and simulations of Hodgkin-Huxley population dynamic networks with unidirectional connectivity and synaptic noise, call for reexamining sources of correlated activity in cortex and shorter information processing time scales.

  14. Analog integrated circuits for the Lotka-Volterra competitive neural networks.

    Asai, T; Ohtani, M; Yonezu, H

    1999-01-01

    A subthreshold MOS integrated circuit (IC) is designed and fabricated for implementing a competitive neural network of the Lotka-Volterra (LV) type which is derived from conventional membrane dynamics of neurons and is used for the selection of external inputs. The steady-state solutions to the LV equation can be classified into three types, each of which represents qualitatively different selection behavior. Among the solutions, the winners-share-all (WSA) solution in which a certain number of neurons remain activated in steady states is particularly useful owing to robustness in the selection of inputs from a noisy environment. The measured results of the fabricated LV IC's agree well with the theoretical prediction as long as the influence of device mismatches is small. Furthermore, results of extensive circuit simulations prove that the large-scale LV circuit producing the WSA solution does exhibit a reliable selection compared with winner-take-all circuits, in the possible presence of device mismatches. PMID:18252623

  15. Correlation between stimulation strength and onset time of signal traveling within the neocortical neural circuits under caffeine application.

    Yoshimura, Hiroshi; Honjo, Miho; Sugai, Tokio; Kaneyama, Keiseki; Segami, Natsuki; Kato, Nobuo

    2011-08-01

    In general, strength of input to neocortical neural circuits affects the amplitude of postsynaptic potentials (PSPs), thereby modulating the way signals are transmitted within the circuits. Caffeine is one of the pharmacological agents able to modulate synaptic activities. The present study investigated how strength of input affects signal propagation in neocortical circuits under the application of caffeine. Spatio-temporal neural activities were observed from visual cortical slices of rats using optical recording methods with voltage-sensitive dye. Electrical stimulations were applied to white matter in the primary visual cortex with bath-application of caffeine. When the strength of stimulation was 0.3mA, signals propagated from the site of stimulation in the primary visual cortex toward the secondary visual cortex along vertical and horizontal pathways. When stimulation strength was reduced from 0.3mA to 0.07mA, start of signal propagation was delayed about 25ms without affecting field PSP amplitude or the manner of signal propagation. Conversely, co-application of caffeine and d-2-amino-5-phosphonovaleric acid (d-AP5) did not induce delays in signal start. These findings suggest that conversion of neural code from amplitude code to temporal code is inducible at the level of neocortical circuits in an N-methyl-d-aspartate (NMDA) receptor activity-dependent manner. PMID:21621566

  16. An improved superconducting neural circuit and its application for a neural network solving a combinatorial optimization problem

    We have proposed a superconducting Hopfield-type neural network for solving the N-Queens problem which is one of combinatorial optimization problems. The sigmoid-shape function of a neuron output is represented by the output of coupled SQUIDs gate consisting of a single-junction and a double-junction SQUIDs. One of the important factors for an improvement of the network performance is an improvement of a threshold characteristic of a neuron circuit. In this paper, we report an improved design of coupled SQUID gates for a superconducting neural network. A step-like function with a steep threshold at a rising edge is desirable for a neuron circuit to solve a combinatorial optimization problem. A neuron circuit is composed of two coupled SQUIDs gates with a cascade connection in order to obtain such characteristics. The designed neuron circuit is fabricated by a 2.5 kA/cm2 Nb/AlOx/Nb process. The operation of a fabricated neuron circuit is experimentally demonstrated. Moreover, we discuss about the performance of the neural network using the improved neuron circuits and delayed negative self-connections.

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

    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.

  18. Technology for integrated circuit micropackages for neural interfaces, based on gold–silicon wafer bonding

    Progress in the development of active neural interface devices requires a very compact method for protecting integrated circuits (ICs). In this paper, a method of forming micropackages is described in detail. The active areas of the chips are sealed in gas-filled cavities of the cap wafer in a wafer-bonding process using Au–Si eutectic. We describe the simple additions to the design of the IC, the post-processing of the active wafer and the required features of the cap wafer. The bonds, which were made at pressure and temperature levels within the range of the tolerance of complementary metal–oxide–semiconductor ICs, are strong enough to meet MIL STD 883G, Method 2019.8 (shear force test). We show results that suggest a method for wafer-scale gross leak testing using FTIR. This micropackaging method requires no special fabrication process and is based on using IC compatible or conventional fabrication steps. (paper)

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

    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

  20. Hierarchical Neural Networks Method for Fault Diagnosis of Large-Scale Analog Circuits

    TAN Yanghong; HE Yigang; FANG Gefeng

    2007-01-01

    A novel hierarchical neural networks (HNNs) method for fault diagnosis of large-scale circuits is proposed. The presented techniques using neural networks(NNs) approaches require a large amount of computation for simulating various faulty component possibilities. For large scale circuits, the number of possible faults, and hence the simulations, grow rapidly and become tedious and sometimes even impractical. Some NNs are distributed to the torn sub-blocks according to the proposed torn principles of large scale circuits. And the NNs are trained in batches by different patterns in the light of the presented rules of various patterns when the DC, AC and transient responses of the circuit are available. The method is characterized by decreasing the over-lapped feasible domains of responses of circuits with tolerance and leads to better performance and higher correct classification. The methodology is illustrated by means of diagnosis examples.

  1. An Implantable Mixed Analog/Digital Neural Stimulator Circuit

    Gudnason, Gunnar; Bruun, Erik; Haugland, Morten

    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...

  2. Design of 3D Active Multichannel Silicon Neural Microelectrode

    WANG Di; ZHANG Guoxiong; LI Xingfei

    2006-01-01

    To find a design method for 3D active multichannel silicon microelectrode,a microstructure of active neural recording system is presented,where two 2D probes,two integrated circuits and two spacers are microassembled on a 5 mm ×7 mm silicon platform,and 32 sites neural signals can be operated simultaneously.A theoretical model for measuring the neural signal by the silicon microelectrode is proposed based on the structure and fabrication process of a single-shank probe.The method of determining the dimensional parameters of the probe shank is discussed in the following three aspects,i.e.the structures of pallium and endocranium,coupled interconnecters noise,and strength characteristic of neural probe.The design criterion is to minimize the size of the neural probe as well as that the probe has enough stiffness to pierce the endocranium.The on-chip unity-gain bandpass amplifier has an overall gain of 42 dB over a bandwidth from 60 Hz to 10 kHz;and the DC-baseline stability circuit is of high input resistance above 30 MΩ to guarantee a cutoff frequency below 100 Hz.The circuit works in stimulating or recording modes.The conversion of the modes depends on the stimulating control signal.

  3. In search of the neural circuits of intrinsic motivation

    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.

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

  5. Neural Circuit Flexibility in a Small Sensorimotor System

    Blitz, Dawn M.; Nusbaum, Michael P.

    2011-01-01

    Neuronal circuits underlying rhythmic behaviors (central pattern generators: CPGs) can generate rhythmic motor output without sensory input. However, sensory input is pivotal for generating behaviorally relevant CPG output. Here we discuss recent work in the decapod crustacean stomatogastric nervous system (STNS) identifying cellular and synaptic mechanisms whereby sensory inputs select particular motor outputs from CPG circuits. This includes several examples in which sensory neurons regulat...

  6. Circuit Design of On-Chip BP Learning Neural Network with Programmable Neuron Characteristics

    卢纯; 石秉学; 陈卢

    2000-01-01

    A circuit system of on chip BP(Back-Propagation) learning neural network with pro grammable neurons has been designed,which comprises a feedforward network,an error backpropagation network and a weight updating circuit. It has the merits of simplicity,programmability, speedness,low power-consumption and high density. A novel neuron circuit with pro grammable parameters has been proposed. It generates not only the sigmoidal function but also its derivative. HSPICE simulations are done to a neuron circuit with level 47 transistor models as a standard 1.2tμm CMOS process. The results show that both functions are matched with their respec ive ideal functions very well. The non-linear partition problem is used to verify the operation of the network. The simulation result shows the superior performance of this BP neural network with on-chip learning.

  7. Circuit-breakers: optical technologies for probing neural signals and systems.

    Zhang, Feng; Aravanis, Alexander M; Adamantidis, Antoine; de Lecea, Luis; Deisseroth, Karl

    2007-08-01

    Neuropsychiatric disorders, which arise from a combination of genetic, epigenetic and environmental influences, epitomize the challenges faced in understanding the mammalian brain. Elucidation and treatment of these diseases will benefit from understanding how specific brain cell types are interconnected and signal in neural circuits. Newly developed neuroengineering tools based on two microbial opsins, channelrhodopsin-2 (ChR2) and halorhodopsin (NpHR), enable the investigation of neural circuit function with cell-type-specific, temporally accurate and reversible neuromodulation. These tools could lead to the development of precise neuromodulation technologies for animal models of disease and clinical neuropsychiatry. PMID:17643087

  8. Longitudinal evidence for functional specialization of the neural circuit supporting working memory in the human brain

    Finn, Amy S.; Sheridan, Margaret A.; Hudson Kam, Carla L.; Hinshaw, Stephen; D’Esposito, Mark

    2010-01-01

    Although children perform more poorly than adults on many cognitive measures, they are better able to learn things such as language and music. These differences could result from the delayed specialization of neural circuits and asynchronies in the maturation of neural substrates required for learning. Working memory—the ability to hold information in mind that is no longer present in the environment—comprises a set of cognitive processes required for many, if not all, forms of learning. A cr...

  9. Neck muscle afferents influence oromotor and cardiorespiratory brainstem neural circuits.

    Edwards, I J; Lall, V K; Paton, J F; Yanagawa, Y; Szabo, G; Deuchars, S A; Deuchars, J

    2015-01-01

    Sensory information arising from the upper neck is important in the reflex control of posture and eye position. It has also been linked to the autonomic control of the cardiovascular and respiratory systems. Whiplash associated disorders (WAD) and cervical dystonia, which involve disturbance to the neck region, can often present with abnormalities to the oromotor, respiratory and cardiovascular systems. We investigated the potential neural pathways underlying such symptoms. Simulating neck afferent activity by electrical stimulation of the second cervical nerve in a working heart brainstem preparation (WHBP) altered the pattern of central respiratory drive and increased perfusion pressure. Tracing central targets of these sensory afferents revealed projections to the intermedius nucleus of the medulla (InM). These anterogradely labelled afferents co-localised with parvalbumin and vesicular glutamate transporter 1 indicating that they are proprioceptive. Anterograde tracing from the InM identified projections to brain regions involved in respiratory, cardiovascular, postural and oro-facial behaviours--the neighbouring hypoglossal nucleus, facial and motor trigeminal nuclei, parabrachial nuclei, rostral and caudal ventrolateral medulla and nucleus ambiguus. In brain slices, electrical stimulation of afferent fibre tracts lateral to the cuneate nucleus monosynaptically excited InM neurones. Direct stimulation of the InM in the WHBP mimicked the response of second cervical nerve stimulation. These results provide evidence of pathways linking upper cervical sensory afferents with CNS areas involved in autonomic and oromotor control, via the InM. Disruption of these neuronal pathways could, therefore, explain the dysphagic and cardiorespiratory abnormalities which may accompany cervical dystonia and WAD. PMID:24595534

  10. Fault Diagnosis of Mixed-Signal Analog Circuit using Artificial Neural Networks

    Ashwani Kumar Narula

    2015-06-01

    Full Text Available This paper presents parametric fault diagnosis in mixed-signal analog circuit using artificial neural networks. Single parametric faults are considered in this study. A benchmark R2R digital to analog converter circuit has been used as an example circuit for experimental validations. The input test pattern required for testing are reduced to optimum value using sensitivity analysis of the circuit under test. The effect of component tolerances has also been taken care of by performing the Monte-Carlo analysis. In this study parametric fault models are defined for the R2R network of the digital to analog converter. The input test patterns are applied to the circuit under test and the output responses are measured for each fault model covering all the Monte-Carlo runs. The classification of the parametric faults is done using artificial neural networks. The fault diagnosis system is developed in LabVIEW environment in the form of a virtual instrument. The artificial neural network is designed using MATLAB and finally embedded in the virtual instrument. The fault diagnosis is validated with simulated data and with the actual data acquired from the circuit hardware.

  11. Time series cross prediction in a single transistor chaotic circuit using neural networks

    L. Magafas

    2009-01-01

    Full Text Available In this paper we will be trying to cross predict a multivariate time series of a single transistor chaotic circuit using neural networks. For this purpose we investigate the influence of a number of first and second order near neighbors in predicting chaotic time series using a back propagation neural network. This influence is examined by changing the number of neurons in the hidden layer of a backprogation neural network with one hidden layer. The number of neurons at the input layer were equal to the embedding dimension of the corresponding strange attractor.

  12. Developmental regulation of spatio-temporal patterns of cortical circuit activation

    Trevor Charles Griffen; Arianna Maffei

    2013-01-01

    Neural circuits are refined in an experience-dependent manner during early postnatal development. How development modulates the spatio-temporal propagation of activity through cortical circuits is poorly understood. Here we use voltage sensitive dye imaging (VSD) to show that there are significant changes in the spatio-temporal patterns of intracortical signals in primary visual cortex from postnatal day 13 (P13), eye opening, to P28, the peak of the critical period for rodent visual cortical...

  13. Developmental regulation of spatio-temporal patterns of cortical circuit activation

    Griffen, Trevor C.; Wang, Lang; Fontanini, Alfredo; Maffei, Arianna

    2013-01-01

    Neural circuits are refined in an experience-dependent manner during early postnatal development. How development modulates the spatio-temporal propagation of activity through cortical circuits is poorly understood. Here we use voltage-sensitive dye imaging (VSD) to show that there are significant changes in the spatio-temporal patterns of intracortical signals in primary visual cortex (V1) from postnatal day 13 (P13), eye opening, to P28, the peak of the critical period for rodent visual cor...

  14. Laser programmable integrated circuit for forming synapses in neural networks

    Fu, C.Y.

    1997-02-11

    Customizable neural network in which one or more resistors form each synapse is disclosed. All the resistors in the synaptic array are identical, thus simplifying the processing issues. Highly doped, amorphous silicon is used as the resistor material, to create extremely high resistances occupying very small spaces. Connected in series with each resistor in the array is at least one severable conductor whose uppermost layer has a lower reflectivity of laser energy than typical metal conductors at a desired laser wavelength. 5 figs.

  15. A Neural Circuit for Spatial Summation in Visual Cortex

    Adesnik, Hillel; Bruns, William; Taniguchi, Hiroki; Huang, Z. Josh; Scanziani, Massimo

    2012-01-01

    The response of cortical neurons to a sensory stimulus is modulated by the context. In the visual cortex, for example, stimulation of a pyramidal cell's receptive field surround can attenuate the cell’s response to a stimulus in its receptive field’s center, a phenomenon called surround suppression. Whether cortical circuits contribute to surround suppression or whether the phenomenon is entirely relayed from earlier stages of visual processing is controversial. Here we discover that, in cont...

  16. Activity transport models for PWR primary circuits

    The corrosion products activated in the primary circuit form a major source of occupational radiation dose in the PWR reactors. Transport of corrosion activity is a complex process including chemistry, reactor physics, thermodynamics and hydrodynamics. All the mechanisms involved are not known and there is no comprehensive theory for the process, so experimental test loops and plant data are very important in research efforts. Several activity transport modelling attempts have been made to improve the water chemistry control and to minimise corrosion in PWR's. In this research report some of these models are reviewed with special emphasis on models designed for Soviet VVER type reactors. (51 refs., 16 figs., 4 tabs.)

  17. Visualization and manipulation of neural activity in the developing vertebrate nervous system

    Jiayi eZhang

    2011-11-01

    Full Text Available Neural activity during vertebrate development has been unambiguously shown to play a critical role in sculpting circuit formation and function. Patterned neural activity in various parts of the developing nervous system is thought to modulate neurite outgrowth, axon targeting and synapse refinement. The nature and role of patterned neural activity during development has been classically studied with in vitro preparations using pharmacological manipulations. In this review we discuss newly available and developing molecular genetic tools for the visualization and manipulation of neural activity patterns specifically during development.

  18. Low Temperature Performance of High-Speed Neural Network Circuits

    Duong, T.; Tran, M.; Daud, T.; Thakoor, A.

    1995-01-01

    Artificial neural networks, derived from their biological counterparts, offer a new and enabling computing paradigm specially suitable for such tasks as image and signal processing with feature classification/object recognition, global optimization, and adaptive control. When implemented in fully parallel electronic hardware, it offers orders of magnitude speed advantage. Basic building blocks of the new architecture are the processing elements called neurons implemented as nonlinear operational amplifiers with sigmoidal transfer function, interconnected through weighted connections called synapses implemented using circuitry for weight storage and multiply functions either in an analog, digital, or hybrid scheme.

  19. Stochastic interpolation model of the medial superior olive neural circuit

    Šanda, Pavel; Maršálek, P.

    2012-01-01

    Roč. 1434, JAN 24 (2012), s. 257-265. ISSN 0006-8993. [International Workshop on Neural Coding. Limassol, 29.10.2010-03.11.2010] R&D Projects: GA ČR(CZ) GAP103/11/0282 Grant ostatní: GA MPO(CZ) FR-TI3/869 Institutional research plan: CEZ:AV0Z50110509 Keywords : coincidence detection * directional hearing * interaural time delay * sound azimuth * interpolation model Subject RIV: FH - Neurology Impact factor: 2.879, year: 2012

  20. Neural circuits of emotion regulation: a comparison of mindfulness-based and cognitive reappraisal strategies.

    Opialla, Sarah; Lutz, Jacqueline; Scherpiet, Sigrid; Hittmeyer, Anna; Jäncke, Lutz; Rufer, Michael; Grosse Holtforth, Martin; Herwig, Uwe; Brühl, Annette B

    2015-02-01

    Dealing with one's emotions is a core skill in everyday life. Effective cognitive control strategies have been shown to be neurobiologically represented in prefrontal structures regulating limbic regions. In addition to cognitive strategies, mindfulness-associated methods are increasingly applied in psychotherapy. We compared the neurobiological mechanisms of these two strategies, i.e. cognitive reappraisal and mindfulness, during both the cued expectation and perception of negative and potentially negative emotional pictures. Fifty-three healthy participants were examined with functional magnetic resonance imaging (47 participants included in analysis). Twenty-four subjects applied mindfulness, 23 used cognitive reappraisal. On the neurofunctional level, both strategies were associated with comparable activity of the medial prefrontal cortex and the amygdala. When expecting negative versus neutral stimuli, the mindfulness group showed stronger activations in ventro- and dorsolateral prefrontal cortex, supramarginal gyrus as well as in the left insula. During the perception of negative versus neutral stimuli, the two groups only differed in an increased activity in the caudate in the cognitive group. Altogether, both strategies recruited overlapping brain regions known to be involved in emotion regulation. This result suggests that common neural circuits are involved in the emotion regulation by mindfulness-based and cognitive reappraisal strategies. Identifying differential activations being associated with the two strategies in this study might be one step towards a better understanding of differential mechanisms of change underlying frequently used psychotherapeutic interventions. PMID:24902936

  1. Design and analysis of an active power factor correction circuit

    Zhou, Zhen

    1989-01-01

    The design of an active-unity power factor correction circuit with variable-hysteresis control for off-line dc-to-dc switching power supplies is described. Design equations relating the boost inductor current ripple to the circuit components selection and circuit performance arc discussed. A computer-aided design program (CADO) is developed to give the optimal circuit components selection. A 500 watt, 300 volt experimental circuit is built to verify the simulation and analysis ...

  2. PCSIM: a parallel simulation environment for neural circuits fully integrated with Python

    Dejan Pecevski

    2009-05-01

    Full Text Available 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.

  3. A multi-channel fully differential programmable integrated circuit for neural recording application

    A multi-channel, fully differential programmable chip for neural recording application is presented. The integrated circuit incorporates eight neural recording amplifiers with tunable bandwidth and gain, eight 4th-order Bessel switch capacitor filters, an 8-to-1 analog time-division multiplexer, a fully differential successive approximation register analog-to-digital converter (SAR ADC), and a serial peripheral interface for communication. The neural recording amplifier presents a programmable gain from 53 dB to 68 dB, a tunable low cut-off frequency from 0.1 Hz to 300 Hz, and 3.77 μVrms input-referred noise over a 5 kHz bandwidth. The SAR ADC digitizes signals at maximum sampling rate of 20 kS/s per channel and achieves an ENOB of 7.4. The integrated circuit is designed and fabricated in 0.18-μm CMOS mix-signal process. We successfully performed a multi-channel in-vivo recording experiment from a rat cortex using the neural recording chip. (semiconductor integrated circuits)

  4. Diversity of Dopaminergic Neural Circuits in Response to Drug Exposure.

    Juarez, Barbara; Han, Ming-Hu

    2016-09-01

    Addictive substances are known to increase dopaminergic signaling in the mesocorticolimbic system. The origin of this dopamine (DA) signaling originates in the ventral tegmental area (VTA), which sends afferents to various targets, including the nucleus accumbens, the medial prefrontal cortex, and the basolateral amygdala. VTA DA neurons mediate stimuli saliency and goal-directed behaviors. These neurons undergo robust drug-induced intrinsic and extrinsic synaptic mechanisms following acute and chronic drug exposure, which are part of brain-wide adaptations that ultimately lead to the transition into a drug-dependent state. Interestingly, recent investigations of the differential subpopulations of VTA DA neurons have revealed projection-specific functional roles in mediating reward, aversion, and stress. It is now critical to view drug-induced neuroadaptations from a circuit-level perspective to gain insight into how differential dopaminergic adaptations and signaling to targets of the mesocorticolimbic system mediates drug reward. This review hopes to describe the projection-specific intrinsic characteristics of these subpopulations, the differential afferent inputs onto these VTA DA neuron subpopulations, and consolidate findings of drug-induced plasticity of VTA DA neurons and highlight the importance of future projection-based studies of this system. PMID:26934955

  5. Impairments of neural circuit function in Alzheimer's disease.

    Busche, Marc Aurel; Konnerth, Arthur

    2016-08-01

    An essential feature of Alzheimer's disease (AD) is the accumulation of amyloid-β (Aβ) peptides in the brain, many years to decades before the onset of overt cognitive symptoms. We suggest that during this very extended early phase of the disease, soluble Aβ oligomers and amyloid plaques alter the function of local neuronal circuits and large-scale networks by disrupting the balance of synaptic excitation and inhibition (E/I balance) in the brain. The analysis of mouse models of AD revealed that an Aβ-induced change of the E/I balance caused hyperactivity in cortical and hippocampal neurons, a breakdown of slow-wave oscillations, as well as network hypersynchrony. Remarkably, hyperactivity of hippocampal neurons precedes amyloid plaque formation, suggesting that hyperactivity is one of the earliest dysfunctions in the pathophysiological cascade initiated by abnormal Aβ accumulation. Therapeutics that correct the E/I balance in early AD may prevent neuronal dysfunction, widespread cell loss and cognitive impairments associated with later stages of the disease.This article is part of the themed issue 'Evolution brings Ca(2+) and ATP together to control life and death'. PMID:27377723

  6. Statistical Estimation of the ,Switching Activity in VLSI Circuits

    Farid N. Najm; Michael G. Xakellis

    1998-01-01

    Higher levels of integration have led to a generation of integrated circuits for which power dissipation and reliability are major design concerns. In CMOS circuits, both of these problems are directly related to the extent of circuit switching activity. The average number of transitions per second at a circuit node is a measure of switching activity that has been called the transition density. This paper presents a statistical simulation technique to estimate individual node transition densi...

  7. The use of brain imaging to elucidate neural circuit changes in cocaine addiction

    Hanlon CA

    2012-09-01

    Full Text Available Colleen A Hanlon,1,2 Melanie Canterberry11Department of Psychiatry and Behavioral Sciences, 2Department of Neurosciences Medical University of South Carolina, Charleston, SC, USAAbstract: Within substance abuse, neuroimaging has experienced tremendous growth as both a research method and a clinical tool in the last decade. The application of functional imaging methods to cocaine dependent patients and individuals in treatment programs, has revealed that the effects of cocaine are not limited to dopamine-rich subcortical structures, but that the cortical projection areas are also disrupted in cocaine dependent patients. In this review, we will first describe several of the imaging methods that are actively being used to address functional and structural abnormalities in addiction. This will be followed by an overview of the cortical and subcortical brain regions that are most often cited as dysfunctional in cocaine users. We will also introduce functional connectivity analyses currently being used to investigate interactions between these cortical and subcortical areas in cocaine users and abstainers. Finally, this review will address recent research which demonstrates that alterations in the functional connectivity in cocaine users may be associated with structural pathology in these circuits, as demonstrated through diffusion tensor imaging. Through the use of these tools in both a basic science setting and as applied to treatment seeking individuals, we now have a greater understanding of the complex cortical and subcortical networks which contribute to the stages of initial craving, dependence, abstinence, and relapse. Although the ability to use neuroimaging to predict treatment response or identify vulnerable populations is still in its infancy, the next decade holds tremendous promise for using neuroimaging to tailor either behavioral or pharmacologic treatment interventions to the individual.Keywords: addiction, neural circuit, functional

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

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

    2012-06-26

    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

  9. Soft Fault Diagnosis for Analog Circuits Based on Slope Fault Feature and BP Neural Networks

    HU Mei; WANG Hong; HU Geng; YANG Shiyuan

    2007-01-01

    Fault diagnosis is very important for development and maintenance of safe and reliable electronic circuits and systems. This paper describes an approach of soft fault diagnosis for analog circuits based on slope fault feature and back propagation neural networks (BPNN). The reported approach uses the voltage relation function between two nodes as fault features; and for linear analog circuits, the voltage relation function is a linear function, thus the slope is invariant as fault feature. Therefore, a unified fault feature for both hard fault (open or short fault) and soft fault (parametric fault) is extracted. Unlike other NN-based diagnosis methods which utilize node voltages or frequency response as fault features, the reported BPNN is trained by the extracted feature vectors, the slope features are calculated by just simulating once for each component, and the trained BPNN can achieve all the soft faults diagnosis of the component. Experiments show that our approach is promising.

  10. Two-photon multiplane imaging of neural circuits (Conference Presentation)

    Yang, Weijian; Miller, Jae-eun K.; Carrillo-Reid, Luis; Pnevmatikakis, Eftychios; Paninski, Liam; Peterka, Darcy S.; Yuste, Rafael

    2016-03-01

    Imaging the neuronal activity throughout the brain with high temporal and spatial resolution is an important step in understanding how the brain works. Two-photon laser scanning microscopy with fluorescent calcium indicators has enabled this type of experiments in vivo. Most of these microscopes acquire images serially, with a single laser beam, limiting the overall imaging speed. To overcome this limit, multiple beamlets can be used to image in parallel multiple regions. Here, we demonstrate a novel scheme of a two-photon laser-scanning microscope that can simultaneously record neuronal activity at multiple planes of the sample with a single photomultiplier tube. A spatial light modulator is used to generate the designated multiple beamlets, and a constrained non-negative matrix factorization algorithm is used to demix the signals from multiple scanned planes. We simultaneously record neuronal activity of multiple layers of a mouse cortex at 10 fps in vivo. This novel imaging scheme provides a powerful tool for mapping the brain activity.

  11. Multi-point optical manipulation and simultaneous imaging of neural circuits through wavefront phase modulation (Presentation Recording)

    Aghayee, Samira; Winkowski, Dan; Kanold, Patrick; Losert, Wolfgang

    2015-08-01

    The spatial connectivity of neural circuits and the various activity patterns they exert is what forms the brain function. How these patterns link to a certain perception or a behavior is a key question in neuroscience. Recording the activity of neural circuits while manipulating arbitrary neurons leads to answering this question. That is why acquiring a fast and reliable method of stimulation and imaging a population of neurons at a single cell resolution is of great importance. Owing to the recent advancements in calcium imaging and optogenetics, tens to hundreds of neurons in a living system can be imaged and manipulated optically. We describe the adaptation of a multi-point optical method that can be used to address the specific challenges faced in the in-vivo study of neuronal networks in the cerebral cortex. One specific challenge in the cerebral cortex is that the information flows perpendicular to the surface. Therefore, addressing multiple points in a three dimensional space simultaneously is of great interest. Using a liquid crystal spatial light modulator, the wavefront of the input laser beam is modified to produce multiple focal points at different depths of the sample for true multipoint two-photon excitation.

  12. Fiberless multicolor neural optoelectrode for in vivo circuit analysis

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

    2016-08-01

    Maximizing the potential of optogenetic approaches in deep brain structures of intact animals requires optical manipulation of neurons at high spatial and temporal resolutions, while simultaneously 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 modulation of the same neuronal population in vivo. We demonstrate successful device implementation by achieving efficient coupling between a side-emitting injection laser diode (ILD) and a dielectric optical waveguide mixer via a gradient-index (GRIN) lens. The use of GRIN lenses attains several design features, including high optical coupling and thermal isolation between ILDs and waveguides. We validated the packaged devices in the intact brain of anesthetized mice co-expressing Channelrhodopsin-2 and Archaerhodopsin in pyramidal cells in the hippocampal CA1 region, achieving high quality recording, activation and silencing of the exact same neurons in a given local region. This fully-integrated approach demonstrates the spatial precision and scalability needed to enable independent activation and silencing of the same or different groups of neurons in dense brain regions while simultaneously recording from them, thus considerably advancing the capabilities of currently available optogenetic toolsets.

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

    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.

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

    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.

  15. Incorporating Artificial Neural Networks in the dynamic thermal-hydraulic model of a controlled cryogenic circuit

    Carli, S.; Bonifetto, R.; Savoldi, L.; Zanino, R.

    2015-09-01

    A model based on Artificial Neural Networks (ANNs) is developed for the heated line portion of a cryogenic circuit, where supercritical helium (SHe) flows and that also includes a cold circulator, valves, pipes/cryolines and heat exchangers between the main loop and a saturated liquid helium (LHe) bath. The heated line mimics the heat load coming from the superconducting magnets to their cryogenic cooling circuits during the operation of a tokamak fusion reactor. An ANN is trained, using the output from simulations of the circuit performed with the 4C thermal-hydraulic (TH) code, to reproduce the dynamic behavior of the heated line, including for the first time also scenarios where different types of controls act on the circuit. The ANN is then implemented in the 4C circuit model as a new component, which substitutes the original 4C heated line model. For different operational scenarios and control strategies, a good agreement is shown between the simplified ANN model results and the original 4C results, as well as with experimental data from the HELIOS facility confirming the suitability of this new approach which, extended to an entire magnet systems, can lead to real-time control of the cooling loops and fast assessment of control strategies for heat load smoothing to the cryoplant.

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

    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.

  17. New Active Digital Pixel Circuit for CMOS Image Sensor

    2001-01-01

    A new active digital pixel circuit for CMOS image sensor is designed consisting of four components: a photo-transducer, a preamplifier, a sample & hold (S & H) circuit and an A/D converter with an inverter. It is optimized by simulation and adjustment based on 2μm standard CMOS process. Each circuit of the components is designed with specific parameters. The simulation results of the whole pixel circuits show that the circuit has such advantages as low distortion, low power consumption, and improvement of the output performances by using an inverter.

  18. Image-processing algorithms realized by discrete-time cellular neural networks and their circuit implementations

    In this study, eight image tasks: connected component detection (CCD) with down, right, +45o and -45o directions, edge detection, shadow projection with left and right directions and point removal are analyzed. These tasks are solved using the binary input and binary output discrete-time cellular neural networks (DTCNNs) associated with suitable templates. Furthermore, the behavior of the DTCNNs can be realized using Boolean functions, and the corresponding equivalent logic circuits are derived. An 8 x 8 DTCNNs-based image-processing chip is implemented by the FPGA technology. A simulation of the chip developed for the CCD task is also presented

  19. Developmental regulation of spatio-temporal patterns of cortical circuit activation

    Trevor Charles Griffen

    2013-01-01

    Full Text Available Neural circuits are refined in an experience-dependent manner during early postnatal development. How development modulates the spatio-temporal propagation of activity through cortical circuits is poorly understood. Here we use voltage sensitive dye imaging (VSD to show that there are significant changes in the spatio-temporal patterns of intracortical signals in primary visual cortex from postnatal day 13 (P13, eye opening, to P28, the peak of the critical period for rodent visual cortical plasticity. Upon direct stimulation of layer 4 (L4, activity spreads to L2/3 and to L5 at all ages. However, while from eye opening to the peak of the critical period, the amplitude and persistence of the voltage signal decrease, peak activation is reached more quickly and the interlaminar gain increases with age. The lateral spread of activation within layers remains unchanged throughout the time window under analysis. These developmental changes in spatio-temporal patterns of intracortical circuit activation are mediated by differences in the contributions of excitatory and inhibitory synaptic components. Our results demonstrate that after eye opening the circuit in primary visual cortex is refined through a progression of changes that shape the spatio-temporal patterns of circuit activation. Signals become more efficiently propagated across layers through developmentally regulated changes in interlaminar gain.

  20. A Circuit for Motor Cortical Modulation of Auditory Cortical Activity

    Nelson, Anders; Schneider, David M.; Takatoh, Jun; Sakurai, Katsuyasu; Wang, Fan; Mooney, Richard

    2013-01-01

    Normal hearing depends on the ability to distinguish self-generated sounds from other sounds, and this ability is thought to involve neural circuits that convey copies of motor command signals to various levels of the auditory system. Although such interactions at the cortical level are believed to facilitate auditory comprehension during movements and drive auditory hallucinations in pathological states, the synaptic organization and function of circuitry linking the motor and auditory corti...

  1. Analog Programmable Distance Calculation Circuit for Winner Takes All Neural Network Realized in the CMOS Technology.

    Talaśka, Tomasz; Kolasa, Marta; Długosz, Rafał; Pedrycz, Witold

    2016-03-01

    This paper presents a programmable analog current-mode circuit used to calculate the distance between two vectors of currents, following two distance measures. The Euclidean (L2) distance is commonly used. However, in many situations, it can be replaced with the Manhattan (L1) one, which is computationally less intensive, whose realization comes with less power dissipation and lower hardware complexity. The presented circuit can be easily reprogrammed to operate with one of these distances. The circuit is one of the components of an analog winner takes all neural network (NN) implemented in the complementary metal-oxide-semiconductor 0.18- [Formula: see text] technology. The learning process of the realized NN has been successfully verified by the laboratory tests of the fabricated chip. The proposed distance calculation circuit (DCC) features a simple structure, which makes it suitable for networks with a relatively large number of neurons realized in hardware and operating in parallel. For example, the network with three inputs occupies a relatively small area of 3900 μm(2). When operating in the L2 mode, the circuit dissipates 85 [Formula: see text] of power from the 1.5 V voltage supply, at maximum data rate of 10 MHz. In the L1 mode, an average dissipated power is reduced to 55 [Formula: see text] from 1.2 V voltage supply, while data rate is 12 MHz in this case. The given data rates are provided for the worst case scenario, where input currents differ by 1%-2% only. In this case, the settling time of the comparators used in the DCC is quite long. However, that kind of situation is very rare in the overall learning process. PMID:26087501

  2. Predicting conversion time of circuit design file by artificial neural networks

    Jang, Sung-Hoon; Lee, Jee-Hyong; Ahn, Byoung-Sup; Ki, Won-Tai; Choi, Ji-Hyeon; Woo, Sang-Gyun; Cho, Han-Ku

    2008-03-01

    GDSII is a data format of the circuit design file for producing semiconductor. GDSII is also used as a transfer format for fabricating photo mask as well. As design rules are getting smaller and RET (Resolution Enhancement Technology) is getting more complicated, the time of converting GDSII to a mask data format has been increased, which influences the period of mask production. Photo mask shops all over the world are widely using computer clusters which are connected through a network, that is, called distributed computing method, to reduce the converting time. Commonly computing resource for conversion is assigned based on the input file size. However, the result of experiments showed that the input file size was improper to predict the computing resource usage. In this paper, we propose the methodology of artificial intelligence with considering the properties of GDSII file to handle circuit design files more efficiently. The conversion time will be optimized by controlling the hardware resource for data conversion as long as the conversion time is predictable through analyzing the design data. Neural networks are used to predict the conversion time for this research. In this paper, the application of neural networks for the time prediction will be discussed and experimental results will be shown with comparing to statistical model based approaches.

  3. Relating functional connectivity in V1 neural circuits and 3D natural scenes using Boltzmann machines.

    Zhang, Yimeng; Li, Xiong; Samonds, Jason M; Lee, Tai Sing

    2016-03-01

    Bayesian theory has provided a compelling conceptualization for perceptual inference in the brain. Central to Bayesian inference is the notion of statistical priors. To understand the neural mechanisms of Bayesian inference, we need to understand the neural representation of statistical regularities in the natural environment. In this paper, we investigated empirically how statistical regularities in natural 3D scenes are represented in the functional connectivity of disparity-tuned neurons in the primary visual cortex of primates. We applied a Boltzmann machine model to learn from 3D natural scenes, and found that the units in the model exhibited cooperative and competitive interactions, forming a "disparity association field", analogous to the contour association field. The cooperative and competitive interactions in the disparity association field are consistent with constraints of computational models for stereo matching. In addition, we simulated neurophysiological experiments on the model, and found the results to be consistent with neurophysiological data in terms of the functional connectivity measurements between disparity-tuned neurons in the macaque primary visual cortex. These findings demonstrate that there is a relationship between the functional connectivity observed in the visual cortex and the statistics of natural scenes. They also suggest that the Boltzmann machine can be a viable model for conceptualizing computations in the visual cortex and, as such, can be used to predict neural circuits in the visual cortex from natural scene statistics. PMID:26712581

  4. Visual experience modulates spatio-temporal dynamics of circuit activation

    Arianna Maffei

    2011-06-01

    Full Text Available Persistent reduction in sensory drive in early development results in multiple plastic changes of different cortical synapses. How these experience-dependent modifications affect the spatio-temporal dynamics of signal propagation in neocortical circuits is poorly understood. Here we demonstrate that brief visual deprivation significantly affects the propagation of electrical signals in the primary visual cortex. The spatio-temporal spread of circuit activation upon direct stimulation of its input layer (Layer 4 is reduced, as is the activation of Layer 2/3 – the main recipient of the output from Layer 4. Our data suggest that the decrease in spatio-temporal activation of L2/3 depends on reduced L4 output, and is not intrinsically generated within L2/3. The data shown here suggest that changes in the synaptic components of the visual cortical circuit result not only in alteration of local integration of excitatory and inhibitory inputs, but also in a significant decrease in overall circuit activation. Furthermore, our data indicate a differential effect of visual deprivation on L4 and L2/3, suggesting that while feedforward activation of L2/3 is reduced, its activation by long range, within layer inputs is unaltered. Thus, brief visual deprivation induces experience-dependent circuit re-organization by modulating not only circuit excitability, but also the spatio-temporal patterns of cortical activation within and between layers.

  5. Analysis of complex neural circuits with nonlinear multidimensional hidden state models.

    Friedman, Alexander; Slocum, Joshua F; Tyulmankov, Danil; Gibb, Leif G; Altshuler, Alex; Ruangwises, Suthee; Shi, Qinru; Toro Arana, Sebastian E; Beck, Dirk W; Sholes, Jacquelyn E C; Graybiel, Ann M

    2016-06-01

    A universal need in understanding complex networks is the identification of individual information channels and their mutual interactions under different conditions. In neuroscience, our premier example, networks made up of billions of nodes dynamically interact to bring about thought and action. Granger causality is a powerful tool for identifying linear interactions, but handling nonlinear interactions remains an unmet challenge. We present a nonlinear multidimensional hidden state (NMHS) approach that achieves interaction strength analysis and decoding of networks with nonlinear interactions by including latent state variables for each node in the network. We compare NMHS to Granger causality in analyzing neural circuit recordings and simulations, improvised music, and sociodemographic data. We conclude that NMHS significantly extends the scope of analyses of multidimensional, nonlinear networks, notably in coping with the complexity of the brain. PMID:27222584

  6. Lyapunov exponents from CHUA's circuit time series using artificial neural networks

    Gonzalez, J. Jesus; Espinosa, Ismael E.; Fuentes, Alberto M.

    1995-01-01

    In this paper we present the general problem of identifying if a nonlinear dynamic system has a chaotic behavior. If the answer is positive the system will be sensitive to small perturbations in the initial conditions which will imply that there is a chaotic attractor in its state space. A particular problem would be that of identifying a chaotic oscillator. We present an example of three well known different chaotic oscillators where we have knowledge of the equations that govern the dynamical systems and from there we can obtain the corresponding time series. In a similar example we assume that we only know the time series and, finally, in another example we have to take measurements in the Chua's circuit to obtain sample points of the time series. With the knowledge about the time series the phase plane portraits are plotted and from them, by visual inspection, it is concluded whether or not the system is chaotic. This method has the problem of uncertainty and subjectivity and for that reason a different approach is needed. A quantitative approach is the computation of the Lyapunov exponents. We describe several methods for obtaining them and apply a little known method of artificial neural networks to the different examples mentioned above. We end the paper discussing the importance of the Lyapunov exponents in the interpretation of the dynamic behavior of biological neurons and biological neural networks.

  7. Recruitment of Polysynaptic Connections Underlies Functional Recovery of a Neural Circuit after Lesion

    Tamvacakis, Arianna N.

    2016-01-01

    Abstract The recruitment of additional neurons to neural circuits often occurs in accordance with changing functional demands. Here we found that synaptic recruitment plays a key role in functional recovery after neural injury. Disconnection of a brain commissure in the nudibranch mollusc, Tritonia diomedea, impairs swimming behavior by eliminating particular synapses in the central pattern generator (CPG) underlying the rhythmic swim motor pattern. However, the CPG functionally recovers within a day after the lesion. The strength of a spared inhibitory synapse within the CPG from Cerebral Neuron 2 (C2) to Ventral Swim Interneuron B (VSI) determines the level of impairment caused by the lesion, which varies among individuals. In addition to this direct synaptic connection, there are polysynaptic connections from C2 and Dorsal Swim Interneurons to VSI that provide indirect excitatory drive but play only minor roles under normal conditions. After disconnecting the pedal commissure (Pedal Nerve 6), the recruitment of polysynaptic excitation became a major source of the excitatory drive to VSI. Moreover, the amount of polysynaptic recruitment, which changed over time, differed among individuals and correlated with the degree of recovery of the swim motor pattern. Thus, functional recovery was mediated by an increase in the magnitude of polysynaptic excitatory drive, compensating for the loss of direct excitation. Since the degree of susceptibility to injury corresponds to existing individual variation in the C2 to VSI synapse, the recovery relied upon the extent to which the network reorganized to incorporate additional synapses.

  8. Manipulating neural activity in physiologically classified neurons: triumphs and challenges.

    Gore, Felicity; Schwartz, Edmund C; Salzman, C Daniel

    2015-09-19

    Understanding brain function requires knowing both how neural activity encodes information and how this activity generates appropriate responses. Electrophysiological, imaging and immediate early gene immunostaining studies have been instrumental in identifying and characterizing neurons that respond to different sensory stimuli, events and motor actions. Here we highlight approaches that have manipulated the activity of physiologically classified neurons to determine their role in the generation of behavioural responses. Previous experiments have often exploited the functional architecture observed in many cortical areas, where clusters of neurons share response properties. However, many brain structures do not exhibit such functional architecture. Instead, neurons with different response properties are anatomically intermingled. Emerging genetic approaches have enabled the identification and manipulation of neurons that respond to specific stimuli despite the lack of discernable anatomical organization. These approaches have advanced understanding of the circuits mediating sensory perception, learning and memory, and the generation of behavioural responses by providing causal evidence linking neural response properties to appropriate behavioural output. However, significant challenges remain for understanding cognitive processes that are probably mediated by neurons with more complex physiological response properties. Currently available strategies may prove inadequate for determining how activity in these neurons is causally related to cognitive behaviour. PMID:26240431

  9. Diffusion models and neural activity

    Ricciardi, L. M.; Lánský, Petr

    London : Nature publishing group, 2003 - (Nadel, L.), s. 968-972 ISBN 0-333-79261-0 R&D Projects: GA ČR GA309/02/0168 Institutional research plan: CEZ:AV0Z5011922 Keywords : Neuronal activity, Diffusion model Subject RIV: ED - Physiology

  10. Neural Dysfunction in Cognitive Control Circuits in Persons at Clinical High-Risk for Psychosis.

    Colibazzi, Tiziano; Horga, Guillermo; Wang, Zhishun; Huo, Yuankai; Corcoran, Cheryl; Klahr, Kristin; Brucato, Gary; Girgis, Ragy; Gill, Kelly; Abi-Dargham, Anissa; Peterson, Bradley S

    2016-04-01

    Cognitive control, a set of functions that develop throughout adolescence, is important in the pathogenesis of psychotic disorders. Whether cognitive control has a role in conferring vulnerability for the development of psychotic illness is still unknown. The aim of this study was to investigate the neural systems supporting cognitive control in individuals deemed to be potentially prodromal for psychotic illness. We recruited 56 participants at clinical high-risk (CHR) for psychosis based on the Structured Interview for Psychosis-Risk Syndromes (SIPS) and 49 healthy controls. Twelve of the CHR participants eventually developed psychosis. We compared functional magnetic resonance imaging (fMRI) BOLD signal during the performance of the Simon task. We tested for differences between CHR individuals and controls in conflict-related functional activity. In the CHR group when compared with controls, we detected smaller conflict-related activations in several cortical areas, including the Dorsolateral Prefrontal Cortex (DLPFC). Furthermore, conflict-related activations in the DLPFC of those CHR individuals who ultimately developed psychosis (CHR converters) were smaller than in non-converters (CHR non-converters). Higher levels of conflict-related activation were associated with better social and role outcome. Risk for psychosis was associated at the neural level with reduced conflict-related brain activity. This neural phenotype appears correlated within the DLPFC with the development of psychosis and with functional outcome. PMID:26354046

  11. Circuit Design: An inquiry lab activity at Maui Community College

    Morzinski, Katie; Azucena, Oscar; Downs, Cooper; Favaloro, Tela; Park, Jung; U, Vivian

    2010-01-01

    We present an inquiry lab activity on Circuit Design that was conducted in Fall 2009 with first-year community college students majoring in Electrical Engineering Technology. This inquiry emphasized the use of engineering process skills, including circuit assembly and problem solving, while learning technical content. Content goals of the inquiry emphasized understanding voltage dividers (Kirchoff's voltage law) and analysis and optimization of resistive networks (Thevenin equivalence). We as...

  12. Visual Experience Modulates Spatio-Temporal Dynamics of Circuit Activation

    Wang, Lang; Fontanini, Alfredo; Maffei, Arianna

    2011-01-01

    Persistent reduction in sensory drive in early development results in multiple plastic changes of different cortical synapses. How these experience-dependent modifications affect the spatio-temporal dynamics of signal propagation in neocortical circuits is poorly understood. Here we demonstrate that brief visual deprivation significantly affects the propagation of electrical signals in the primary visual cortex. The spatio-temporal spread of circuit activation upon direct stimulation of its i...

  13. Visual experience modulates spatio-temporal dynamics of circuit activation

    Arianna Maffei

    2011-01-01

    Persistent reduction in sensory drive in early development results in multiple plastic changes of different cortical synapses. How these experience-dependent modifications affect the spatio-temporal dynamics of signal propagation in neocortical circuits is poorly understood. Here we demonstrate that brief visual deprivation significantly affects the propagation of electrical signals in the primary visual cortex. The spatio-temporal spread of circuit activation upon direct stimulation of its i...

  14. Information transmission in oscillatory neural activity

    Koepsell, Kilian

    2008-01-01

    Periodic neural activity not locked to the stimulus or to motor responses is usually ignored. Here, we present new tools for modeling and quantifying the information transmission based on periodic neural activity that occurs with quasi-random phase relative to the stimulus. We propose a model to reproduce characteristic features of oscillatory spike trains, such as histograms of inter-spike intervals and phase locking of spikes to an oscillatory influence. The proposed model is based on an inhomogeneous Gamma process governed by a density function that is a product of the usual stimulus-dependent rate and a quasi-periodic function. Further, we present an analysis method generalizing the direct method (Rieke et al, 1999; Brenner et al, 2000) to assess the information content in such data. We demonstrate these tools on recordings from relay cells in the lateral geniculate nucleus of the cat.

  15. Neural activity associated with self-reflection

    Herwig Uwe; Kaffenberger Tina; Schell Caroline; Jäncke Lutz; Brühl Annette B

    2012-01-01

    Abstract Background Self-referential cognitions are important for self-monitoring and self-regulation. Previous studies have addressed the neural correlates of self-referential processes in response to or related to external stimuli. We here investigated brain activity associated with a short, exclusively mental process of self-reflection in the absence of external stimuli or behavioural requirements. Healthy subjects reflected either on themselves, a personally known or an unknown person dur...

  16. Measurements of the Effects of Smoke on Active Circuits

    Smoke has long been recognized as the most common source of fire damage to electrical equipment; however, most failures have been analyzed after the fire was out and the smoke vented. The effects caused while the smoke is still in the air have not been explored. Such effects have implications for new digital equipment being installed in nuclear reactors. The U.S. Nuclear Regulatory Commission is sponsoring work to determine the impact of smoke on digital instrumentation and control. As part of this program, Sandia National Laboratories has tested simple active circuits to determine how smoke affects them. These tests included the study of three possible failure modes on a functional board: (1) circuit bridging, (2) corrosion (metal loss), and (3) induction of stray capacitance. The performance of nine different circuits was measured continuously on bare and conformably coated boards during smoke exposures lasting 1 hour each and continued for 24 hours after the exposure started. The circuit that was most affected by smoke (100% change in measured values) was the one most sensitive to circuit bridging. Its high impedance (50 MOmega) was shorted during the exposure, but in some cases recovered after the smoke was vented. The other two failure modes, corrosion and induced stray capacitance, caused little change in the function of the circuits. The smoke permanently increased resistance of the circuit tested for corrosion, implying that the cent acts were corroded. However, the change was very small (< 2%). The stray-capacitance test circuit showed very little change after a smoke exposure in either the short or long term. The results of the tests suggest that conformal coatings and type of circuit are major considerations when designing digital circuitry to be used in critical control systems

  17. Measurements of the Effects of Smoke on Active Circuits

    Tanaka, T.J.

    1999-02-09

    Smoke has long been recognized as the most common source of fire damage to electrical equipment; however, most failures have been analyzed after the fire was out and the smoke vented. The effects caused while the smoke is still in the air have not been explored. Such effects have implications for new digital equipment being installed in nuclear reactors. The U.S. Nuclear Regulatory Commission is sponsoring work to determine the impact of smoke on digital instrumentation and control. As part of this program, Sandia National Laboratories has tested simple active circuits to determine how smoke affects them. These tests included the study of three possible failure modes on a functional board: (1) circuit bridging, (2) corrosion (metal loss), and (3) induction of stray capacitance. The performance of nine different circuits was measured continuously on bare and conformably coated boards during smoke exposures lasting 1 hour each and continued for 24 hours after the exposure started. The circuit that was most affected by smoke (100% change in measured values) was the one most sensitive to circuit bridging. Its high impedance (50 M{Omega}) was shorted during the exposure, but in some cases recovered after the smoke was vented. The other two failure modes, corrosion and induced stray capacitance, caused little change in the function of the circuits. The smoke permanently increased resistance of the circuit tested for corrosion, implying that the cent acts were corroded. However, the change was very small (< 2%). The stray-capacitance test circuit showed very little change after a smoke exposure in either the short or long term. The results of the tests suggest that conformal coatings and type of circuit are major considerations when designing digital circuitry to be used in critical control systems.

  18. Measurements of the effects of smoke on active circuits

    Smoke has long been recognized as the most common source of fire damage to electrical equipment; however, most failures have been analyzed after the fire was out and the smoke vented. The effects caused while the smoke is still in the air have not been explored. Such effects have implications for new digital equipment being installed in nuclear reactors. The US Nuclear Regulatory Commission is sponsoring work to determine the impact of smoke on digital instrumentation and control. As part of this program, Sandia National Laboratories has tested simple active circuits to determine how smoke affects them. These tests included the study of three possible failure modes on a functional board: (1) circuit bridging, (2) corrosion (metal loss), and (3) induction of stray capacitance. The performance of nine different circuits was measured continuously on bare and conformally coated boards during smoke exposures lasting 1 hour each and continued for 24 hours after the exposure started. The circuit that was most affected by smoke (100% change in measured values) was the one most sensitive to circuit bridging. Its high impedance (50 Mohm) was shorted during the exposure, but in some cases recovered after the smoke was vented. The other two failure modes, corrosion and induced stray capacitance, caused little change in the function of the circuits. The smoke permanently increased resistance of the circuit tested for corrosion, implying that the contacts were corroded. However, the change was very small (< 2%). The stray capacitance test circuit showed very little change after a smoke exposure in either the short or long term. The results of the tests suggest that conformal coatings and type of circuit are major considerations when designing digital circuitry to be used in critical control systems

  19. Mouse vision as a gateway for understanding how experience shapes neural circuits

    Priebe, Nicholas J; McGee, Aaron W.

    2014-01-01

    Genetic programs controlling ontogeny drive many of the essential connectivity patterns within the brain. Yet it is activity, derived from the experience of interacting with the world, that sculpts the precise circuitry of the central nervous system. Such experience-dependent plasticity has been observed throughout the brain but has been most extensively studied in the neocortex. A prime example of this refinement of neural circuitry is found in primary visual cortex (V1), where functional co...

  20. MOUSE VISION AS A GATEWAY FOR UNDERSTANDING HOW EXPERIENCE SHAPES NEURAL CIRCUITS

    Nicholas Priebe; McGee, Aaron W.

    2014-01-01

    Genetic programs controlling ontogeny drive many of the essential connectivity patterns within the brain. Yet it is activity, derived from the experience of interacting with the world, that sculpts the precise circuitry of the central nervous system. Such experience-dependent plasticity has been observed throughout the brain but has been most extensively studied in the neocortex. A prime example of this refinement of neural circuitry is found in primary visual cortex (V1), where functional c...

  1. Local circuit neurons in the striatum regulate neural and behavioral responses to dopaminergic stimulation

    Saka, E.; Iadarola, M.; FitzGerald, D J; Graybiel, A M

    2002-01-01

    Interneurons are critical for shaping neuronal circuit activity in many parts of the central nervous system. To study interneuron function in the basal ganglia, we tested and characterized an NK-1 receptor-based method for targeted ablation of specific classes of interneuron in the striatum. Our findings demonstrate that the neurotoxin SP-PE35, a substance P–Pseudomonas exotoxin conjugate, selectively targets striatal cholinergic and nitric oxide synthase/somatostatinergic interneurons when i...

  2. Circuit Design: An inquiry lab activity at Maui Community College

    Morzinski, Katie; Downs, Cooper; Favaloro, Tela; Park, Jung; U, Vivian

    2010-01-01

    We present an inquiry lab activity on Circuit Design that was conducted in Fall 2009 with first-year community college students majoring in Electrical Engineering Technology. This inquiry emphasized the use of engineering process skills, including circuit assembly and problem solving, while learning technical content. Content goals of the inquiry emphasized understanding voltage dividers (Kirchoff's voltage law) and analysis and optimization of resistive networks (Thevenin equivalence). We assumed prior exposure to series and parallel circuits and Ohm's law (the relationship between voltage, current, and resistance) and designed the inquiry to develop these skills. The inquiry utilized selection of engineering challenges on a specific circuit (the Wheatstone Bridge) to realize these learning goals. Students generated questions and observations during the starters, which were categorized into four engineering challenges or design goals. The students formed teams and chose one challenge to focus on during the i...

  3. MOUSE VISION AS A GATEWAY FOR UNDERSTANDING HOW EXPERIENCE SHAPES NEURAL CIRCUITS

    Nicholas Priebe

    2014-10-01

    Full Text Available Genetic programs controlling ontogeny drive many of the essential connectivity patterns within the brain. Yet it is activity, derived from the experience of interacting with the world, that sculpts the precise circuitry of the central nervous system. Such experience-dependent plasticity has been observed throughout the brain but has been most extensively studied in the neocortex. A prime example of this refinement of neural circuitry is found in primary visual cortex (V1, where functional connectivity changes have been observed both during development and in adulthood. The mouse visual system has become a predominant model for investigating the principles that underlie experience-dependent plasticity, given the general conservation of visual neural circuitry across mammals as well as the powerful tools and techniques recently developed for use in rodent. The genetic tractability of mice has permitted the identification of signaling pathways that translate experience-driven activity patterns into changes in circuitry. Further, the accessibility of visual cortex has allowed neural activity to be manipulated with optogenetics and observed with genetically-encoded calcium sensors. Consequently, mouse visual cortex has become one of the dominant platforms to study experience-dependent plasticity.

  4. Mouse vision as a gateway for understanding how experience shapes neural circuits.

    Priebe, Nicholas J; McGee, Aaron W

    2014-01-01

    Genetic programs controlling ontogeny drive many of the essential connectivity patterns within the brain. Yet it is activity, derived from the experience of interacting with the world, that sculpts the precise circuitry of the central nervous system. Such experience-dependent plasticity has been observed throughout the brain but has been most extensively studied in the neocortex. A prime example of this refinement of neural circuitry is found in primary visual cortex (V1), where functional connectivity changes have been observed both during development and in adulthood. The mouse visual system has become a predominant model for investigating the principles that underlie experience-dependent plasticity, given the general conservation of visual neural circuitry across mammals as well as the powerful tools and techniques recently developed for use in rodent. The genetic tractability of mice has permitted the identification of signaling pathways that translate experience-driven activity patterns into changes in circuitry. Further, the accessibility of visual cortex has allowed neural activity to be manipulated with optogenetics and observed with genetically-encoded calcium sensors. Consequently, mouse visual cortex has become one of the dominant platforms to study experience-dependent plasticity. PMID:25324730

  5. A point-process response model for spike trains from single neurons in neural circuits under optogenetic stimulation.

    Luo, X; Gee, S; Sohal, V; Small, D

    2016-02-10

    Optogenetics is a new tool to study neuronal circuits that have been genetically modified to allow stimulation by flashes of light. We study recordings from single neurons within neural circuits under optogenetic stimulation. The data from these experiments present a statistical challenge of modeling a high-frequency point process (neuronal spikes) while the input is another high-frequency point process (light flashes). We further develop a generalized linear model approach to model the relationships between two point processes, employing additive point-process response functions. The resulting model, point-process responses for optogenetics (PRO), provides explicit nonlinear transformations to link the input point process with the output one. Such response functions may provide important and interpretable scientific insights into the properties of the biophysical process that governs neural spiking in response to optogenetic stimulation. We validate and compare the PRO model using a real dataset and simulations, and our model yields a superior area-under-the-curve value as high as 93% for predicting every future spike. For our experiment on the recurrent layer V circuit in the prefrontal cortex, the PRO model provides evidence that neurons integrate their inputs in a sophisticated manner. Another use of the model is that it enables understanding how neural circuits are altered under various disease conditions and/or experimental conditions by comparing the PRO parameters. PMID:26411923

  6. Optical Neural Interfaces

    Warden, Melissa R.; Cardin, Jessica A.; Deisseroth, Karl

    2014-01-01

    Genetically encoded optical actuators and indicators have changed the landscape of neuroscience, enabling targetable control and readout of specific components of intact neural circuits in behaving animals. Here, we review the development of optical neural interfaces, focusing on hardware designed for optical control of neural activity, integrated optical control and electrical readout, and optical readout of population and single-cell neural activity in freely moving mammals.

  7. Neural mechanisms of the nucleus accumbens circuit in reward and aversive learning.

    Hikida, Takatoshi; Morita, Makiko; Macpherson, Tom

    2016-07-01

    The basal ganglia are key neural substrates not only for motor function, but also cognitive functions including reward and aversive learning. Critical for these processes are the functional role played by two projection neurons within nucleus accumbens (NAc); the D1- and D2-expressing neurons. Recently, we have developed a novel reversible neurotransmission blocking technique that specifically blocks neurotransmission from NAc D1- and D2-expressing neurons, allowing for in vivo analysis. In this review, we outline the functional dissociation of NAc D1- and D2-expressing neurons of the basal ganglia in reward and aversive learning, as well as drug addiction. These studies have revealed the importance of activation of NAc D1 receptors for reward learning and drug addiction, and inactivation of NAc D2 receptors for aversive learning and flexibility. Based on these findings, we propose a neural mechanism, in which dopamine neurons in the ventral tegmental area that send inputs to the NAc work as a switch between D1- and D2-expressing neurons. These basal ganglia neural mechanisms will give us new insights into the pathophysiology of neuropsychiatric diseases. PMID:26827817

  8. What genetic model organisms offer the study of behavior and neural circuits.

    White, Benjamin H

    2016-06-01

    The past decade has witnessed the development of powerful, genetically encoded tools for manipulating and monitoring neuronal function in freely moving animals. These tools are most readily deployed in genetic model organisms and efforts to map the circuits that govern behavior have increasingly focused on worms, flies, zebrafish, and mice. The traditional virtues of these animals for genetic studies in terms of small size, short generation times, and ease of animal husbandry in a laboratory setting have facilitated rapid progress, and the neural basis of an increasing number of behaviors is being established at cellular resolution in each of these animals. The depth and breadth of this analysis should soon offer a significantly more comprehensive understanding of how the circuitry underlying behavior is organized in particular animals and promises to help answer long-standing questions that have waited for such a brain-wide perspective on nervous system function. The comprehensive understanding achieved in genetic model animals is thus likely to make them into paradigmatic examples that will serve as touchstones for comparisons to understand how behavior is organized in other animals, including ourselves. PMID:27328841

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

    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.

  10. A Dual Infection Pseudorabies Virus Conditional Reporter Approach to Identify Projections to Collateralized Neurons in Complex Neural Circuits

    J Patrick Card; Oren Kobiler; Ludmir, Ethan B.; Vedant Desai; Sved, Alan F.; Enquist, Lynn W.

    2011-01-01

    Replication and transneuronal transport of pseudorabies virus (PRV) are widely used to define the organization of neural circuits in rodent brain. Here we report a dual infection approach that highlights connections to neurons that collateralize within complex networks. The method combines Cre recombinase (Cre) expression from a PRV recombinant (PRV-267) and Cre-dependent reporter gene expression from a second infecting strain of PRV (PRV-263). PRV-267 expresses both Cre and a monomeric red f...

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

    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. PMID:27185915

  12. Long-range neural activity evoked by premotor cortex stimulation: a TMS/EEG co-registration study

    Marco eZanon

    2013-11-01

    Full Text Available The premotor cortex is one of the fundamental structures composing the neural networks of the human brain. It is implicated in many behaviors and cognitive tasks, ranging from movement to attention and eye-related activity. Therefore, neural circuits that are related to premotor cortex have been studied to clarify their connectivity and/or role in different tasks. In the present work, we aimed to investigate the propagation of the neural activity evoked in the dorsal premotor cortex using transcranial magnetic stimulation/electroencephalography (TMS/EEG. Towards this end, interest was focused on the neural dynamics elicited in long-ranging temporal and spatial networks. Twelve healthy volunteers underwent a single-pulse TMS protocol in a resting condition with eyes closed, and the evoked activity, measured by EEG, was compared to a sham condition in a time window ranging from 45 msec to about 200 msec after TMS. Spatial and temporal investigations were carried out with sLORETA. TMS was found to induce propagation of neural activity mainly in the contralateral sensorimotor and frontal cortices, at about 130 msec after delivery of the stimulus. Different types of analyses showed propagated activity also in posterior, mainly visual, regions, in a time window between 70 and 130 msec. Finally, a likely rebounding activation of the sensorimotor and frontal regions, was observed in various time ranges. Taken together, the present findings further characterize the neural circuits that are driven by dorsal premotor cortex activation in healthy humans.

  13. Neural circuits containing olfactory neurons are involved in prepulse inhibition of the startle reflex in rats

    Haichen eNiu

    2015-03-01

    Full Text Available Many neuropsychiatric disorders, such as schizophrenia, have been associated with abnormalities in the function of the olfactory system and prepulse inhibition (PPI of the startle reflex. However, whether these two abnormalities are related is unclear. The present study was designed to determine whether inhibiting olfactory sensory input via the infusion of zinc sulfate (ZnE, 0.17 M, 0.5 ml into the olfactory naris disrupts PPI. Furthermore, lidocaine/MK801 was bilaterally microinjected into the olfactory bulb (OB to examine whether the blockade of olfactory sensory input impairs PPI. To identify the neural projections that connect the olfaction- and PPI-related areas of the CNS, trans-synaptic retrograde tracing using a recombinant pseudorabies virus (PRV was performed. Our results demonstrated that blocking olfactory sensory input altered olfaction-related behavior. At the functional level, we demonstrated that the inhibition of olfactory sensory input impaired PPI of the startle response subsequent to a decrease in c-fos expression in relevant brain regions. Furthermore, the results of a similar and more robust experiment indicated that blocking olfactory sensory input via the microinjection of lidocaine/MK801 into the OB impaired PPI. At the circuit level, based on trans-synaptic retrograde tracing using PRV, we demonstrated that a large portion of the labeled neurons in several regions of the olfactory cortices connected to the pedunculopontine tegmental nucleus (PPTg. Thus, these data suggest that the olfactory system participates in the regulation of PPI and plays a role in the effect of PPI on the startle response in rats.

  14. Single-Cell Memory Regulates a Neural Circuit for Sensory Behavior

    Kyogo Kobayashi

    2016-01-01

    Full Text Available Unveiling the molecular and cellular mechanisms underlying memory has been a challenge for the past few decades. Although synaptic plasticity is proven to be essential for memory formation, the significance of “single-cell memory” still remains elusive. Here, we exploited a primary culture system for the analysis of C. elegans neurons and show that a single thermosensory neuron has an ability to form, retain, and reset a temperature memory. Genetic and proteomic analyses found that the expression of the single-cell memory exhibits inter-individual variability, which is controlled by the evolutionarily conserved CaMKI/IV and Raf pathway. The variable responses of a sensory neuron influenced the neural activity of downstream interneurons, suggesting that modulation of the sensory neurons ultimately determines the behavioral output in C. elegans. Our results provide proof of single-cell memory and suggest that the individual differences in neural responses at the single-cell level can confer individuality.

  15. Comprehensive figures of merit for passive and active plasmonic circuits

    Krasavin, Alexey V.; Zayats, Anatoly V.

    2015-01-01

    In this article a comprehensive figures of merit for both passive and active plasmonic circuit components are introduced, benchmarking their performance for the realisation of high-bandwidth optical data communication in electronic chips. For the first time the figure of merit for passive plasmonic interconnects has been derived in terms of ultimate global characteristics of the plasmonic circuitry, particularly bandwidth and power consumption densities. Then, these parameters were linked to ...

  16. Exposure to Forced Swim Stress Alters Local Circuit Activity and Plasticity in the Dentate Gyrus of the Hippocampus

    Orli Yarom

    2008-01-01

    Full Text Available Studies have shown that, depending on its severity and context, stress can affect neural plasticity. Most related studies focused on synaptic plasticity and long-term potentiation (LTP of principle cells. However, evidence suggests that following high-frequency stimulation, which induces LTP in principal cells, modifications also take place at the level of complex interactions with interneurons within the dentate gyrus, that is, at the local circuit level. So far, the possible effects of stress on local circuit activity and plasticity were not studied. Therefore, we set out to examine the possible alterations in local circuit activity and plasticity following exposure to stress. Local circuit activity and plasticity were measured by using frequency dependant inhibition (FDI and commissural modulation protocols following exposure to a 15 minute-forced swim trial. Exposure to stress did not alter FDI. The application of theta-burst stimulation (TBS reduced FDI in both control and stressed rats, but this type of plasticity was greater in stressed rats. Commissural-induced inhibition was significantly higher in stressed rats both before and after applying theta-burst stimulation. These findings indicate that the exposure to acute stress affects aspects of local circuit activity and plasticity in the dentate gyrus. It is possible that these alterations underlie some of the behavioral consequences of the stress experience.

  17. Identifying Emotions on the Basis of Neural Activation.

    Kassam, Karim S; Markey, Amanda R; Cherkassky, Vladimir L; Loewenstein, George; Just, Marcel Adam

    2013-01-01

    We attempt to determine the discriminability and organization of neural activation corresponding to the experience of specific emotions. Method actors were asked to self-induce nine emotional states (anger, disgust, envy, fear, happiness, lust, pride, sadness, and shame) while in an fMRI scanner. Using a Gaussian Naïve Bayes pooled variance classifier, we demonstrate the ability to identify specific emotions experienced by an individual at well over chance accuracy on the basis of: 1) neural activation of the same individual in other trials, 2) neural activation of other individuals who experienced similar trials, and 3) neural activation of the same individual to a qualitatively different type of emotion induction. Factor analysis identified valence, arousal, sociality, and lust as dimensions underlying the activation patterns. These results suggest a structure for neural representations of emotion and inform theories of emotional processing. PMID:23840392

  18. Successful reconstruction of a physiological circuit with known connectivity from spiking activity alone.

    Felipe Gerhard

    Full Text Available Identifying the structure and dynamics of synaptic interactions between neurons is the first step to understanding neural network dynamics. The presence of synaptic connections is traditionally inferred through the use of targeted stimulation and paired recordings or by post-hoc histology. More recently, causal network inference algorithms have been proposed to deduce connectivity directly from electrophysiological signals, such as extracellularly recorded spiking activity. Usually, these algorithms have not been validated on a neurophysiological data set for which the actual circuitry is known. Recent work has shown that traditional network inference algorithms based on linear models typically fail to identify the correct coupling of a small central pattern generating circuit in the stomatogastric ganglion of the crab Cancer borealis. In this work, we show that point process models of observed spike trains can guide inference of relative connectivity estimates that match the known physiological connectivity of the central pattern generator up to a choice of threshold. We elucidate the necessary steps to derive faithful connectivity estimates from a model that incorporates the spike train nature of the data. We then apply the model to measure changes in the effective connectivity pattern in response to two pharmacological interventions, which affect both intrinsic neural dynamics and synaptic transmission. Our results provide the first successful application of a network inference algorithm to a circuit for which the actual physiological synapses between neurons are known. The point process methodology presented here generalizes well to larger networks and can describe the statistics of neural populations. In general we show that advanced statistical models allow for the characterization of effective network structure, deciphering underlying network dynamics and estimating information-processing capabilities.

  19. An active control synchronization for two modified Chua circuits

    Li, Guo-Hui

    2005-03-01

    From modern control theory, an active control method to synchronize two modified Chua circuits with each other, which exhibit chaos, is presented. Some sufficient conditions of linear stability of the chaotic synchronization are obtained from rigorous mathematic justification. On the basis of the state-observer, the controller is analytically deduced using the active control. It is shown that this technique can be applied to achieve synchronization of the two systems with each other, whether they are identical or not. Finally, numerical simulations show the effectiveness of the proposed control scheme.

  20. An active control synchronization for two modified Chua circuits

    Li Guo-Hui

    2005-01-01

    From modern control theory, an active control method to synchronize two modified Chua circuits with each other, which exhibit chaos, is presented. Some sufficient conditions of linear stability of the chaotic synchronization are obtained from rigorous mathematic justification. On the basis of the state-observer, the controller is analytically deduced using the active control. It is shown that this technique can be applied to achieve synchroniztion of the tow systems with each other, whether they are identical or not. Finally, numerical simulations show the effectiveness of the proposed control scheme.

  1. Active Snubber Circuit for High Power Inverter Leg

    Rasmussen, Tonny Wederberg; Johansen, Morten Holst

    2009-01-01

    Abstract— High power converters in the conventional 6 pulse configuration with 6 switching elements IGBTs (Insulated Gate Bipolar Transistor) are pushed to the limit of power. Especially the switching loss is high. This reduces the switching frequency due to cooling problems. Passive snubber...... circuits have been introduced to reduce the loss even though some of the loss is removed from the IGBT to the snubber resistance. This paper takes also the next step to introduce the active Undeland snubber which in principle is lossless. The paper describes this solution together with some simulations...... indicating that the switching loss is reduced. Comparison between hard switched, passive and active snubber is done....

  2. Activity patterns of cultured neural networks on micro electrode arrays

    Rutten, W.L.C.; Pelt, van J.

    2001-01-01

    A hybrid neuro-electronic interface is a cell-cultured micro electrode array, acting as a neural information transducer for stimulation and/or recording of neural activity in the brain or the spinal cord (ventral motor region or dorsal sensory region). It consists of an array of micro electrodes on

  3. Active Match Load Circuit Intended for Testing Piezoelectric Transformers

    Andersen, Thomas; Rødgaard, Martin Schøler; Andersen, Michael A. E.

    2012-01-01

    An adjustable high voltage active load circuit for voltage amplitudes above 100 volts, especially intended for resistive matching the output impedance of a piezoelectric transformer (PT) is proposed in this paper. PTs have been around for over 50 years, were C. A. Rosen is common known for his...... famous Rosen type design back in the 1950s. After the discovered of new piezoelectric materials and new PT designs have been invented, the PT based power converters are in the area where they can outperform tradition electromagnetic based converters in certain applications. The performance of PTs can...

  4. The use of brain imaging to elucidate neural circuit changes in cocaine addiction

    Hanlon, Colleen A; Canterberry, Melanie

    2012-01-01

    Within substance abuse, neuroimaging has experienced tremendous growth as both a research method and a clinical tool in the last decade. The application of functional imaging methods to cocaine dependent patients and individuals in treatment programs, has revealed that the effects of cocaine are not limited to dopamine-rich subcortical structures, but that the cortical projection areas are also disrupted in cocaine dependent patients. In this review, we will first describe several of the imaging methods that are actively being used to address functional and structural abnormalities in addiction. This will be followed by an overview of the cortical and subcortical brain regions that are most often cited as dysfunctional in cocaine users. We will also introduce functional connectivity analyses currently being used to investigate interactions between these cortical and subcortical areas in cocaine users and abstainers. Finally, this review will address recent research which demonstrates that alterations in the functional connectivity in cocaine users may be associated with structural pathology in these circuits, as demonstrated through diffusion tensor imaging. Through the use of these tools in both a basic science setting and as applied to treatment seeking individuals, we now have a greater understanding of the complex cortical and subcortical networks which contribute to the stages of initial craving, dependence, abstinence, and relapse. Although the ability to use neuroimaging to predict treatment response or identify vulnerable populations is still in its infancy, the next decade holds tremendous promise for using neuroimaging to tailor either behavioral or pharmacologic treatment interventions to the individual. PMID:23162375

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

    Gregg W. Crabtree

    2014-11-01

    Full Text Available 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 towards a likely dominant role of short-term synaptic plasticity alterations in schizophrenia while dysfunction in autism spectrum disorders may be due to a combination of both short-term and long-term synaptic plasticity alterations.

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

    Wiebke Potjans

    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.

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

    Potjans, Wiebke; Morrison, Abigail; Diesmann, Markus

    2010-01-01

    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. PMID:21151370

  8. Active quenching circuit for a InGaAs single-photon avalanche diode

    We present a novel gated operation active quenching circuit (AQC). In order to simulate the quenching circuit a complete SPICE model of a InGaAs SPAD is set up according to the I–V characteristic measurement results of the detector. The circuit integrated with aROIC (readout integrated circuit) is fabricated in an CSMC 0.5 μm CMOS process and then hybrid packed with the detector. Chip measurement results show that the functionality of the circuit is correct and the performance is suitable for practical system applications. (semiconductor integrated circuits)

  9. Comprehensive figures of merit for passive and active plasmonic circuits

    Krasavin, Alexey V

    2015-01-01

    In this article a comprehensive figures of merit for both passive and active plasmonic circuit components are introduced, benchmarking their performance for the realisation of high-bandwidth optical data communication in electronic chips. For the first time the figure of merit for passive plasmonic interconnects has been derived in terms of ultimate global characteristics of the plasmonic circuitry, particularly bandwidth and power consumption densities. Then, these parameters were linked to the local waveguide characteristics, such as mode propagation length, bending radius, etc. The figure has been applied to provide a comprehensive comparison to the main types of the plasmonics waveguides and can serve as an excellent benchmark for future designs. Completing the development of broadband optical on-chip data communication, we developed an all-inclusive figure of merit for active photonic- or plasmonic-based electro-optic modulators, establishing the communication between electronic and photonic chip domains...

  10. Neural Activity Reveals Preferences Without Choices

    Smith, Alec; Bernheim, B. Douglas; Camerer, Colin

    2014-01-01

    We investigate the feasibility of inferring the choices people would make (if given the opportunity) based on their neural responses to the pertinent prospects when they are not engaged in actual decision making. The ability to make such inferences is of potential value when choice data are unavailable, or limited in ways that render standard methods of estimating choice mappings problematic. We formulate prediction models relating choices to “non-choice” neural responses and use them to predict out-of-sample choices for new items and for new groups of individuals. The predictions are sufficiently accurate to establish the feasibility of our approach. PMID:25729468

  11. Evaluating a genetically encoded optical sensor of neural activity using electrophysiology in intact adult fruit flies

    Gilles Laurent

    2007-11-01

    Full Text Available Genetically encoded optical indicators hold the promise of enabling non-invasive monitoring of activity in identified neurons in behaving organisms. However, the interpretation of images of brain activity produced using such sensors is not straightforward. Several recent studies of sensory coding used G-CaMP 1.3-a calcium sensor-as an indicator of neural activity; some of these studies characterized the imaged neurons as having narrow tuning curves, a conclusion not always supported by parallel electrophysiological studies. To better understand the possible cause of these conflicting results, we performed simultaneous in vivo 2-photon imaging and electrophysiological recording of G-CaMP 1.3 expressing neurons in the antennal lobe (AL of intact fruitflies. We find that G-CaMP has a relatively high threshold, that its signal often fails to capture spiking response kinetics, and that it can miss even high instantaneous rates of activity if those are not sustained. While G-CaMP can be misleading, it is clearly useful for the identification of promising neural targets: when electrical activity is well above the sensor's detection threshold, its signal is fairly well correlated with mean firing rate and G-CaMP does not appear to alter significantly the responses of neurons that express it. The methods we present should enable any genetically encoded sensor, activator, or silencer to be evaluated in an intact neural circuit in vivo in Drosophila.

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

    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.

  13. Performance Evaluation a Developed Energy Harvesting Interface Circuit in Active Technique

    Ramizi Mohamed; Mahidur R. Sarker; Azah Mohamed

    2014-01-01

    This study presents the performance evaluation a developed energy harvesting interface circuit in active technique. The energy harvesting interface circuit for micro-power applications uses equivalent voltage of the piezoelectric materials have been developed and simulated. Circuit designs and simulation results are presented for a conventional diode rectifier with voltage doubler in passive technique. Most of the existing techniques are mainly passive-based energy harvesting circuits. Genera...

  14. Active Engine Mounting Control Algorithm Using Neural Network

    Fadly Jashi Darsivan

    2009-01-01

    Full Text Available This paper proposes the application of neural network as a controller to isolate engine vibration in an active engine mounting system. It has been shown that the NARMA-L2 neurocontroller has the ability to reject disturbances from a plant. The disturbance is assumed to be both impulse and sinusoidal disturbances that are induced by the engine. The performance of the neural network controller is compared with conventional PD and PID controllers tuned using Ziegler-Nichols. From the result simulated the neural network controller has shown better ability to isolate the engine vibration than the conventional controllers.

  15. Neural activity during encoding predicts false memories created by misinformation

    Okado, Yoko; Stark, Craig E.L.

    2005-01-01

    False memories are often demonstrated using the misinformation paradigm, in which a person's recollection of a witnessed event is altered after exposure to misinformation about the event. The neural basis of this phenomenon, however, remains unknown. We used fMRI to investigate encoding processes during the viewing of an event and misinformation to see whether neural activity during either encoding phase could predict what would be remembered. fMRI data were collected as participants studied ...

  16. Learning to Discern Images Modifies Neural Activity

    Gregor Rainer; Han Lee; Logothetis, Nikos K.

    2004-01-01

    One of the most remarkable capabilities of the adult brain is its ability to learn and continuously adapt to an ever-changing environment. While many studies have documented how learning improves the perception and identification of visual stimuli, relatively little is known about how it modifies the underlying neural mechanisms. We trained monkeys to identify natural images that were degraded by interpolation with visual noise. We found that learning led to an improvement in monkeys' ability...

  17. Matching tutor to student: rules and mechanisms for efficient two-stage learning in neural circuits

    Tesileanu, Tiberiu; Balasubramanian, Vijay

    2016-01-01

    Existing models of birdsong learning assume that brain area LMAN introduces variability into song for trial-and-error learning. Recent data suggest that LMAN also encodes a corrective bias driving short-term improvements in song. These later consolidate in area RA, a motor cortex analogue downstream of LMAN. We develop a new model of such two-stage learning. Using a stochastic gradient descent approach, we derive how 'tutor' circuits should match plasticity mechanisms in 'student' circuits for efficient learning. We further describe a reinforcement learning framework with which the tutor can build its teaching signal. We show that mismatching the tutor signal and plasticity mechanism can impair or abolish 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.

  18. Sex differences in the neural circuit that mediates female sexual receptivity

    Flanagan-Cato, Loretta M.

    2011-01-01

    Female sexual behavior in rodents, typified by the lordosis posture, is hormone-dependent and sex-specific. Ovarian hormones control this behavior via receptors in the hypothalamic ventromedial nucleus (VMH). This review considers the sex differences in the morphology, neurochemistry and neural circuitry of the VMH to gain insights into the mechanisms that control lordosis. The VMH is larger in males compared with females, due to more synaptic connections. Another sex difference is the respon...

  19. Zebrafish foxc1a drives appendage-specific neural circuit development

    Banerjee, Santanu; Hayer, Katharina; Hogenesch, John B.; Granato, Michael

    2015-01-01

    Neural connectivity between the spinal cord and paired appendages is key to the superior locomotion of tetrapods and aquatic vertebrates. In contrast to nerves that innervate axial muscles, those innervating appendages converge at a specialized structure, the plexus, where they topographically reorganize before navigating towards their muscle targets. Despite its importance for providing appendage mobility, the genetic program that drives nerve convergence at the plexus, as well as the functi...

  20. A neural circuit mechanism integrating motivational state with memory expression in Drosophila

    Krashes, Michael J.; DasGupta, Shamik; Vreede, Andrew; White, Benjamin; Armstrong, J. Douglas; Waddell, Scott

    2009-01-01

    Motivational states are important determinants of behavior. In fruit flies appetitive memory expression is constrained by satiety and promoted by hunger. Here we identify a neural mechanism that integrates the motivational state of hunger and memory. We show that stimulation of neurons that express Neuropeptide F (dNPF), an ortholog of mammalian NPY, mimicks food-deprivation and promotes memory performance in satiated flies. Robust appetitive memory performance requires the dNPF receptor in s...

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

    Basilis Zikopoulos

    2013-01-01

    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 pathway...

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

    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.

  3. Cortical Correlates of Low-Level Perception: From Neural Circuits to Percepts.

    Frégnac, Yves; Bathellier, Brice

    2015-10-01

    Low-level perception results from neural-based computations, which build a multimodal skeleton of unconscious or self-generated inferences on our environment. This review identifies bottleneck issues concerning the role of early primary sensory cortical areas, mostly in rodent and higher mammals (cats and non-human primates), where perception substrates can be searched at multiple scales of neural integration. We discuss the limitation of purely bottom-up approaches for providing realistic models of early sensory processing and the need for identification of fast adaptive processes, operating within the time of a percept. Future progresses will depend on the careful use of comparative neuroscience (guiding the choices of experimental models and species adapted to the questions under study), on the definition of agreed-upon benchmarks for sensory stimulation, on the simultaneous acquisition of neural data at multiple spatio-temporal scales, and on the in vivo identification of key generic integration and plasticity algorithms validated experimentally and in simulations. PMID:26447576

  4. Optical imaging of neural and hemodynamic brain activity

    Schei, Jennifer Lynn

    Optical imaging technologies can be used to record neural and hemodynamic activity. Neural activity elicits physiological changes that alter the optical tissue properties. Specifically, changes in polarized light are concomitant with neural depolarization. We measured polarization changes from an isolated lobster nerve during action potential propagation using both reflected and transmitted light. In transmission mode, polarization changes were largest throughout the center of the nerve, suggesting that most of the optical signal arose from the inner nerve bundle. In reflection mode, polarization changes were largest near the edges, suggesting that most of the optical signal arose from the outer sheath. To overcome irregular cell orientation found in the brain, we measured polarization changes from a nerve tied in a knot. Our results show that neural activation produces polarization changes that can be imaged even without regular cell orientations. Neural activation expends energy resources and elicits metabolic delivery through blood vessel dilation, increasing blood flow and volume. We used spectroscopic imaging techniques combined with electrophysiological measurements to record evoked neural and hemodynamic responses from the auditory cortex of the rat. By using implantable optics, we measured responses across natural wake and sleep states, as well as responses following different amounts of sleep deprivation. During quiet sleep, evoked metabolic responses were larger compared to wake, perhaps because blood vessels were more compliant. When animals were sleep deprived, evoked hemodynamic responses were smaller following longer periods of deprivation. These results suggest that prolonged neural activity through sleep deprivation may diminish vascular compliance as indicated by the blunted vascular response. Subsequent sleep may allow vessels to relax, restoring their ability to deliver blood. These results also suggest that severe sleep deprivation or chronic

  5. Neural Network-Based Active Control for Offshore Platforms

    周亚军; 赵德有

    2003-01-01

    A new active control scheme, based on neural network, for the suppression of oscillation in multiple-degree-of-freedom (MDOF) offshore platforms, is studied in this paper. With the main advantages of neural network, i.e. the inherent robustness, fault tolerance, and generalized capability of its parallel massive interconnection structure, the active structural control of offshore platforms under random waves is accomplished by use of the BP neural network model. The neural network is trained offline with the data generated from numerical analysis, and it simulates the process of Classical Linear Quadratic Regular Control for the platform under random waves. After the learning phase, the trained network has learned about the nonlinear dynamic behavior of the active control system, and is capable of predicting the active control forces of the next time steps. The results obtained show that the active control is feasible and effective, and it finally overcomes time delay owing to the robustness, fault tolerance, and generalized capability of artificial neural network.

  6. Dopamine-induced dissociation of BOLD and neural activity in macaque visual cortex.

    Zaldivar, Daniel; Rauch, Alexander; Whittingstall, Kevin; Logothetis, Nikos K; Goense, Jozien

    2014-12-01

    Neuromodulators determine how neural circuits process information during cognitive states such as wakefulness, attention, learning, and memory. fMRI can provide insight into their function and dynamics, but their exact effect on BOLD responses remains unclear, limiting our ability to interpret the effects of changes in behavioral state using fMRI. Here, we investigated the effects of dopamine (DA) injections on neural responses and haemodynamic signals in macaque primary visual cortex (V1) using fMRI (7T) and intracortical electrophysiology. Aside from DA's involvement in diseases such as Parkinson's and schizophrenia, it also plays a role in visual perception. We mimicked DAergic neuromodulation by systemic injection of L-DOPA and Carbidopa (LDC) or by local application of DA in V1 and found that systemic application of LDC increased the signal-to-noise ratio (SNR) and amplitude of the visually evoked neural responses in V1. However, visually induced BOLD responses decreased, whereas cerebral blood flow (CBF) responses increased. This dissociation of BOLD and CBF suggests that dopamine increases energy metabolism by a disproportionate amount relative to the CBF response, causing the reduced BOLD response. Local application of DA in V1 had no effect on neural activity, suggesting that the dopaminergic effects are mediated by long-range interactions. The combination of BOLD-based and CBF-based fMRI can provide a signature of dopaminergic neuromodulation, indicating that the application of multimodal methods can improve our ability to distinguish sensory processing from neuromodulatory effects. PMID:25456449

  7. High Accuracy Human Activity Monitoring using Neural network

    Sharma, Annapurna; Chung, Wan-Young

    2011-01-01

    This paper presents the designing of a neural network for the classification of Human activity. A Triaxial accelerometer sensor, housed in a chest worn sensor unit, has been used for capturing the acceleration of the movements associated. All the three axis acceleration data were collected at a base station PC via a CC2420 2.4GHz ISM band radio (zigbee wireless compliant), processed and classified using MATLAB. A neural network approach for classification was used with an eye on theoretical and empirical facts. The work shows a detailed description of the designing steps for the classification of human body acceleration data. A 4-layer back propagation neural network, with Levenberg-marquardt algorithm for training, showed best performance among the other neural network training algorithms.

  8. Performance Evaluation a Developed Energy Harvesting Interface Circuit in Active Technique

    Ramizi Mohamed

    2014-10-01

    Full Text Available This study presents the performance evaluation a developed energy harvesting interface circuit in active technique. The energy harvesting interface circuit for micro-power applications uses equivalent voltage of the piezoelectric materials have been developed and simulated. Circuit designs and simulation results are presented for a conventional diode rectifier with voltage doubler in passive technique. Most of the existing techniques are mainly passive-based energy harvesting circuits. Generally, the power harvesting capability of the passive technique is very low. To increase the harvested energy, the active technique and its components such as MOSFET, thyristor and transistor have chosen to design the proposed energy harvesting interface circuit. In this study, it has simulated both the conventional in passive circuit and developed energy harvester in active technique. The developed interface circuits consisting of piezoelectric element with input source of vibration, AC-DC thyristor doubler rectifier circuit and DC-DC boost converter using thyristor with storage device. In the development circuits, it is noted that the components thyristor instead of mainly diode available in conventional circuits have chosen. Because the forward voltage potential (0.7 V is higher than the incoming input voltage (0.2 V. Finally, the complete energy harvester using PSPICE software have designed and simulated. The proposed circuits in PSPICE generate the boost-up DC voltage up to 2 V. The overall efficiency of the developed circuit is 70%, followed by the software simulation, which is greater than conventional circuit efficiency of 20% in performance evaluator. It is concluded that the developed circuit output voltage can be used to operate for the applications in autonomous devices.

  9. A Framework for Quantitative Modeling of Neural Circuits Involved in Sleep-to-Wake Transition

    Siamak eSorooshyari

    2015-02-01

    Full Text Available Identifying the neuronal circuits and dynamics of sleep-to-wake transition is essential to understanding brain regulation of behavioral states, including sleep-wake cycles, arousal, and hyperarousal. Recent work by different laboratories has used optogenetics to determine the role of individual neuromodulators in state transitions. The optogenetically-driven data does not yet provide a multi-dimensional schematic of the mechanisms underlying changes in vigilance states. This work presents a modeling framework to interpret, assist, and drive research on the sleep-regulatory network. We identify feedback, redundancy, and gating hierarchy as three fundamental aspects of this model. The presented model is expected to expand as additional data on the contribution of each transmitter to a vigilance state becomes available. Incorporation of conductance-based models of neuronal ensembles into this model and existing models of cortical excitability will provide more comprehensive insight into sleep dynamics as well as sleep and arousal-related disorders.

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

    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.

  11. Altered regional and circuit resting-state activity associated with unilateral hearing loss.

    Xingchao Wang

    Full Text Available The deprivation of sensory input after hearing damage results in functional reorganization of the brain including cross-modal plasticity in the sensory cortex and changes in cognitive processing. However, it remains unclear whether partial deprivation from unilateral auditory loss (UHL would similarly affect the neural circuitry of cognitive processes in addition to the functional organization of sensory cortex. Here, we used resting-state functional magnetic resonance imaging to investigate intrinsic activity in 34 participants with UHL from acoustic neuroma in comparison with 22 matched normal controls. In sensory regions, we found decreased regional homogeneity (ReHo in the bilateral calcarine cortices in UHL. However, there was an increase of ReHo in the right anterior insular cortex (rAI, the key node of cognitive control network (CCN and multimodal sensory integration, as well as in the left parahippocampal cortex (lPHC, a key node in the default mode network (DMN. Moreover, seed-based resting-state functional connectivity analysis showed an enhanced relationship between rAI and several key regions of the DMN. Meanwhile, lPHC showed more negative relationship with components in the CCN and greater positive relationship in the DMN. Such reorganizations of functional connectivity within the DMN and between the DMN and CCN were confirmed by a graph theory analysis. These results suggest that unilateral sensory input damage not only alters the activity of the sensory areas but also reshapes the regional and circuit functional organization of the cognitive control network.

  12. Advanced active quenching circuits for single-photon avalanche photodiodes

    Stipčević, M.; Christensen, B. G.; Kwiat, P. G.; Gauthier, D. J.

    2016-05-01

    Commercial photon-counting modules, often based on actively quenched solid-state avalanche photodiode sensors, are used in wide variety of applications. Manufacturers characterize their detectors by specifying a small set of parameters, such as detection efficiency, dead time, dark counts rate, afterpulsing probability and single photon arrival time resolution (jitter), however they usually do not specify the conditions under which these parameters are constant or present a sufficient description. In this work, we present an in-depth analysis of the active quenching process and identify intrinsic limitations and engineering challenges. Based on that, we investigate the range of validity of the typical parameters used by two commercial detectors. We identify an additional set of imperfections that must be specified in order to sufficiently characterize the behavior of single-photon counting detectors in realistic applications. The additional imperfections include rate-dependence of the dead time, jitter, detection delay shift, and "twilighting." Also, the temporal distribution of afterpulsing and various artifacts of the electronics are important. We find that these additional non-ideal behaviors can lead to unexpected effects or strong deterioration of the system's performance. Specifically, we discuss implications of these new findings in a few applications in which single-photon detectors play a major role: the security of a quantum cryptographic protocol, the quality of single-photon-based random number generators and a few other applications. Finally, we describe an example of an optimized avalanche quenching circuit for a high-rate quantum key distribution system based on time-bin entangled photons.

  13. Cultured Neural Networks: Optimization of Patterned Network Adhesiveness and Characterization of their Neural Activity

    W. L. C. Rutten

    2006-01-01

    Full Text Available One type of future, improved neural interface is the “cultured probe”. It is a hybrid type of neural information transducer or prosthesis, for stimulation and/or recording of neural activity. It would consist of a microelectrode array (MEA on a planar substrate, each electrode being covered and surrounded by a local circularly confined network (“island” of cultured neurons. The main purpose of the local networks is that they act as biofriendly intermediates for collateral sprouts from the in vivo system, thus allowing for an effective and selective neuron–electrode interface. As a secondary purpose, one may envisage future information processing applications of these intermediary networks. In this paper, first, progress is shown on how substrates can be chemically modified to confine developing networks, cultured from dissociated rat cortex cells, to “islands” surrounding an electrode site. Additional coating of neurophobic, polyimide-coated substrate by triblock-copolymer coating enhances neurophilic-neurophobic adhesion contrast. Secondly, results are given on neuronal activity in patterned, unconnected and connected, circular “island” networks. For connected islands, the larger the island diameter (50, 100 or 150 μm, the more spontaneous activity is seen. Also, activity may show a very high degree of synchronization between two islands. For unconnected islands, activity may start at 22 days in vitro (DIV, which is two weeks later than in unpatterned networks.

  14. Anabolic steroids alter the physiological activity of aggression circuits in the lateral anterior hypothalamus.

    Morrison, T R; Sikes, R W; Melloni, R H

    2016-02-19

    Syrian hamsters exposed to anabolic/androgenic steroids (AAS) during adolescence consistently show increased aggressive behavior across studies. Although the behavioral and anatomical profiles of AAS-induced alterations have been well characterized, there is a lack of data describing physiological changes that accompany these alterations. For instance, behavioral pharmacology and neuroanatomical studies show that AAS-induced changes in the vasopressin (AVP) neural system within the latero-anterior hypothalamus (LAH) interact with the serotonin (5HT) and dopamine (DA) systems to modulate aggression. To characterize the electrophysiological profile of the AAS aggression circuit, we recorded LAH neurons in adolescent male hamsters in vivo and microiontophoretically applied agonists and antagonists of aggressive behavior. The interspike interval (ISI) of neurons from AAS-treated animals correlated positively with aggressive behaviors, and adolescent AAS exposure altered parameters of activity in regular firing neurons while also changing the proportion of neuron types (i.e., bursting, regular, irregular). AAS-treated animals had more responsive neurons that were excited by AVP application, while cells from control animals showed the opposite effect and were predominantly inhibited by AVP. Both DA D2 antagonists and 5HT increased the firing frequency of AVP-responsive cells from AAS animals and dual application of AVP and D2 antagonists doubled the excitatory effect of AVP or D2 antagonist administration alone. These data suggest that multiple DA circuits in the LAH modulate AAS-induced aggressive responding. More broadly, these data show that multiple neurochemical interactions at the neurophysiological level are altered by adolescent AAS exposure. PMID:26691962

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

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

    2015-09-01

    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

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

    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.

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

    Marusak, Hilary A; Etkin, Amit; Thomason, Moriah E

    2015-01-01

    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. PMID:26199869

  18. A Realization of SC-CNN-Based Circuit Using FTFN

    Günay, Enis; UZUNHİSARCIKLI, Esma; KILIÇ, Recai; ALÇI, Mustafa

    2005-01-01

    In this paper, a realization of the State Controlled Cellular Neural Network (SC-CNN)-based circuit using Four Terminal Floating Nullor (FTFN) as active element is presented. In this realization, a new version of autonomous Chua's circuit has been considered using FTFN realization of SC-CNN-based circuit. The performance of the proposed SC-CNN-based circuit is demonstrated by PSpice simulations.

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

    Wang, Xiao-Jing

    2016-01-01

    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. PMID:27551824

  20. Improved AC pixel electrode circuit for active matrix of organic light-emitting display

    Si, Yujuan; Lang, Liuqi; Chen, Wanzhong; Liu, Shiyong

    2004-05-01

    In this paper, a modified four-transistor pixel circuit for active-matrix organic light-emitting displays (AMOLED) was developed to improve the performance of OLED device. This modified pixel circuit can provide an AC driving mode to make the OLED working in a reversed-biased voltage during the certain cycle. The optimized values of the reversed-biased voltage and the characteristics of the pixel circuit were investigated using AIM-SPICE. The simulated results reveal that this circuit can provide a suitable output current and voltage characteristic, and little change was made in luminance current.

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

    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.

  2. Neural Activity When People Solve Verbal Problems with Insight

    Jung-Beeman Mark

    2004-01-01

    Full Text Available People sometimes solve problems with a unique process called insight, accompanied by an "Aha!" experience. It has long been unclear whether different cognitive and neural processes lead to insight versus noninsight solutions, or if solutions differ only in subsequent subjective feeling. Recent behavioral studies indicate distinct patterns of performance and suggest differential hemispheric involvement for insight and noninsight solutions. Subjects solved verbal problems, and after each correct solution indicated whether they solved with or without insight. We observed two objective neural correlates of insight. Functional magnetic resonance imaging (Experiment 1 revealed increased activity in the right hemisphere anterior superior temporal gyrus for insight relative to noninsight solutions. The same region was active during initial solving efforts. Scalp electroencephalogram recordings (Experiment 2 revealed a sudden burst of high-frequency (gamma-band neural activity in the same area beginning 0.3 s prior to insight solutions. This right anterior temporal area is associated with making connections across distantly related information during comprehension. Although all problem solving relies on a largely shared cortical network, the sudden flash of insight occurs when solvers engage distinct neural and cognitive processes that allow them to see connections that previously eluded them.

  3. Neural circuit architecture defects in a Drosophila model of Fragile X syndrome are alleviated by minocycline treatment and genetic removal of matrix metalloproteinase

    Saul S. Siller

    2011-09-01

    Fragile X syndrome (FXS, caused by loss of the fragile X mental retardation 1 (FMR1 product (FMRP, is the most common cause of inherited intellectual disability and autism spectrum disorders. FXS patients suffer multiple behavioral symptoms, including hyperactivity, disrupted circadian cycles, and learning and memory deficits. Recently, a study in the mouse FXS model showed that the tetracycline derivative minocycline effectively remediates the disease state via a proposed matrix metalloproteinase (MMP inhibition mechanism. Here, we use the well-characterized Drosophila FXS model to assess the effects of minocycline treatment on multiple neural circuit morphological defects and to investigate the MMP hypothesis. We first treat Drosophila Fmr1 (dfmr1 null animals with minocycline to assay the effects on mutant synaptic architecture in three disparate locations: the neuromuscular junction (NMJ, clock neurons in the circadian activity circuit and Kenyon cells in the mushroom body learning and memory center. We find that minocycline effectively restores normal synaptic structure in all three circuits, promising therapeutic potential for FXS treatment. We next tested the MMP hypothesis by assaying the effects of overexpressing the sole Drosophila tissue inhibitor of MMP (TIMP in dfmr1 null mutants. We find that TIMP overexpression effectively prevents defects in the NMJ synaptic architecture in dfmr1 mutants. Moreover, co-removal of dfmr1 similarly rescues TIMP overexpression phenotypes, including cellular tracheal defects and lethality. To further test the MMP hypothesis, we generated dfmr1;mmp1 double null mutants. Null mmp1 mutants are 100% lethal and display cellular tracheal defects, but co-removal of dfmr1 allows adult viability and prevents tracheal defects. Conversely, co-removal of mmp1 ameliorates the NMJ synaptic architecture defects in dfmr1 null mutants, despite the lack of detectable difference in MMP1 expression or gelatinase activity between the single

  4. Neural circuit competition in cocaine-seeking: Roles of the infralimbic cortex and nucleus accumbens shell

    LaLumiere, Ryan T.; Smith, Kyle C.; Kalivas, Peter W.

    2012-01-01

    Following cocaine self-administration and extinction training, activity in the infralimbic cortex (IL) suppresses cocaine-seeking behavior. IL inactivation induces cocaine-seeking, whereas activation suppresses cocaine-reinstated drug-seeking. We asked how the suppression of cocaine-seeking induced by IL activation integrates with the circuitry promoting reinstated cocaine-seeking. Following cocaine self-administration and extinction training, rats underwent cue-induced reinstatement. In orde...

  5. Early interfaced neural activity from chronic amputated nerves

    Kshitija Garde

    2009-05-01

    Full Text Available Direct interfacing of transected peripheral nerves with advanced robotic prosthetic devices has been proposed as a strategy for achieving natural motor control and sensory perception of such bionic substitutes, thus fully functionally replacing missing limbs in amputees. Multi-electrode arrays placed in the brain and peripheral nerves have been used successfully to convey neural control of prosthetic devices to the user. However, reactive gliosis, micro hemorrhages, axonopathy and excessive inflammation, currently limit their long-term use. Here we demonstrate that enticement of peripheral nerve regeneration through a non-obstructive multi-electrode array, after either acute or chronic nerve amputation, offers a viable alternative to obtain early neural recordings and to enhance long-term interfacing of nerve activity. Non restrictive electrode arrays placed in the path of regenerating nerve fibers allowed the recording of action potentials as early as 8 days post-implantation with high signal-to-noise ratio, as long as 3 months in some animals, and with minimal inflammation at the nerve tissue-metal electrode interface. Our findings suggest that regenerative on-dependent multi-electrode arrays of open design allow the early and stable interfacing of neural activity from amputated peripheral nerves and might contribute towards conveying full neural control and sensory feedback to users of robotic prosthetic devices. .

  6. Application of neural networks to seismic active control

    An exploratory study on seismic active control using an artificial neural network (ANN) is presented in which a singledegree-of-freedom (SDF) structural system is controlled by a trained neural network. A feed-forward neural network and the backpropagation training method are used in the study. In backpropagation training, the learning rate is determined by ensuring the decrease of the error function at each training cycle. The training patterns for the neural net are generated randomly. Then, the trained ANN is used to compute the control force according to the control algorithm. The control strategy proposed herein is to apply the control force at every time step to destroy the build-up of the system response. The ground motions considered in the simulations are the N21E and N69W components of the Lake Hughes No. 12 record that occurred in the San Fernando Valley in California on February 9, 1971. Significant reduction of the structural response by one order of magnitude is observed. Also, it is shown that the proposed control strategy has the ability to reduce the peak that occurs during the first few cycles of the time history. These promising results assert the potential of applying ANNs to active structural control under seismic loads

  7. Analytical criteria for local activity of CNN with five state variables and application to Hyper-chaos synchronization Chua's circuit

    2002-01-01

    The analytic criteria for the local activity theory in one-port cellular neural network (CNN) with five local state variables are presented. The application to a Hyper-chaos synchronization Chua's circuit (HCSCC) CNN with 1125 variables is studied. The bifurcation diagrams of the HCSCC CNN show that they are slightly different from the smoothed CNN with one or two ports and four state variables calculated earlier. The evolution of the patterns of the state variables of the HCSCC CNN is stimulated. Oscillatory patterns, chaotic patterns, convergent or divergent patterns may emerge if the selected cell parameters are located in the locally active domains but nearby or in the edge of chaos domain.

  8. Perception Neural Networks for Active Noise Control Systems

    Wang Xiaoli

    2012-11-01

    Full Text Available In a response to a growing demand for environments of 70dB or less noise levels, many industrial sectors have focused with some form of noise control system. Active noise control (ANC has proven to be the most effective technology. This paper mainly investigates application of neural network on self-adaptation system in active noise control (ANC. An active silencing control system is made which adopts a motional feedback loudspeaker as not a noise controlling source but a detecting sensor. The working fundamentals and the characteristics of the motional feedback loudspeaker are analyzed in detail. By analyzing each acoustical path, identification based adaptive linear neural network is built. This kind of identifying method can be achieved conveniently. The estimated result of each sound channel matches well with its real sound character, respectively.

  9. Dynamical criticality in the collective activity of a neural population

    Mora, Thierry

    The past decade has seen a wealth of physiological data suggesting that neural networks may behave like critical branching processes. Concurrently, the collective activity of neurons has been studied using explicit mappings to classic statistical mechanics models such as disordered Ising models, allowing for the study of their thermodynamics, but these efforts have ignored the dynamical nature of neural activity. I will show how to reconcile these two approaches by learning effective statistical mechanics models of the full history of the collective activity of a neuron population directly from physiological data, treating time as an additional dimension. Applying this technique to multi-electrode recordings from retinal ganglion cells, and studying the thermodynamics of the inferred model, reveals a peak in specific heat reminiscent of a second-order phase transition.

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

    Jarcho, Johanna M; Romer, Adrienne L; Shechner, Tomer; Galvan, Adriana; Guyer, Amanda E; Leibenluft, Ellen; Pine, Daniel S; Nelson, Eric E

    2015-06-01

    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. PMID:25933410

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

    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.

  12. A High Step-Down Interleaved Buck Converter with Active-Clamp Circuits for Wind Turbines

    Chih-Lung Shen

    2012-12-01

    Full Text Available In this paper, a high step-down interleaved buck coupled-inductor converter (IBCC with active-clamp circuits for wind energy conversion has been studied. In high step-down voltage applications, an IBCC can extend duty ratio and reduce voltage stresses on active switches. In order to reduce switching losses of active switches to improve conversion efficiency, a IBCC with soft-switching techniques is usually required. Compared with passive-clamp circuits, the IBCC with active-clamp circuits have lower switching losses and minimum ringing voltage of the active switches. Thus, the proposed IBCC with active-clamp circuits for wind energy conversion can significantly increase conversion efficiency. Finally, a 240 W prototype of the proposed IBCC with active-clamp circuits was built and implemented. Experimental results have shown that efficiency can reach as high as 91%. The proposed IBCC with active-clamp circuits is presented in high step-down voltage applications to verify the performance and the feasibility for energy conversion of wind turbines.

  13. The effects of gratitude expression on neural activity.

    Kini, Prathik; Wong, Joel; McInnis, Sydney; Gabana, Nicole; Brown, Joshua W

    2016-03-01

    Gratitude is a common aspect of social interaction, yet relatively little is known about the neural bases of gratitude expression, nor how gratitude expression may lead to longer-term effects on brain activity. To address these twin issues, we recruited subjects who coincidentally were entering psychotherapy for depression and/or anxiety. One group participated in a gratitude writing intervention, which required them to write letters expressing gratitude. The therapy-as-usual control group did not perform a writing intervention. After three months, subjects performed a "Pay It Forward" task in the fMRI scanner. In the task, subjects were repeatedly endowed with a monetary gift and then asked to pass it on to a charitable cause to the extent they felt grateful for the gift. Operationalizing gratitude as monetary gifts allowed us to engage the subjects and quantify the gratitude expression for subsequent analyses. We measured brain activity and found regions where activity correlated with self-reported gratitude experience during the task, even including related constructs such as guilt motivation and desire to help as statistical controls. These were mostly distinct from brain regions activated by empathy or theory of mind. Also, our between groups cross-sectional study found that a simple gratitude writing intervention was associated with significantly greater and lasting neural sensitivity to gratitude - subjects who participated in gratitude letter writing showed both behavioral increases in gratitude and significantly greater neural modulation by gratitude in the medial prefrontal cortex three months later. PMID:26746580

  14. Passive and active elements using fractional Lβ C α circuit

    Radwan, Ahmed Gomaa

    2011-10-01

    This paper introduces a qualitative revision of the traditional LC tank circuit in the fractional domain. The paper can be divided into six major parts, aiming in turn to establish the various conditions under which L βCα impedance may act as a resistor, negative resistor, or a positive or negative pure imaginary inductor or capacitor, in accordance to new frequency definitions; illustrate the process by which the phase response chooses the shortest path from initial to final phase, and use this illustration to verify the cases discussed in part one; develop the generalized parameters for the bandpass filter response of the L βCα circuit, such as the resonance frequency and quality factor versus α-β plane; discuss sensitivity analyses with respect to the fractional orders, as well as the time domain analyses for the impulse and step responses with their analytical formulas; and lastly, to propose some possible applications for this generalized circuit. Mathematical and PSpice simulation results are included to validate the discussion. © 2011 IEEE.

  15. 78 FR 37203 - Authorization of Production Activity; Subzone 196A; TTI, Inc. (Electromechanical and Circuit...

    2013-06-20

    ... comment (78 FR 15683, 03-12-2013). The FTZ Board has determined that no further review of the activity is... and Circuit Protection Devices Production/Kitting); Fort Worth, Texas On February 13, 2013, TTI,...

  16. Feasibility of Tunable Amplifier and Bandpass Filter for Mobile Handsets Using Active Inductor Circuits

    Majeed, B.; N. T. Ali; J. Rodriguez Tellez

    2002-01-01

    In this paper active inductor circuits are employed to assess their suitability for providing a tuning function in GaAs MMIC circuits. The specifications for a mobile handset amplifier and a bandpass filter operating from a 3 V supply rail are used as test vehicles. The design and simulation of the circuits employs a low-cost commercially available low pinch-off GaAs MESFET process. The suitability of active inductors for tuning in such applications considers issues such as frequency tuning r...

  17. Neural circuits underlying hyperactivity in an animal model for anorexia nervosa

    Verhagen, L.A.W.

    2009-01-01

    Anorexia nervosa (AN) means literally “a nervous loss of appetite” and is characterized by reduced food intake, extreme body weight loss, hypothermia, amenorrhea and emaciation. The average prevalence of AN has been reported to be 0.3% and has the highest mortality rate (>10%) of all psychiatric disorders. Excessive physical activity is demonstrated by many, if not most, patients with AN at some point in the course of the disorder, and has been described as a hallmark feature of the syndrome....

  18. Where's the Noise? Key Features of Spontaneous Activity and Neural Variability Arise through Learning in a Deterministic Network.

    Hartmann, Christoph; Lazar, Andreea; Nessler, Bernhard; Triesch, Jochen

    2015-12-01

    Even in the absence of sensory stimulation the brain is spontaneously active. This background "noise" seems to be the dominant cause of the notoriously high trial-to-trial variability of neural recordings. Recent experimental observations have extended our knowledge of trial-to-trial variability and spontaneous activity in several directions: 1. Trial-to-trial variability systematically decreases following the onset of a sensory stimulus or the start of a motor act. 2. Spontaneous activity states in sensory cortex outline the region of evoked sensory responses. 3. Across development, spontaneous activity aligns itself with typical evoked activity patterns. 4. The spontaneous brain activity prior to the presentation of an ambiguous stimulus predicts how the stimulus will be interpreted. At present it is unclear how these observations relate to each other and how they arise in cortical circuits. Here we demonstrate that all of these phenomena can be accounted for by a deterministic self-organizing recurrent neural network model (SORN), which learns a predictive model of its sensory environment. The SORN comprises recurrently coupled populations of excitatory and inhibitory threshold units and learns via a combination of spike-timing dependent plasticity (STDP) and homeostatic plasticity mechanisms. Similar to balanced network architectures, units in the network show irregular activity and variable responses to inputs. Additionally, however, the SORN exhibits sequence learning abilities matching recent findings from visual cortex and the network's spontaneous activity reproduces the experimental findings mentioned above. Intriguingly, the network's behaviour is reminiscent of sampling-based probabilistic inference, suggesting that correlates of sampling-based inference can develop from the interaction of STDP and homeostasis in deterministic networks. We conclude that key observations on spontaneous brain activity and the variability of neural responses can be

  19. Optimal Coding Predicts Attentional Modulation of Activity in Neural Systems

    Jaramillo, Santiago; Pearlmutter, Barak A.

    2007-01-01

    Neuronal activity in response to a fixed stimulus has been shown to change as a function of attentional state, implying that the neural code also changes with attention. We propose an information-theoretic account of such modulation: that the nervous system adapts to optimally encode sensory stimuli while taking into account the changing relevance of different features. We show using computer simulation that such modulation emerges in a coding system informed about the uneven relevance of ...

  20. Activated sludge process based on artificial neural network

    张文艺; 蔡建安

    2002-01-01

    Considering the difficulty of creating water quality model for activated sludge system, a typical BP artificial neural network model has been established to simulate the operation of a waste water treatment facilities. The comparison of prediction results with the on-spot measurements shows the model, the model is accurate and this model can also be used to realize intelligentized on-line control of the wastewater processing process.

  1. Efficient universal computing architectures for decoding neural activity.

    Benjamin I Rapoport

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

  2. Simulation of Aorta Artery Aneurysms Using Active Electronic Circuit

    Kamran Hassani

    2007-01-01

    Full Text Available The fusiform and saccular aneurysms in different aorta artery sections were studied using an electronic circuit of cardiovascular system. The geometrical model of each artery section including thoracic and abdominal were generated in accordance with original anatomical data. By increasing the rate of aneurysm in each studied section, the pressure drop were calculated using CFD method, furthermore the compliance variations due to aneurysms were determined by mathematical method. The equivalent electronic circuit was then used to study the effects of the pressure drops and compliance variations on whole cardiovascular system. The results of the simulation exhibited the features of the pathology, including hypertension, the increase of the pulse pressure with the rate of aneurysm and the large magnitude of back flow during systole. Finally, the obtained results were compared with relevant clinical data .We have concluded from the study that aorta aneurysms in both fusiform and saccular, especially at highest diameters, may be the most important determinant of the artery rapture and heart failure.

  3. Comparison of bidirectional power electronics with unidirectional topologies using active discharging circuits for feeding DEAP transducer

    Hoffstadt, Thorben; Maas, Jürgen

    2015-04-01

    To enable a continuous operation of a DEAP transducer, the feeding power electronics must provide the capability to charge and discharge the transducer to enable a continuous voltage adjustment. While in case of energy harvesting applications a bidirectional power electronics is mandatory, for actuator applications also unidirectional power electronics with active discharging circuits can be used. Thus, in this contribution a bidirectional flyback-converter is compared to a unidirectional with different discharging circuits. For this purpose, the design of a resistive and an inductive-resistive discharging circuit is proposed, that are connected in parallel to the DEAP and activated when required. Modulation schemes for both discharging circuits are derived that enable a continuous voltage control. Based on realized prototypes of the investigated topologies the different converters are finally compared to each other.

  4. Loss compensation in Metamaterials through embedding of active transistor based negative differential resistance circuits

    Xu, Wangren; Padilla, Willie J.; Sonkusale, Sameer

    2012-01-01

    This paper presents an all-electronic approach for loss compensation in metamaterials. This is achieved by embedding active-transistors based negative differential resistance (NDR) circuits in each unit cell of the metamaterial lattice. NDR circuits provide tunable loss compensation over a broad frequency range limited only by the maximum operating frequency of transistors that is reaching terahertz values in newer semiconductor processes. Design, simulation and experimental results of metama...

  5. Sustained activity in hierarchical modular neural networks: self-organized criticality and oscillations

    Sheng-Jun Wang

    2011-06-01

    Full Text Available Cerebral cortical brain networks possess a number of conspicuous features of structure and dynamics. First, these networks have an intricate, non-random organization. They are structured in a hierarchical modular fashion, from large-scale regions of the whole brain, via cortical areas and area subcompartments organized as structural and functional maps to cortical columns, and finally circuits made up of individual neurons. Second, the networks display self-organized sustained activity, which is persistent in the absence of external stimuli. At the systems level, such activity is characterized by complex rhythmical oscillations over a broadband background, while at the cellular level, neuronal discharges have been observed to display avalanches, indicating that cortical networks are at the state of self-organized criticality. We explored the relationship between hierarchical neural network organization and sustained dynamics using large-scale network modeling. It was shown that sparse random networks with balanced excitation and inhibition can sustain neural activity without external stimulation. We find that a hierarchical modular architecture can generate sustained activity better than random networks. Moreover, the system can simultaneously support rhythmical oscillations and self-organized criticality, which are not present in the respective random networks. The underlying mechanism is that each dense module cannot sustain activity on its own, but displays self-organized criticality in the presence of weak perturbations. The hierarchical modular networks provide the coupling among subsystems with self-organized criticality. These results imply that the hierarchical modular architecture of cortical networks plays an important role in shaping the ongoing spontaneous activity of the brain, potentially allowing the system to take advantage of both the sensitivityof critical state and predictability and timing of oscillations for efficient

  6. Motor neuron activation in peripheral nerves using infrared neural stimulation

    Peterson, E. J.; Tyler, D. J.

    2014-02-01

    Objective. Localized activation of peripheral axons may improve selectivity of peripheral nerve interfaces. Infrared neural stimulation (INS) employs localized delivery to activate neural tissue. This study investigated INS to determine whether localized delivery limited functionality in larger mammalian nerves. Approach. The rabbit sciatic nerve was stimulated extraneurally with 1875 nm wavelength infrared light, electrical stimulation, or a combination of both. Infrared-sensitive regions (ISR) of the nerve surface and electromyogram (EMG) recruitment of the Medial Gastrocnemius, Lateral Gastrocnemius, Soleus, and Tibialis Anterior were the primary output measures. Stimulation applied included infrared-only, electrical-only, and combined infrared and electrical. Main results. 81% of nerves tested were sensitive to INS, with 1.7 ± 0.5 ISR detected per nerve. INS was selective to a single muscle within 81% of identified ISR. Activation energy threshold did not change significantly with stimulus power, but motor activation decreased significantly when radiant power was decreased. Maximum INS levels typically recruited up to 2-9% of any muscle. Combined infrared and electrical stimulation differed significantly from electrical recruitment in 7% of cases. Significance. The observed selectivity of INS indicates that it may be useful in augmenting rehabilitation, but significant challenges remain in increasing sensitivity and response magnitude to improve the functionality of INS.

  7. Sparing of the hippocampus, limbic circuit and neural stem cell compartment during partial brain radiotherapy for glioma: a dosimetric feasibility study

    The aim of this study was to assess the feasibility of sparing contralateral or bilateral neural stem cell (NSC) compartment, hippocampus and limbic circuit during partial brain radiotherapy (PBRT). Treatment plans were generated for five hemispheric high-grade gliomas, five hemispheric low-grade gliomas and two brainstem gliomas (12 patients). For each, standard intensity-modulated radiotherapy (IMRT) plans were generated, as well as IMRT plans which spared contralateral (hemispheric cases) or bilateral (brainstem cases) limbic circuit, hippocampus, and NSC. Biologically equivalent dose for late effects (BEDlate effects) was generated for limbic circuit, hippocampus and NSC. Per cent relative reduction in mean physical dose and BED was calculated for each plan (standard vs. sparing). We were able to reduce physical dose and BEDlate effects to these critical structures by 23.5–56.8% and 23.6–66%, respectively. It is possible to spare contralateral limbic circuit, NSC and hippocampus during PBRT for both high- and low-grade gliomas using IMRT, and to spare the hippocampus bilaterally during PBRT for brainstem low-grade gliomas. This approach may reduce late cognitive sequelae of cranial radiotherapy.

  8. Infrared neural stimulation fails to evoke neural activity in the deaf guinea pig cochlea.

    Thompson, Alexander C; Fallon, James B; Wise, Andrew K; Wade, Scott A; Shepherd, Robert K; Stoddart, Paul R

    2015-06-01

    At present there is some debate as to the processes by which infrared neural stimulation (INS) activates neurons in the cochlea, as the lasers used for INS can potentially generate a range of secondary stimuli e.g. an acoustic stimulus is produced when the light is absorbed by water. To clarify whether INS in the cochlea requires functioning hair cells and to explore the potential relevance to cochlear implants, experiments using INS were performed in the cochleae of both normal hearing and profoundly deaf guinea pigs. A response to laser stimulation was readily evoked in normal hearing cochlea. However, no response was evoked in any profoundly deaf cochleae, for either acute or chronic deafening, contrary to previous work where a response was observed after acute deafening with ototoxic drugs. A neural response to electrical stimulation was readily evoked in all cochleae after deafening. The absence of a response from optical stimuli in profoundly deaf cochleae suggests that the response from INS in the cochlea is hair cell mediated. PMID:25796297

  9. Kohonen Neural Network Stress Detection Using Only Electrodermal Activity Features

    BORNOIU, I.-V.

    2014-08-01

    Full Text Available This paper presents a method for identifying human stress levels by using a Kohonen neural network. The study focuses on differentiating between a relaxed and a stressed state and it presents a series of parameters (skin conductance response signal power, skin conductance response signal frequency, skin conductance level gradient, response rise time and response amplitude extracted only from the electrodermal activity signal. A very strict recording protocol was used to minimize the artifacts caused by the bad connection between electrodes and skin. A stress inducing method is presented that can be used to replicate results in laboratory conditions.

  10. Sociocultural patterning of neural activity during self-reflection

    Ma, Yina; Bang, Dan; Wang, Chenbo;

    2014-01-01

    Chinese than in Danish participants. Moreover, the group difference in TPJ activity was mediated by a measure of a cultural value (i.e., interdependence of self-construal). Our findings suggest that individuals in different sociocultural contexts may learn and/or adopt distinct strategies for self......Western cultures encourage self-construals independent of social contexts whereas East Asian cultures foster interdependent self-construals that rely on how others perceive the self. How are culturally specific self-construals mediated by the human brain? Using functional MRI, we monitored neural......-reflection by changing the weight of the mPFC and TPJ in the social brain network....

  11. Reduction of activation and contamination of reactor circuits

    After investigation of the metal loss rate of INCOLOY 800 samples by several test series performes at 3420C and 150 bar with different oxygen contents in demineralized water (deionate), the protective gold plating applied on the inner side of the first autoclave system had to be renewed. Within the period of reporting the second autoclave system (same dimensions as the first autoclave system) also provided with an inner gold plating was nearly completed. Also a small sized third autoclave system has been completed which allows to study the metal loss rate to pressurized water of standard stainless steel, the material making up 15% of the inner surface of a primary reactor circuit. Reduction of the oxygen content in deionate by noble gas sweeping, which is much more effective than chemical reduction by hydrazine, was improved in combination with the first autoclave system. Apparently the minimum oxygen content of 0,05 mg/kg required for primary loop water of pressurized reactors can still be lowered by the factor of 20. (orig./RW)

  12. Activational and effort-related aspects of motivation: neural mechanisms and implications for psychopathology.

    Salamone, John D; Yohn, Samantha E; López-Cruz, Laura; San Miguel, Noemí; Correa, Mercè

    2016-05-01

    Motivation has been defined as the process that allows organisms to regulate their internal and external environment, and control the probability, proximity and availability of stimuli. As such, motivation is a complex process that is critical for survival, which involves multiple behavioural functions mediated by a number of interacting neural circuits. Classical theories of motivation suggest that there are both directional and activational aspects of motivation, and activational aspects (i.e. speed and vigour of both the instigation and persistence of behaviour) are critical for enabling organisms to overcome work-related obstacles or constraints that separate them from significant stimuli. The present review discusses the role of brain dopamine and related circuits in behavioural activation, exertion of effort in instrumental behaviour, and effort-related decision-making, based upon both animal and human studies. Impairments in behavioural activation and effort-related aspects of motivation are associated with psychiatric symptoms such as anergia, fatigue, lassitude and psychomotor retardation, which cross multiple pathologies, including depression, schizophrenia, and Parkinson's disease. Therefore, this review also attempts to provide an interdisciplinary approach that integrates findings from basic behavioural neuroscience, behavioural economics, clinical neuropsychology, psychiatry, and neurology, to provide a coherent framework for future research and theory in this critical field. Although dopamine systems are a critical part of the brain circuitry regulating behavioural activation, exertion of effort, and effort-related decision-making, mesolimbic dopamine is only one part of a distributed circuitry that includes multiple neurotransmitters and brain areas. Overall, there is a striking similarity between the brain areas involved in behavioural activation and effort-related processes in rodents and in humans. Animal models of effort-related decision

  13. Imaging evolutionarily conserved neural networks: preferential activation of the olfactory system by food-related odor.

    Kulkarni, Praveen; Stolberg, Tara; Sullivanjr, J M; Ferris, Craig F

    2012-04-21

    Rodents routinely forge and rely on hippocampal-dependent spatial memory to guide them to sources of caloric rich food in their environment. Has evolution affected the olfactory system and its connections to the hippocampus and limbic cortex, so rodents have an innate sensitivity to energy rich food and their location? To test this notion, we used functional magnetic resonance imaging in awake rats to observe changes in brain activity in response to four odors: benzaldehyde (almond odor), isoamyl acetate (banana odor), methyl benzoate (rosy odor), and limonene (citrus odor). We chose the almond odor because nuts are high in calories and would be expected to convey greater valance as compared to the other odors. Moreover, the standard food chow is devoid of nuts, so laboratory bred rats would not have any previous exposure to this food. Activation maps derived from computational analysis using a 3D segmented rat MRI atlas were dramatically different between odors. Animals exposed to banana, rosy and citrus odors showed modest activation of the primary olfactory system, hippocampus and limbic cortex. However, animals exposed to almond showed a robust increase in brain activity in the primary olfactory system particularly the main olfactory bulb, anterior olfactory nucleus and tenia tecta. The most significant difference in brain activation between odors was observed in the hippocampus and limbic cortex. These findings show that fMRI can be used to identify neural circuits that have an innate sensitivity to environmental stimuli that may help in an animal's survival. PMID:22343130

  14. Experiences of activity measurements of primary circuit materials in a WWR-SM research reactor

    The activity of water and gas samples taken from the primary circuit have been measured nondestructively for more than two years to monitor the technological parameters of the reactor. In the primary water samples 17 fission products and seven activated traces, as well as six radioactive conponents in the gas samples were determined routinely by Ge/Li gamma-spectrometry. (author)

  15. An adaptive active control for the modified Chua's circuit

    In this Letter, it is shown that a couple of the modified Chua's systems with different parameters and initial conditions can be synchronized using active control when the values of parameters both in drive system and response system are known aforehand. Furthermore, an adaptive active control approach is proposed based on Lyapunov stability theory to make the states of two identical Chua's systems with unknown constant parameters be asymptotically synchronized. In addition, the proposed adaptive active control method guarantees that the designed controller is independent to those uncertain parameters. Simulation results by using both active control and adaptive active control are provided, and the feasibility and effectiveness of the proposed adaptive active control are demonstrated

  16. Visual avoidance in phobia: particularities in neural activity, autonomic responding, and cognitive risk evaluations

    Tatjana Aue

    2013-05-01

    Full Text Available We investigated the neural mechanisms and the autonomic and cognitive responses associated with visual avoidance behavior in spider phobia. Spider phobic and control participants imagined visiting different forest locations with the possibility of encountering spiders, snakes, or birds (neutral reference category. In each experimental trial, participants saw a picture of a forest location followed by a picture of a spider, snake, or bird, and then rated their personal risk of encountering these animals in this context, as well as their fear. The greater the visual avoidance of spiders that a phobic participant demonstrated (as measured by eye tracking, the higher were her autonomic arousal and neural activity in the amygdala, orbitofrontal cortex (OFC, anterior cingulate cortex (ACC, and precuneus at picture onset. Visual avoidance of spiders in phobics also went hand in hand with subsequently reduced cognitive risk of encounters. Control participants, in contrast, displayed a positive relationship between gaze duration toward spiders, on the one hand, and autonomic responding, as well as OFC, ACC, and precuneus activity, on the other hand. In addition, they showed reduced encounter risk estimates when they looked longer at the animal pictures. Our data are consistent with the idea that one reason for phobics to avoid phobic information may be grounded in heightened activity in the fear circuit, which signals potential threat. Because of the absence of alternative efficient regulation strategies, visual avoidance may then function to down-regulate cognitive risk evaluations for threatening information about the phobic stimuli. Control participants, in contrast, may be characterized by a different coping style, whereby paying visual attention to potentially threatening information may help them to actively down-regulate cognitive evaluations of risk.

  17. Multiswitching Synchronization of a Driven Hyperchaotic Circuit Using Active Backstepping

    A. Ayotunde Ajayi

    2014-01-01

    Full Text Available An active backstepping technique is proposed for the realization of multiswitching synchronization of periodically forced hyperchaotic Van der Pol-Duffing oscillators. The active backstepping technique is a systematic design approach with recursive procedures that skillfully optimizes the choice of Lyapunov functions and active control technique. Using the active backstepping technique, the usual master-slave synchronization scheme is extended to study the synchronization of systems with different combinations of the slave states variables with master state variables. Our numerical results confirm the effectiveness of the proposed analytical technique.

  18. Striatal plasticity and basal ganglia circuit function

    Kreitzer, Anatol C.; Malenka, Robert C.

    2008-01-01

    The dorsal striatum, which consists of the caudate and putamen, is the gateway to the basal ganglia. It receives convergent excitatory afferents from cortex and thalamus and forms the origin of the direct and indirect pathways—distinct basal ganglia circuits involved in motor control. It is also a major site of activity-dependent synaptic plasticity. Striatal plasticity alters the transfer of information throughout basal ganglia circuits and may represent a key neural substrate for adaptive m...

  19. Classification of the extracellular fields produced by activated neural structures

    Perry Danielle

    2005-09-01

    Full Text Available Abstract Background Classifying the types of extracellular potentials recorded when neural structures are activated is an important component in understanding nerve pathophysiology. Varying definitions and approaches to understanding the factors that influence the potentials recorded during neural activity have made this issue complex. Methods In this article, many of the factors which influence the distribution of electric potential produced by a traveling action potential are discussed from a theoretical standpoint with illustrative simulations. Results For an axon of arbitrary shape, it is shown that a quadrupolar potential is generated by action potentials traveling along a straight axon. However, a dipole moment is generated at any point where an axon bends or its diameter changes. Next, it is shown how asymmetric disturbances in the conductivity of the medium surrounding an axon produce dipolar potentials, even during propagation along a straight axon. Next, by studying the electric fields generated by a dipole source in an insulating cylinder, it is shown that in finite volume conductors, the extracellular potentials can be very different from those in infinite volume conductors. Finally, the effects of impulses propagating along axons with inhomogeneous cable properties are analyzed. Conclusion Because of the well-defined factors affecting extracellular potentials, the vague terms far-field and near-field potentials should be abandoned in favor of more accurate descriptions of the potentials.

  20. An Efficiency Improved Active Power Decoupling Circuit with Minimized Implementation Cost

    Tang, Yi; Blaabjerg, Frede

    2014-01-01

    Active power decoupling techniques are promising solutions for capacitance reduction in single-phase AC/DC or DC/AC systems. This paper proposes a novel circuit topology which can realize the power decoupling function without adding additional active switches into the circuit. Also, the proposed...... topology does not require additional passive component, e.g. inductors or film capacitors for ripple energy storage because this task can be accomplished by the dc-link capacitors themselves, and therefore its implementation cost can be minimized. Another unique feature of the proposed topology...

  1. Transcriptional Regulatory Circuits Controlling Brown Fat Development and Activation

    Seale, Patrick

    2015-01-01

    Brown and beige adipose tissue is specialized for heat production and can be activated to reduce obesity and metabolic dysfunction in animals. Recent studies also have indicated that human brown fat activity levels correlate with leanness. This has revitalized interest in brown fat biology and has driven the discovery of many new regulators of brown fat development and function. This review summarizes recent advances in our understanding of the transcriptional mechanisms that control brown an...

  2. Reduced parahippocampal connectivity produces schizophrenia-like memory deficits in simulated neural circuits with reduced parahippocampal connectivity

    L. Talamini; M. Meeter; B. Elvevåg; J.M.J. Murre; T.E. Goldberg

    2005-01-01

    Episodic memory impairments are well characterized in schizophrenia, but their neural origin is unclear. The objective of this experiment is to determine whether the episodic memory impairments in schizophrenia may originate from reduced parahippocampal connectivity. The experimental design used was

  3. Dopamine Modulation of Emotional Processing in Cortical and Subcortical Neural Circuits: Evidence for a Final Common Pathway in Schizophrenia?

    Laviolette, Steven R

    2007-01-01

    The neural regulation of emotional perception, learning, and memory is essential for normal behavioral and cognitive functioning. Many of the symptoms displayed by individuals with schizophrenia may arise from fundamental disturbances in the ability to accurately process emotionally salient sensory information. The neurotransmitter dopamine (DA) and its ability to modulate neural regions involved in emotional learning, perception, and memory formation has received considerable research attent...

  4. Activity-dependent plasticity in the isolated embryonic avian brainstem following manipulations of rhythmic spontaneous neural activity.

    Vincen-Brown, Michael A; Revill, Ann L; Pilarski, Jason Q

    2016-07-15

    When rhythmic spontaneous neural activity (rSNA) first appears in the embryonic chick brainstem and cranial nerve motor axons it is principally driven by nicotinic neurotransmission (NT). At this early age, the nicotinic acetylcholine receptor (nAChR) agonist nicotine is known to critically disrupt rSNA at low concentrations (0.1-0.5μM), which are levels that mimic the blood plasma levels of a fetus following maternal cigarette smoking. Thus, we quantified the effect of persistent exposure to exogenous nicotine on rSNA using an in vitro developmental model. We found that rSNA was eliminated by continuous bath application of exogenous nicotine, but rSNA recovered activity within 6-12h despite the persistent activation and desensitization of nAChRs. During the recovery period rSNA was critically driven by chloride-mediated membrane depolarization instead of nicotinic NT. To test whether this observed compensation was unique to the antagonism of nicotinic NT or whether the loss of spiking behavior also played a role, we eliminated rSNA by lowering overall excitatory drive with a low [K(+)]o superfusate. In this context, rSNA again recovered, although the recovery time was much quicker, and exhibited a lower frequency, higher duration, and an increase in the number of bursts per episode when compared to control embryos. Importantly, we show that the main compensatory response to lower overall excitatory drive, similar to nicotinergic block, is a result of potentiated chloride mediated membrane depolarization. These results support increasing evidence that early neural circuits sense spiking behavior to maintain primordial bioelectric rhythms. Understanding the nature of developmental plasticity in the nervous system, especially versions that preserve rhythmic behaviors following clinically meaningful environmental stimuli, both normal and pathological, will require similar studies to determine the consequences of feedback compensation at more mature chronological ages

  5. Cat's medullary reticulospinal and subnucleus reticularis dorsalis noxious neurons form a coupled neural circuit through collaterals of descending axons.

    Leiras, Roberto; Martín-Cora, Francisco; Velo, Patricia; Liste, Tania; Canedo, Antonio

    2016-01-01

    Animals and human beings sense and react to real/potential dangerous stimuli. However, the supraspinal mechanisms relating noxious sensing and nocifensive behavior are mostly unknown. The collateralization and spatial organization of interrelated neurons are important determinants of coordinated network function. Here we electrophysiologically studied medial medullary reticulospinal neurons (mMRF-RSNs) antidromically identified from the cervical cord of anesthetized cats and found that 1) more than 40% (79/183) of the sampled mMRF-RSNs emitted bifurcating axons running within the dorsolateral (DLF) and ventromedial (VMF) ipsilateral fascicles; 2) more than 50% (78/151) of the tested mMRF-RSNs with axons running in the VMF collateralized to the subnucleus reticularis dorsalis (SRD) that also sent ipsilateral descending fibers bifurcating within the DLF and the VMF. This percentage of mMRF collateralization to the SRD increased to more than 81% (53/65) when considering the subpopulation of mMRF-RSNs responsive to noxiously heating the skin; 3) reciprocal monosynaptic excitatory relationships were electrophysiologically demonstrated between noxious sensitive mMRF-RSNs and SRD cells; and 4) injection of the anterograde tracer Phaseolus vulgaris leucoagglutinin evidenced mMRF to SRD and SRD to mMRF projections contacting the soma and proximal dendrites. The data demonstrated a SRD-mMRF network interconnected mainly through collaterals of descending axons running within the VMF, with the subset of noxious sensitive cells forming a reverberating circuit probably amplifying mutual outputs simultaneously regulating motor activity and spinal noxious afferent input. The results provide evidence that noxious stimulation positively engages a reticular SRD-mMRF-SRD network involved in pain-sensory-to-motor transformation and modulation. PMID:26581870

  6. Integrated Brain Circuits: Astrocytic Networks Modulate Neuronal Activity and Behavior

    Halassa, Michael M.; Haydon, Philip G.

    2011-01-01

    The past decade has seen an explosion of research on roles of neuron-astrocyte interactions in the control of brain function. We highlight recent studies performed on the tripartite synapse, the structure consisting of pre- and postsynaptic elements of the synapse and an associated astrocytic process. Astrocytes respond to neuronal activity and neuro-transmitters, through the activation of metabotropic receptors, and can release the gliotransmitters ATP, D-serine, and glutamate, which act on neurons. Astrocyte-derived ATP modulates synaptic transmission, either directly or through its metabolic product adenosine. D-serine modulates NMDA receptor function, whereas glia-derived glutamate can play important roles in relapse following withdrawal from drugs of abuse. Cell type–specific molecular genetics has allowed a new level of examination of the function of astrocytes in brain function and has revealed an important role of these glial cells that is mediated by adenosine accumulation in the control of sleep and in cognitive impairments that follow sleep deprivation. PMID:20148679

  7. Artificial Neural Network Characteristic For Neutron Activation Analysis

    Neutron activation analysis (NAA) is one of analysis methods for identification of elements from material. Irradiated unknown material could be identified by gamma spectrum pattern analysis. The recognition process will be done easily if we have a smart system. One of the smart system choices was artificial neural network (ANN). The gamma spectrum emitted from radioactive nuclide has specific pattern, therefore smart system will try to classify the input data. Firstly, Hp-Ge detector detects gamma radiation from material, then the gamma radiations is counted by multi channel analysis instrument (MCA). The smart system based ANN system was tested to identify 50 material, in which the system has been trained by using one data only for each classifications. The result showed that the ANN appreciates 100% identification capability or has a good performance

  8. Effects of Near-Infrared Laser on Neural Cell Activity

    Near-infrared laser has been used to relieve patients from various kinds of pain caused by postherpetic neuralgesia, myofascial dysfunction, surgical and traumatic wound, cancer, and rheumatoid arthritis. Clinically, He-Ne (λ=632.8 nm, 780 nm) and Ga-Al-As (805 ± 25 nm) lasers are used to irradiate trigger points or nerve ganglion. However the precise mechanisms of such biological actions of the laser have not yet been resolved. Since laser therapy is often effective to suppress the pain caused by hyperactive excitation of sensory neurons, interactions with laser light and neural cells are suggested. As neural excitation requires large amount of energy liberated from adenosine triphosphate (ATP), we examined the effect of 830-nm laser irradiation on the energy metabolism of the rat central nervous system and isolated mitochondria from brain. The diode laser was applied for 15 min with irradiance of 4.8 W/cm2 on a 2 mm-diameter spot at the brain surface. Tissue ATP content of the irradiated area in the cerebral cortex was 19% higher than that of the non-treated area (opposite side of the cortex), whereas the ADP content showed no significant difference. Irradiation at another wavelength (652 nm) had no effect on either ATP or ADP contents. The temperature of the brain tissue was increased 4.5-5.0 deg. C during the irradiation of both 830-nm and 652-nm laser light. Direct irradiation of the mitochondrial suspension did not show any wavelength-dependent acceleration of respiration rate nor ATP synthesis. These results suggest that the increase in tissue ATP content did not result from the thermal effect, but from specific effect of the laser operated at 830 nm. Electrophysiological studies showed the hyperpolarization of membrane potential of isolated neurons and decrease in membrane resistance with irradiation of the laser, suggesting an activation of potassium channels. Intracellular ATP is reported to regulate some kinds of potassium channels. Possible mechanisms

  9. Can simple interactions capture complex features of neural activity underlying behavior in a virtual reality environment?

    Meshulam, Leenoy; Gauthier, Jeffrey; Brody, Carlos; Tank, David; Bialek, William

    The complex neural interactions which are abundant in most recordings of neural activity are relatively poorly understood. A prime example of such interactions can be found in the in vivo neural activity which underlies complex behaviors of mice, imaged in brain regions such as hippocampus and parietal cortex. Experimental techniques now allow us to accurately follow these neural interactions in the simultaneous activity of large neuronal populations of awake behaving animals. Here, we demonstrate that pairwise maximum entropy models can predict a surprising number of properties of the neural activity. The models, that are constrained with activity rates and interactions between pairs of neurons, are well fit to the activity `states' in the hippocampus and cortex of mice performing cognitive tasks while navigating in a virtual reality environment.

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

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

    2009-01-01

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