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Sample records for neural activity generated

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

    Science.gov (United States)

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

    2013-01-01

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

  2. Physical methods for generating and decoding neural activity in Hirudo verbana

    Science.gov (United States)

    Migliori, Benjamin John

    The interface between living nervous systems and hardware is an excellent proving ground for precision experimental methods and information classification systems. Nervous systems are complex (104 -- 10 15(!) connections), fragile, and highly active in intricate, constantly evolving patterns. However, despite the conveniently electrical nature of neural transmission, the interface between nervous systems and hardware poses significant experimental difficulties. As the desire for direct interfaces with neural signals continues to expand, the need for methods of generating and measuring neural activity with high spatiotemporal precision has become increasingly critical. In this thesis, I describe advances I have made in the ability to modify, generate, measure, and understand neural signals both in- and ex-vivo. I focus on methods developed for transmitting and extracting signals in the intact nervous system of Hirudo verbana (the medicinal leech), an animal with a minimally complex nervous system (10000 neurons distributed in packets along a nerve cord) that exhibits a diverse array of behaviors. To introduce artificial activity patterns, I developed a photothermal activation system in which a highly focused laser is used to irradiate carbon microparticles in contact with target neurons. The resulting local temperature increase generates an electrical current that forces the target neuron to fire neural signals, thereby providing a unique neural input mechanism. These neural signals can potentially be used to alter behavioral choice or generate specific behavioral output, and can be used endogenously in many animal models. I also describe new tools developed to expand the application of this method. In complement to this input system, I describe a new method of analyzing neural output signals involved in long-range coordination of behaviors. Leech behavioral signals are propagated between neural packets as electrical pulses in the nerve connective, a bundle of

  3. Stem cells from human exfoliated deciduous tooth exhibit stromal-derived inducing activity and lead to generation of neural crest cells from human embryonic stem cells.

    Science.gov (United States)

    Karbalaie, Khadijeh; Tanhaei, Somayyeh; Rabiei, Farzaneh; Kiani-Esfahani, Abbas; Masoudi, Najmeh Sadat; Nasr-Esfahani, Mohammad Hossein; Baharvand, Hossein

    2015-01-01

    The neural crest is a transient structure of early vertebrate embryos that generates neural crest cells (NCCs). These cells can migrate throughout the body and produce a diverse array of mature tissue types. Due to the ethical and technical problems surrounding the isolation of these early human embryo cells, researchers have focused on in vitro studies to produce NCCs and increase their knowledge of neural crest development. In this experimental study, we cultured human embryonic stem cells (hESCs) on stromal stem cells from human exfoliated deciduous teeth (SHED) for a two-week period. We used different approaches to characterize these differentiated cells as neural precursor cells (NPCs) and NCCs. In the first co-culture week, hESCs appeared as crater-like structures with marginal rosettes. NPCs derived from these structures expressed the early neural crest marker p75 in addition to numerous other genes associated with neural crest induction such as SNAIL, SLUG, PTX3 and SOX9. Flow cytometry analysis showed 70% of the cells were AP2/P75 positive. Moreover, the cells were able to self-renew, sustain multipotent differentiation potential, and readily form neurospheres in suspension culture. SHED, as an adult stem cell with a neural crest origin, has stromal-derived inducing activity (SDIA) and can be used as an NCC inducer from hESCs. These cells provide an invaluable resource to study neural crest differentiation in both normal and disordered human neural crest development.

  4. Neural network approaches to dynamic collision-free trajectory generation.

    Science.gov (United States)

    Yang, S X; Meng, M

    2001-01-01

    In this paper, dynamic collision-free trajectory generation in a nonstationary environment is studied using biologically inspired neural network approaches. The proposed neural network is topologically organized, where the dynamics of each neuron is characterized by a shunting equation or an additive equation. The state space of the neural network can be either the Cartesian workspace or the joint space of multi-joint robot manipulators. There are only local lateral connections among neurons. The real-time optimal trajectory is generated through the dynamic activity landscape of the neural network without explicitly searching over the free space nor the collision paths, without explicitly optimizing any global cost functions, without any prior knowledge of the dynamic environment, and without any learning procedures. Therefore the model algorithm is computationally efficient. The stability of the neural network system is guaranteed by the existence of a Lyapunov function candidate. In addition, this model is not very sensitive to the model parameters. Several model variations are presented and the differences are discussed. As examples, the proposed models are applied to generate collision-free trajectories for a mobile robot to solve a maze-type of problem, to avoid concave U-shaped obstacles, to track a moving target and at the same to avoid varying obstacles, and to generate a trajectory for a two-link planar robot with two targets. The effectiveness and efficiency of the proposed approaches are demonstrated through simulation and comparison studies.

  5. Neural mechanisms of sequence generation in songbirds

    Science.gov (United States)

    Langford, Bruce

    Animal models in research are useful for studying more complex behavior. For example, motor sequence generation of actions requiring good muscle coordination such as writing with a pen, playing an instrument, or speaking, may involve the interaction of many areas in the brain, each a complex system in itself; thus it can be difficult to determine causal relationships between neural behavior and the behavior being studied. Birdsong, however, provides an excellent model behavior for motor sequence learning, memory, and generation. The song consists of learned sequences of notes that are spectrographically stereotyped over multiple renditions of the song, similar to syllables in human speech. The main areas of the songbird brain involve in singing are known, however, the mechanisms by which these systems store and produce song are not well understood. We used a custom built, head-mounted, miniature motorized microdrive to chronically record the neural firing patterns of identified neurons in HVC, a pre-motor cortical nucleus which has been shown to be important in song timing. These were done in Bengalese finch which generate a song made up of stereotyped notes but variable note sequences. We observed song related bursting in neurons projecting to Area X, a homologue to basal ganglia, and tonic firing in HVC interneurons. Interneuron had firing rate patterns that were consistent over multiple renditions of the same note sequence. We also designed and built a light-weight, low-powered wireless programmable neural stimulator using Bluetooth Low Energy Protocol. It was able to generate perturbations in the song when current pulses were administered to RA, which projects to the brainstem nucleus responsible for syringeal muscle control.

  6. The neural component-process architecture of endogenously generated emotion.

    Science.gov (United States)

    Engen, Haakon G; Kanske, Philipp; Singer, Tania

    2017-02-01

    Despite the ubiquity of endogenous emotions and their role in both resilience and pathology, the processes supporting their generation are largely unknown. We propose a neural component process model of endogenous generation of emotion (EGE) and test it in two functional magnetic resonance imaging (fMRI) experiments (N = 32/293) where participants generated and regulated positive and negative emotions based on internal representations, usin self-chosen generation methods. EGE activated nodes of salience (SN), default mode (DMN) and frontoparietal control (FPCN) networks. Component processes implemented by these networks were established by investigating their functional associations, activation dynamics and integration. SN activation correlated with subjective affect, with midbrain nodes exclusively distinguishing between positive and negative affect intensity, showing dynamics consistent generation of core affect. Dorsomedial DMN, together with ventral anterior insula, formed a pathway supporting multiple generation methods, with activation dynamics suggesting it is involved in the generation of elaborated experiential representations. SN and DMN both coupled to left frontal FPCN which in turn was associated with both subjective affect and representation formation, consistent with FPCN supporting the executive coordination of the generation process. These results provide a foundation for research into endogenous emotion in normal, pathological and optimal function. © The Author (2016). Published by Oxford University Press.

  7. Myelin plasticity, neural activity, and traumatic neural injury.

    Science.gov (United States)

    Kondiles, Bethany R; Horner, Philip J

    2018-02-01

    The possibility that adult organisms exhibit myelin plasticity has recently become a topic of great interest. Many researchers are exploring the role of myelin growth and adaptation in daily functions such as memory and motor learning. Here we consider evidence for three different potential categories of myelin plasticity: the myelination of previously bare axons, remodeling of existing sheaths, and the removal of a sheath with replacement by a new internode. We also review evidence that points to the importance of neural activity as a mechanism by which oligodendrocyte precursor cells (OPCs) are cued to differentiate into myelinating oligodendrocytes, which may potentially be an important component of myelin plasticity. Finally, we discuss demyelination in the context of traumatic neural injury and present an argument for altering neural activity as a potential therapeutic target for remyelination following injury. © 2017 Wiley Periodicals, Inc. Develop Neurobiol 78: 108-122, 2018. © 2017 Wiley Periodicals, Inc.

  8. Embedding responses in spontaneous neural activity shaped through sequential learning.

    Science.gov (United States)

    Kurikawa, Tomoki; Kaneko, Kunihiko

    2013-01-01

    Recent experimental measurements have demonstrated that spontaneous neural activity in the absence of explicit external stimuli has remarkable spatiotemporal structure. This spontaneous activity has also been shown to play a key role in the response to external stimuli. To better understand this role, we proposed a viewpoint, "memories-as-bifurcations," that differs from the traditional "memories-as-attractors" viewpoint. Memory recall from the memories-as-bifurcations viewpoint occurs when the spontaneous neural activity is changed to an appropriate output activity upon application of an input, known as a bifurcation in dynamical systems theory, wherein the input modifies the flow structure of the neural dynamics. Learning, then, is a process that helps create neural dynamical systems such that a target output pattern is generated as an attractor upon a given input. Based on this novel viewpoint, we introduce in this paper an associative memory model with a sequential learning process. Using a simple hebbian-type learning, the model is able to memorize a large number of input/output mappings. The neural dynamics shaped through the learning exhibit different bifurcations to make the requested targets stable upon an increase in the input, and the neural activity in the absence of input shows chaotic dynamics with occasional approaches to the memorized target patterns. These results suggest that these dynamics facilitate the bifurcations to each target attractor upon application of the corresponding input, which thus increases the capacity for learning. This theoretical finding about the behavior of the spontaneous neural activity is consistent with recent experimental observations in which the neural activity without stimuli wanders among patterns evoked by previously applied signals. In addition, the neural networks shaped by learning properly reflect the correlations of input and target-output patterns in a similar manner to those designed in our previous study.

  9. Embedding responses in spontaneous neural activity shaped through sequential learning.

    Directory of Open Access Journals (Sweden)

    Tomoki Kurikawa

    Full Text Available Recent experimental measurements have demonstrated that spontaneous neural activity in the absence of explicit external stimuli has remarkable spatiotemporal structure. This spontaneous activity has also been shown to play a key role in the response to external stimuli. To better understand this role, we proposed a viewpoint, "memories-as-bifurcations," that differs from the traditional "memories-as-attractors" viewpoint. Memory recall from the memories-as-bifurcations viewpoint occurs when the spontaneous neural activity is changed to an appropriate output activity upon application of an input, known as a bifurcation in dynamical systems theory, wherein the input modifies the flow structure of the neural dynamics. Learning, then, is a process that helps create neural dynamical systems such that a target output pattern is generated as an attractor upon a given input. Based on this novel viewpoint, we introduce in this paper an associative memory model with a sequential learning process. Using a simple hebbian-type learning, the model is able to memorize a large number of input/output mappings. The neural dynamics shaped through the learning exhibit different bifurcations to make the requested targets stable upon an increase in the input, and the neural activity in the absence of input shows chaotic dynamics with occasional approaches to the memorized target patterns. These results suggest that these dynamics facilitate the bifurcations to each target attractor upon application of the corresponding input, which thus increases the capacity for learning. This theoretical finding about the behavior of the spontaneous neural activity is consistent with recent experimental observations in which the neural activity without stimuli wanders among patterns evoked by previously applied signals. In addition, the neural networks shaped by learning properly reflect the correlations of input and target-output patterns in a similar manner to those designed in

  10. Combinatorially Generated Piecewise Activation Functions

    OpenAIRE

    Chen, Justin

    2016-01-01

    In the neuroevolution literature, research has primarily focused on evolving the number of nodes, connections, and weights in artificial neural networks. Few attempts have been made to evolve activation functions. Research in evolving activation functions has mainly focused on evolving function parameters, and developing heterogeneous networks by selecting from a fixed pool of activation functions. This paper introduces a novel technique for evolving heterogeneous artificial neural networks t...

  11. Application of Artificial Neural Networks for Predicting Generated Wind Power

    OpenAIRE

    Vijendra Singh

    2016-01-01

    This paper addresses design and development of an artificial neural network based system for prediction of wind energy produced by wind turbines. Now in the last decade, renewable energy emerged as an additional alternative source for electrical power generation. We need to assess wind power generation capacity by wind turbines because of its non-exhaustible nature. The power generation by electric wind turbines depends on the speed of wind, flow direction, fluctuations, density of air, gener...

  12. Neural networks with discontinuous/impact activations

    CERN Document Server

    Akhmet, Marat

    2014-01-01

    This book presents as its main subject new models in mathematical neuroscience. A wide range of neural networks models with discontinuities are discussed, including impulsive differential equations, differential equations with piecewise constant arguments, and models of mixed type. These models involve discontinuities, which are natural because huge velocities and short distances are usually observed in devices modeling the networks. A discussion of the models, appropriate for the proposed applications, is also provided. This book also: Explores questions related to the biological underpinning for models of neural networks\\ Considers neural networks modeling using differential equations with impulsive and piecewise constant argument discontinuities Provides all necessary mathematical basics for application to the theory of neural networks Neural Networks with Discontinuous/Impact Activations is an ideal book for researchers and professionals in the field of engineering mathematics that have an interest in app...

  13. Physical activity and environmental enrichment regulate the generation of neural precursors in the adult mouse substantia nigra in a dopamine-dependent manner

    Directory of Open Access Journals (Sweden)

    Klaissle Philipp

    2012-10-01

    Full Text Available Abstract Background Parkinson’s disease is characterized by a continuous loss of neurons within the substantia nigra (SN leading to a depletion of dopamine. Within the adult SN as a non-neurogenic region, cells with mainly oligodendrocytic precursor characteristics, expressing the neuro-glial antigen-2 (NG2 are continuously generated. Proliferation of these cells is altered in animal models of Parkinson’s disease (PD. Exercise and environmental enrichment re-increase proliferation of NG2+ cells in PD models, however, a possible mechanistic role of dopamine for this increase is not completely understood. NG2+ cells can differentiate into oligodendrocytes but also into microglia and neurons as observed in vitro suggesting a possible hint for endogenous regenerative capacity of the SN. We investigated the role of dopamine in NG2-generation and differentiation in the adult SN stimulated by physical activity and environmental enrichment. Results We used the 1-methyl-4-phenyl-1,2,3,6-tetrahydropyridine (MPTP-model for dopamine depletion and analysed newborn cells in the SN at different maturation stages and time points depending on voluntary physical activity, enriched environment and levodopa-treatment. We describe an activity- induced increase of new NG2-positive cells and also mature oligodendrocytes in the SN of healthy mice. Running and enriched environment refused to stimulate NG2-generation and oligodendrogenesis in MPTP-mice, an effect which could be reversed by pharmacological levodopa-induced rescue. Conclusion We suggest dopamine being a key regulator for activity-induced generation of NG2-cells and oliogodendrocytes in the SN as a potentially relevant mechanism in endogenous nigral cellular plasticity.

  14. Neural progenitors generated from the mesenchymal stem cells of first-trimester human placenta matured in the hypoxic-ischemic rat brain and mediated restoration of locomotor activity.

    Science.gov (United States)

    Park, S; Koh, S-E; Maeng, S; Lee, W-D; Lim, J; Lee, Y-J

    2011-03-01

    Term placenta is a great reservoir of mesenchymal stem cells (MSCs), however, the potential of the earlier placenta is largely unknown. In this report, we established 17 MSC lines from 19 first-trimester human placenta (fPMSC). fPMSC proliferated for 90-150 days in vitro and by enhanced cellular interaction, fPMSC differentiated into nestin-expressing neural progenitor cells (fPMSC-NP), accompanied by inductions of immature neuron-specific genes. Therapeutic effect of the fPMSC-NP was tested in the animal model of hypoxia-ischemia (HI) which was devastating to dopaminergic neurons and to locomotor activity. Improvement of motor activity was evident as early as 2 weeks after transplantation of the fPMSC-NP into bilateral striatum and became indistinguishable from that of the age-matched normal animals by 8 weeks but no spontaneous recovery was observed in the control-grafted animals. Immunohistochemical analyses revealed that the implanted fPMSC-NP matured into ectodermal cells including the tyrosine hydroxylase (TH)-expressing neurons in the recipient striatum. So, the improved motor behavior was likely due to the dopaminergic differentiation of the implanted fPMSC-NP in the dopaminergic-denervated host brain. Based on this result, we propose that progenitors may be more advantageous than the terminally differentiated cells for the purpose of cell replacement therapies since the progenitors are easily obtainable and are expected to be more pliable to the new environment. Copyright © 2011. Published by Elsevier Ltd.

  15. Face Deidentification with Generative Deep Neural Networks

    OpenAIRE

    Meden, Blaž; Mallı, Refik Can; FABIJAN, SEBASTJAN; Ekenel, Hazım Kemal; Štruc, Vitomir; Peer, Peter

    2017-01-01

    Face deidentification is an active topic amongst privacy and security researchers. Early deidentification methods relying on image blurring or pixelization were replaced in recent years with techniques based on formal anonymity models that provide privacy guaranties and at the same time aim at retaining certain characteristics of the data even after deidentification. The latter aspect is particularly important, as it allows to exploit the deidentified data in applications for which identity i...

  16. Influence of neural adaptation on dynamics and equilibrium state of neural activities in a ring neural network

    Science.gov (United States)

    Takiyama, Ken

    2017-12-01

    How neural adaptation affects neural information processing (i.e. the dynamics and equilibrium state of neural activities) is a central question in computational neuroscience. In my previous works, I analytically clarified the dynamics and equilibrium state of neural activities in a ring-type neural network model that is widely used to model the visual cortex, motor cortex, and several other brain regions. The neural dynamics and the equilibrium state in the neural network model corresponded to a Bayesian computation and statistically optimal multiple information integration, respectively, under a biologically inspired condition. These results were revealed in an analytically tractable manner; however, adaptation effects were not considered. Here, I analytically reveal how the dynamics and equilibrium state of neural activities in a ring neural network are influenced by spike-frequency adaptation (SFA). SFA is an adaptation that causes gradual inhibition of neural activity when a sustained stimulus is applied, and the strength of this inhibition depends on neural activities. I reveal that SFA plays three roles: (1) SFA amplifies the influence of external input in neural dynamics; (2) SFA allows the history of the external input to affect neural dynamics; and (3) the equilibrium state corresponds to the statistically optimal multiple information integration independent of the existence of SFA. In addition, the equilibrium state in a ring neural network model corresponds to the statistically optimal integration of multiple information sources under biologically inspired conditions, independent of the existence of SFA.

  17. Generating three-qubit quantum circuits with neural networks

    Science.gov (United States)

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

    2017-10-01

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

  18. Machine Comprehension by Text-to-Text Neural Question Generation

    OpenAIRE

    Yuan, Xingdi; Wang, Tong; Gulcehre, Caglar; Sordoni, Alessandro; Bachman, Philip; Subramanian, Sandeep; Zhang, Saizheng; Trischler, Adam

    2017-01-01

    We propose a recurrent neural model that generates natural-language questions from documents, conditioned on answers. We show how to train the model using a combination of supervised and reinforcement learning. After teacher forcing for standard maximum likelihood training, we fine-tune the model using policy gradient techniques to maximize several rewards that measure question quality. Most notably, one of these rewards is the performance of a question-answering system. We motivate question ...

  19. Neural Network-Based Abstract Generation for Opinions and Arguments

    OpenAIRE

    Wang, Lu; Ling, Wang

    2016-01-01

    We study the problem of generating abstractive summaries for opinionated text. We propose an attention-based neural network model that is able to absorb information from multiple text units to construct informative, concise, and fluent summaries. An importance-based sampling method is designed to allow the encoder to integrate information from an important subset of input. Automatic evaluation indicates that our system outperforms state-of-the-art abstractive and extractive summarization syst...

  20. Genetic control of active neural circuits

    Directory of Open Access Journals (Sweden)

    Leon Reijmers

    2009-12-01

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

  1. Neural activation in stress-related exhaustion

    DEFF Research Database (Denmark)

    Gavelin, Hanna Malmberg; Neely, Anna Stigsdotter; Andersson, Micael

    2017-01-01

    The primary purpose of this study was to investigate the association between burnout and neural activation during working memory processing in patients with stress-related exhaustion. Additionally, we investigated the neural effects of cognitive training as part of stress rehabilitation. Fifty......-five patients with clinical diagnosis of exhaustion disorder were administered the n-back task during fMRI scanning at baseline. Ten patients completed a 12-week cognitive training intervention, as an addition to stress rehabilitation. Eleven patients served as a treatment-as-usual control group. At baseline...

  2. Code generation: a strategy for neural network simulators.

    Science.gov (United States)

    Goodman, Dan F M

    2010-10-01

    We demonstrate a technique for the design of neural network simulation software, runtime code generation. This technique can be used to give the user complete flexibility in specifying the mathematical model for their simulation in a high level way, along with the speed of code written in a low level language such as C+ +. It can also be used to write code only once but target different hardware platforms, including inexpensive high performance graphics processing units (GPUs). Code generation can be naturally combined with computer algebra systems to provide further simplification and optimisation of the generated code. The technique is quite general and could be applied to any simulation package. We demonstrate it with the 'Brian' simulator ( http://www.briansimulator.org ).

  3. Artificial earthquake record generation using cascade neural network

    Directory of Open Access Journals (Sweden)

    Bani-Hani Khaldoon A.

    2017-01-01

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

  4. Neural predictive control for active buffet alleviation

    Science.gov (United States)

    Pado, Lawrence E.; Lichtenwalner, Peter F.; Liguore, Salvatore L.; Drouin, Donald

    1998-06-01

    The adaptive neural control of aeroelastic response (ANCAR) and the affordable loads and dynamics independent research and development (IRAD) programs at the Boeing Company jointly examined using neural network based active control technology for alleviating undesirable vibration and aeroelastic response in a scale model aircraft vertical tail. The potential benefits of adaptive control includes reducing aeroelastic response associated with buffet and atmospheric turbulence, increasing flutter margins, and reducing response associated with nonlinear phenomenon like limit cycle oscillations. By reducing vibration levels and thus loads, aircraft structures can have lower acquisition cost, reduced maintenance, and extended lifetimes. Wind tunnel tests were undertaken on a rigid 15% scale aircraft in Boeing's mini-speed wind tunnel, which is used for testing at very low air speeds up to 80 mph. The model included a dynamically scaled flexible fail consisting of an aluminum spar with balsa wood cross sections with a hydraulically powered rudder. Neural predictive control was used to actuate the vertical tail rudder in response to strain gauge feedback to alleviate buffeting effects. First mode RMS strain reduction of 50% was achieved. The neural predictive control system was developed and implemented by the Boeing Company to provide an intelligent, adaptive control architecture for smart structures applications with automated synthesis, self-optimization, real-time adaptation, nonlinear control, and fault tolerance capabilities. It is designed to solve complex control problems though a process of automated synthesis, eliminating costly control design and surpassing it in many instances by accounting for real world non-linearities.

  5. Talking Drums: Generating drum grooves with neural networks

    Science.gov (United States)

    Hutchings, P.

    2017-05-01

    Presented is a method of generating a full drum kit part for a provided kick-drum sequence. A sequence to sequence neural network model used in natural language translation was adopted to encode multiple musical styles and an online survey was developed to test different techniques for sampling the output of the softmax function. The strongest results were found using a sampling technique that drew from the three most probable outputs at each subdivision of the drum pattern but the consistency of output was found to be heavily dependent on style.

  6. Cultured neural networks: Optimisation of patterned network adhesiveness and characterisation of their neural activity

    NARCIS (Netherlands)

    Rutten, Wim; Ruardij, T.G.; Marani, Enrico; Roelofsen, B.H.

    2006-01-01

    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

  7. Activity Patterns of Cultured Neural Networks on Micro Electrode Arrays

    National Research Council Canada - National Science Library

    Rutten, Wim

    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...

  8. Learning Orthographic Structure With Sequential Generative Neural Networks.

    Science.gov (United States)

    Testolin, Alberto; Stoianov, Ivilin; Sperduti, Alessandro; Zorzi, Marco

    2016-04-01

    Learning the structure of event sequences is a ubiquitous problem in cognition and particularly in language. One possible solution is to learn a probabilistic generative model of sequences that allows making predictions about upcoming events. Though appealing from a neurobiological standpoint, this approach is typically not pursued in connectionist modeling. Here, we investigated a sequential version of the restricted Boltzmann machine (RBM), a stochastic recurrent neural network that extracts high-order structure from sensory data through unsupervised generative learning and can encode contextual information in the form of internal, distributed representations. We assessed whether this type of network can extract the orthographic structure of English monosyllables by learning a generative model of the letter sequences forming a word training corpus. We show that the network learned an accurate probabilistic model of English graphotactics, which can be used to make predictions about the letter following a given context as well as to autonomously generate high-quality pseudowords. The model was compared to an extended version of simple recurrent networks, augmented with a stochastic process that allows autonomous generation of sequences, and to non-connectionist probabilistic models (n-grams and hidden Markov models). We conclude that sequential RBMs and stochastic simple recurrent networks are promising candidates for modeling cognition in the temporal domain. Copyright © 2015 Cognitive Science Society, Inc.

  9. Coding stimulus amplitude by correlated neural activity.

    Science.gov (United States)

    Metzen, Michael G; Ávila-Åkerberg, Oscar; Chacron, Maurice J

    2015-04-01

    While correlated activity is observed ubiquitously in the brain, its role in neural coding has remained controversial. Recent experimental results have demonstrated that correlated but not single-neuron activity can encode the detailed time course of the instantaneous amplitude (i.e., envelope) of a stimulus. These have furthermore demonstrated that such coding required and was optimal for a nonzero level of neural variability. However, a theoretical understanding of these results is still lacking. Here we provide a comprehensive theoretical framework explaining these experimental findings. Specifically, we use linear response theory to derive an expression relating the correlation coefficient to the instantaneous stimulus amplitude, which takes into account key single-neuron properties such as firing rate and variability as quantified by the coefficient of variation. The theoretical prediction was in excellent agreement with numerical simulations of various integrate-and-fire type neuron models for various parameter values. Further, we demonstrate a form of stochastic resonance as optimal coding of stimulus variance by correlated activity occurs for a nonzero value of noise intensity. Thus, our results provide a theoretical explanation of the phenomenon by which correlated but not single-neuron activity can code for stimulus amplitude and how key single-neuron properties such as firing rate and variability influence such coding. Correlation coding by correlated but not single-neuron activity is thus predicted to be a ubiquitous feature of sensory processing for neurons responding to weak input.

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

    Directory of Open Access Journals (Sweden)

    Hirotaka Inoue

    2003-12-01

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

  11. Activity in part of the neural correlates of consciousness reflects integration.

    Science.gov (United States)

    Eriksson, Johan

    2017-10-01

    Integration is commonly viewed as a key process for generating conscious experiences. Accordingly, there should be increased activity within the neural correlates of consciousness when demands on integration increase. We used fMRI and "informational masking" to isolate the neural correlates of consciousness and measured how the associated brain activity changed as a function of required integration. Integration was manipulated by comparing the experience of hearing simple reoccurring tones to hearing harmonic tone triplets. The neural correlates of auditory consciousness included superior temporal gyrus, lateral and medial frontal regions, cerebellum, and also parietal cortex. Critically, only activity in left parietal cortex increased significantly as a function of increasing demands on integration. We conclude that integration can explain part of the neural activity associated with the generation conscious experiences, but that much of associated brain activity apparently reflects other processes. Copyright © 2017 Elsevier Inc. All rights reserved.

  12. The neural coding of creative idea generation across adolescence and early adulthood

    Directory of Open Access Journals (Sweden)

    Sietske eKleibeuker

    2013-12-01

    Full Text Available Creativity is considered key to human prosperity, yet the neurocognitive principles underlying creative performance, and their development, are still poorly understood. To fill this void, we examined the neural correlates of divergent thinking in adults (25-30 yrs and adolescents (15-17 yrs. Participants generated alternative uses (AU or ordinary characteristics (OC for common objects while brain activity was assessed using fMRI. Adults outperformed adolescents on the number of solutions for AU and OC trials. Contrasting neural activity for AU with OC trials revealed increased recruitment of left angular gyrus, left supramarginal gyrus, and bilateral middle temporal gyrus in both adults and adolescents. When only trials with multiple alternative uses were included in the analysis, participants showed additional left inferior frontal gyrus (IFG/middle frontal gyrus (MFG activation for AU compared to OC trials. Correspondingly, individual difference analyses showed a positive correlation between activations for AU relative to OC trials in left IFG/MFG and divergent thinking performance and activations were more pronounced in adults than in adolescents. Taken together, the results of this study demonstrated that creative idea generation involves recruitment of mainly left lateralized parietal and temporal brain regions. Generating multiple creative ideas, a hallmark of divergent thinking, shows additional lateral PFC activation that is not yet optimized in adolescence.

  13. The neural coding of creative idea generation across adolescence and early adulthood.

    Science.gov (United States)

    Kleibeuker, Sietske W; Koolschijn, P Cédric M P; Jolles, Dietsje D; De Dreu, Carsten K W; Crone, Eveline A

    2013-01-01

    Creativity is considered key to human prosperity, yet the neurocognitive principles underlying creative performance, and their development, are still poorly understood. To fill this void, we examined the neural correlates of divergent thinking in adults (25-30 years) and adolescents (15-17 years). Participants generated alternative uses (AU) or ordinary characteristics (OC) for common objects while brain activity was assessed using fMRI. Adults outperformed adolescents on the number of solutions for AU and OC trials. Contrasting neural activity for AU with OC trials revealed increased recruitment of left angular gyrus, left supramarginal gyrus, and bilateral middle temporal gyrus in both adults and adolescents. When only trials with multiple AU were included in the analysis, participants showed additional left inferior frontal gyrus (IFG)/middle frontal gyrus (MFG) activation for AU compared to OC trials. Correspondingly, individual difference analyses showed a positive correlation between activations for AU relative to OC trials in left IFG/MFG and divergent thinking performance and activations were more pronounced in adults than in adolescents. Taken together, the results of this study demonstrated that creative idea generation involves recruitment of mainly left lateralized parietal and temporal brain regions. Generating multiple creative ideas, a hallmark of divergent thinking, shows additional lateral PFC activation that is not yet optimized in adolescence.

  14. The neural coding of creative idea generation across adolescence and early adulthood

    Science.gov (United States)

    Kleibeuker, Sietske W.; Koolschijn, P. Cédric M. P.; Jolles, Dietsje D.; De Dreu, Carsten K. W.; Crone, Eveline A.

    2013-01-01

    Creativity is considered key to human prosperity, yet the neurocognitive principles underlying creative performance, and their development, are still poorly understood. To fill this void, we examined the neural correlates of divergent thinking in adults (25–30 years) and adolescents (15–17 years). Participants generated alternative uses (AU) or ordinary characteristics (OC) for common objects while brain activity was assessed using fMRI. Adults outperformed adolescents on the number of solutions for AU and OC trials. Contrasting neural activity for AU with OC trials revealed increased recruitment of left angular gyrus, left supramarginal gyrus, and bilateral middle temporal gyrus in both adults and adolescents. When only trials with multiple AU were included in the analysis, participants showed additional left inferior frontal gyrus (IFG)/middle frontal gyrus (MFG) activation for AU compared to OC trials. Correspondingly, individual difference analyses showed a positive correlation between activations for AU relative to OC trials in left IFG/MFG and divergent thinking performance and activations were more pronounced in adults than in adolescents. Taken together, the results of this study demonstrated that creative idea generation involves recruitment of mainly left lateralized parietal and temporal brain regions. Generating multiple creative ideas, a hallmark of divergent thinking, shows additional lateral PFC activation that is not yet optimized in adolescence. PMID:24416008

  15. A NEURAL OSCILLATOR-NETWORK MODEL OF TEMPORAL PATTERN GENERATION

    NARCIS (Netherlands)

    Schomaker, Lambert

    Most contemporary neural network models deal with essentially static, perceptual problems of classification and transformation. Models such as multi-layer feedforward perceptrons generally do not incorporate time as an essential dimension, whereas biological neural networks are inherently temporal

  16. Spanish Young Generation (JJNN) Activities

    Energy Technology Data Exchange (ETDEWEB)

    Millan, Miguel [INITEC Nuclear- Westinghouse, Padilla 17, 28006 Madrid (Spain)

    2008-07-01

    Spanish Young Generation has been very active during 2006-2008. JJNN have mainly focused on communication activities, as conferences at universities, schools and nuclear companies. Lately, becoming in referent of the young politics, journalist and the young people in Nuclear Subjects is the new and most challenging target of the Spanish Young Generation. In order to accomplish with their objects and commitments with their members, JJNN are developing all kinds of activities focused in the young people and the JJNN members. (authors)

  17. Active voltammetric microsensors with neural signal processing.

    Energy Technology Data Exchange (ETDEWEB)

    Vogt, M. C.

    1998-12-11

    Many industrial and environmental processes, including bioremediation, would benefit from the feedback and control information provided by a local multi-analyte chemical sensor. For most processes, such a sensor would need to be rugged enough to be placed in situ for long-term remote monitoring, and inexpensive enough to be fielded in useful numbers. The multi-analyte capability is difficult to obtain from common passive sensors, but can be provided by an active device that produces a spectrum-type response. Such new active gas microsensor technology has been developed at Argonne National Laboratory. The technology couples an electrocatalytic ceramic-metallic (cermet) microsensor with a voltammetric measurement technique and advanced neural signal processing. It has been demonstrated to be flexible, rugged, and very economical to produce and deploy. Both narrow interest detectors and wide spectrum instruments have been developed around this technology. Much of this technology's strength lies in the active measurement technique employed. The technique involves applying voltammetry to a miniature electrocatalytic cell to produce unique chemical ''signatures'' from the analytes. These signatures are processed with neural pattern recognition algorithms to identify and quantify the components in the analyte. The neural signal processing allows for innovative sampling and analysis strategies to be employed with the microsensor. In most situations, the whole response signature from the voltammogram can be used to identify, classify, and quantify an analyte, without dissecting it into component parts. This allows an instrument to be calibrated once for a specific gas or mixture of gases by simple exposure to a multi-component standard rather than by a series of individual gases. The sampled unknown analytes can vary in composition or in concentration, the calibration, sensing, and processing methods of these active voltammetric microsensors can

  18. Engineering applications of fpgas chaotic systems, artificial neural networks, random number generators, and secure communication systems

    CERN Document Server

    Tlelo-Cuautle, Esteban; de la Fraga, Luis Gerardo

    2016-01-01

    This book offers readers a clear guide to implementing engineering applications with FPGAs, from the mathematical description to the hardware synthesis, including discussion of VHDL programming and co-simulation issues. Coverage includes FPGA realizations such as: chaos generators that are described from their mathematical models; artificial neural networks (ANNs) to predict chaotic time series, for which a discussion of different ANN topologies is included, with different learning techniques and activation functions; random number generators (RNGs) that are realized using different chaos generators, and discussions of their maximum Lyapunov exponent values and entropies. Finally, optimized chaotic oscillators are synchronized and realized to implement a secure communication system that processes black and white and grey-scale images. In each application, readers will find VHDL programming guidelines and computer arithmetic issues, along with co-simulation examples with Active-HDL and Simulink. Readers will b...

  19. Can Neural Activity Propagate by Endogenous Electrical Field?

    Science.gov (United States)

    Qiu, Chen; Shivacharan, Rajat S.; Zhang, Mingming

    2015-01-01

    It is widely accepted that synaptic transmissions and gap junctions are the major governing mechanisms for signal traveling in the neural system. Yet, a group of neural waves, either physiological or pathological, share the same speed of ∼0.1 m/s without synaptic transmission or gap junctions, and this speed is not consistent with axonal conduction or ionic diffusion. The only explanation left is an electrical field effect. We tested the hypothesis that endogenous electric fields are sufficient to explain the propagation with in silico and in vitro experiments. Simulation results show that field effects alone can indeed mediate propagation across layers of neurons with speeds of 0.12 ± 0.09 m/s with pathological kinetics, and 0.11 ± 0.03 m/s with physiologic kinetics, both generating weak field amplitudes of ∼2–6 mV/mm. Further, the model predicted that propagation speed values are inversely proportional to the cell-to-cell distances, but do not significantly change with extracellular resistivity, membrane capacitance, or membrane resistance. In vitro recordings in mice hippocampi produced similar speeds (0.10 ± 0.03 m/s) and field amplitudes (2.5–5 mV/mm), and by applying a blocking field, the propagation speed was greatly reduced. Finally, osmolarity experiments confirmed the model's prediction that cell-to-cell distance inversely affects propagation speed. Together, these results show that despite their weak amplitude, electric fields can be solely responsible for spike propagation at ∼0.1 m/s. This phenomenon could be important to explain the slow propagation of epileptic activity and other normal propagations at similar speeds. SIGNIFICANCE STATEMENT Neural activity (waves or spikes) can propagate using well documented mechanisms such as synaptic transmission, gap junctions, or diffusion. However, the purpose of this paper is to provide an explanation for experimental data showing that neural signals can propagate by means other than synaptic

  20. ORGANIC ELECTRODE COATINGS FOR NEXT-GENERATION NEURAL INTERFACES

    Directory of Open Access Journals (Sweden)

    Ulises A Aregueta-Robles

    2014-05-01

    Full Text Available Traditional neuronal interfaces utilize metallic electrodes which in recent years have reached a plateau in terms of the ability to provide safe stimulation at high resolution or rather with high densities of microelectrodes with improved spatial selectivity. To achieve higher resolution it has become clear that reducing the size of electrodes is required to enable higher electrode counts from the implant device. The limitations of interfacing electrodes including low charge injection limits, mechanical mismatch and foreign body response can be addressed through the use of organic electrode coatings which typically provide a softer, more roughened surface to enable both improved charge transfer and lower mechanical mismatch with neural tissue. Coating electrodes with conductive polymers or carbon nanotubes offers a substantial increase in charge transfer area compared to conventional platinum electrodes. These organic conductors provide safe electrical stimulation of tissue while avoiding undesirable chemical reactions and cell damage. However, the mechanical properties of conductive polymers are not ideal, as they are quite brittle. Hydrogel polymers present a versatile coating option for electrodes as they can be chemically modified to provide a soft and conductive scaffold. However, the in vivo chronic inflammatory response of these conductive hydrogels remains unknown. A more recent approach proposes tissue engineering the electrode interface through the use of encapsulated neurons within hydrogel coatings. This approach may provide a method for activating tissue at the cellular scale, however several technological challenges must be addressed to demonstrate feasibility of this innovative idea. The review focuses on the various organic coatings which have been investigated to improve neural interface electrodes.

  1. Identifying Emotions on the Basis of Neural Activation.

    Directory of Open Access Journals (Sweden)

    Karim S Kassam

    Full Text Available 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.

  2. Functional overlap of top-down emotion regulation and generation: an fMRI study identifying common neural substrates between cognitive reappraisal and cognitively generated emotions.

    Science.gov (United States)

    Otto, Benjamin; Misra, Supriya; Prasad, Aditya; McRae, Kateri

    2014-09-01

    One factor that influences the success of emotion regulation is the manner in which the regulated emotion was generated. Recent research has suggested that reappraisal, a top-down emotion regulation strategy, is more effective in decreasing self-reported negative affect when emotions were generated from the top-down, versus the bottom-up. On the basis of a process overlap framework, we hypothesized that the neural regions active during reappraisal would overlap more with emotions that were generated from the top-down, rather than from the bottom-up. In addition, we hypothesized that increased neural overlap between reappraisal and the history effects of top-down emotion generation would be associated with increased reappraisal success. The results of several analyses suggested that reappraisal and emotions that were generated from the top-down share a core network of prefrontal, temporal, and cingulate regions. This overlap is specific; no such overlap was observed between reappraisal and emotions that were generated in a bottom-up fashion. This network consists of regions previously implicated in linguistic processing, cognitive control, and self-relevant appraisals, which are processes thought to be crucial to both reappraisal and top-down emotion generation. Furthermore, individuals with high reappraisal success demonstrated greater neural overlap between reappraisal and the history of top-down emotion generation than did those with low reappraisal success. The overlap of these key regions, reflecting overlapping processes, provides an initial insight into the mechanism by which generation history may facilitate emotion regulation.

  3. Deep Generative Adversarial Neural Networks for Realistic Prostate Lesion MRI Synthesis

    OpenAIRE

    Kitchen, Andy; Seah, Jarrel

    2017-01-01

    Generative Adversarial Neural Networks (GANs) are applied to the synthetic generation of prostate lesion MRI images. GANs have been applied to a variety of natural images, is shown show that the same techniques can be used in the medical domain to create realistic looking synthetic lesion images. 16mm x 16mm patches are extracted from 330 MRI scans from the SPIE ProstateX Challenge 2016 and used to train a Deep Convolutional Generative Adversarial Neural Network (DCGAN) utilizing cutting edge...

  4. Biological oscillations for learning walking coordination: dynamic recurrent neural network functionally models physiological central pattern generator.

    Science.gov (United States)

    Hoellinger, Thomas; Petieau, Mathieu; Duvinage, Matthieu; Castermans, Thierry; Seetharaman, Karthik; Cebolla, Ana-Maria; Bengoetxea, Ana; Ivanenko, Yuri; Dan, Bernard; Cheron, Guy

    2013-01-01

    The existence of dedicated neuronal modules such as those organized in the cerebral cortex, thalamus, basal ganglia, cerebellum, or spinal cord raises the question of how these functional modules are coordinated for appropriate motor behavior. Study of human locomotion offers an interesting field for addressing this central question. The coordination of the elevation of the 3 leg segments under a planar covariation rule (Borghese et al., 1996) was recently modeled (Barliya et al., 2009) by phase-adjusted simple oscillators shedding new light on the understanding of the central pattern generator (CPG) processing relevant oscillation signals. We describe the use of a dynamic recurrent neural network (DRNN) mimicking the natural oscillatory behavior of human locomotion for reproducing the planar covariation rule in both legs at different walking speeds. Neural network learning was based on sinusoid signals integrating frequency and amplitude features of the first three harmonics of the sagittal elevation angles of the thigh, shank, and foot of each lower limb. We verified the biological plausibility of the neural networks. Best results were obtained with oscillations extracted from the first three harmonics in comparison to oscillations outside the harmonic frequency peaks. Physiological replication steadily increased with the number of neuronal units from 1 to 80, where similarity index reached 0.99. Analysis of synaptic weighting showed that the proportion of inhibitory connections consistently increased with the number of neuronal units in the DRNN. This emerging property in the artificial neural networks resonates with recent advances in neurophysiology of inhibitory neurons that are involved in central nervous system oscillatory activities. The main message of this study is that this type of DRNN may offer a useful model of physiological central pattern generator for gaining insights in basic research and developing clinical applications.

  5. Neural oscillations: beta band activity across motor networks.

    Science.gov (United States)

    Khanna, Preeya; Carmena, Jose M

    2015-06-01

    Local field potential (LFP) activity in motor cortical and basal ganglia regions exhibits prominent beta (15-40Hz) oscillations during reaching and grasping, muscular contraction, and attention tasks. While in vitro and computational work has revealed specific mechanisms that may give rise to the frequency and duration of this oscillation, there is still controversy about what behavioral processes ultimately drive it. Here, simultaneous behavioral and large-scale neural recording experiments from non-human primate and human subjects are reviewed in the context of specific hypotheses about how beta band activity is generated. Finally, a new experimental paradigm utilizing operant conditioning combined with motor tasks is proposed as a way to further investigate this oscillation. Copyright © 2014 Elsevier Ltd. All rights reserved.

  6. Multiple faces elicit augmented neural activity

    Directory of Open Access Journals (Sweden)

    Aina ePuce

    2013-06-01

    Full Text Available How do our brains respond when we are being watched by a group of people? Despite the large volume of literature devoted to face processing, this question has received very little attention. Here we measured the effects on the face-sensitive N170 and other ERPs to viewing displays of one, two and three faces in two experiments. In Experiment 1, overall image brightness and contrast were adjusted to be constant, whereas in Experiment 2 local contrast and brightness of individual faces were not manipulated. A robust positive-negative-positive (P100-N170-P250 ERP complex and an additional late positive ERP, the P400, were elicited to all stimulus types. As the number of faces in the display increased, N170 amplitude increased for both stimulus sets, and latency increased in Experiment 2. P100 latency and P250 amplitude were affected by changes in overall brightness and contrast, but not by the number of faces in the display per se. In Experiment 1 when overall brightness and contrast were adjusted to be constant, later ERP (P250 and P400 latencies showed differences as a function of hemisphere. Hence, our data indicate that N170 increases its magnitude when multiple faces are seen, apparently impervious to basic low-level stimulus features including stimulus size. Outstanding questions remain regarding category-sensitive neural activity that is elicited to viewing multiple items of stimulus categories other than faces.

  7. Goal-independent mechanisms for free response generation: creative and pseudo-random performance share neural substrates.

    Science.gov (United States)

    de Manzano, Örjan; Ullén, Fredrik

    2012-01-02

    To what extent free response generation in different tasks uses common and task-specific neurocognitive processes has remained unclear. Here, we investigated overlap and differences in neural activity during musical improvisation and pseudo-random response generation. Brain activity was measured using fMRI in a group of professional classical pianists, who performed musical improvisation of melodies, pseudo-random key-presses and a baseline condition (sight-reading), on either two, six or twelve keys on a piano keyboard. The results revealed an extensive overlap in neural activity between the two generative conditions. Active regions included the dorsolateral and dorsomedial prefrontal cortices, inferior frontal gyrus, anterior cingulate cortex and pre-SMA. No regions showed higher activity in improvisation than in pseudo-random generation. These findings suggest that the activated regions fulfill generic functions that are utilized in different types of free generation tasks, independent of overall goal. In contrast, pseudo-random generation was accompanied by higher activity than improvisation in several regions. This presumably reflects the participants' musical expertise as well as the pseudo-random generation task's high load on attention, working memory, and executive control. The results highlight the significance of using naturalistic tasks to study human behavior and cognition. No brain activity was related to the size of the response set. We discuss that this may reflect that the musicians were able to use specific strategies for improvisation, by which there was no simple relationship between response set size and neural activity. Copyright © 2011 Elsevier Inc. All rights reserved.

  8. The Effects of GABAergic Polarity Changes on Episodic Neural Network Activity in Developing Neural Systems

    Directory of Open Access Journals (Sweden)

    Wilfredo Blanco

    2017-09-01

    Full Text Available Early in development, neural systems have primarily excitatory coupling, where even GABAergic synapses are excitatory. Many of these systems exhibit spontaneous episodes of activity that have been characterized through both experimental and computational studies. As development progress the neural system goes through many changes, including synaptic remodeling, intrinsic plasticity in the ion channel expression, and a transformation of GABAergic synapses from excitatory to inhibitory. What effect each of these, and other, changes have on the network behavior is hard to know from experimental studies since they all happen in parallel. One advantage of a computational approach is that one has the ability to study developmental changes in isolation. Here, we examine the effects of GABAergic synapse polarity change on the spontaneous activity of both a mean field and a neural network model that has both glutamatergic and GABAergic coupling, representative of a developing neural network. We find some intuitive behavioral changes as the GABAergic neurons go from excitatory to inhibitory, shared by both models, such as a decrease in the duration of episodes. We also find some paradoxical changes in the activity that are only present in the neural network model. In particular, we find that during early development the inter-episode durations become longer on average, while later in development they become shorter. In addressing this unexpected finding, we uncover a priming effect that is particularly important for a small subset of neurons, called the “intermediate neurons.” We characterize these neurons and demonstrate why they are crucial to episode initiation, and why the paradoxical behavioral change result from priming of these neurons. The study illustrates how even arguably the simplest of developmental changes that occurs in neural systems can present non-intuitive behaviors. It also makes predictions about neural network behavioral changes

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

    Science.gov (United States)

    Ganguly, Karunesh; Poo, Mu-Ming

    2013-10-30

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

  10. Neural correlates of generation and inhibition of verbal association patterns in mood disorders

    OpenAIRE

    Piguet, Camille; Desseilles, Martin; Cojan, Yann; Sterpenich, Virginie; Dayer, Alexandre; Bertschy, Gilles; Vuilleumier, Patrik

    2014-01-01

    OBJECTIVES: Thought disorders such as rumination or flight of ideas are frequent in patients with mood disorders, and not systematically linked to mood state. These symptoms point to anomalies in cognitive processes mediating the generation and control of thoughts; for example, associative thinking and inhibition. However, their neural substrates are not known. METHOD: To obtain an ecological measure of neural processes underlying the generation and suppression of spontaneous thoughts, we des...

  11. Neural Activity Reveals Preferences Without Choices

    Science.gov (United States)

    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

  12. Modulation of Neural Activity during Guided Viewing of Visual Art

    Directory of Open Access Journals (Sweden)

    Guillermo Herrera-Arcos

    2017-11-01

    Full Text Available Mobile Brain-Body Imaging (MoBI technology was deployed to record multi-modal data from 209 participants to examine the brain’s response to artistic stimuli at the Museo de Arte Contemporáneo (MARCO in Monterrey, México. EEG signals were recorded as the subjects walked through the exhibit in guided groups of 6–8 people. Moreover, guided groups were either provided with an explanation of each art piece (Guided-E, or given no explanation (Guided-NE. The study was performed using portable Muse (InteraXon, Inc, Toronto, ON, Canada headbands with four dry electrodes located at AF7, AF8, TP9, and TP10. Each participant performed a baseline (BL control condition devoid of artistic stimuli and selected his/her favorite piece of art (FP during the guided tour. In this study, we report data related to participants’ demographic information and aesthetic preference as well as effects of art viewing on neural activity (EEG in a select subgroup of 18–30 year-old subjects (Nc = 25 that generated high-quality EEG signals, on both BL and FP conditions. Dependencies on gender, sensor placement, and presence or absence of art explanation were also analyzed. After denoising, clustering of spectral EEG models was used to identify neural patterns associated with BL and FP conditions. Results indicate statistically significant suppression of beta band frequencies (15–25 Hz in the prefrontal electrodes (AF7 and AF8 during appreciation of subjects’ favorite painting, compared to the BL condition, which was significantly different from EEG responses to non-favorite paintings (NFP. No significant differences in brain activity in relation to the presence or absence of explanation during exhibit tours were found. Moreover, a frontal to posterior asymmetry in neural activity was observed, for both BL and FP conditions. These findings provide new information about frequency-related effects of preferred art viewing in brain activity, and support the view that art

  13. Modulation of Neural Activity during Guided Viewing of Visual Art

    Science.gov (United States)

    Herrera-Arcos, Guillermo; Tamez-Duque, Jesús; Acosta-De-Anda, Elsa Y.; Kwan-Loo, Kevin; de-Alba, Mayra; Tamez-Duque, Ulises; Contreras-Vidal, Jose L.; Soto, Rogelio

    2017-01-01

    Mobile Brain-Body Imaging (MoBI) technology was deployed to record multi-modal data from 209 participants to examine the brain’s response to artistic stimuli at the Museo de Arte Contemporáneo (MARCO) in Monterrey, México. EEG signals were recorded as the subjects walked through the exhibit in guided groups of 6–8 people. Moreover, guided groups were either provided with an explanation of each art piece (Guided-E), or given no explanation (Guided-NE). The study was performed using portable Muse (InteraXon, Inc, Toronto, ON, Canada) headbands with four dry electrodes located at AF7, AF8, TP9, and TP10. Each participant performed a baseline (BL) control condition devoid of artistic stimuli and selected his/her favorite piece of art (FP) during the guided tour. In this study, we report data related to participants’ demographic information and aesthetic preference as well as effects of art viewing on neural activity (EEG) in a select subgroup of 18–30 year-old subjects (Nc = 25) that generated high-quality EEG signals, on both BL and FP conditions. Dependencies on gender, sensor placement, and presence or absence of art explanation were also analyzed. After denoising, clustering of spectral EEG models was used to identify neural patterns associated with BL and FP conditions. Results indicate statistically significant suppression of beta band frequencies (15–25 Hz) in the prefrontal electrodes (AF7 and AF8) during appreciation of subjects’ favorite painting, compared to the BL condition, which was significantly different from EEG responses to non-favorite paintings (NFP). No significant differences in brain activity in relation to the presence or absence of explanation during exhibit tours were found. Moreover, a frontal to posterior asymmetry in neural activity was observed, for both BL and FP conditions. These findings provide new information about frequency-related effects of preferred art viewing in brain activity, and support the view that art

  14. Modulation of Neural Activity during Guided Viewing of Visual Art.

    Science.gov (United States)

    Herrera-Arcos, Guillermo; Tamez-Duque, Jesús; Acosta-De-Anda, Elsa Y; Kwan-Loo, Kevin; de-Alba, Mayra; Tamez-Duque, Ulises; Contreras-Vidal, Jose L; Soto, Rogelio

    2017-01-01

    Mobile Brain-Body Imaging (MoBI) technology was deployed to record multi-modal data from 209 participants to examine the brain's response to artistic stimuli at the Museo de Arte Contemporáneo (MARCO) in Monterrey, México. EEG signals were recorded as the subjects walked through the exhibit in guided groups of 6-8 people. Moreover, guided groups were either provided with an explanation of each art piece (Guided-E), or given no explanation (Guided-NE). The study was performed using portable Muse (InteraXon, Inc, Toronto, ON, Canada) headbands with four dry electrodes located at AF7, AF8, TP9, and TP10. Each participant performed a baseline (BL) control condition devoid of artistic stimuli and selected his/her favorite piece of art (FP) during the guided tour. In this study, we report data related to participants' demographic information and aesthetic preference as well as effects of art viewing on neural activity (EEG) in a select subgroup of 18-30 year-old subjects (Nc = 25) that generated high-quality EEG signals, on both BL and FP conditions. Dependencies on gender, sensor placement, and presence or absence of art explanation were also analyzed. After denoising, clustering of spectral EEG models was used to identify neural patterns associated with BL and FP conditions. Results indicate statistically significant suppression of beta band frequencies (15-25 Hz) in the prefrontal electrodes (AF7 and AF8) during appreciation of subjects' favorite painting, compared to the BL condition, which was significantly different from EEG responses to non-favorite paintings (NFP). No significant differences in brain activity in relation to the presence or absence of explanation during exhibit tours were found. Moreover, a frontal to posterior asymmetry in neural activity was observed, for both BL and FP conditions. These findings provide new information about frequency-related effects of preferred art viewing in brain activity, and support the view that art appreciation is

  15. Active Engine Mounting Control Algorithm Using Neural Network

    Directory of Open Access Journals (Sweden)

    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.

  16. Patterns recognition of electric brain activity using artificial neural networks

    Science.gov (United States)

    Musatov, V. Yu.; Pchelintseva, S. V.; Runnova, A. E.; Hramov, A. E.

    2017-04-01

    An approach for the recognition of various cognitive processes in the brain activity in the perception of ambiguous images. On the basis of developed theoretical background and the experimental data, we propose a new classification of oscillating patterns in the human EEG by using an artificial neural network approach. After learning of the artificial neural network reliably identified cube recognition processes, for example, left-handed or right-oriented Necker cube with different intensity of their edges, construct an artificial neural network based on Perceptron architecture and demonstrate its effectiveness in the pattern recognition of the EEG in the experimental.

  17. ANNarchy: a code generation approach to neural simulations on parallel hardware

    Directory of Open Access Journals (Sweden)

    Julien eVitay

    2015-07-01

    Full Text Available Many modern neural simulators focus on the simulation of networks of spiking neurons on parallel hardware. Another important framework in computational neuroscience, rate-coded neural networks, is mostly difficult or impossible to implement using these simulators. We present here the ANNarchy (Artificial Neural Networks architect neural simulator, which allows to easily define and simulate rate-coded and spiking networks, as well as combinations of both. The interface in Python has been designed to be close to the PyNN interface, while the definition of neuron and synapse models can be specified using an equation-oriented mathematical description similar to the Brian neural simulator. This information is used to generate C++ code that will efficiently perform the simulation on the chosen parallel hardware (multi-core system or graphical processing unit. Several numerical methods are available to transform ordinary differential equations into an efficient C++ code. We compare the parallel performance of the simulator to existing solutions.

  18. Adaptive RBF Neural Network Control for Three-Phase Active Power Filter

    Directory of Open Access Journals (Sweden)

    Juntao Fei

    2013-05-01

    Full Text Available Abstract An adaptive radial basis function (RBF neural network control system for three-phase active power filter (APF is proposed to eliminate harmonics. Compensation current is generated to track command current so as to eliminate the harmonic current of non-linear load and improve the quality of the power system. The asymptotical stability of the APF system can be guaranteed with the proposed adaptive neural network strategy. The parameters of the neural network can be adaptively updated to achieve the desired tracking task. The simulation results demonstrate good performance, for example showing small current tracking error, reduced total harmonic distortion (THD, improved accuracy and strong robustness in the presence of parameters variation and nonlinear load. It is shown that the adaptive RBF neural network control system for three-phase APF gives better control than hysteresis control.

  19. High Accuracy Human Activity Monitoring using Neural network

    OpenAIRE

    Sharma, Annapurna; Lee, Young-Dong; 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 a...

  20. Application of clustering analysis in the prediction of photovoltaic power generation based on neural network

    Science.gov (United States)

    Cheng, K.; Guo, L. M.; Wang, Y. K.; Zafar, M. T.

    2017-11-01

    In order to select effective samples in the large number of data of PV power generation years and improve the accuracy of PV power generation forecasting model, this paper studies the application of clustering analysis in this field and establishes forecasting model based on neural network. Based on three different types of weather on sunny, cloudy and rainy days, this research screens samples of historical data by the clustering analysis method. After screening, it establishes BP neural network prediction models using screened data as training data. Then, compare the six types of photovoltaic power generation prediction models before and after the data screening. Results show that the prediction model combining with clustering analysis and BP neural networks is an effective method to improve the precision of photovoltaic power generation.

  1. Generation and properties of a new human ventral mesencephalic neural stem cell line

    DEFF Research Database (Denmark)

    Villa, Ana; Liste, Isabel; Courtois, Elise T

    2009-01-01

    Neural stem cells (NSCs) are powerful research tools for the design and discovery of new approaches to cell therapy in neurodegenerative diseases like Parkinson's disease. Several epigenetic and genetic strategies have been tested for long-term maintenance and expansion of these cells in vitro....... Here we report the generation of a new stable cell line of human neural stem cells derived from ventral mesencephalon (hVM1) based on v-myc immortalization. The cells expressed neural stem cell and radial glia markers like nestin, vimentin and 3CB2 under proliferation conditions. After withdrawal...

  2. The Effect of Training Data Set Composition on the Performance of a Neural Image Caption Generator

    Science.gov (United States)

    2017-09-01

    ARL-TR-8124 ● SEP 2017 US Army Research Laboratory The Effect of Training Data Set Composition on the Performance of a Neural...Laboratory The Effect of Training Data Set Composition on the Performance of a Neural Image Caption Generator by Abigail Wilson Montgomery Blair...REPORT TYPE Technical Report 3. DATES COVERED (From - To) 4. TITLE AND SUBTITLE The Effect of Training Data Set Composition on the Performance of a

  3. Vascular Endothelial Growth Factor Receptor 3 Controls Neural Stem Cell Activation in Mice and Humans

    Directory of Open Access Journals (Sweden)

    Jinah Han

    2015-02-01

    Full Text Available Neural stem cells (NSCs continuously produce new neurons within the adult mammalian hippocampus. NSCs are typically quiescent but activated to self-renew or differentiate into neural progenitor cells. The molecular mechanisms of NSC activation remain poorly understood. Here, we show that adult hippocampal NSCs express vascular endothelial growth factor receptor (VEGFR 3 and its ligand VEGF-C, which activates quiescent NSCs to enter the cell cycle and generate progenitor cells. Hippocampal NSC activation and neurogenesis are impaired by conditional deletion of Vegfr3 in NSCs. Functionally, this is associated with compromised NSC activation in response to VEGF-C and physical activity. In NSCs derived from human embryonic stem cells (hESCs, VEGF-C/VEGFR3 mediates intracellular activation of AKT and ERK pathways that control cell fate and proliferation. These findings identify VEGF-C/VEGFR3 signaling as a specific regulator of NSC activation and neurogenesis in mammals.

  4. Performance of Deep and Shallow Neural Networks, the Universal Approximation Theorem, Activity Cliffs, and QSAR.

    Science.gov (United States)

    Winkler, David A; Le, Tu C

    2017-01-01

    Neural networks have generated valuable Quantitative Structure-Activity/Property Relationships (QSAR/QSPR) models for a wide variety of small molecules and materials properties. They have grown in sophistication and many of their initial problems have been overcome by modern mathematical techniques. QSAR studies have almost always used so-called "shallow" neural networks in which there is a single hidden layer between the input and output layers. Recently, a new and potentially paradigm-shifting type of neural network based on Deep Learning has appeared. Deep learning methods have generated impressive improvements in image and voice recognition, and are now being applied to QSAR and QSAR modelling. This paper describes the differences in approach between deep and shallow neural networks, compares their abilities to predict the properties of test sets for 15 large drug data sets (the kaggle set), discusses the results in terms of the Universal Approximation theorem for neural networks, and describes how DNN may ameliorate or remove troublesome "activity cliffs" in QSAR data sets. © 2017 Wiley-VCH Verlag GmbH & Co. KGaA, Weinheim.

  5. Positive mood enhances reward-related neural activity.

    Science.gov (United States)

    Young, Christina B; Nusslock, Robin

    2016-06-01

    Although behavioral research has shown that positive mood leads to desired outcomes in nearly every major life domain, no studies have directly examined the effects of positive mood on the neural processes underlying reward-related affect and goal-directed behavior. To address this gap, participants in the present fMRI study experienced either a positive (n = 20) or neutral (n = 20) mood induction and subsequently completed a monetary incentive delay task that assessed reward and loss processing. Consistent with prediction, positive mood elevated activity specifically during reward anticipation in corticostriatal neural regions that have been implicated in reward processing and goal-directed behavior, including the nucleus accumbens, caudate, lateral orbitofrontal cortex and putamen, as well as related paralimbic regions, including the anterior insula and ventromedial prefrontal cortex. These effects were not observed during reward outcome, loss anticipation or loss outcome. Critically, this is the first study to report that positive mood enhances reward-related neural activity. Our findings have implications for uncovering the neural mechanisms by which positive mood enhances goal-directed behavior, understanding the malleability of reward-related neural activity, and developing targeted treatments for psychiatric disorders characterized by deficits in reward processing. © The Author (2016). Published by Oxford University Press. For Permissions, please email: journals.permissions@oup.com.

  6. Neural generators of the auditory evoked potential components P3a and P3b.

    Science.gov (United States)

    Wronka, Eligiusz; Kaiser, Jan; Coenen, Anton M L

    2012-01-01

    The aim of the present study was to define the scalp topography of the two subcomponents of the P3 component of the auditory evoked potential elicited in a three-stimulus oddball paradigm and to identify their cortical generators using the standardized low resolution electromagnetic tomography (sLORETA). Subjects were presented with a random sequence of auditory stimuli and instructed to respond to an infrequently occurring target stimulus inserted into a sequence of frequent standard and rare non-target stimuli. Results show that the magnitude of the frontal P3a is determined by the relative physical difference among stimuli, as it was larger for the stimulus more deviant from the standard. Major neural generators of the P3a were localized within frontal cortex and anterior cingulate gyrus. In contrast to this, the P3b, showing maximal amplitude at parietal locations, was larger for stimuli demanding a response than for the rare non-target. Major sources of the P3b included the superior parietal lobule and the posterior part of the cingulate gyrus. Our findings are in line with the hypothesis that P3a is related to alerting activity during the initial allocation of attention, while P3b is related to activation of a posterior network when the neuronal model of perceived stimulation is compared with the attentional trace.

  7. Understanding the Implications of Neural Population Activity on Behavior

    Science.gov (United States)

    Briguglio, John

    Learning how neural activity in the brain leads to the behavior we exhibit is one of the fundamental questions in Neuroscience. In this dissertation, several lines of work are presented to that use principles of neural coding to understand behavior. In one line of work, we formulate the efficient coding hypothesis in a non-traditional manner in order to test human perceptual sensitivity to complex visual textures. We find a striking agreement between how variable a particular texture signal is and how sensitive humans are to its presence. This reveals that the efficient coding hypothesis is still a guiding principle for neural organization beyond the sensory periphery, and that the nature of cortical constraints differs from the peripheral counterpart. In another line of work, we relate frequency discrimination acuity to neural responses from auditory cortex in mice. It has been previously observed that optogenetic manipulation of auditory cortex, in addition to changing neural responses, evokes changes in behavioral frequency discrimination. We are able to account for changes in frequency discrimination acuity on an individual basis by examining the Fisher information from the neural population with and without optogenetic manipulation. In the third line of work, we address the question of what a neural population should encode given that its inputs are responses from another group of neurons. Drawing inspiration from techniques in machine learning, we train Deep Belief Networks on fake retinal data and show the emergence of Garbor-like filters, reminiscent of responses in primary visual cortex. In the last line of work, we model the state of a cortical excitatory-inhibitory network during complex adaptive stimuli. Using a rate model with Wilson-Cowan dynamics, we demonstrate that simple non-linearities in the signal transferred from inhibitory to excitatory neurons can account for real neural recordings taken from auditory cortex. This work establishes and tests

  8. Learning Orthographic Structure with Sequential Generative Neural Networks

    Science.gov (United States)

    Testolin, Alberto; Stoianov, Ivilin; Sperduti, Alessandro; Zorzi, Marco

    2016-01-01

    Learning the structure of event sequences is a ubiquitous problem in cognition and particularly in language. One possible solution is to learn a probabilistic generative model of sequences that allows making predictions about upcoming events. Though appealing from a neurobiological standpoint, this approach is typically not pursued in…

  9. Neural correlates of maintaining generated images in visual working memory.

    Science.gov (United States)

    Ewerdwalbesloh, Julia A; Palva, Satu; Rösler, Frank; Khader, Patrick H

    2016-12-01

    How are images that have been assembled from their constituting elements maintained as a coherent representation in visual working memory (vWM)? Here, we compared two conditions of vWM maintenance that only differed in how vWM contents had been created. Participants maintained images that they either had to assemble from single features or that they had perceived as complete objects. Object complexity varied between two and four features. We analyzed electroencephalogram phase coupling as a measure of cortical connectivity in a time interval immediately before a probe stimulus appeared. We assumed that during this time both groups maintained essentially the same images, but that images constructed from their elements would require more neural coupling than images based on a complete percept. Increased coupling between frontal and parietal-to-occipital cortical sources was found for the maintenance of constructed in comparison to nonconstructed objects in the theta, alpha, beta, and gamma frequency bands. A similar pattern was found for an increase in vWM load (2 vs. 4 features) for nonconstructed objects. Under increased construction load (2 vs. 4 features for constructed images), the pattern was restricted to fronto-parietal couplings, suggesting that the fronto-parietal attention network is coping with the higher attentional demands involved in maintaining constructed images, but without increasing the communication with the occipital visual buffer in which the visual representations are assumed to be stored. We conclude from these findings that the maintenance of constructed images in vWM requires additional attentional processes to keep object elements together as a coherent representation. Hum Brain Mapp 37:4349-4362, 2016. © 2016 Wiley Periodicals, Inc. © 2016 Wiley Periodicals, Inc.

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

    Directory of Open Access Journals (Sweden)

    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.

  11. Central Sensitization: A Generator of Pain Hypersensitivity by Central Neural Plasticity

    Science.gov (United States)

    Latremoliere, Alban; Woolf, Clifford J.

    2009-01-01

    Central sensitization represents an enhancement in the function of neurons and circuits in nociceptive pathways caused by increases in membrane excitability and synaptic efficacy as well as to reduced inhibition and is a manifestation of the remarkable plasticity of the somatosensory nervous system in response to activity, inflammation, and neural injury. The net effect of central sensitization is to recruit previously subthreshold synaptic inputs to nociceptive neurons, generating an increased or augmented action potential output: a state of facilitation, potentiation, augmentation, or amplification. Central sensitization is responsible for many of the temporal, spatial, and threshold changes in pain sensibility in acute and chronic clinical pain settings and exemplifies the fundamental contribution of the central nervous system to the generation of pain hypersensitivity. Because central sensitization results from changes in the properties of neurons in the central nervous system, the pain is no longer coupled, as acute nociceptive pain is, to the presence, intensity, or duration of noxious peripheral stimuli. Instead, central sensitization produces pain hypersensitivity by changing the sensory response elicited by normal inputs, including those that usually evoke innocuous sensations. Perspective In this article, we review the major triggers that initiate and maintain central sensitization in healthy individuals in response to nociceptor input and in patients with inflammatory and neuropathic pain, emphasizing the fundamental contribution and multiple mechanisms of synaptic plasticity caused by changes in the density, nature, and properties of ionotropic and metabotropic glutamate receptors. PMID:19712899

  12. Neural activity predicts attitude change in cognitive dissonance.

    Science.gov (United States)

    van Veen, Vincent; Krug, Marie K; Schooler, Jonathan W; Carter, Cameron S

    2009-11-01

    When our actions conflict with our prior attitudes, we often change our attitudes to be more consistent with our actions. This phenomenon, known as cognitive dissonance, is considered to be one of the most influential theories in psychology. However, the neural basis of this phenomenon is unknown. Using a Solomon four-group design, we scanned participants with functional MRI while they argued that the uncomfortable scanner environment was nevertheless a pleasant experience. We found that cognitive dissonance engaged the dorsal anterior cingulate cortex and anterior insula; furthermore, we found that the activation of these regions tightly predicted participants' subsequent attitude change. These effects were not observed in a control group. Our findings elucidate the neural representation of cognitive dissonance, and support the role of the anterior cingulate cortex in detecting cognitive conflict and the neural prediction of attitude change.

  13. High solar activity predictions through an artificial neural network

    Science.gov (United States)

    Orozco-Del-Castillo, M. G.; Ortiz-Alemán, J. C.; Couder-Castañeda, C.; Hernández-Gómez, J. J.; Solís-Santomé, A.

    The effects of high-energy particles coming from the Sun on human health as well as in the integrity of outer space electronics make the prediction of periods of high solar activity (HSA) a task of significant importance. Since periodicities in solar indexes have been identified, long-term predictions can be achieved. In this paper, we present a method based on an artificial neural network to find a pattern in some harmonics which represent such periodicities. We used data from 1973 to 2010 to train the neural network, and different historical data for its validation. We also used the neural network along with a statistical analysis of its performance with known data to predict periods of HSA with different confidence intervals according to the three-sigma rule associated with solar cycles 24-26, which we found to occur before 2040.

  14. Death and rebirth of neural activity in sparse inhibitory networks

    Science.gov (United States)

    Angulo-Garcia, David; Luccioli, Stefano; Olmi, Simona; Torcini, Alessandro

    2017-05-01

    Inhibition is a key aspect of neural dynamics playing a fundamental role for the emergence of neural rhythms and the implementation of various information coding strategies. Inhibitory populations are present in several brain structures, and the comprehension of their dynamics is strategical for the understanding of neural processing. In this paper, we clarify the mechanisms underlying a general phenomenon present in pulse-coupled heterogeneous inhibitory networks: inhibition can induce not only suppression of neural activity, as expected, but can also promote neural re-activation. In particular, for globally coupled systems, the number of firing neurons monotonically reduces upon increasing the strength of inhibition (neuronal death). However, the random pruning of connections is able to reverse the action of inhibition, i.e. in a random sparse network a sufficiently strong synaptic strength can surprisingly promote, rather than depress, the activity of neurons (neuronal rebirth). Thus, the number of firing neurons reaches a minimum value at some intermediate synaptic strength. We show that this minimum signals a transition from a regime dominated by neurons with a higher firing activity to a phase where all neurons are effectively sub-threshold and their irregular firing is driven by current fluctuations. We explain the origin of the transition by deriving a mean field formulation of the problem able to provide the fraction of active neurons as well as the first two moments of their firing statistics. The introduction of a synaptic time scale does not modify the main aspects of the reported phenomenon. However, for sufficiently slow synapses the transition becomes dramatic, and the system passes from a perfectly regular evolution to irregular bursting dynamics. In this latter regime the model provides predictions consistent with experimental findings for a specific class of neurons, namely the medium spiny neurons in the striatum.

  15. Neural activity when people solve verbal problems with insight.

    Directory of Open Access Journals (Sweden)

    Mark Jung-Beeman

    2004-04-01

    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.

  16. Embodied Learning of a Generative Neural Model for Biological Motion Perception and Inference

    Directory of Open Access Journals (Sweden)

    Fabian eSchrodt

    2015-07-01

    Full Text Available Although an action observation network and mirror neurons for understanding the actions and intentions of others have been under deep, interdisciplinary consideration over recent years, it remains largely unknown how the brain manages to map visually perceived biological motion of others onto its own motor system. This paper shows how such a mapping may be established, even if the biologically motion is visually perceived from a new vantage point. We introduce a learning artificial neural network model and evaluate it on full body motion tracking recordings. The model implements an embodied, predictive inference approach. It first learns to correlate and segment multimodal sensory streams of own bodily motion. In doing so, it becomes able to anticipate motion progression, to complete missing modal information, and to self-generate learned motion sequences. When biological motion of another person is observed, this self-knowledge is utilized to recognize similar motion patterns and predict their progress. Due to the relative encodings, the model shows strong robustness in recognition despite observing rather large varieties of body morphology and posture dynamics. By additionally equipping the model with the capability to rotate its visual frame of reference, it is able to deduce the visual perspective onto the observed person, establishing full consistency to the embodied self-motion encodings by means of active inference. In further support of its neuro-cognitive plausibility, we also model typical bistable perceptions when crucial depth information is missing. In sum, the introduced neural model proposes a solution to the problem of how the human brain may establish correspondence between observed bodily motion and its own motor system, thus offering a mechanism that supports the development of mirror neurons.

  17. Neural activations correlated with reading speed during reading novels.

    Science.gov (United States)

    Fujimaki, Norio; Munetsuna, Shinji; Sasaki, Toyofumi; Hayakawa, Tomoe; Ihara, Aya; Wei, Qiang; Terazono, Yasushi; Murata, Tsutomu

    2009-12-01

    Functional magnetic resonance imaging was used to measure neural activations in subjects instructed to silently read novels at ordinary and rapid speeds. Among the 19 subjects, 8 were experts in a rapid reading technique. Subjects pressed a button to turn pages during reading, and the interval between turning pages was recorded to evaluate the reading speed. For each subject, we evaluated activations in 14 areas and at 2 instructed reading speeds. Neural activations decreased with increasing reading speed in the left middle and posterior superior temporal area, left inferior frontal area, left precentral area, and the anterior temporal areas of both hemispheres, which have been reported to be active for linguistic processes, while neural activation increased with increasing reading speed in the right intraparietal sulcus, which is considered to reflect visuo-spatial processes. Despite the considerable reading speed differences, correlation analysis showed no significant difference in activation dependence on reading speed with respect to the subject groups and instructed reading speeds. The activation reduction with speed increase in language-related areas was opposite to the previous reports for low reading speeds. The present results suggest that subjects reduced linguistic processes with reading speed increase from ordinary to rapid speed.

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

    Directory of Open Access Journals (Sweden)

    Pulin Gong

    2009-12-01

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

  19. Early interfaced neural activity from chronic amputated nerves

    Directory of Open Access Journals (Sweden)

    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. .

  20. Generation of retinal pigment epithelial cells from human embryonic stem cell-derived spherical neural masses.

    Science.gov (United States)

    Cho, Myung Soo; Kim, Sang Jin; Ku, Seung-Yup; Park, Jung Hyun; Lee, Haksup; Yoo, Dae Hoon; Park, Un Chul; Song, Seul Ae; Choi, Young Min; Yu, Hyeong Gon

    2012-09-01

    Dysfunction and loss of retinal pigment epithelium (RPE) are major pathologic changes observed in various retinal degenerative diseases such as aged-related macular degeneration. RPE generated from human pluripotent stem cells can be a good candidate for RPE replacement therapy. Here, we show the differentiation of human embryonic stem cells (hESCs) toward RPE with the generation of spherical neural masses (SNMs), which are pure masses of hESCs-derived neural precursors. During the early passaging of SNMs, cystic structures arising from opened neural tube-like structures showed pigmented epithelial morphology. These pigmented cells were differentiated into functional RPE by neuroectodermal induction and mechanical purification. Most of the differentiated cells showed typical RPE morphologies, such as a polygonal-shaped epithelial monolayer, and transmission electron microscopy revealed apical microvilli, pigment granules, and tight junctions. These cells also expressed molecular markers of RPE, including Mitf, ZO-1, RPE65, CRALBP, and bestrophin. The generated RPE also showed phagocytosis of isolated bovine photoreceptor outer segment and secreting pigment epithelium-derived factor and vascular endothelial growth factor. Functional RPE could be generated from SNM in our method. Because SNMs have several advantages, including the capability of expansion for long periods without loss of differentiation capability, easy storage and thawing, and no need for feeder cells, our method for RPE differentiation may be used as an efficient strategy for generating functional RPE cells for retinal regeneration therapy. Copyright © 2012 Elsevier B.V. All rights reserved.

  1. Graphene in the Design and Engineering of Next-Generation Neural Interfaces.

    Science.gov (United States)

    Kostarelos, Kostas; Vincent, Melissa; Hebert, Clement; Garrido, Jose A

    2017-11-01

    Neural interfaces are becoming a powerful toolkit for clinical interventions requiring stimulation and/or recording of the electrical activity of the nervous system. Active implantable devices offer a promising approach for the treatment of various diseases affecting the central or peripheral nervous systems by electrically stimulating different neuronal structures. All currently used neural interface devices are designed to perform a single function: either record activity or electrically stimulate tissue. Because of their electrical and electrochemical performance and their suitability for integration into flexible devices, graphene-based materials constitute a versatile platform that could help address many of the current challenges in neural interface design. Here, how graphene and other 2D materials possess an array of properties that can enable enhanced functional capabilities for neural interfaces is illustrated. It is emphasized that the technological challenges are similar for all alternative types of materials used in the engineering of neural interface devices, each offering a unique set of advantages and limitations. Graphene and 2D materials can indeed play a commanding role in the efforts toward wider clinical adoption of bioelectronics and electroceuticals. © 2017 WILEY-VCH Verlag GmbH & Co. KGaA, Weinheim.

  2. Generation of Regionally Specified Neural Progenitors and Functional Neurons from Human Embryonic Stem Cells under Defined Conditions

    Directory of Open Access Journals (Sweden)

    Agnete Kirkeby

    2012-06-01

    Full Text Available To model human neural-cell-fate specification and to provide cells for regenerative therapies, we have developed a method to generate human neural progenitors and neurons from human embryonic stem cells, which recapitulates human fetal brain development. Through the addition of a small molecule that activates canonical WNT signaling, we induced rapid and efficient dose-dependent specification of regionally defined neural progenitors ranging from telencephalic forebrain to posterior hindbrain fates. Ten days after initiation of differentiation, the progenitors could be transplanted to the adult rat striatum, where they formed neuron-rich and tumor-free grafts with maintained regional specification. Cells patterned toward a ventral midbrain (VM identity generated a high proportion of authentic dopaminergic neurons after transplantation. The dopamine neurons showed morphology, projection pattern, and protein expression identical to that of human fetal VM cells grafted in parallel. VM-patterned but not forebrain-patterned neurons released dopamine and reversed motor deficits in an animal model of Parkinson's disease.

  3. Generation of hourly irradiation synthetic series using the neural network multilayer perceptron

    Energy Technology Data Exchange (ETDEWEB)

    Hontoria, L.; Aguilera, J. [Universidad de Jaen, Linares-Jaen (Spain). Dpto. de Electronica; Zufiria, P. [Ciudad Universitaria, Madrid (Spain). Grupo de Redes Neuronales

    2002-05-01

    In this work, a methodology based on the neural network model called multilayer perceptron (MLP) to solve a typical problem in solar energy is presented. This methodology consists of the generation of synthetic series of hourly solar irradiation. The model presented is based on the capacity of the MLP for finding relations between variables for which interrelation is unknown explicitly. The information available can be included progressively at the series generator at different stages. A comparative study with other solar irradiation synthetic generation methods has been done in order to demonstrate the validity of the one proposed. (author)

  4. Monitoring activity in neural circuits with genetically encoded indicators

    Directory of Open Access Journals (Sweden)

    Gerard Joseph Broussard

    2014-12-01

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

  5. Reconstruction of three-dimensional porous media using generative adversarial neural networks

    Science.gov (United States)

    Mosser, Lukas; Dubrule, Olivier; Blunt, Martin J.

    2017-10-01

    To evaluate the variability of multiphase flow properties of porous media at the pore scale, it is necessary to acquire a number of representative samples of the void-solid structure. While modern x-ray computer tomography has made it possible to extract three-dimensional images of the pore space, assessment of the variability in the inherent material properties is often experimentally not feasible. We present a method to reconstruct the solid-void structure of porous media by applying a generative neural network that allows an implicit description of the probability distribution represented by three-dimensional image data sets. We show, by using an adversarial learning approach for neural networks, that this method of unsupervised learning is able to generate representative samples of porous media that honor their statistics. We successfully compare measures of pore morphology, such as the Euler characteristic, two-point statistics, and directional single-phase permeability of synthetic realizations with the calculated properties of a bead pack, Berea sandstone, and Ketton limestone. Results show that generative adversarial networks can be used to reconstruct high-resolution three-dimensional images of porous media at different scales that are representative of the morphology of the images used to train the neural network. The fully convolutional nature of the trained neural network allows the generation of large samples while maintaining computational efficiency. Compared to classical stochastic methods of image reconstruction, the implicit representation of the learned data distribution can be stored and reused to generate multiple realizations of the pore structure very rapidly.

  6. Persistent activity in neural networks with dynamic synapses.

    Directory of Open Access Journals (Sweden)

    Omri Barak

    2007-02-01

    Full Text Available Persistent activity states (attractors, observed in several neocortical areas after the removal of a sensory stimulus, are believed to be the neuronal basis of working memory. One of the possible mechanisms that can underlie persistent activity is recurrent excitation mediated by intracortical synaptic connections. A recent experimental study revealed that connections between pyramidal cells in prefrontal cortex exhibit various degrees of synaptic depression and facilitation. Here we analyze the effect of synaptic dynamics on the emergence and persistence of attractor states in interconnected neural networks. We show that different combinations of synaptic depression and facilitation result in qualitatively different network dynamics with respect to the emergence of the attractor states. This analysis raises the possibility that the framework of attractor neural networks can be extended to represent time-dependent stimuli.

  7. Artificial Neural Network for Real Time Load Flow Calculation: Application to a Micro Grid with Wind Generators

    Directory of Open Access Journals (Sweden)

    H. Hadj Abdallah

    2005-09-01

    Full Text Available This work presents a method for solving the problem of load flow in electric power systems including a wind power station with asynchronous generators. For this type of power station, the generated active power is only known and consequently the absorbed reactive power must be determined. So we have used the circular diagram at each iteration and by considering this node as a consuming node in the load flow program. Since the wind speed is not constant, the generated power is neither constant. To predict the state of the network in real time, we have used the artificial neural networks after a stage of training using a rich base of data.

  8. Development of modularity in the neural activity of children's brains

    OpenAIRE

    Chen, Man; Deem, Michael W.

    2015-01-01

    We study how modularity of the human brain changes as children develop into adults. Theory suggests that modularity can enhance the response function of a networked system subject to changing external stimuli. Thus, greater cognitive performance might be achieved for more modular neural activity, and modularity might likely increase as children develop. The value of modularity calculated from fMRI data is observed to increase during childhood development and peak in young adulthood. Head moti...

  9. Bioinorganic Life and Neural Activity: Toward a Chemistry of Consciousness?

    Science.gov (United States)

    Chang, Christopher J

    2017-03-21

    Identifying what elements are required for neural activity as potential path toward consciousness, which represents life with the state or quality of awareness, is a "Holy Grail" of chemistry. As life itself arises from coordinated interactions between elements across the periodic table, the majority of which are metals, new approaches for analysis, binding, and control of these primary chemical entities can help enrich our understanding of inorganic chemistry in living systems in a context that is both universal and personal.

  10. Modified Neural Network for Dynamic Control and Operation of a Hybrid Generation Systems

    Directory of Open Access Journals (Sweden)

    Cong-Hui Huang

    2014-12-01

    Full Text Available This paper presents modified neural network for dynamic control and operation of a hybrid generation systems. PV and wind power are the primary power sources of the system to take full advantages of renewable energy, and the diesel-engine is used as a backup system. The simulation model of the hybrid system was developed using MATLAB Simulink. To achieve a fast and stable response for the real power control, the intelligent controller consists of a Radial Basis Function Network (RBFN and an modified Elman Neural Network (ENN for maximum power point tracking (MPPT. The pitch angle of wind turbine is controlled by ENN, and the PV system uses RBFN, where the output signal is used to control the DC I DC boost converters to achieve the MPPT. And the results show the hybrid generation system can effectively extract the maximum power from the PV and wind energy sources.

  11. Physiological modules for generating discrete and rhythmic movements: action identification by a dynamic recurrent neural network.

    Science.gov (United States)

    Bengoetxea, Ana; Leurs, Françoise; Hoellinger, Thomas; Cebolla, Ana M; Dan, Bernard; McIntyre, Joseph; Cheron, Guy

    2014-01-01

    In this study we employed a dynamic recurrent neural network (DRNN) in a novel fashion to reveal characteristics of control modules underlying the generation of muscle activations when drawing figures with the outstretched arm. We asked healthy human subjects to perform four different figure-eight movements in each of two workspaces (frontal plane and sagittal plane). We then trained a DRNN to predict the movement of the wrist from information in the EMG signals from seven different muscles. We trained different instances of the same network on a single movement direction, on all four movement directions in a single movement plane, or on all eight possible movement patterns and looked at the ability of the DRNN to generalize and predict movements for trials that were not included in the training set. Within a single movement plane, a DRNN trained on one movement direction was not able to predict movements of the hand for trials in the other three directions, but a DRNN trained simultaneously on all four movement directions could generalize across movement directions within the same plane. Similarly, the DRNN was able to reproduce the kinematics of the hand for both movement planes, but only if it was trained on examples performed in each one. As we will discuss, these results indicate that there are important dynamical constraints on the mapping of EMG to hand movement that depend on both the time sequence of the movement and on the anatomical constraints of the musculoskeletal system. In a second step, we injected EMG signals constructed from different synergies derived by the PCA in order to identify the mechanical significance of each of these components. From these results, one can surmise that discrete-rhythmic movements may be constructed from three different fundamental modules, one regulating the co-activation of all muscles over the time span of the movement and two others elliciting patterns of reciprocal activation operating in orthogonal directions.

  12. Physiological modules for generating discrete and rhythmic movements: action identification by a dynamic recurrent neural network.

    Directory of Open Access Journals (Sweden)

    Ana eBengoetxea

    2014-09-01

    Full Text Available In this study we employed a dynamic recurrent neural network (DRNN in a novel fashion to reveal characteristics of control modules underlying the generation of muscle activations when drawing figures with the outstretched arm. We asked healthy human subjects to perform four different figure-eight movements in each of two workspaces (frontal plane and sagittal plane. We then trained a DRNN to predict the movement of the wrist from information in the EMG signals from seven different muscles. We trained different instances of the same network on a single movement direction, on all four movement directions in a single movement plane, or on all eight possible movement patterns and looked at the ability of the DRNN to generalize and predict movements for trials that were not included in the training set. Within a single movement plane, a DRNN trained on one movement direction was not able to predict movements of the hand for trials in the other three directions, but a DRNN trained simultaneously on all four movement directions could generalize across movement directions within the same plane. Similarly, the DRNN was able to reproduce the kinematics of the hand for both movement planes, but only if it was trained on examples performed in each one. As we will discuss, these results indicate that there are important dynamical constraints on the mapping of EMG to hand movement that depend on both the time sequence of the movement and on the anatomical constraints of the musculoskeletal system. In a second step, we injected EMG signals constructed from different synergies derived by the PCA in order to identify the mechanical significance of each of these components. From these results, one can surmise that discrete-rhythmic movements may be constructed from three different fundamental modules, one regulating the co-activation of all muscles over the time span of the movement and two others patterns of reciprocal activation operating in orthogonal

  13. Intelligent fuzzy-neural pattern generation and control of a quadrupedal bionic inspection robot

    Science.gov (United States)

    Sayfeddine, D.; Bulgakov, A. G.

    2017-02-01

    This paper represents a case study on ‘single leg single step’ pattern generation and control of quadrupedal bionic robot movement using intelligent fuzzy-neural approaches. The aim is to set up a flip-flop mechanical configuration allowing the robot to move one step forward. The same algorithm can be integrated to develop a full trajectory pattern as an interconnected task of global path planning for autonomous quadrupedal robots.

  14. Reconfigurable embedded system architecture for next-generation Neural Signal Processing.

    Science.gov (United States)

    Balasubramanian, Karthikeyan; Obeid, Iyad

    2010-01-01

    This work presents a new architectural framework for next generation Neural Signal Processing (NSP). The essential features of the NSP hardware platform include scalability, reconfigurability, real-time processing ability and data storage. This proposed framework has been implemented in a proof-of-concept NSP prototype using an embedded system architecture synthesized in a Xilinx(®)Virtex(®)5 development board. The prototype includes a threshold-based spike detector and a fuzzy logic-based spike sorter.

  15. Effects of bursting dynamic features on the generation of multi-clustered structure of neural network with symmetric spike-timing-dependent plasticity learning rule.

    Science.gov (United States)

    Liu, Hui; Song, Yongduan; Xue, Fangzheng; Li, Xiumin

    2015-11-01

    In this paper, the generation of multi-clustered structure of self-organized neural network with different neuronal firing patterns, i.e., bursting or spiking, has been investigated. The initially all-to-all-connected spiking neural network or bursting neural network can be self-organized into clustered structure through the symmetric spike-timing-dependent plasticity learning for both bursting and spiking neurons. However, the time consumption of this clustering procedure of the burst-based self-organized neural network (BSON) is much shorter than the spike-based self-organized neural network (SSON). Our results show that the BSON network has more obvious small-world properties, i.e., higher clustering coefficient and smaller shortest path length than the SSON network. Also, the results of larger structure entropy and activity entropy of the BSON network demonstrate that this network has higher topological complexity and dynamical diversity, which benefits for enhancing information transmission of neural circuits. Hence, we conclude that the burst firing can significantly enhance the efficiency of clustering procedure and the emergent clustered structure renders the whole network more synchronous and therefore more sensitive to weak input. This result is further confirmed from its improved performance on stochastic resonance. Therefore, we believe that the multi-clustered neural network which self-organized from the bursting dynamics has high efficiency in information processing.

  16. Effects of bursting dynamic features on the generation of multi-clustered structure of neural network with symmetric spike-timing-dependent plasticity learning rule

    Energy Technology Data Exchange (ETDEWEB)

    Liu, Hui; Song, Yongduan; Xue, Fangzheng; Li, Xiumin, E-mail: xmli@cqu.edu.cn [Key Laboratory of Dependable Service Computing in Cyber Physical Society of Ministry of Education, Chongqing University, Chongqing 400044 (China); College of Automation, Chongqing University, Chongqing 400044 (China)

    2015-11-15

    In this paper, the generation of multi-clustered structure of self-organized neural network with different neuronal firing patterns, i.e., bursting or spiking, has been investigated. The initially all-to-all-connected spiking neural network or bursting neural network can be self-organized into clustered structure through the symmetric spike-timing-dependent plasticity learning for both bursting and spiking neurons. However, the time consumption of this clustering procedure of the burst-based self-organized neural network (BSON) is much shorter than the spike-based self-organized neural network (SSON). Our results show that the BSON network has more obvious small-world properties, i.e., higher clustering coefficient and smaller shortest path length than the SSON network. Also, the results of larger structure entropy and activity entropy of the BSON network demonstrate that this network has higher topological complexity and dynamical diversity, which benefits for enhancing information transmission of neural circuits. Hence, we conclude that the burst firing can significantly enhance the efficiency of clustering procedure and the emergent clustered structure renders the whole network more synchronous and therefore more sensitive to weak input. This result is further confirmed from its improved performance on stochastic resonance. Therefore, we believe that the multi-clustered neural network which self-organized from the bursting dynamics has high efficiency in information processing.

  17. Multivariate synthetic streamflow generation using a hybrid model based on artificial neural networks

    Directory of Open Access Journals (Sweden)

    J. C. Ochoa-Rivera

    2002-01-01

    Full Text Available A model for multivariate streamflow generation is presented, based on a multilayer feedforward neural network. The structure of the model results from two components, the neural network (NN deterministic component and a random component which is assumed to be normally distributed. It is from this second component that the model achieves the ability to incorporate effectively the uncertainty associated with hydrological processes, making it valuable as a practical tool for synthetic generation of streamflow series. The NN topology and the corresponding analytical explicit formulation of the model are described in detail. The model is calibrated with a series of monthly inflows to two reservoir sites located in the Tagus River basin (Spain, while validation is performed through estimation of a set of statistics that is relevant for water resources systems planning and management. Among others, drought and storage statistics are computed and compared for both the synthetic and historical series. The performance of the NN-based model was compared to that of a standard autoregressive AR(2 model. Results show that NN represents a promising modelling alternative for simulation purposes, with interesting potential in the context of water resources systems management and optimisation. Keywords: neural networks, perceptron multilayer, error backpropagation, hydrological scenario generation, multivariate time-series..

  18. Compensatory Neural Activity in Response to Cognitive Fatigue.

    Science.gov (United States)

    Wang, Chao; Trongnetrpunya, Amy; Samuel, Immanuel Babu Henry; Ding, Mingzhou; Kluger, Benzi M

    2016-04-06

    Prolonged continuous performance of a cognitively demanding task induces cognitive fatigue and is associated with a time-related deterioration of objective performance, the degree of which is referred to cognitive fatigability. Although the neural underpinnings of cognitive fatigue are poorly understood, prior studies report changes in neural activity consistent with deterioration of task-related networks over time. While compensatory brain activity is reported to maintain motor task performance in the face of motor fatigue and cognitive performance in the face of other stressors (e.g., aging) and structural changes, there are no studies to date demonstrating compensatory activity for cognitive fatigue. High-density electroencephalography was recorded from human subjects during a 160 min continuous performance of a cognitive control task. While most time-varying neural activity showed a linear decline over time, we identified an evoked potential over the anterior frontal region which demonstrated an inverted U-shaped time-on-task profile. This evoked brain activity peaked between 60 and 100 min into the task and was positively associated with better behavioral performance only during this interval. Following the peak and during subsequent decline of this anterior frontal activity, the rate of performance decline also accelerated. These findings demonstrate that this anterior frontal brain activity, which is not part of the primary task-related activity at baseline, is recruited to compensate for fatigue-induced impairments in the primary task-related network, and that this compensation terminates as cognitive fatigue further progresses. These findings may be relevant to understanding individual differences in cognitive fatigability and developing interventions for clinical conditions afflicted by fatigue. Fatigue refers to changes in objective performance and subjective effort induced by continuous task performance. We examined the neural underpinnings of cognitive

  19. The cognitive and neural basis of option generation and subsequent choice.

    Science.gov (United States)

    Kaiser, Stefan; Simon, Joe J; Kalis, Annemarie; Schweizer, Sophie; Tobler, Philippe N; Mojzisch, Andreas

    2013-12-01

    Decision-making research has thoroughly investigated how people choose from a set of externally provided options. However, in ill-structured real-world environments, possible options for action are not defined by the situation but have to be generated by the agent. Here, we apply behavioral analysis (Study 1) and functional magnetic resonance imaging (Study 2) to investigate option generation and subsequent choice. For this purpose, we employ a new experimental task that requires participants to generate options for simple real-world scenarios and to subsequently decide among the generated options. Correlational analysis with a cognitive test battery suggests that retrieval of options from long-term memory is a relevant process during option generation. The results of the fMRI study demonstrate that option generation in simple real-world scenarios recruits the anterior prefrontal cortex. Furthermore, we show that choice behavior and its neural correlates differ between self-generated and externally provided options. Specifically, choice between self-generated options is associated with stronger recruitment of the dorsal anterior cingulate cortex. This impact of option generation on subsequent choice underlines the need for an expanded model of decision making to accommodate choice between self-generated options.

  20. The effects of gratitude expression on neural activity.

    Science.gov (United States)

    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. Copyright © 2015 Elsevier Inc. All rights reserved.

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

    Science.gov (United States)

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

    2017-06-02

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

  2. Cognitive emotion regulation in children: Reappraisal of emotional faces modulates neural source activity in a frontoparietal network.

    Science.gov (United States)

    Wessing, Ida; Rehbein, Maimu A; Romer, Georg; Achtergarde, Sandra; Dobel, Christian; Zwitserlood, Pienie; Fürniss, Tilman; Junghöfer, Markus

    2015-06-01

    Emotion regulation has an important role in child development and psychopathology. Reappraisal as cognitive regulation technique can be used effectively by children. Moreover, an ERP component known to reflect emotional processing called late positive potential (LPP) can be modulated by children using reappraisal and this modulation is also related to children's emotional adjustment. The present study seeks to elucidate the neural generators of such LPP effects. To this end, children aged 8-14 years reappraised emotional faces, while neural activity in an LPP time window was estimated using magnetoencephalography-based source localization. Additionally, neural activity was correlated with two indexes of emotional adjustment and age. Reappraisal reduced activity in the left dorsolateral prefrontal cortex during down-regulation and enhanced activity in the right parietal cortex during up-regulation. Activity in the visual cortex decreased with increasing age, more adaptive emotion regulation and less anxiety. Results demonstrate that reappraisal changed activity within a frontoparietal network in children. Decreasing activity in the visual cortex with increasing age is suggested to reflect neural maturation. A similar decrease with adaptive emotion regulation and less anxiety implies that better emotional adjustment may be associated with an advance in neural maturation. Copyright © 2015 The Authors. Published by Elsevier Ltd.. All rights reserved.

  3. Cognitive emotion regulation in children: Reappraisal of emotional faces modulates neural source activity in a frontoparietal network

    Directory of Open Access Journals (Sweden)

    Ida Wessing

    2015-06-01

    Full Text Available Emotion regulation has an important role in child development and psychopathology. Reappraisal as cognitive regulation technique can be used effectively by children. Moreover, an ERP component known to reflect emotional processing called late positive potential (LPP can be modulated by children using reappraisal and this modulation is also related to children's emotional adjustment. The present study seeks to elucidate the neural generators of such LPP effects. To this end, children aged 8–14 years reappraised emotional faces, while neural activity in an LPP time window was estimated using magnetoencephalography-based source localization. Additionally, neural activity was correlated with two indexes of emotional adjustment and age. Reappraisal reduced activity in the left dorsolateral prefrontal cortex during down-regulation and enhanced activity in the right parietal cortex during up-regulation. Activity in the visual cortex decreased with increasing age, more adaptive emotion regulation and less anxiety. Results demonstrate that reappraisal changed activity within a frontoparietal network in children. Decreasing activity in the visual cortex with increasing age is suggested to reflect neural maturation. A similar decrease with adaptive emotion regulation and less anxiety implies that better emotional adjustment may be associated with an advance in neural maturation.

  4. Learning to Generate Sequences with Combination of Hebbian and Non-hebbian Plasticity in Recurrent Spiking Neural Networks.

    Science.gov (United States)

    Panda, Priyadarshini; Roy, Kaushik

    2017-01-01

    Synaptic Plasticity, the foundation for learning and memory formation in the human brain, manifests in various forms. Here, we combine the standard spike timing correlation based Hebbian plasticity with a non-Hebbian synaptic decay mechanism for training a recurrent spiking neural model to generate sequences. We show that inclusion of the adaptive decay of synaptic weights with standard STDP helps learn stable contextual dependencies between temporal sequences, while reducing the strong attractor states that emerge in recurrent models due to feedback loops. Furthermore, we show that the combined learning scheme suppresses the chaotic activity in the recurrent model substantially, thereby enhancing its' ability to generate sequences consistently even in the presence of perturbations.

  5. Generation of neural progenitors from induced Bama miniature pig pluripotent cells.

    Science.gov (United States)

    Li, Xue; Shan, Zhi-Yan; Wu, Yan-Shuang; Shen, Xing-Hui; Liu, Chun-Jia; Shen, Jing-Ling; Liu, Zhong-Hua; Lei, Lei

    2014-01-01

    Pig pluripotent cells may represent an advantageous experimental tool for developing therapeutic application in the human biomedical field. However, it has previously been proven to be difficult to establish from the early embryo and its pluripotency has not been distinctly documented. In recent years, induced pluripotent stem (iPS) cell technology provides a new method of reprogramming somatic cells to pluripotent state. The generation of iPS cells together with or without certain small molecules has become a routine technique. However, the generation of iPS cells from pig embryonic tissues using viral infections together with small molecules has not been reported. Here, we reported the generation of induced pig pluripotent cells (iPPCs) using the iPS technology in combination with valproic acid (VPA). VPA treatment significantly increased the expression of pluripotent genes and played an important role in early reprogramming. We showed that iPPCs resembled pig epiblast cells in their morphology and pluripotent markers, such as OCT4, NANOG, and SSEA1. It had a normal karyotype and could form embryoid bodies, which express three germ layer markers in vitro. In addition, the iPPCs might directly differentiate into neural progenitors after being induced with the retinoic acid and extracellular matrix. Our study established a reasonable method to generate pig pluripotent cells, which might be a new donor cell source for human neural disease therapy.

  6. Plasmid-based generation of induced neural stem cells from adult human fibroblasts

    Directory of Open Access Journals (Sweden)

    Philipp Capetian

    2016-10-01

    Full Text Available Direct reprogramming from somatic to neural cell types has become an alternative to induced pluripotent stem cells. Most protocols employ viral expression systems, posing the risk of random genomic integration. Recent developments led to plasmid-based protocols, lowering this risk. However, these protocols either relied on continuous presence of a variety of small molecules or were only able to reprogram murine cells. We therefore established a reprogramming protocol based on vectors containing the Epstein-Barr virus (EBV-derived oriP/EBNA1 as well as the defined expression factors Oct3/4, Sox2, Klf4, L-myc, Lin28, and a small hairpin directed against p53. We employed a defined neural medium in combination with the neurotrophins bFGF, EGF and FGF4 for cultivation without the addition of small molecules. After reprogramming, cells demonstrated a temporary increase in the expression of endogenous Oct3/4. We obtained induced neural stem cells (iNSC 30 days after transfection. In contrast to previous results, plasmid vectors as well as a residual expression of reprogramming factors remained detectable in all cell lines. Cells showed a robust differentiation into neuronal (72% and glial cells (9% astrocytes, 6% oligodendrocytes. Despite the temporary increase of pluripotency-associated Oct3/4 expression during reprogramming, we did not detect pluripotent stem cells or non-neural cells in culture (except occasional residual fibroblasts. Neurons showed electrical activity and functional glutamatergic synapses. Our results demonstrate that reprogramming adult human fibroblasts to iNSC by plasmid vectors and basic neural medium without small molecules is possible and feasible. However, a full set of pluripotency-associated transcription factors may indeed result in the acquisition of a transient (at least partial pluripotent intermediate during reprogramming. In contrast to previous reports, the EBV-based plasmid system remained present and active inside

  7. A Granger causality measure for point process models of ensemble neural spiking activity.

    Directory of Open Access Journals (Sweden)

    Sanggyun Kim

    2011-03-01

    Full Text Available The ability to identify directional interactions that occur among multiple neurons in the brain is crucial to an understanding of how groups of neurons cooperate in order to generate specific brain functions. However, an optimal method of assessing these interactions has not been established. Granger causality has proven to be an effective method for the analysis of the directional interactions between multiple sets of continuous-valued data, but cannot be applied to neural spike train recordings due to their discrete nature. This paper proposes a point process framework that enables Granger causality to be applied to point process data such as neural spike trains. The proposed framework uses the point process likelihood function to relate a neuron's spiking probability to possible covariates, such as its own spiking history and the concurrent activity of simultaneously recorded neurons. Granger causality is assessed based on the relative reduction of the point process likelihood of one neuron obtained excluding one of its covariates compared to the likelihood obtained using all of its covariates. The method was tested on simulated data, and then applied to neural activity recorded from the primary motor cortex (MI of a Felis catus subject. The interactions present in the simulated data were predicted with a high degree of accuracy, and when applied to the real neural data, the proposed method identified causal relationships between many of the recorded neurons. This paper proposes a novel method that successfully applies Granger causality to point process data, and has the potential to provide unique physiological insights when applied to neural spike trains.

  8. A Granger causality measure for point process models of ensemble neural spiking activity.

    Science.gov (United States)

    Kim, Sanggyun; Putrino, David; Ghosh, Soumya; Brown, Emery N

    2011-03-01

    The ability to identify directional interactions that occur among multiple neurons in the brain is crucial to an understanding of how groups of neurons cooperate in order to generate specific brain functions. However, an optimal method of assessing these interactions has not been established. Granger causality has proven to be an effective method for the analysis of the directional interactions between multiple sets of continuous-valued data, but cannot be applied to neural spike train recordings due to their discrete nature. This paper proposes a point process framework that enables Granger causality to be applied to point process data such as neural spike trains. The proposed framework uses the point process likelihood function to relate a neuron's spiking probability to possible covariates, such as its own spiking history and the concurrent activity of simultaneously recorded neurons. Granger causality is assessed based on the relative reduction of the point process likelihood of one neuron obtained excluding one of its covariates compared to the likelihood obtained using all of its covariates. The method was tested on simulated data, and then applied to neural activity recorded from the primary motor cortex (MI) of a Felis catus subject. The interactions present in the simulated data were predicted with a high degree of accuracy, and when applied to the real neural data, the proposed method identified causal relationships between many of the recorded neurons. This paper proposes a novel method that successfully applies Granger causality to point process data, and has the potential to provide unique physiological insights when applied to neural spike trains.

  9. Emergence of gamma motor activity in an artificial neural network model of the corticospinal system.

    Science.gov (United States)

    Grandjean, Bernard; Maier, Marc A

    2017-02-01

    Muscle spindle discharge during active movement is a function of mechanical and neural parameters. Muscle length changes (and their derivatives) represent its primary mechanical, fusimotor drive its neural component. However, neither the action nor the function of fusimotor and in particular of γ-drive, have been clearly established, since γ-motor activity during voluntary, non-locomotor movements remains largely unknown. Here, using a computational approach, we explored whether γ-drive emerges in an artificial neural network model of the corticospinal system linked to a biomechanical antagonist wrist simulator. The wrist simulator included length-sensitive and γ-drive-dependent type Ia and type II muscle spindle activity. Network activity and connectivity were derived by a gradient descent algorithm to generate reciprocal, known target α-motor unit activity during wrist flexion-extension (F/E) movements. Two tasks were simulated: an alternating F/E task and a slow F/E tracking task. Emergence of γ-motor activity in the alternating F/E network was a function of α-motor unit drive: if muscle afferent (together with supraspinal) input was required for driving α-motor units, then γ-drive emerged in the form of α-γ coactivation, as predicted by empirical studies. In the slow F/E tracking network, γ-drive emerged in the form of α-γ dissociation and provided critical, bidirectional muscle afferent activity to the cortical network, containing known bidirectional target units. The model thus demonstrates the complementary aspects of spindle output and hence γ-drive: i) muscle spindle activity as a driving force of α-motor unit activity, and ii) afferent activity providing continuous sensory information, both of which crucially depend on γ-drive.

  10. Comparison of 2D and 3D neural induction methods for the generation of neural progenitor cells from human induced pluripotent stem cells.

    Science.gov (United States)

    Chandrasekaran, Abinaya; Avci, Hasan X; Ochalek, Anna; Rösingh, Lone N; Molnár, Kinga; László, Lajos; Bellák, Tamás; Téglási, Annamária; Pesti, Krisztina; Mike, Arpad; Phanthong, Phetcharat; Bíró, Orsolya; Hall, Vanessa; Kitiyanant, Narisorn; Krause, Karl-Heinz; Kobolák, Julianna; Dinnyés, András

    2017-12-01

    Neural progenitor cells (NPCs) from human induced pluripotent stem cells (hiPSCs) are frequently induced using 3D culture methodologies however, it is unknown whether spheroid-based (3D) neural induction is actually superior to monolayer (2D) neural induction. Our aim was to compare the efficiency of 2D induction with 3D induction method in their ability to generate NPCs, and subsequently neurons and astrocytes. Neural differentiation was analysed at the protein level qualitatively by immunocytochemistry and quantitatively by flow cytometry for NPC (SOX1, PAX6, NESTIN), neuronal (MAP2, TUBB3), cortical layer (TBR1, CUX1) and glial markers (SOX9, GFAP, AQP4). Electron microscopy demonstrated that both methods resulted in morphologically similar neural rosettes. However, quantification of NPCs derived from 3D neural induction exhibited an increase in the number of PAX6/NESTIN double positive cells and the derived neurons exhibited longer neurites. In contrast, 2D neural induction resulted in more SOX1 positive cells. While 2D monolayer induction resulted in slightly less mature neurons, at an early stage of differentiation, the patch clamp analysis failed to reveal any significant differences between the electrophysiological properties between the two induction methods. In conclusion, 3D neural induction increases the yield of PAX6+/NESTIN+ cells and gives rise to neurons with longer neurites, which might be an advantage for the production of forebrain cortical neurons, highlighting the potential of 3D neural induction, independent of iPSCs' genetic background. Copyright © 2017 The Authors. Published by Elsevier B.V. All rights reserved.

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

    Science.gov (United States)

    1988-03-01

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

  12. Long-range correlations in rabbit brain neural activity.

    Science.gov (United States)

    de la Fuente, I M; Perez-Samartin, A L; Martínez, L; Garcia, M A; Vera-Lopez, A

    2006-02-01

    We have analyzed the presence of persistence properties in rabbit brain electrical signals by means of non-equilibrium statistical physics tools. To measure long-memory properties of these experimental signals, we have first determined whether the data are fractional Gaussian noise (fGn) or fractional Brownian motion (fBm) by calculating the slope of the power spectral density plot of the series. The results show that the series correspond to fBm. Then, the data were studied by means of the bridge detrended scaled windowed variance analysis, detecting long-term correlation. Three different types of experimental signals have been studied: neural basal activity without stimulation, the response induced by a single flash light stimulus and the average of the activity evoked by 200 flash light stimulations. Analysis of the series revealed the existence of persistent behavior in all cases. Moreover, the results also exhibited an increasing correlation in the level of long-term memory from recordings without stimulation, to one sweep recording or 200 sweeps averaged recordings. Thus, brain neural electrical activity is affected not only by its most recent states, but also by previous states much more distant in the past.

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

    Directory of Open Access Journals (Sweden)

    Bogdan C. Raducanu

    2017-10-01

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

  14. Sociocultural patterning of neural activity during self-reflection

    DEFF Research Database (Denmark)

    Ma, Yina; Bang, Dan; Wang, Chenbo

    2014-01-01

    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...... that judgments of self vs. a public figure elicited greater activation in the medial prefrontal cortex (mPFC) in Danish than in Chinese participants regardless of attribute dimensions for judgments. However, self-judgments of social attributes induced greater activity in the temporoparietal junction (TPJ......) in 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...

  15. Genetic Algorithms for Optimal Reactive Power Compensation of a Power System with Wind Generators based on Artificial Neural Networks

    Directory of Open Access Journals (Sweden)

    L. Krichen

    2007-03-01

    Full Text Available In this paper, we develop a method to maintain an acceptable voltages profile and minimization of active losses of a power system including wind generators in real time. These tasks are ensured by acting on capacitor and inductance benches implemented in the consuming nodes. To solve this problem, we minimize an objective function associated to active losses under constraints imposed on the voltages and the reactive productions of the various benches. The minimization procedure was realised by the use of genetic algorithms (GA. The major disadvantage of this technique is that it requires a significant computing time thus not making it possible to deal with the problem in real time. After a training phase, a neural model has the capacity to provide a good estimation of the voltages, the reactive productions and the losses for forecast curves of the load and the wind speed, in real time.

  16. Imidacloprid Exposure Suppresses Neural Crest Cells Generation during Early Chick Embryo Development.

    Science.gov (United States)

    Wang, Chao-Jie; Wang, Guang; Wang, Xiao-Yu; Liu, Meng; Chuai, Manli; Lee, Kenneth Ka Ho; He, Xiao-Song; Lu, Da-Xiang; Yang, Xuesong

    2016-06-15

    Imidacloprid is a neonicotinoid pesticide that is widely used in the control pests found on crops and fleas on pets. However, it is still unclear whether imidacloprid exposure could affect early embryo development-despite some studies having been conducted on the gametes. In this study, we demonstrated that imidacloprid exposure could lead to abnormal craniofacial osteogenesis in the developing chick embryo. Cranial neural crest cells (NCCs) are the progenitor cells of the chick cranial skull. We found that the imidacloprid exposure retards the development of gastrulating chick embryos. HNK-1, PAX7, and Ap-2α immunohistological stainings indicated that cranial NCCs generation was inhibited after imidacloprid exposure. Double immunofluorescent staining (Ap-2α and PHIS3 or PAX7 and c-Caspase3) revealed that imidacloprid exposure inhibited both NCC proliferation and apoptosis. In addition, it inhibited NCCs production by repressing Msx1 and BMP4 expression in the developing neural tube and by altering expression of EMT-related adhesion molecules (Cad6B, E-Cadherin, and N-cadherin) in the developing neural crests. We also determined that imidacloprid exposure suppressed cranial NCCs migration and their ability to differentiate. In sum, we have provided experimental evidence that imidacloprid exposure during embryogenesis disrupts NCCs development, which in turn causes defective cranial bone development.

  17. Generation and properties of a new human ventral mesencephalic neural stem cell line

    Energy Technology Data Exchange (ETDEWEB)

    Villa, Ana; Liste, Isabel; Courtois, Elise T.; Seiz, Emma G.; Ramos, Milagros [Center of Molecular Biology ' Severo Ochoa' , Autonomous University of Madrid-C.S.I.C., Campus Cantoblanco 28049-Madrid (Spain); Meyer, Morten [Department of Anatomy and Neurobiology, Institute of Medical Biology, University of Southern Denmark, Winslowparken 21,st, DK-500, Odense C (Denmark); Juliusson, Bengt; Kusk, Philip [NsGene A/S, Ballerup (Denmark); Martinez-Serrano, Alberto, E-mail: amserrano@cbm.uam.es [Center of Molecular Biology ' Severo Ochoa' , Autonomous University of Madrid-C.S.I.C., Campus Cantoblanco 28049-Madrid (Spain)

    2009-07-01

    Neural stem cells (NSCs) are powerful research tools for the design and discovery of new approaches to cell therapy in neurodegenerative diseases like Parkinson's disease. Several epigenetic and genetic strategies have been tested for long-term maintenance and expansion of these cells in vitro. Here we report the generation of a new stable cell line of human neural stem cells derived from ventral mesencephalon (hVM1) based on v-myc immortalization. The cells expressed neural stem cell and radial glia markers like nestin, vimentin and 3CB2 under proliferation conditions. After withdrawal of growth factors, proliferation and expression of v-myc were dramatically reduced and the cells differentiated into astrocytes, oligodendrocytes and neurons. hVM1 cells yield a large number of dopaminergic neurons (about 12% of total cells are TH{sup +}) after differentiation, which also produce dopamine. In addition to proneural genes (NGN2, MASH1), differentiated cells show expression of several genuine mesencephalic dopaminergic markers such as: LMX1A, LMX1B, GIRK2, ADH2, NURR1, PITX3, VMAT2 and DAT, indicating that they retain their regional identity. Our data indicate that this cell line and its clonal derivatives may constitute good candidates for the study of development and physiology of human dopaminergic neurons in vitro, and to develop tools for Parkinson's disease cell replacement preclinical research and drug testing.

  18. Sensory-related neural activity regulates the structure of vascular networks in the cerebral cortex

    Science.gov (United States)

    Lacoste, Baptiste; Comin, Cesar H.; Ben-Zvi, Ayal; Kaeser, Pascal S.; Xu, Xiaoyin; Costa, Luciano da F.; Gu, Chenghua

    2014-01-01

    SUMMARY Neurovascular interactions are essential for proper brain function. While the effect of neural activity on cerebral blood flow has been extensively studied, whether neural activity influences vascular patterning remains elusive. Here, we demonstrate that neural activity promotes the formation of vascular networks in the early postnatal mouse barrel cortex. Using a combination of genetics, imaging, and computational tools to allow simultaneous analysis of neuronal and vascular components, we found that vascular density and branching were decreased in the barrel cortex when sensory input was reduced by either a complete deafferentation, a genetic impairment of neurotransmitter release at thalamocortical synapses, or a selective reduction of sensory-related neural activity by whisker plucking. In contrast, enhancement of neural activity by whisker stimulation led to an increase in vascular density and branching. The finding that neural activity is necessary and sufficient to trigger alterations of vascular networks reveals a novel feature of neurovascular interactions. PMID:25155955

  19. Sensory-related neural activity regulates the structure of vascular networks in the cerebral cortex.

    Science.gov (United States)

    Lacoste, Baptiste; Comin, Cesar H; Ben-Zvi, Ayal; Kaeser, Pascal S; Xu, Xiaoyin; Costa, Luciano da F; Gu, Chenghua

    2014-09-03

    Neurovascular interactions are essential for proper brain function. While the effect of neural activity on cerebral blood flow has been extensively studied, whether or not neural activity influences vascular patterning remains elusive. Here, we demonstrate that neural activity promotes the formation of vascular networks in the early postnatal mouse barrel cortex. Using a combination of genetics, imaging, and computational tools to allow simultaneous analysis of neuronal and vascular components, we found that vascular density and branching were decreased in the barrel cortex when sensory input was reduced by either a complete deafferentation, a genetic impairment of neurotransmitter release at thalamocortical synapses, or a selective reduction of sensory-related neural activity by whisker plucking. In contrast, enhancement of neural activity by whisker stimulation led to an increase in vascular density and branching. The finding that neural activity is necessary and sufficient to trigger alterations of vascular networks reveals an important feature of neurovascular interactions. Copyright © 2014 Elsevier Inc. All rights reserved.

  20. Neural activity in the hippocampus during conflict resolution.

    Science.gov (United States)

    Sakimoto, Yuya; Okada, Kana; Hattori, Minoru; Takeda, Kozue; Sakata, Shogo

    2013-01-15

    This study examined configural association theory and conflict resolution models in relation to hippocampal neural activity during positive patterning tasks. According to configural association theory, the hippocampus is important for responses to compound stimuli in positive patterning tasks. In contrast, according to the conflict resolution model, the hippocampus is important for responses to single stimuli in positive patterning tasks. We hypothesized that if configural association theory is applicable, and not the conflict resolution model, the hippocampal theta power should be increased when compound stimuli are presented. If, on the other hand, the conflict resolution model is applicable, but not configural association theory, then the hippocampal theta power should be increased when single stimuli are presented. If both models are valid and applicable in the positive patterning task, we predict that the hippocampal theta power should be increased by presentation of both compound and single stimuli during the positive patterning task. To examine our hypotheses, we measured hippocampal theta power in rats during a positive patterning task. The results showed that hippocampal theta power increased during the presentation of a single stimulus, but did not increase during the presentation of a compound stimulus. This finding suggests that the conflict resolution model is more applicable than the configural association theory for describing neural activity during positive patterning tasks. Copyright © 2012 Elsevier B.V. All rights reserved.

  1. The versatility of RhoA activities in neural differentiation.

    Science.gov (United States)

    Horowitz, Arie; Yang, Junning; Cai, Jingli; Iacovitti, Lorraine

    2017-01-26

    In this commentary we discuss a paper we published recently on the activities of the GTPase RhoA during neural differentiation of murine embryonic stem cells, and relate our findings to previous studies. We narrate how we found that RhoA impedes neural differentiation by inhibiting the production as well as the secretion of noggin, a soluble factor that antagonizes bone morphogenetic protein. We discuss how the questions we tried to address shaped the study, and how embryonic stem cells isolated from a genetically modified mouse model devoid of Syx, a RhoA-specific guanine exchange factor, were used to address them. We detail several signaling pathways downstream of RhoA that are hindered by the absence of Syx, and obstructed by retinoic acid, resulting in an increase of noggin production; we explain how the lower RhoA activity and, consequently, the sparser peri-junctional stress fibers in Syx -/- cells facilitated noggin secretion; and we report unpublished results showing that pharmacological inhibition of RhoA accelerates the neuronal differentiation of human embryonic stem cells. Finally, we identify signaling mechanisms in our recent study that warrant further study, and speculate on the possibility of manipulating RhoA signaling in combination with other pathways to drive the differentiation of neuronal subtypes.

  2. Social power and approach-related neural activity

    Science.gov (United States)

    Smolders, Ruud; Cremer, David De

    2012-01-01

    It has been argued that power activates a general tendency to approach whereas powerlessness activates a tendency to inhibit. The assumption is that elevated power involves reward-rich environments, freedom and, as a consequence, triggers an approach-related motivational orientation and attention to rewards. In contrast, reduced power is associated with increased threat, punishment and social constraint and thereby activates inhibition-related motivation. Moreover, approach motivation has been found to be associated with increased relative left-sided frontal brain activity, while withdrawal motivation has been associated with increased right sided activations. We measured EEG activity while subjects engaged in a task priming either high or low social power. Results show that high social power is indeed associated with greater left-frontal brain activity compared to low social power, providing the first neural evidence for the theory that high power is associated with approach-related motivation. We propose a framework accounting for differences in both approach motivation and goal-directed behaviour associated with different levels of power. PMID:19304842

  3. System Identification of a Nonlinear Multivariable Steam Generator Power Plant Using Time Delay and Wavelet Neural Networks

    Directory of Open Access Journals (Sweden)

    Laila Khalilzadeh Ganjali-khani

    2013-01-01

    Full Text Available One of the most effective strategies for steam generator efficiency enhancement is to improve the control system. For such an improvement, it is essential to have an accurate model for the steam generator of power plant. In this paper, an industrial steam generator is considered as a nonlinear multivariable system for identification. An important step in nonlinear system identification is the development of a nonlinear model. In recent years, artificial neural networks have been successfully used for identification of nonlinear systems in many researches. Wavelet neural networks (WNNs also are used as a powerful tool for nonlinear system identification. In this paper we present a time delay neural network model and a WNN model in order to identify an industrial steam generator. Simulation results show the effectiveness of the proposed models in the system identification and demonstrate that the WNN model is more precise to estimate the plant outputs.

  4. Relationship between caregivers' income generation activities and ...

    African Journals Online (AJOL)

    Enhancing Child Nutrition through Animal Source Food Management (ENAM) project provided financial and technical support for caregivers' Income Generation Activities (IGA) with the aim of increasing their access to Animal Source Foods (ASF) for improved child nutrition. Using baseline data from the ENAM project, this ...

  5. Targeted activation of primitive neural stem cells in the mouse brain.

    Science.gov (United States)

    Reeve, Rachel L; Yammine, Samantha Z; DeVeale, Brian; van der Kooy, Derek

    2016-06-01

    Primitive neural stem cells (pNSCs) are the earliest NSCs to appear in the developing forebrain. They persist into the adult forebrain where they can generate all cells in the neural lineage and therefore hold great potential for brain regeneration. Thus, pNSCs are an ideal population to target to promote endogenous NSC activation. pNSCs can be isolated from the periventricular region as leukaemia inhibitory factor-responsive cells, and comprise a rare population in the adult mouse brain. We hypothesized that the pup periventricular region gives rise to more clonal pNSC-derived neurospheres but that pup-derived pNSCs are otherwise comparable to adult-derived pNSCs, and can be used to identify selective markers and activators of endogenous pNSCs. We tested the self-renewal ability, differentiation capacity and gene expression profile of pup-derived pNSCs and found them each to be comparable to adult-derived pNSCs, including being GFAP(-) , nestin(mid) , Oct4(+) . Next, we used pup pNSCs to test pharmacological compounds to activate pNSCs to promote endogenous brain repair. We hypothesized that pNSCs could be activated by targeting the cell surface proteins C-Kit and ErbB2, which were enriched in pNSCs relative to definitive NSCs (dNSCs) in an in vitro screen. C-Kit and ErbB2 signalling inhibition had distinct effects on pNSCs and dNSCs in vitro, and when infused directly into the adult brain in vivo. Targeted activation of pNSCs with C-Kit and ErbB2 modulation is a valuable strategy to activate the earliest cell in the neural lineage to contribute to endogenous brain regeneration. © 2016 Federation of European Neuroscience Societies and John Wiley & Sons Ltd.

  6. Learning-Related Changes in Adolescents' Neural Networks during Hypothesis-Generating and Hypothesis-Understanding Training

    Science.gov (United States)

    Lee, Jun-Ki; Kwon, Yongju

    2012-01-01

    Fourteen science high school students participated in this study, which investigated neural-network plasticity associated with hypothesis-generating and hypothesis-understanding in learning. The students were divided into two groups and participated in either hypothesis-generating or hypothesis-understanding type learning programs, which were…

  7. Neural Manifolds for the Control of Movement.

    Science.gov (United States)

    Gallego, Juan A; Perich, Matthew G; Miller, Lee E; Solla, Sara A

    2017-06-07

    The analysis of neural dynamics in several brain cortices has consistently uncovered low-dimensional manifolds that capture a significant fraction of neural variability. These neural manifolds are spanned by specific patterns of correlated neural activity, the "neural modes." We discuss a model for neural control of movement in which the time-dependent activation of these neural modes is the generator of motor behavior. This manifold-based view of motor cortex may lead to a better understanding of how the brain controls movement. Copyright © 2017 Elsevier Inc. All rights reserved.

  8. Natural lecithin promotes neural network complexity and activity.

    Science.gov (United States)

    Latifi, Shahrzad; Tamayol, Ali; Habibey, Rouhollah; Sabzevari, Reza; Kahn, Cyril; Geny, David; Eftekharpour, Eftekhar; Annabi, Nasim; Blau, Axel; Linder, Michel; Arab-Tehrany, Elmira

    2016-05-27

    Phospholipids in the brain cell membranes contain different polyunsaturated fatty acids (PUFAs), which are critical to nervous system function and structure. In particular, brain function critically depends on the uptake of the so-called "essential" fatty acids such as omega-3 (n-3) and omega-6 (n-6) PUFAs that cannot be readily synthesized by the human body. We extracted natural lecithin rich in various PUFAs from a marine source and transformed it into nanoliposomes. These nanoliposomes increased neurite outgrowth, network complexity and neural activity of cortical rat neurons in vitro. We also observed an upregulation of synapsin I (SYN1), which supports the positive role of lecithin in synaptogenesis, synaptic development and maturation. These findings suggest that lecithin nanoliposomes enhance neuronal development, which may have an impact on devising new lecithin delivery strategies for therapeutic applications.

  9. Neural activity reveals perceptual grouping in working memory.

    Science.gov (United States)

    Rabbitt, Laura R; Roberts, Daniel M; McDonald, Craig G; Peterson, Matthew S

    2017-03-01

    There is extensive evidence that the contralateral delay activity (CDA), a scalp recorded event-related brain potential, provides a reliable index of the number of objects held in visual working memory. Here we present evidence that the CDA not only indexes visual object working memory, but also the number of locations held in spatial working memory. In addition, we demonstrate that the CDA can be predictably modulated by the type of encoding strategy employed. When individual locations were held in working memory, the pattern of CDA modulation mimicked previous findings for visual object working memory. Specifically, CDA amplitude increased monotonically until working memory capacity was reached. However, when participants were instructed to group individual locations to form a constellation, the CDA was prolonged and reached an asymptote at two locations. This result provides neural evidence for the formation of a unitary representation of multiple spatial locations. Published by Elsevier B.V.

  10. IAEA activities on steam generator life management

    Energy Technology Data Exchange (ETDEWEB)

    Gueorguiev, B.; Lyssakov, V.; Trampus, P. [International Atomic Energy Agency, Div. of Nuclear Power, Vienna (Austria)

    2002-07-01

    The International Atomic Energy Agency (IAEA) carries out a set of activities in the field of Nuclear Power Plant (NPP) life management. Main activities within this area are implemented through the Technical Working Group on Life Management of NPPs, and mostly concentrated on studies of understanding mechanisms of degradation and their monitoring, optimisation of maintenance management, economic aspects, proven practices of and approaches to plant life management including decommissioning. The paper covers two ongoing activities related to steam generator life management: the International Database on NPP Steam Generators and the Co-ordinated Research Project on Verification of WWER Steam Generator Tube Integrity (WWER is the Russian designed PWR). The lifetime assessment of main components relies on an ability to assess their condition and predict future degradation trends, which to a large extent is dependent on the availability of relevant data. Effective management of ageing and degradation processes requires a large amount of data. Several years ago the IAEA started to work on the International Database on NPP Life Management. This is a multi-module database consisting of modules such as reactor pressure vessels materials, piping, steam generators, and concrete structures. At present the work on pressure vessel materials, on piping as well as on steam generator is completed. The paper will present the concept and structure of the steam generator module of the database. In countries operating WWER NPPs, there are big differences in the eddy current inspection strategy and practice as well as in the approach to steam generator heat exchanger tube structural integrity assessment. Responding to the need for a co-ordinated research to compare eddy current testing results with destructive testing using pulled out tubes from WWER steam generators, the IAEA launched this project. The main objectives of the project are to summarise the operating experiences of WWER

  11. Decorrelation of Neural-Network Activity by Inhibitory Feedback

    Science.gov (United States)

    Einevoll, Gaute T.; Diesmann, Markus

    2012-01-01

    Correlations in spike-train ensembles can seriously impair the encoding of information by their spatio-temporal structure. An inevitable source of correlation in finite neural networks is common presynaptic input to pairs of neurons. Recent studies demonstrate that spike correlations in recurrent neural networks are considerably smaller than expected based on the amount of shared presynaptic input. Here, we explain this observation by means of a linear network model and simulations of networks of leaky integrate-and-fire neurons. We show that inhibitory feedback efficiently suppresses pairwise correlations and, hence, population-rate fluctuations, thereby assigning inhibitory neurons the new role of active decorrelation. We quantify this decorrelation by comparing the responses of the intact recurrent network (feedback system) and systems where the statistics of the feedback channel is perturbed (feedforward system). Manipulations of the feedback statistics can lead to a significant increase in the power and coherence of the population response. In particular, neglecting correlations within the ensemble of feedback channels or between the external stimulus and the feedback amplifies population-rate fluctuations by orders of magnitude. The fluctuation suppression in homogeneous inhibitory networks is explained by a negative feedback loop in the one-dimensional dynamics of the compound activity. Similarly, a change of coordinates exposes an effective negative feedback loop in the compound dynamics of stable excitatory-inhibitory networks. The suppression of input correlations in finite networks is explained by the population averaged correlations in the linear network model: In purely inhibitory networks, shared-input correlations are canceled by negative spike-train correlations. In excitatory-inhibitory networks, spike-train correlations are typically positive. Here, the suppression of input correlations is not a result of the mere existence of correlations between

  12. To compare the effect of Active Neural Mobilization during Intermittent Lumbar Traction and Intermittent Lumbar Traction followed by Active Neural Mobilization in cases of Lumbar Radiculopathy

    OpenAIRE

    Jaywant Nagulkar; Kalyani Nagulkar

    2016-01-01

    To compare the effectiveness of Active neural mobilization (ANM) during intermittent lumbar traction (ILT) and intermittent lumbar traction followed by active neural mobilization treatment in patients of low back pain (LBP) with radiculopathy.. To study the effect of ANM during ILT and ILT followed by ANM in patients of LBP with radiculopathy on VAS scale, P1 angle of SLR, P2 angle of SLR and Oswestry disability index(ODI). To compare the effect of ANM during ILT and ILT followed ...

  13. 3-D components of a biological neural network visualized in computer generated imagery. II - Macular neural network organization

    Science.gov (United States)

    Ross, Muriel D.; Meyer, Glenn; Lam, Tony; Cutler, Lynn; Vaziri, Parshaw

    1990-01-01

    Computer-assisted reconstructions of small parts of the macular neural network show how the nerve terminals and receptive fields are organized in 3-dimensional space. This biological neural network is anatomically organized for parallel distributed processing of information. Processing appears to be more complex than in computer-based neural network, because spatiotemporal factors figure into synaptic weighting. Serial reconstruction data show anatomical arrangements which suggest that (1) assemblies of cells analyze and distribute information with inbuilt redundancy, to improve reliability; (2) feedforward/feedback loops provide the capacity for presynaptic modulation of output during processing; (3) constrained randomness in connectivities contributes to adaptability; and (4) local variations in network complexity permit differing analyses of incoming signals to take place simultaneously. The last inference suggests that there may be segregation of information flow to central stations subserving particular functions.

  14. Neural activity during traumatic film viewing is linked to endogenous estradiol and hormonal contraception.

    Science.gov (United States)

    Miedl, Stephan F; Wegerer, Melanie; Kerschbaum, Hubert; Blechert, Jens; Wilhelm, Frank H

    2018-01-01

    Women are at higher risk for Posttraumatic Stress Disorder (PTSD) and recent research has highlighted a modulating role of female sex hormones for cognitive and emotional processes potentially underlying PTSD symptoms. However, studies combining fMRI recordings of brain activity during trauma film viewing with assessment of female sex hormones are missing. The trauma film paradigm - a widely used experimental analogue for trauma exposure - confronts healthy participants with traumatic film clips and thus allows studying peritraumatic processing under laboratory conditions. Following this paradigm, the current fMRI study examined the role of endogenous estradiol and synthetic sex hormones for the neural processing of traumatic (i.e., depicting interpersonal violence) vs. neutral films in 53 healthy women (mean age 22.3 years; 23 using hormonal contraception, HC). As predicted, traumatic films strongly activated areas of the fear processing network, such as amygdala, insula, and dorsal anterior cingulate cortex. Estradiol levels in women not using HC were positively correlated with ventromedial prefrontal activity. Furthermore, women using HC as compared to women without HC demonstrated heightened insula and dorsal anterior cingulate cortex activity during traumatic film viewing. These experimental results highlight the effects of both gonadal hormone status and HC intake on peritraumatic processing in neural regions relevant for emotion generation and regulation that have been found to be abnormal in PTSD. Copyright © 2017 Elsevier Ltd. All rights reserved.

  15. Identification of non-linear models of neural activity in bold fmri

    DEFF Research Database (Denmark)

    Jacobsen, Daniel Jakup; Madsen, Kristoffer Hougaard; Hansen, Lars Kai

    2006-01-01

    Non-linear hemodynamic models express the BOLD signal as a nonlinear, parametric functional of the temporal sequence of local neural activity. Several models have been proposed for this neural activity. We identify one such parametric model by estimating the distribution of its parameters. These ...

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

    Science.gov (United States)

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

    2009-01-01

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

  17. Neural Network Hydrological Modelling: Linear Output Activation Functions?

    Science.gov (United States)

    Abrahart, R. J.; Dawson, C. W.

    2005-12-01

    The power to represent non-linear hydrological processes is of paramount importance in neural network hydrological modelling operations. The accepted wisdom requires non-polynomial activation functions to be incorporated in the hidden units such that a single tier of hidden units can thereafter be used to provide a 'universal approximation' to whatever particular hydrological mechanism or function is of interest to the modeller. The user can select from a set of default activation functions, or in certain software packages, is able to define their own function - the most popular options being logistic, sigmoid and hyperbolic tangent. If a unit does not transform its inputs it is said to possess a 'linear activation function' and a combination of linear activation functions will produce a linear solution; whereas the use of non-linear activation functions will produce non-linear solutions in which the principle of superposition does not hold. For hidden units, speed of learning and network complexities are important issues. For the output units, it is desirable to select an activation function that is suited to the distribution of the target values: e.g. binary targets (logistic); categorical targets (softmax); continuous-valued targets with a bounded range (logistic / tanh); positive target values with no known upper bound (exponential; but beware of overflow); continuous-valued targets with no known bounds (linear). It is also standard practice in most hydrological applications to use the default software settings and to insert a set of identical non-linear activation functions in the hidden layer and output layer processing units. Mixed combinations have nevertheless been reported in several hydrological modelling papers and the full ramifications of such activities requires further investigation and assessment i.e. non-linear activation functions in the hidden units connected to linear or clipped-linear activation functions in the output unit. There are two

  18. Activity-dependent modulation of neural circuit synaptic connectivity

    Directory of Open Access Journals (Sweden)

    Charles R Tessier

    2009-07-01

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

  19. EEG-fMRI Bayesian framework for neural activity estimation: a simulation study

    Science.gov (United States)

    Croce, Pierpaolo; Basti, Alessio; Marzetti, Laura; Zappasodi, Filippo; Del Gratta, Cosimo

    2016-12-01

    Objective. Due to the complementary nature of electroencephalography (EEG) and functional magnetic resonance imaging (fMRI), and given the possibility of simultaneous acquisition, the joint data analysis can afford a better understanding of the underlying neural activity estimation. In this simulation study we want to show the benefit of the joint EEG-fMRI neural activity estimation in a Bayesian framework. Approach. We built a dynamic Bayesian framework in order to perform joint EEG-fMRI neural activity time course estimation. The neural activity is originated by a given brain area and detected by means of both measurement techniques. We have chosen a resting state neural activity situation to address the worst case in terms of the signal-to-noise ratio. To infer information by EEG and fMRI concurrently we used a tool belonging to the sequential Monte Carlo (SMC) methods: the particle filter (PF). Main results. First, despite a high computational cost, we showed the feasibility of such an approach. Second, we obtained an improvement in neural activity reconstruction when using both EEG and fMRI measurements. Significance. The proposed simulation shows the improvements in neural activity reconstruction with EEG-fMRI simultaneous data. The application of such an approach to real data allows a better comprehension of the neural dynamics.

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

    Directory of Open Access Journals (Sweden)

    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.

  1. SPR imaging combined with cyclic voltammetry for the detection of neural activity

    Directory of Open Access Journals (Sweden)

    Hui Li

    2014-03-01

    Full Text Available Surface plasmon resonance (SPR detects changes in refractive index at a metal-dielectric interface. In this study, SPR imaging (SPRi combined with cyclic voltammetry (CV was applied to detect neural activity in isolated bullfrog sciatic nerves. The neural activities induced by chemical and electrical stimulation led to an SPR response, and the activities were recorded in real time. The activities of different parts of the sciatic nerve were recorded and compared. The results demonstrated that SPR imaging combined with CV is a powerful tool for the investigation of neural activity.

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

    Science.gov (United States)

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

    2017-09-01

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

  3. Estimation of the energy of a PV generator using artificial neural network

    Energy Technology Data Exchange (ETDEWEB)

    Almonacid, F.; Rus, C.; Perez, P.J.; Hontoria, L. [Grupo Investigacion y Desarrollo en Energia Solar y Automatica, Dpto. de Ingenieria Electronica, E.P.S. Jaen, Universidad de Jaen, E.P.S de Linares, C/Alfonso X E1 Sabio no 28, 23071 Jaen (Spain)

    2009-12-15

    The integration of grid-connected photovoltaic (GCPVS) systems into urban buildings is very popular in industrialized countries. Many countries enhance the international collaboration efforts which accelerate the development and deployment of photovoltaic solar energy as a significant and sustainable renewable energy option. A previous method, based on artificial neural networks (ANNs), has been developed to electrical characterisation of PV modules. This method was able to generate V-I curves of si-crystalline PV modules for any irradiance and module cell temperature. The results showed that the proposed ANN introduced a good accurate prediction for si-crystalline PV modules performance when compared with the measured values. Now, this method, based on ANNs, is going to be applied to obtain a suitable value of the power provided by a photovoltaic installation. Specifically this method is going to be applied to obtain the power provided by a particular installation, the 'Univer generator', since modules used in these works were the same as the ones used in this photovoltaic generator. (author)

  4. Fracture Mechanics Method for Word Embedding Generation of Neural Probabilistic Linguistic Model

    Directory of Open Access Journals (Sweden)

    Size Bi

    2016-01-01

    Full Text Available Word embedding, a lexical vector representation generated via the neural linguistic model (NLM, is empirically demonstrated to be appropriate for improvement of the performance of traditional language model. However, the supreme dimensionality that is inherent in NLM contributes to the problems of hyperparameters and long-time training in modeling. Here, we propose a force-directed method to improve such problems for simplifying the generation of word embedding. In this framework, each word is assumed as a point in the real world; thus it can approximately simulate the physical movement following certain mechanics. To simulate the variation of meaning in phrases, we use the fracture mechanics to do the formation and breakdown of meaning combined by a 2-gram word group. With the experiments on the natural linguistic tasks of part-of-speech tagging, named entity recognition and semantic role labeling, the result demonstrated that the 2-dimensional word embedding can rival the word embeddings generated by classic NLMs, in terms of accuracy, recall, and text visualization.

  5. On the relationships between generative encodings, regularity, and learning abilities when evolving plastic artificial neural networks

    National Research Council Canada - National Science Library

    Tonelli, Paul; Mouret, Jean-Baptiste

    2013-01-01

    .... It is commonly believed that two keys for evolving nature-like artificial neural networks are (1) the developmental process that links genes to nervous systems, which enables the evolution of large, regular neural networks...

  6. Cortical Neural Activity Predicts Sensory Acuity Under Optogenetic Manipulation.

    Science.gov (United States)

    Briguglio, John J; Aizenberg, Mark; Balasubramanian, Vijay; Geffen, Maria N

    2018-02-21

    Excitatory and inhibitory neurons in the mammalian sensory cortex form interconnected circuits that control cortical stimulus selectivity and sensory acuity. Theoretical studies have predicted that suppression of inhibition in such excitatory-inhibitory networks can lead to either an increase or, paradoxically, a decrease in excitatory neuronal firing, with consequent effects on stimulus selectivity. We tested whether modulation of inhibition or excitation in the auditory cortex of male mice could evoke such a variety of effects in tone-evoked responses and in behavioral frequency discrimination acuity. We found that, indeed, the effects of optogenetic manipulation on stimulus selectivity and behavior varied in both magnitude and sign across subjects, possibly reflecting differences in circuitry or expression of optogenetic factors. Changes in neural population responses consistently predicted behavioral changes for individuals separately, including improvement and impairment in acuity. This correlation between cortical and behavioral change demonstrates that, despite the complex and varied effects that these manipulations can have on neuronal dynamics, the resulting changes in cortical activity account for accompanying changes in behavioral acuity. SIGNIFICANCE STATEMENT Excitatory and inhibitory interactions determine stimulus specificity and tuning in sensory cortex, thereby controlling perceptual discrimination acuity. Modeling has predicted that suppressing the activity of inhibitory neurons can lead to increased or, paradoxically, decreased excitatory activity depending on the architecture of the network. Here, we capitalized on differences between subjects to test whether suppressing/activating inhibition and excitation can in fact exhibit such paradoxical effects for both stimulus sensitivity and behavioral discriminability. Indeed, the same optogenetic manipulation in the auditory cortex of different mice could improve or impair frequency discrimination

  7. To create or to recall? Neural mechanisms underlying the generation of creative new ideas.

    Science.gov (United States)

    Benedek, Mathias; Jauk, Emanuel; Fink, Andreas; Koschutnig, Karl; Reishofer, Gernot; Ebner, Franz; Neubauer, Aljoscha C

    2014-03-01

    This fMRI study investigated brain activation during creative idea generation using a novel approach allowing spontaneous self-paced generation and expression of ideas. Specifically, we addressed the fundamental question of what brain processes are relevant for the generation of genuinely new creative ideas, in contrast to the mere recollection of old ideas from memory. In general, creative idea generation (i.e., divergent thinking) was associated with extended activations in the left prefrontal cortex and the right medial temporal lobe, and with deactivation of the right temporoparietal junction. The generation of new ideas, as opposed to the retrieval of old ideas, was associated with stronger activation in the left inferior parietal cortex which is known to be involved in mental simulation, imagining, and future thought. Moreover, brain activation in the orbital part of the inferior frontal gyrus was found to increase as a function of the creativity (i.e., originality and appropriateness) of ideas pointing to the role of executive processes for overcoming dominant but uncreative responses. We conclude that the process of idea generation can be generally understood as a state of focused internally-directed attention involving controlled semantic retrieval. Moreover, left inferior parietal cortex and left prefrontal regions may subserve the flexible integration of previous knowledge for the construction of new and creative ideas. Copyright © 2013 Elsevier Inc. All rights reserved.

  8. To create or to recall? Neural mechanisms underlying the generation of creative new ideas☆

    Science.gov (United States)

    Benedek, Mathias; Jauk, Emanuel; Fink, Andreas; Koschutnig, Karl; Reishofer, Gernot; Ebner, Franz; Neubauer, Aljoscha C.

    2014-01-01

    This fMRI study investigated brain activation during creative idea generation using a novel approach allowing spontaneous self-paced generation and expression of ideas. Specifically, we addressed the fundamental question of what brain processes are relevant for the generation of genuinely new creative ideas, in contrast to the mere recollection of old ideas from memory. In general, creative idea generation (i.e., divergent thinking) was associated with extended activations in the left prefrontal cortex and the right medial temporal lobe, and with deactivation of the right temporoparietal junction. The generation of new ideas, as opposed to the retrieval of old ideas, was associated with stronger activation in the left inferior parietal cortex which is known to be involved in mental simulation, imagining, and future thought. Moreover, brain activation in the orbital part of the inferior frontal gyrus was found to increase as a function of the creativity (i.e., originality and appropriateness) of ideas pointing to the role of executive processes for overcoming dominant but uncreative responses. We conclude that the process of idea generation can be generally understood as a state of focused internally-directed attention involving controlled semantic retrieval. Moreover, left inferior parietal cortex and left prefrontal regions may subserve the flexible integration of previous knowledge for the construction of new and creative ideas. PMID:24269573

  9. Short-term EEG dynamics and neural generators evoked by navigational images.

    Science.gov (United States)

    Leroy, Axelle; Cevallos, Carlos; Cebolla, Ana-Maria; Caharel, Stéphanie; Dan, Bernard; Cheron, Guy

    2017-01-01

    The ecological environment offered by virtual reality is primarily supported by visual information. The different image contents and their rhythmic presentation imply specific bottom-up and top-down processing. Because these processes already occur during passive observation we studied the brain responses evoked by the presentation of specific 3D virtual tunnels with respect to 2D checkerboard. For this, we characterized electroencephalograhy dynamics (EEG), the evoked potentials and related neural generators involved in various visual paradigms. Time-frequency analysis showed modulation of alpha-beta oscillations indicating the presence of stronger prediction and after-effects of the 3D-tunnel with respect to the checkerboard. Whatever the presented image, the generators of the P100 were situated bilaterally in the occipital cortex (BA18, BA19) and in the right inferior temporal cortex (BA20). In checkerboard but not 3D-tunnel presentation, the left fusiform gyrus (BA37) was additionally recruited. P200 generators were situated in the temporal cortex (BA21) and the cerebellum (lobule VI/Crus I) specifically for the checkerboard while the right parahippocampal gyrus (BA36) and the cerebellum (lobule IV/V and IX/X) were involved only during the 3D-tunnel presentation. For both type of image, P300 generators were localized in BA37 but also in BA19, the right BA21 and the cerebellar lobule VI for only the checkerboard and the left BA20-BA21 for only the 3D-tunnel. Stronger P300 delta-theta oscillations recorded in this later situation point to a prevalence of the effect of changing direction over the proper visual content of the 3D-tunnel. The parahippocampal gyrus (BA36) implicated in navigation was also identified when the 3D-tunnel was compared to their scrambled versions, highlighting an action-oriented effect linked to navigational content.

  10. Short-term EEG dynamics and neural generators evoked by navigational images.

    Directory of Open Access Journals (Sweden)

    Axelle Leroy

    Full Text Available The ecological environment offered by virtual reality is primarily supported by visual information. The different image contents and their rhythmic presentation imply specific bottom-up and top-down processing. Because these processes already occur during passive observation we studied the brain responses evoked by the presentation of specific 3D virtual tunnels with respect to 2D checkerboard. For this, we characterized electroencephalograhy dynamics (EEG, the evoked potentials and related neural generators involved in various visual paradigms. Time-frequency analysis showed modulation of alpha-beta oscillations indicating the presence of stronger prediction and after-effects of the 3D-tunnel with respect to the checkerboard. Whatever the presented image, the generators of the P100 were situated bilaterally in the occipital cortex (BA18, BA19 and in the right inferior temporal cortex (BA20. In checkerboard but not 3D-tunnel presentation, the left fusiform gyrus (BA37 was additionally recruited. P200 generators were situated in the temporal cortex (BA21 and the cerebellum (lobule VI/Crus I specifically for the checkerboard while the right parahippocampal gyrus (BA36 and the cerebellum (lobule IV/V and IX/X were involved only during the 3D-tunnel presentation. For both type of image, P300 generators were localized in BA37 but also in BA19, the right BA21 and the cerebellar lobule VI for only the checkerboard and the left BA20-BA21 for only the 3D-tunnel. Stronger P300 delta-theta oscillations recorded in this later situation point to a prevalence of the effect of changing direction over the proper visual content of the 3D-tunnel. The parahippocampal gyrus (BA36 implicated in navigation was also identified when the 3D-tunnel was compared to their scrambled versions, highlighting an action-oriented effect linked to navigational content.

  11. Generation of daily solar irradiation by means of artificial neural net works

    Energy Technology Data Exchange (ETDEWEB)

    Siqueira, Adalberto N.; Tiba, Chigueru; Fraidenraich, Naum [Departamento de Energia Nuclear, da Universidade Federal de Pernambuco, Av. Prof. Luiz Freire, 1000 - CDU, CEP 50.740-540 Recife, Pernambuco (Brazil)

    2010-11-15

    The present study proposes the utilization of Artificial Neural Networks (ANN) as an alternative for generating synthetic series of daily solar irradiation. The sequences were generated from the use of daily temporal series of a group of meteorological variables that were measured simultaneously. The data used were measured between the years of 1998 and 2006 in two temperate climate localities of Brazil, Ilha Solteira (Sao Paulo) and Pelotas (Rio Grande do Sul). The estimates were taken for the months of January, April, July and October, through two models which are distinguished regarding the use or nonuse of measured bright sunshine hours as an input variable. An evaluation of the performance of the 56 months of solar irradiation generated by way of ANN showed that by using the measured bright sunshine hours as an input variable (model 1), the RMSE obtained were less or equal to 23.2% being that of those, although 43 of those months presented RMSE less or equal to 12.3%. In the case of the model that did not use the measured bright sunshine hours but used a daylight length (model 2), RMSE were obtained that varied from 8.5% to 37.5%, although 38 of those months presented RMSE less or equal to 20.0%. A comparison of the monthly series for all of the years, achieved by means of the Kolmogorov-Smirnov test (to a confidence level of 99%), demonstrated that of the 16 series generated by ANN model only two, obtained by model 2 for the months of April and July in Pelotas, presented significant difference in relation to the distributions of the measured series and that all mean deviations obtained were inferior to 0.39 MJ/m{sup 2}. It was also verified that the two ANN models were able to reproduce the principal statistical characteristics of the frequency distributions of the measured series such as: mean, mode, asymmetry and Kurtosis. (author)

  12. Sensory Entrainment Mechanisms in Auditory Perception: Neural Synchronization Cortico-Striatal Activation

    Science.gov (United States)

    Sameiro-Barbosa, Catia M.; Geiser, Eveline

    2016-01-01

    The auditory system displays modulations in sensitivity that can align with the temporal structure of the acoustic environment. This sensory entrainment can facilitate sensory perception and is particularly relevant for audition. Systems neuroscience is slowly uncovering the neural mechanisms underlying the behaviorally observed sensory entrainment effects in the human sensory system. The present article summarizes the prominent behavioral effects of sensory entrainment and reviews our current understanding of the neural basis of sensory entrainment, such as synchronized neural oscillations, and potentially, neural activation in the cortico-striatal system. PMID:27559306

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

    Science.gov (United States)

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

    2017-01-01

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

  14. Development of modularity in the neural activity of children's brains.

    Science.gov (United States)

    Chen, Man; Deem, Michael W

    2015-01-26

    We study how modularity of the human brain changes as children develop into adults. Theory suggests that modularity can enhance the response function of a networked system subject to changing external stimuli. Thus, greater cognitive performance might be achieved for more modular neural activity, and modularity might likely increase as children develop. The value of modularity calculated from functional magnetic resonance imaging (fMRI) data is observed to increase during childhood development and peak in young adulthood. Head motion is deconvolved from the fMRI data, and it is shown that the dependence of modularity on age is independent of the magnitude of head motion. A model is presented to illustrate how modularity can provide greater cognitive performance at short times, i.e. task switching. A fitness function is extracted from the model. Quasispecies theory is used to predict how the average modularity evolves with age, illustrating the increase of modularity during development from children to adults that arises from selection for rapid cognitive function in young adults. Experiments exploring the effect of modularity on cognitive performance are suggested. Modularity may be a potential biomarker for injury, rehabilitation, or disease.

  15. Neural control and precision of flight muscle activation in Drosophila.

    Science.gov (United States)

    Lehmann, Fritz-Olaf; Bartussek, Jan

    2017-01-01

    Precision of motor commands is highly relevant in a large context of various locomotor behaviors, including stabilization of body posture, heading control and directed escape responses. While posture stability and heading control in walking and swimming animals benefit from high friction via ground reaction forces and elevated viscosity of water, respectively, flying animals have to cope with comparatively little aerodynamic friction on body and wings. Although low frictional damping in flight is the key to the extraordinary aerial performance and agility of flying birds, bats and insects, it challenges these animals with extraordinary demands on sensory integration and motor precision. Our review focuses on the dynamic precision with which Drosophila activates its flight muscular system during maneuvering flight, considering relevant studies on neural and muscular mechanisms of thoracic propulsion. In particular, we tackle the precision with which flies adjust power output of asynchronous power muscles and synchronous flight control muscles by monitoring muscle calcium and spike timing within the stroke cycle. A substantial proportion of the review is engaged in the significance of visual and proprioceptive feedback loops for wing motion control including sensory integration at the cellular level. We highlight that sensory feedback is the basis for precise heading control and body stability in flies.

  16. Neural activity associated with metaphor comprehension: spatial analysis.

    Science.gov (United States)

    Sotillo, María; Carretié, Luis; Hinojosa, José A; Tapia, Manuel; Mercado, Francisco; López-Martín, Sara; Albert, Jacobo

    2005-01-03

    Though neuropsychological data indicate that the right hemisphere (RH) plays a major role in metaphor processing, other studies suggest that, at least during some phases of this processing, a RH advantage may not exist. The present study explores, through a temporally agile neural signal--the event-related potentials (ERPs)--, and through source-localization algorithms applied to ERP recordings, whether the crucial phase of metaphor comprehension presents or not a RH advantage. Participants (n=24) were submitted to a S1-S2 experimental paradigm. S1 consisted of visually presented metaphoric sentences (e.g., "Green lung of the city"), followed by S2, which consisted of words that could (i.e., "Park") or could not (i.e., "Semaphore") be defined by S1. ERPs elicited by S2 were analyzed using temporal principal component analysis (tPCA) and source-localization algorithms. These analyses revealed that metaphorically related S2 words showed significantly higher N400 amplitudes than non-related S2 words. Source-localization algorithms showed differential activity between the two S2 conditions in the right middle/superior temporal areas. These results support the existence of an important RH contribution to (at least) one phase of metaphor processing and, furthermore, implicate the temporal cortex with respect to that contribution.

  17. Channelrhodopsins: visual regeneration and neural activation by a light switch

    Science.gov (United States)

    Natasha, G; Tan, Aaron; Farhatnia, Yasmin; Rajadas, Jayakumar; Hamblin, Michael R.; Khaw, Peng T.; Seifalian, Alexander M.

    2013-01-01

    The advent of optogenetics provides a new direction for the field of neuroscience and biotechnology, serving both as a refined investigative tool and as potential cure for many medical conditions via genetic manipulation. Although still in its infancy, recent advances in optogenetics has made it possible to remotely manipulate in vivo cellular functions using light. Coined Nature Methods’ ‘Method of the Year’ in 2010, the optogenetic toolbox has the potential to control cell, tissue and even animal behaviour. This optogenetic toolbox consists of light-sensitive proteins that are able to modulate membrane potential in response to light. Channelrhodopsins (ChR) are light-gated microbial ion channels, which were first described in green algae. ChR2 (a subset of ChR) is a seven transmembrane a helix protein, which evokes membrane depolarization and mediates an action potential upon photostimulation with blue (470 nm) light. By contrast to other seven-transmembrane proteins that require second messengers to open ion channels, ChR2 form ion channels themselves, allowing ultrafast depolarization (within 50 milliseconds of illumination). It has been shown that integration of ChR2 into various tissues of mice can activate neural circuits, control heart muscle contractions, and even restore breathing after spinal cord injury. More compellingly, a plethora of evidence has indicated that artificial expression of ChR2 in retinal ganglion cells can reinstate visual perception in mice with retinal degeneration. PMID:23664865

  18. Comparison of a spiking neural network and an MLP for robust identification of generator dynamics in a multimachine power system.

    Science.gov (United States)

    Johnson, Cameron; Venayagamoorthy, Ganesh Kumar; Mitra, Pinaki

    2009-01-01

    The application of a spiking neural network (SNN) and a multi-layer perceptron (MLP) for online identification of generator dynamics in a multimachine power system are compared in this paper. An integrate-and-fire model of an SNN which communicates information via the inter-spike interval is applied. The neural network identifiers are used to predict the speed and terminal voltage deviations one time-step ahead of generators in a multimachine power system. The SNN is developed in two steps: (i) neuron centers determined by offline k-means clustering and (ii) output weights obtained by online training. The sensitivity of the SNN to the neuron centers determined in the first step is evaluated on generators of different ratings and parameters. Performances of the SNN and MLP are compared to evaluate robustness on the identification of generator dynamics under small and large disturbances, and to illustrate that SNNs are capable of learning nonlinear dynamics of complex systems.

  19. Neural computational modeling reveals a major role of corticospinal gating of central oscillations in the generation of essential tremor

    Directory of Open Access Journals (Sweden)

    Hong-en Qu

    2017-01-01

    Full Text Available Essential tremor, also referred to as familial tremor, is an autosomal dominant genetic disease and the most common movement disorder. It typically involves a postural and motor tremor of the hands, head or other part of the body. Essential tremor is driven by a central oscillation signal in the brain. However, the corticospinal mechanisms involved in the generation of essential tremor are unclear. Therefore, in this study, we used a neural computational model that includes both monosynaptic and multisynaptic corticospinal pathways interacting with a propriospinal neuronal network. A virtual arm model is driven by the central oscillation signal to simulate tremor activity behavior. Cortical descending commands are classified as alpha or gamma through monosynaptic or multisynaptic corticospinal pathways, which converge respectively on alpha or gamma motoneurons in the spinal cord. Several scenarios are evaluated based on the central oscillation signal passing down to the spinal motoneurons via each descending pathway. The simulated behaviors are compared with clinical essential tremor characteristics to identify the corticospinal pathways responsible for transmitting the central oscillation signal. A propriospinal neuron with strong cortical inhibition performs a gating function in the generation of essential tremor. Our results indicate that the propriospinal neuronal network is essential for relaying the central oscillation signal and the production of essential tremor.

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

    Directory of Open Access Journals (Sweden)

    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

  1. Active optics for next generation space telescopes

    Science.gov (United States)

    Costes, V.; Perret, L.; Laubier, D.; Delvit, J. M.; Imbert, C.; Cadiergues, L.; Faure, C.

    2017-09-01

    High resolution observation systems need bigger and bigger telescopes. The design of such telescopes is a key issue for the whole satellite. In order to improve the imaging resolution with minimum impact on the satellite, a big effort must be made to improve the telescope compactness. Compactness is also important for the agility of the satellite and for the size and cost of the launcher. This paper shows how compact a high resolution telescope can be. A diffraction limited telescope can be less than ten times shorter than its focal length. But the compactness impacts drastically the opto-mechanical sensitivity and the optical performances. Typically, a gain of a factor of 2 leads to a mechanical tolerance budget 6 times more difficult. The need to implement active optics for positioning requirements raises very quickly. Moreover, the capability to compensate shape defaults of the primary mirror is the way to simplify the mirror manufacture, to mitigate the development risks and to minimize the cost. The larger the primary mirror is, the more interesting it is to implement active optics for shape compensations. CNES is preparing next generation of earth observation satellite in the frame of OTOS (Observation de la Terre Optique Super-Résolue; High resolution earth observing optical system). OTOS is a technology program. In particular, optical technological developments and breadboards dedicated to active optics are on-going. The aim is to achieve TRL 5 to TRL6 for these new technologies and to validate the global performances of such an active telescope.

  2. k-Same-Net: k-Anonymity with Generative Deep Neural Networks for Face Deidentification

    Directory of Open Access Journals (Sweden)

    Blaž Meden

    2018-01-01

    Full Text Available Image and video data are today being shared between government entities and other relevant stakeholders on a regular basis and require careful handling of the personal information contained therein. A popular approach to ensure privacy protection in such data is the use of deidentification techniques, which aim at concealing the identity of individuals in the imagery while still preserving certain aspects of the data after deidentification. In this work, we propose a novel approach towards face deidentification, called k-Same-Net, which combines recent Generative Neural Networks (GNNs with the well-known k-Anonymitymechanism and provides formal guarantees regarding privacy protection on a closed set of identities. Our GNN is able to generate synthetic surrogate face images for deidentification by seamlessly combining features of identities used to train the GNN model. Furthermore, it allows us to control the image-generation process with a small set of appearance-related parameters that can be used to alter specific aspects (e.g., facial expressions, age, gender of the synthesized surrogate images. We demonstrate the feasibility of k-Same-Net in comprehensive experiments on the XM2VTS and CK+ datasets. We evaluate the efficacy of the proposed approach through reidentification experiments with recent recognition models and compare our results with competing deidentification techniques from the literature. We also present facial expression recognition experiments to demonstrate the utility-preservation capabilities of k-Same-Net. Our experimental results suggest that k-Same-Net is a viable option for facial deidentification that exhibits several desirable characteristics when compared to existing solutions in this area.

  3. Multipotent neural stem cells generate glial cells of the central complex through transit amplifying intermediate progenitors in Drosophila brain development.

    Science.gov (United States)

    Viktorin, Gudrun; Riebli, Nadia; Popkova, Anna; Giangrande, Angela; Reichert, Heinrich

    2011-08-15

    The neural stem cells that give rise to the neural lineages of the brain can generate their progeny directly or through transit amplifying intermediate neural progenitor cells (INPs). The INP-producing neural stem cells in Drosophila are called type II neuroblasts, and their neural progeny innervate the central complex, a prominent integrative brain center. Here we use genetic lineage tracing and clonal analysis to show that the INPs of these type II neuroblast lineages give rise to glial cells as well as neurons during postembryonic brain development. Our data indicate that two main types of INP lineages are generated, namely mixed neuronal/glial lineages and neuronal lineages. Genetic loss-of-function and gain-of-function experiments show that the gcm gene is necessary and sufficient for gliogenesis in these lineages. The INP-derived glial cells, like the INP-derived neuronal cells, make major contributions to the central complex. In postembryonic development, these INP-derived glial cells surround the entire developing central complex neuropile, and once the major compartments of the central complex are formed, they also delimit each of these compartments. During this process, the number of these glial cells in the central complex is increased markedly through local proliferation based on glial cell mitosis. Taken together, these findings uncover a novel and complex form of neurogliogenesis in Drosophila involving transit amplifying intermediate progenitors. Moreover, they indicate that type II neuroblasts are remarkably multipotent neural stem cells that can generate both the neuronal and the glial progeny that make major contributions to one and the same complex brain structure. Copyright © 2011 Elsevier Inc. All rights reserved.

  4. SNW1 is a critical regulator of spatial BMP activity, neural plate border formation, and neural crest specification in vertebrate embryos.

    Directory of Open Access Journals (Sweden)

    Mary Y Wu

    2011-02-01

    Full Text Available Bone morphogenetic protein (BMP gradients provide positional information to direct cell fate specification, such as patterning of the vertebrate ectoderm into neural, neural crest, and epidermal tissues, with precise borders segregating these domains. However, little is known about how BMP activity is regulated spatially and temporally during vertebrate development to contribute to embryonic patterning, and more specifically to neural crest formation. Through a large-scale in vivo functional screen in Xenopus for neural crest fate, we identified an essential regulator of BMP activity, SNW1. SNW1 is a nuclear protein known to regulate gene expression. Using antisense morpholinos to deplete SNW1 protein in both Xenopus and zebrafish embryos, we demonstrate that dorsally expressed SNW1 is required for neural crest specification, and this is independent of mesoderm formation and gastrulation morphogenetic movements. By exploiting a combination of immunostaining for phosphorylated Smad1 in Xenopus embryos and a BMP-dependent reporter transgenic zebrafish line, we show that SNW1 regulates a specific domain of BMP activity in the dorsal ectoderm at the neural plate border at post-gastrula stages. We use double in situ hybridizations and immunofluorescence to show how this domain of BMP activity is spatially positioned relative to the neural crest domain and that of SNW1 expression. Further in vivo and in vitro assays using cell culture and tissue explants allow us to conclude that SNW1 acts upstream of the BMP receptors. Finally, we show that the requirement of SNW1 for neural crest specification is through its ability to regulate BMP activity, as we demonstrate that targeted overexpression of BMP to the neural plate border is sufficient to restore neural crest formation in Xenopus SNW1 morphants. We conclude that through its ability to regulate a specific domain of BMP activity in the vertebrate embryo, SNW1 is a critical regulator of neural plate

  5. Wrestling model of the repertoire of activity propagation modes in quadruple neural networks.

    Science.gov (United States)

    Shteingart, Hanan; Raichman, Nadav; Baruchi, Itay; Ben-Jacob, Eshel

    2010-01-01

    The spontaneous activity of engineered quadruple cultured neural networks (of four-coupled sub-networks) exhibits a repertoire of different types of mutual synchronization events. Each event corresponds to a specific activity propagation mode (APM) defined by the order of activity propagation between the sub-networks. We statistically characterized the frequency of spontaneous appearance of the different types of APMs. The relative frequencies of the APMs were then examined for their power-law properties. We found that the frequencies of appearance of the leading (most frequent) APMs have close to constant algebraic ratio reminiscent of Zipf's scaling of words. We show that the observations are consistent with a simplified "wrestling" model. This model represents an extension of the "boxing arena" model which was previously proposed to describe the ratio between the two activity modes in two coupled sub-networks. The additional new element in the "wrestling" model presented here is that the firing within each network is modeled by a time interval generator with similar intra-network Lévy distribution. We modeled the different burst-initiation zones' interaction by competition between the stochastic generators with Gaussian inter-network variability. Estimation of the model parameters revealed similarity across different cultures while the inter-burst-interval of the cultures was similar across different APMs as numerical simulation of the model predicts.

  6. Probabilistic Models and Generative Neural Networks: Towards an Unified Framework for Modeling Normal and Impaired Neurocognitive Functions.

    Science.gov (United States)

    Testolin, Alberto; Zorzi, Marco

    2016-01-01

    Connectionist models can be characterized within the more general framework of probabilistic graphical models, which allow to efficiently describe complex statistical distributions involving a large number of interacting variables. This integration allows building more realistic computational models of cognitive functions, which more faithfully reflect the underlying neural mechanisms at the same time providing a useful bridge to higher-level descriptions in terms of Bayesian computations. Here we discuss a powerful class of graphical models that can be implemented as stochastic, generative neural networks. These models overcome many limitations associated with classic connectionist models, for example by exploiting unsupervised learning in hierarchical architectures (deep networks) and by taking into account top-down, predictive processing supported by feedback loops. We review some recent cognitive models based on generative networks, and we point out promising research directions to investigate neuropsychological disorders within this approach. Though further efforts are required in order to fill the gap between structured Bayesian models and more realistic, biophysical models of neuronal dynamics, we argue that generative neural networks have the potential to bridge these levels of analysis, thereby improving our understanding of the neural bases of cognition and of pathologies caused by brain damage.

  7. Probabilistic models and generative neural networks: towards a unified framework for modeling normal and impaired neurocognitive functions

    Directory of Open Access Journals (Sweden)

    Alberto Testolin

    2016-07-01

    Full Text Available Connectionist models can be characterized within the more general framework of probabilistic graphical models, which allow to efficiently describe complex statistical distributions involving a large number of interacting variables. This integration allows building more realistic computational models of cognitive functions, which more faithfully reflect the underlying neural mechanisms at the same time providing a useful bridge to higher-level descriptions in terms of Bayesian computations. Here we discuss a powerful class of graphical models that can be implemented as stochastic, generative neural networks. These models overcome many limitations associated with classic connectionist models, for example by exploiting unsupervised learning in hierarchical architectures (deep networks and by taking into account top-down, predictive processing supported by feedback loops. We review some recent cognitive models based on generative networks, and we point out promising research directions to investigate neuropsychological disorders within this approach. Though further efforts are required in order to fill the gap between structured Bayesian models and more realistic, biophysical models of neuronal dynamics, we argue that generative neural networks have the potential to bridge these levels of analysis, thereby improving our understanding of the neural bases of cognition and of pathologies caused by brain damage.

  8. Optogenetics in Silicon: A Neural Processor for Predicting Optically Active Neural Networks.

    Science.gov (United States)

    Junwen Luo; Nikolic, Konstantin; Evans, Benjamin D; Na Dong; Xiaohan Sun; Andras, Peter; Yakovlev, Alex; Degenaar, Patrick

    2017-02-01

    We present a reconfigurable neural processor for real-time simulation and prediction of opto-neural behaviour. We combined a detailed Hodgkin-Huxley CA3 neuron integrated with a four-state Channelrhodopsin-2 (ChR2) model into reconfigurable silicon hardware. Our architecture consists of a Field Programmable Gated Array (FPGA) with a custom-built computing data-path, a separate data management system and a memory approach based router. Advancements over previous work include the incorporation of short and long-term calcium and light-dependent ion channels in reconfigurable hardware. Also, the developed processor is computationally efficient, requiring only 0.03 ms processing time per sub-frame for a single neuron and 9.7 ms for a fully connected network of 500 neurons with a given FPGA frequency of 56.7 MHz. It can therefore be utilized for exploration of closed loop processing and tuning of biologically realistic optogenetic circuitry.

  9. Neural activity during health messaging predicts reductions in smoking above and beyond self-report.

    Science.gov (United States)

    Falk, Emily B; Berkman, Elliot T; Whalen, Danielle; Lieberman, Matthew D

    2011-03-01

    The current study tested whether neural activity in response to messages designed to help smokers quit could predict smoking reduction, above and beyond self-report. Using neural activity in an a priori region of interest (a subregion of medial prefrontal cortex [MPFC]), in response to ads designed to help smokers quit smoking, we prospectively predicted reductions in smoking in a community sample of smokers (N = 28) who were attempting to quit smoking. Smoking was assessed via expired carbon monoxide (CO; a biological measure of recent smoking) at baseline and 1 month following exposure to professionally developed quitting ads. A positive relationship was observed between activity in the MPFC region of interest and successful quitting (increased activity in MPFC was associated with a greater decrease in expired CO). The addition of neural activity to a model predicting changes in CO from self-reported intentions, self-efficacy, and ability to relate to the messages significantly improved model fit, doubling the variance explained (R²self-report = .15, R²self-report + neural activity = .35, R²change = .20). Neural activity is a useful complement to existing self-report measures. In this investigation, we extend prior work predicting behavior change based on neural activity in response to persuasive media to an important health domain and discuss potential psychological interpretations of the brain-behavior link. Our results support a novel use of neuroimaging technology for understanding the psychology of behavior change and facilitating health promotion. (c) 2011 APA, all rights reserved

  10. Neural Activity Patterns in the Human Brain Reflect Tactile Stickiness Perception

    Science.gov (United States)

    Kim, Junsuk; Yeon, Jiwon; Ryu, Jaekyun; Park, Jang-Yeon; Chung, Soon-Cheol; Kim, Sung-Phil

    2017-01-01

    Our previous human fMRI study found brain activations correlated with tactile stickiness perception using the uni-variate general linear model (GLM) (Yeon et al., 2017). Here, we conducted an in-depth investigation on neural correlates of sticky sensations by employing a multivoxel pattern analysis (MVPA) on the same dataset. In particular, we statistically compared multi-variate neural activities in response to the three groups of sticky stimuli: A supra-threshold group including a set of sticky stimuli that evoked vivid sticky perception; an infra-threshold group including another set of sticky stimuli that barely evoked sticky perception; and a sham group including acrylic stimuli with no physically sticky property. Searchlight MVPAs were performed to search for local activity patterns carrying neural information of stickiness perception. Similar to the uni-variate GLM results, significant multi-variate neural activity patterns were identified in postcentral gyrus, subcortical (basal ganglia and thalamus), and insula areas (insula and adjacent areas). Moreover, MVPAs revealed that activity patterns in posterior parietal cortex discriminated the perceptual intensities of stickiness, which was not present in the uni-variate analysis. Next, we applied a principal component analysis (PCA) to the voxel response patterns within identified clusters so as to find low-dimensional neural representations of stickiness intensities. Follow-up clustering analyses clearly showed separate neural grouping configurations between the Supra- and Infra-threshold groups. Interestingly, this neural categorization was in line with the perceptual grouping pattern obtained from the psychophysical data. Our findings thus suggest that different stickiness intensities would elicit distinct neural activity patterns in the human brain and may provide a neural basis for the perception and categorization of tactile stickiness. PMID:28936171

  11. Generating passive NIR images from active LIDAR

    Science.gov (United States)

    Hagstrom, Shea; Broadwater, Joshua

    2016-05-01

    Many modern LIDAR platforms contain an integrated RGB camera for capturing contextual imagery. However, these RGB cameras do not collect a near-infrared (NIR) color channel, omitting information useful for many analytical purposes. This raises the question of whether LIDAR data, collected in the NIR, can be used as a substitute for an actual NIR image in this situation. Generating a LIDAR-based NIR image is potentially useful in situations where another source of NIR, such as satellite imagery, is not available. LIDAR is an active sensing system that operates very differently from a passive system, and thus requires additional processing and calibration to approximate the output of a passive instrument. We examine methods of approximating passive NIR images from LIDAR for real-world datasets, and assess differences with true NIR images.

  12. Anisotropy of ongoing neural activity in the primate visual cortex

    Directory of Open Access Journals (Sweden)

    Maier A

    2014-09-01

    Full Text Available Alexander Maier,1 Michele A Cox,1 Kacie Dougherty,1 Brandon Moore,1 David A Leopold2 1Department of Psychology, College of Arts and Science, Vanderbilt University, Nashville, TN, USA; 2Section on Cognitive Neurophysiology and Imaging, National Institute of Mental Health, National Institute of Health, Bethesda, MD, USA Abstract: The mammalian neocortex features distinct anatomical variation in its tangential and radial extents. This review consolidates previously published findings from our group in order to compare and contrast the spatial profile of neural activity coherence across these distinct cortical dimensions. We focus on studies of ongoing local field potential (LFP data obtained simultaneously from multiple sites in the primary visual cortex in two types of experiments in which electrode contacts were spaced either along the cortical surface or at different laminar positions. These studies demonstrate that across both dimensions the coherence of ongoing LFP fluctuations diminishes as a function of interelectrode distance, although the nature and spatial scale of this falloff is very different. Along the cortical surface, the overall LFP coherence declines gradually and continuously away from a given position. In contrast, across the cortical layers, LFP coherence is discontinuous and compartmentalized as a function of depth. Specifically, regions of high LFP coherence fall into discrete superficial and deep laminar zones, with an abrupt discontinuity between the granular and infragranular layers. This spatial pattern of ongoing LFP coherence is similar when animals are at rest and when they are engaged in a behavioral task. These results point to the existence of partially segregated laminar zones of cortical processing that extend tangentially within the laminar compartments and are thus oriented orthogonal to the cortical columns. We interpret these electrophysiological observations in light of the known anatomical organization of

  13. Electromagnetic fields induce neural differentiation of human bone marrow derived mesenchymal stem cells via ROS mediated EGFR activation.

    Science.gov (United States)

    Park, Jeong-Eun; Seo, Young-Kwon; Yoon, Hee-Hoon; Kim, Chan-Wha; Park, Jung-Keug; Jeon, Songhee

    2013-03-01

    Even though the inducing effect of electromagnetic fields (EMF) on the neural differentiation of human bone marrow mesenchymal stem cells (hBM-MSCs) is a distinctive, the underlying mechanism of differentiation remains unclear. To find out the signaling pathways involved in the neural differentiation of BM-MSCs by EMF, we examined the CREB phosphorylation and Akt or ERK activation as an upstream of CREB. In hBM-MSCs treated with ELF-EMF (50 Hz, 1 mT), the expression of neural markers such as NF-L, MAP2, and NeuroD1 increased at 6 days and phosphorylation of Akt and CREB but not ERK increased at 90 min in BM-MSCs. Moreover, EMF increased phosphorylation of epidermal growth factor receptor (EGFR) as an upstream receptor tyrosine kinase of PI3K/Akt at 90 min. It has been well documented that ELF-MF exposure may alter cellular processes by increasing intracellular reactive oxygen species (ROS) concentrations. Thus, we examined EMF-induced ROS production in BM-MSCs. Moreover, pretreatment with a ROS scavenger, N-acetylcystein, and an EGFR inhibitor, AG-1478, prevented the phosphorylation of EGFR and downstream molecules. These results suggest that EMF induce neural differentiation through activation of EGFR signaling and mild generation of ROS. Copyright © 2013 Elsevier Ltd. All rights reserved.

  14. Self-organization of spiking neural network that generates autonomous behavior in a real mobile robot.

    Science.gov (United States)

    Alnajjar, Fady; Murase, Kazuyuki

    2006-08-01

    In this paper, we propose self-organization algorithm of spiking neural network (SNN) applicable to autonomous robot for generation of adoptive and goal-directed behavior. First, we formulated a SNN model whose inputs and outputs were analog and the hidden unites are interconnected each other. Next, we implemented it into a miniature mobile robot Khepera. In order to see whether or not a solution(s) for the given task(s) exists with the SNN, the robot was evolved with the genetic algorithm in the environment. The robot acquired the obstacle avoidance and navigation task successfully, exhibiting the presence of the solution. After that, a self-organization algorithm based on a use-dependent synaptic potentiation and depotentiation at synapses of input layer to hidden layer and of hidden layer to output layer was formulated and implemented into the robot. In the environment, the robot incrementally organized the network and the given tasks were successfully performed. The time needed to acquire the desired adoptive and goal-directed behavior using the proposed self-organization method was much less than that with the genetic evolution, approximately one fifth.

  15. Beyond GLMs: a generative mixture modeling approach to neural system identification.

    Directory of Open Access Journals (Sweden)

    Lucas Theis

    Full Text Available Generalized linear models (GLMs represent a popular choice for the probabilistic characterization of neural spike responses. While GLMs are attractive for their computational tractability, they also impose strong assumptions and thus only allow for a limited range of stimulus-response relationships to be discovered. Alternative approaches exist that make only very weak assumptions but scale poorly to high-dimensional stimulus spaces. Here we seek an approach which can gracefully interpolate between the two extremes. We extend two frequently used special cases of the GLM-a linear and a quadratic model-by assuming that the spike-triggered and non-spike-triggered distributions can be adequately represented using Gaussian mixtures. Because we derive the model from a generative perspective, its components are easy to interpret as they correspond to, for example, the spike-triggered distribution and the interspike interval distribution. The model is able to capture complex dependencies on high-dimensional stimuli with far fewer parameters than other approaches such as histogram-based methods. The added flexibility comes at the cost of a non-concave log-likelihood. We show that in practice this does not have to be an issue and the mixture-based model is able to outperform generalized linear and quadratic models.

  16. Generation of Integration-free and Region-Specific Neural Progenitors from Primate Fibroblasts

    Directory of Open Access Journals (Sweden)

    Jianfeng Lu

    2013-05-01

    Full Text Available Postnatal and adult human and monkey fibroblasts were infected with Sendai virus containing the Yamanaka factors for 24 hr, then they were cultured in a chemically defined medium containing leukemia inhibitory factor (LIF, transforming growth factor (TGF-β inhibitor SB431542, and glycogen synthase kinase (GSK-3β inhibitor CHIR99021 at 39°C for inactivation of the virus. Induced neural progenitor (iNP colonies appeared as early as day 13 and can be expanded for >20 passages. Under the same defined condition, no induced pluripotent stem cell (iPSC colonies formed at either 37°C or 39°C. The iNPs predominantly express hindbrain genes and differentiate into hindbrain neurons, and when caudalized, they produced an enriched population of spinal motor neurons. Following transplantation into the forebrain, the iNP-derived cells retained the hindbrain identity. The ability to generate defined, integration-free iNPs from adult primate fibroblasts under a defined condition with predictable fate choices will facilitate disease modeling and therapeutic development.

  17. Generation of Human Induced Pluripotent Stem Cell‐Derived Bona Fide Neural Stem Cells for Ex Vivo Gene Therapy of Metachromatic Leukodystrophy

    Science.gov (United States)

    Meneghini, Vasco; Sala, Davide; De Cicco, Silvia; Luciani, Marco; Cavazzin, Chiara; Paulis, Marianna; Mentzen, Wieslawa; Morena, Francesco; Giannelli, Serena; Sanvito, Francesca; Villa, Anna; Bulfone, Alessandro; Broccoli, Vania; Martino, Sabata

    2016-01-01

    Abstract Allogeneic fetal‐derived human neural stem cells (hfNSCs) that are under clinical evaluation for several neurodegenerative diseases display a favorable safety profile, but require immunosuppression upon transplantation in patients. Neural progenitors derived from patient‐specific induced pluripotent stem cells (iPSCs) may be relevant for autologous ex vivo gene‐therapy applications to treat genetic diseases with unmet medical need. In this scenario, obtaining iPSC‐derived neural stem cells (NSCs) showing a reliable “NSC signature” is mandatory. Here, we generated human iPSC (hiPSC) clones via reprogramming of skin fibroblasts derived from normal donors and patients affected by metachromatic leukodystrophy (MLD), a fatal neurodegenerative lysosomal storage disease caused by genetic defects of the arylsulfatase A (ARSA) enzyme. We differentiated hiPSCs into NSCs (hiPS‐NSCs) sharing molecular, phenotypic, and functional identity with hfNSCs, which we used as a “gold standard” in a side‐by‐side comparison when validating the phenotype of hiPS‐NSCs and predicting their performance after intracerebral transplantation. Using lentiviral vectors, we efficiently transduced MLD hiPSCs, achieving supraphysiological ARSA activity that further increased upon neural differentiation. Intracerebral transplantation of hiPS‐NSCs into neonatal and adult immunodeficient MLD mice stably restored ARSA activity in the whole central nervous system. Importantly, we observed a significant decrease of sulfatide storage when ARSA‐overexpressing cells were used, with a clear advantage in those mice receiving neonatal as compared with adult intervention. Thus, we generated a renewable source of ARSA‐overexpressing iPSC‐derived bona fide hNSCs with improved features compared with clinically approved hfNSCs. Patient‐specific ARSA‐overexpressing hiPS‐NSCs may be used in autologous ex vivo gene therapy protocols to provide long‐lasting enzymatic

  18. P01.22GENERATION OF GENETICALLY ENGINEERED INDUCED PLURIPOTENT STEM CELL-DERIVED NEURAL STEM CELLS WITHOUT USING VIRAL VECTORS

    Science.gov (United States)

    Yamasaki, T.; Kawaji, H.; Kamio, Y.; Amano, S.; Sameshima, T.; Sakai, N.; Tokuyama, T.; Namba, H.

    2014-01-01

    Suicide gene therapy using genetically engineered stem cells are is one of the most feasible and promising approaches for glioma therapy. Various stem cells, such as neural and mesenchymal stem cells, have been tested for their tumor tropic activity. We have tested stem cells transduced with the herpes simplex virus-thymidine kinase gene (HSV-TK, suicide gene) encoding a viral thymidine kinase which phosphorylates prodrug ganciclovir (GCV) for experimental glioma in rodents, because the HSV-TK/GCV system generates a potent bystander effect. Recently we found that induced pluripotent stem cells (iPSs) also had tumor tropic activity under both in vitro and in vivo conditions. One of the major limitations of use of HSV-TK gene-trasnduced iPSs in clinical field is the use of virus vectors that randomly integrate into the host genome and are associated with the risk of malignant transformation due to insertional mutagenesis. In the present study, we present a non-viral transfection method for obtaining HSV-TK expressing iPS-derived neural stem cells to circumvent the concerns associated with use of viral vectors. Mouse iPS cells were generated from somatic cells by the plasmid vectors expressing Oct4, Sox2, Klf4, c-Myc and Nanog-GFP-IRES-Puror. We differentiated the mouse iPS cells into neural stem cells and then transfected with the plasmid containing HSV-TK gene using electroporation method. In this way, we obtained HSV-TK gene-trasnduced iPSs-derived neural stem cells without using viral vectors for further pre-clinical expariments of glioma therapy.

  19. Parasympathetic neural activity accounts for the lowering of exercise heart rate at high altitude

    DEFF Research Database (Denmark)

    Boushel, Robert Christopher; Calbet, J A; Rådegran, G

    2001-01-01

    In chronic hypoxia, both heart rate (HR) and cardiac output (Q) are reduced during exercise. The role of parasympathetic neural activity in lowering HR is unresolved, and its influence on Q and oxygen transport at high altitude has never been studied.......In chronic hypoxia, both heart rate (HR) and cardiac output (Q) are reduced during exercise. The role of parasympathetic neural activity in lowering HR is unresolved, and its influence on Q and oxygen transport at high altitude has never been studied....

  20. Attenuation of β-Amyloid Deposition and Neurotoxicity by Chemogenetic Modulation of Neural Activity.

    Science.gov (United States)

    Yuan, Peng; Grutzendler, Jaime

    2016-01-13

    Aberrant neural hyperactivity has been observed in early stages of Alzheimer's disease (AD) and may be a driving force in the progression of amyloid pathology. Evidence for this includes the findings that neural activity may modulate β-amyloid (Aβ) peptide secretion and experimental stimulation of neural activity can increase amyloid deposition. However, whether long-term attenuation of neural activity prevents the buildup of amyloid plaques and associated neural pathologies remains unknown. Using viral-mediated delivery of designer receptors exclusively activated by designer drugs (DREADDs), we show in two AD-like mouse models that chronic intermittent increases or reductions of activity have opposite effects on Aβ deposition. Neural activity reduction markedly decreases Aβ aggregation in regions containing axons or dendrites of DREADD-expressing neurons, suggesting the involvement of synaptic and nonsynaptic Aβ release mechanisms. Importantly, activity attenuation is associated with a reduction in axonal dystrophy and synaptic loss around amyloid plaques. Thus, modulation of neural activity could constitute a potential therapeutic strategy for ameliorating amyloid-induced pathology in AD. A novel chemogenetic approach to upregulate and downregulate neuronal activity in Alzheimer's disease (AD) mice was implemented. This led to the first demonstration that chronic intermittent attenuation of neuronal activity in vivo significantly reduces amyloid deposition. The study also demonstrates that modulation of β-amyloid (Aβ) release can occur at both axonal and dendritic fields, suggesting the involvement of synaptic and nonsynaptic Aβ release mechanisms. Activity reductions also led to attenuation of the synaptic pathology associated with amyloid plaques. Therefore, chronic attenuation of neuronal activity could constitute a novel therapeutic approach for AD. Copyright © 2016 the authors 0270-6474/16/360632-10$15.00/0.

  1. To compare the effect of Active Neural Mobilization during Intermittent Lumbar Traction and Intermittent Lumbar Traction followed by Active Neural Mobilization in cases of Lumbar Radiculopathy

    Directory of Open Access Journals (Sweden)

    Jaywant Nagulkar

    2016-08-01

    Full Text Available To compare the effectiveness of Active neural mobilization (ANM during intermittent lumbar traction (ILT and intermittent lumbar traction followed by active neural mobilization treatment in patients of low back pain (LBP with radiculopathy.. To study the effect of ANM during ILT and ILT followed by ANM in patients of LBP with radiculopathy on VAS scale, P1 angle of SLR, P2 angle of SLR and Oswestry disability index(ODI. To compare the effect of ANM during ILT and ILT followed by ANM in patients of LBP with radiculopathy on visual analog scale (VAS scale, P1 angle of SLR, P2 angle of SLR and Oswestry disability index. In this study 107 patients of LBP with radiculopathy were randomly assigned into two different groups. Group A containing 54 patients received active neural mobilization during intermittent lumber traction and group B received intermittent lumber traction followed by active neural mobilization. The data on all the outcome measures were recorded on day 0 pre-treatment and on 10th day post treatment. Data were analyzed using statistical software Intercorted STATA VERSION 9.0. Patients in both the groups showed improvement in all 4 outcome measures as compared to baseline assessment values. Patients treated in group A showed more improvement as compared to group B. This study concluded that ANM during ILT gives more relief and yields better responses in patients of LBP with radiculopathy and may help person to resume his daily activities.

  2. MR-based synthetic CT generation using a deep convolutional neural network method.

    Science.gov (United States)

    Han, Xiao

    2017-04-01

    Interests have been rapidly growing in the field of radiotherapy to replace CT with magnetic resonance imaging (MRI), due to superior soft tissue contrast offered by MRI and the desire to reduce unnecessary radiation dose. MR-only radiotherapy also simplifies clinical workflow and avoids uncertainties in aligning MR with CT. Methods, however, are needed to derive CT-equivalent representations, often known as synthetic CT (sCT), from patient MR images for dose calculation and DRR-based patient positioning. Synthetic CT estimation is also important for PET attenuation correction in hybrid PET-MR systems. We propose in this work a novel deep convolutional neural network (DCNN) method for sCT generation and evaluate its performance on a set of brain tumor patient images. The proposed method builds upon recent developments of deep learning and convolutional neural networks in the computer vision literature. The proposed DCNN model has 27 convolutional layers interleaved with pooling and unpooling layers and 35 million free parameters, which can be trained to learn a direct end-to-end mapping from MR images to their corresponding CTs. Training such a large model on our limited data is made possible through the principle of transfer learning and by initializing model weights from a pretrained model. Eighteen brain tumor patients with both CT and T1-weighted MR images are used as experimental data and a sixfold cross-validation study is performed. Each sCT generated is compared against the real CT image of the same patient on a voxel-by-voxel basis. Comparison is also made with respect to an atlas-based approach that involves deformable atlas registration and patch-based atlas fusion. The proposed DCNN method produced a mean absolute error (MAE) below 85 HU for 13 of the 18 test subjects. The overall average MAE was 84.8 ± 17.3 HU for all subjects, which was found to be significantly better than the average MAE of 94.5 ± 17.8 HU for the atlas-based method. The DCNN

  3. Bayesian Inference for Neural Electromagnetic Source Localization: Analysis of MEG Visual Evoked Activity

    Energy Technology Data Exchange (ETDEWEB)

    George, J.S.; Schmidt, D.M.; Wood, C.C.

    1999-02-01

    We have developed a Bayesian approach to the analysis of neural electromagnetic (MEG/EEG) data that can incorporate or fuse information from other imaging modalities and addresses the ill-posed inverse problem by sarnpliig the many different solutions which could have produced the given data. From these samples one can draw probabilistic inferences about regions of activation. Our source model assumes a variable number of variable size cortical regions of stimulus-correlated activity. An active region consists of locations on the cortical surf ace, within a sphere centered on some location in cortex. The number and radi of active regions can vary to defined maximum values. The goal of the analysis is to determine the posterior probability distribution for the set of parameters that govern the number, location, and extent of active regions. Markov Chain Monte Carlo is used to generate a large sample of sets of parameters distributed according to the posterior distribution. This sample is representative of the many different source distributions that could account for given data, and allows identification of probable (i.e. consistent) features across solutions. Examples of the use of this analysis technique with both simulated and empirical MEG data are presented.

  4. Task-dependent modulation of oscillatory neural activity during movements

    DEFF Research Database (Denmark)

    Herz, D. M.; Christensen, M. S.; Reck, C.

    2011-01-01

    -dependent modulation of frequency coupling within this network. To this end we recorded 122-multichannel EEG in 13 healthy subjects while they performed three simple motor tasks. EEG data source modeling using individual MR images was carried out with a multiple source beamformer approach. A bilateral motor network...... for inferring on architecture and coupling parameters of neural networks....

  5. Voltage Estimation in Active Distribution Grids Using Neural Networks

    DEFF Research Database (Denmark)

    Pertl, Michael; Heussen, Kai; Gehrke, Oliver

    2016-01-01

    the observability of distribution systems has to be improved. To increase the situational awareness of the power system operator data driven methods can be employed. These methods benefit from newly available data sources such as smart meters. This paper presents a voltage estimation method based on neural networks...

  6. Amniotic fluid paraoxonase-1 activity, thyroid hormone concentration and oxidant status in neural tube defects.

    Science.gov (United States)

    Sak, Sibel; Agacayak, Elif; Tunc, Senem Yaman; Icen, Mehmet Sait; Findik, Fatih Mehmet; Sak, Muhammet Erdal; Yalinkaya, Ahmet; Gul, Talip

    2016-09-01

    The aim of this study was to investigate the potential association between neural tube defects and paraoxonase-1 activity in amniotic fluid. We studied total oxidant status, total antioxidant capacity, paraoxonase-1 activity and thyroid hormone amniotic fluid concentration in fetuses with neural tube defects. The present study was performed at the Department of Obstetrics and Gynaecology and the Department of Clinical Biochemistry of Dicle University between September 2011 and June 2013. The study group included 37 amniotic fluid samples from pregnant women (16-20 weeks of gestation) with fetuses affected by neural tube defects. The control group consisted of 36 pregnant women who were diagnosed with a high-risk pregnancy according to first or second trimester aneuploidy screening and were later confirmed on amniocentesis to have genetically normal fetuses. Amniotic fluid paraoxonase-1 activity and total oxidant status were significantly higher (P = 0.023, P = 0.029, respectively) whereas free T4 was significantly lower (P = 0.022) in fetuses with neural tube defects compared with control subjects. In fetuses with neural tube defects, amniotic fluid paraoxonase-1 activity correlated positively with total oxidant status (r = 0.424**, P = 0.010), and amniotic fluid total antioxidant capacity correlated positively with free t4 (r = 0.381*, P = 0.022). This is the first study in the literature to show an association between paraoxonase-1 activity and thyroid hormone concentration and neural tube defects. © 2016 Japan Society of Obstetrics and Gynecology.

  7. High baseline activity in inferior temporal cortex improves neural and behavioral discriminability during visual categorization

    Directory of Open Access Journals (Sweden)

    Nazli eEmadi

    2014-11-01

    Full Text Available Spontaneous firing is a ubiquitous property of neural activity in the brain. Recent literature suggests that this baseline activity plays a key role in perception. However, it is not known how the baseline activity contributes to neural coding and behavior. Here, by recording from the single neurons in the inferior temporal cortex of monkeys performing a visual categorization task, we thoroughly explored the relationship between baseline activity, the evoked response, and behavior. Specifically we found that a low-frequency (< 8 Hz oscillation in the spike train, prior and phase-locked to the stimulus onset, was correlated with increased gamma power and neuronal baseline activity. This enhancement of the baseline activity was then followed by an increase in the neural selectivity and the response reliability and eventually a higher behavioral performance.

  8. Rapid adaptive remote focusing microscope for sensing of volumetric neural activity.

    Science.gov (United States)

    Žurauskas, Mantas; Barnstedt, Oliver; Frade-Rodriguez, Maria; Waddell, Scott; Booth, Martin J

    2017-10-01

    The ability to record neural activity in the brain of a living organism at cellular resolution is of great importance for defining the neural circuit mechanisms that direct behavior. Here we present an adaptive two-photon microscope optimized for extraction of neural signals over volumes in intact Drosophila brains, even in the presence of specimen motion. High speed volume imaging was made possible through reduction of spatial resolution while maintaining the light collection efficiency of a high resolution, high numerical aperture microscope. This enabled simultaneous recording of odor-evoked calcium transients in a defined volume of mushroom body Kenyon cell bodies in a live fruit fly.

  9. Micro- and Nanotechnologies for Optical Neural Interfaces

    Science.gov (United States)

    Pisanello, Ferruccio; Sileo, Leonardo; De Vittorio, Massimo

    2016-01-01

    In last decade, the possibility to optically interface with the mammalian brain in vivo has allowed unprecedented investigation of functional connectivity of neural circuitry. Together with new genetic and molecular techniques to optically trigger and monitor neural activity, a new generation of optical neural interfaces is being developed, mainly thanks to the exploitation of both bottom-up and top-down nanofabrication approaches. This review highlights the role of nanotechnologies for optical neural interfaces, with particular emphasis on new devices and methodologies for optogenetic control of neural activity and unconventional methods for detection and triggering of action potentials using optically-active colloidal nanoparticles. PMID:27013939

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

    Directory of Open Access Journals (Sweden)

    Rendong Tang

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

  11. 5-Azacytidine and BDNF enhance the maturation of neurons derived from EGF-generated neural stem cells.

    Science.gov (United States)

    Schinstine, M; Iacovitti, L

    1997-04-01

    EGF-generated neural stem cells can form astrocytes, neurons, and oligodendrocytes upon differentiation; however, the proportion of cells that actually form neurons is very small. In the present study, we have studied the effect that 5-azacytidine (5AzaC), a demethylation agent, and brain-derived growth factor (BDNF) have on the differentiation and maturation of neurons originating from EGF-generated neural stem cells. Stem cells were maintained under a variety of culture conditions using combinations of 5AzaC and BDNF either alone or together. More neurons, as determined by the number of beta-tubulin III-immunoreactive somata, were present in cultures maintained in BDNF medium (a nearly fourfold increase compared to control cultures). 5AzaC did not significantly affect neuronal number, regardless of the presence of BDNF. In addition to neuronal number, the effect of 5AzaC and BDNF on the distribution of the microtubule proteins MAP2 and Tau was analyzed. In most cultures, MAP2 and Tau were colocalized throughout the neuron. In contrast, neurons cotreated with 5AzaC and BDNF contained neurons that began to exhibit cytoskeletal segregation of MAP2 into the somatodendritic compartments. Tau remained dispersed within the somata and the axon. This effect was not produced when 5AzaC or BDNF was used individually. These results demonstrate that 5AzaC and BDNF cooperate to produce more mature neurons from EGF-generated neural stem cells then either molecule can alone.

  12. Active Vibration Control of the Smart Plate Using Artificial Neural Network Controller

    Directory of Open Access Journals (Sweden)

    Mohit

    2015-01-01

    Full Text Available The active vibration control (AVC of a rectangular plate with single input and single output approach is investigated using artificial neural network. The cantilever plate of finite length, breadth, and thickness having piezoelectric patches as sensors/actuators fixed at the upper and lower surface of the metal plate is considered for examination. The finite element model of the cantilever plate is utilized to formulate the whole strategy. The compact RIO and MATLAB simulation software are exercised to get the appropriate results. The cantilever plate is subjected to impulse input and uniform white noise disturbance. The neural network is trained offline and tuned with LQR controller. The various training algorithms to tune the neural network are exercised. The best efficient algorithm is finally considered to tune the neural network controller designed for active vibration control of the smart plate.

  13. Analysis of electromyographic activity in spastic biceps brachii muscle following neural mobilization.

    Science.gov (United States)

    Castilho, Jéssica; Ferreira, Luiz Alfredo Braun; Pereira, Wagner Menna; Neto, Hugo Pasini; Morelli, José Geraldo da Silva; Brandalize, Danielle; Kerppers, Ivo Ilvan; Oliveira, Claudia Santos

    2012-07-01

    Hypertonia is prevalent in anti-gravity muscles, such as the biceps brachii. Neural mobilization is one of the techniques currently used to reduce spasticity. The aim of the present study was to assess electromyographic (EMG) activity in spastic biceps brachii muscles before and after neural mobilization of the upper limb contralateral to the hemiplegia. Repeated pre-test and post-test EMG measurements were performed on six stroke victims with grade 1 or 2 spasticity (Modified Ashworth Scale). The Upper Limb Neurodynamic Test (ULNT1) was the mobilization technique employed. After neural mobilization contralateral to the lesion, electromyographic activity in the biceps brachii decreased by 17% and 11% for 90° flexion and complete extension of the elbow, respectively. However, the results were not statistically significant (p gt; 0.05). When performed using contralateral techniques, neural mobilization alters the electrical signal of spastic muscles. Copyright © 2011 Elsevier Ltd. All rights reserved.

  14. On the relationships between generative encodings, regularity, and learning abilities when evolving plastic artificial neural networks.

    Directory of Open Access Journals (Sweden)

    Paul Tonelli

    Full Text Available A major goal of bio-inspired artificial intelligence is to design artificial neural networks with abilities that resemble those of animal nervous systems. It is commonly believed that two keys for evolving nature-like artificial neural networks are (1 the developmental process that links genes to nervous systems, which enables the evolution of large, regular neural networks, and (2 synaptic plasticity, which allows neural networks to change during their lifetime. So far, these two topics have been mainly studied separately. The present paper shows that they are actually deeply connected. Using a simple operant conditioning task and a classic evolutionary algorithm, we compare three ways to encode plastic neural networks: a direct encoding, a developmental encoding inspired by computational neuroscience models, and a developmental encoding inspired by morphogen gradients (similar to HyperNEAT. Our results suggest that using a developmental encoding could improve the learning abilities of evolved, plastic neural networks. Complementary experiments reveal that this result is likely the consequence of the bias of developmental encodings towards regular structures: (1 in our experimental setup, encodings that tend to produce more regular networks yield networks with better general learning abilities; (2 whatever the encoding is, networks that are the more regular are statistically those that have the best learning abilities.

  15. Differentiation of neurons from neural precursors generated in floating spheres from embryonic stem cells

    Directory of Open Access Journals (Sweden)

    Forrester Jeff

    2009-09-01

    Full Text Available Abstract Background Neural differentiation of embryonic stem (ES cells is usually achieved by induction of ectoderm in embryoid bodies followed by the enrichment of neuronal progenitors using a variety of factors. Obtaining reproducible percentages of neural cells is difficult and the methods are time consuming. Results Neural progenitors were produced from murine ES cells by a combination of nonadherent conditions and serum starvation. Conversion to neural progenitors was accompanied by downregulation of Oct4 and NANOG and increased expression of nestin. ES cells containing a GFP gene under the control of the Sox1 regulatory regions became fluorescent upon differentiation to neural progenitors, and ES cells with a tau-GFP fusion protein became fluorescent upon further differentiation to neurons. Neurons produced from these cells upregulated mature neuronal markers, or differentiated to glial and oligodendrocyte fates. The neurons gave rise to action potentials that could be recorded after application of fixed currents. Conclusion Neural progenitors were produced from murine ES cells by a novel method that induced neuroectoderm cells by a combination of nonadherent conditions and serum starvation, in contrast to the embryoid body method in which neuroectoderm cells must be selected after formation of all three germ layers.

  16. On the relationships between generative encodings, regularity, and learning abilities when evolving plastic artificial neural networks.

    Science.gov (United States)

    Tonelli, Paul; Mouret, Jean-Baptiste

    2013-01-01

    A major goal of bio-inspired artificial intelligence is to design artificial neural networks with abilities that resemble those of animal nervous systems. It is commonly believed that two keys for evolving nature-like artificial neural networks are (1) the developmental process that links genes to nervous systems, which enables the evolution of large, regular neural networks, and (2) synaptic plasticity, which allows neural networks to change during their lifetime. So far, these two topics have been mainly studied separately. The present paper shows that they are actually deeply connected. Using a simple operant conditioning task and a classic evolutionary algorithm, we compare three ways to encode plastic neural networks: a direct encoding, a developmental encoding inspired by computational neuroscience models, and a developmental encoding inspired by morphogen gradients (similar to HyperNEAT). Our results suggest that using a developmental encoding could improve the learning abilities of evolved, plastic neural networks. Complementary experiments reveal that this result is likely the consequence of the bias of developmental encodings towards regular structures: (1) in our experimental setup, encodings that tend to produce more regular networks yield networks with better general learning abilities; (2) whatever the encoding is, networks that are the more regular are statistically those that have the best learning abilities.

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

    Directory of Open Access Journals (Sweden)

    Christopher John Goldsmith

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

  18. Parametric characterization of neural activity in the locus coeruleus in response to vagus nerve stimulation.

    Science.gov (United States)

    Hulsey, Daniel R; Riley, Jonathan R; Loerwald, Kristofer W; Rennaker, Robert L; Kilgard, Michael P; Hays, Seth A

    2017-03-01

    Vagus nerve stimulation (VNS) has emerged as a therapy to treat a wide range of neurological disorders, including epilepsy, depression, stroke, and tinnitus. Activation of neurons in the locus coeruleus (LC) is believed to mediate many of the effects of VNS in the central nervous system. Despite the importance of the LC, there is a dearth of direct evidence characterizing neural activity in response to VNS. A detailed understanding of the brain activity evoked by VNS across a range of stimulation parameters may guide selection of stimulation regimens for therapeutic use. In this study, we recorded neural activity in the LC and the mesencephalic trigeminal nucleus (Me5) in response to VNS over a broad range of current amplitudes, pulse frequencies, train durations, inter-train intervals, and pulse widths. Brief 0.5s trains of VNS drive rapid, phasic firing of LC neurons at 0.1mA. Higher current intensities and longer pulse widths drive greater increases in LC firing rate. Varying the pulse frequency substantially affects the timing, but not the total amount, of phasic LC activity. VNS drives pulse-locked neural activity in the Me5 at current levels above 1.2mA. These results provide insight into VNS-evoked phasic neural activity in multiple neural structures and may be useful in guiding the selection of VNS parameters to enhance clinical efficacy. Copyright © 2016 Elsevier Inc. All rights reserved.

  19. Optimizing for generalization in the decoding of internally generated activity in the hippocampus.

    Science.gov (United States)

    van der Meer, Matthijs A A; Carey, Alyssa A; Tanaka, Youki

    2017-05-01

    The decoding of a sensory or motor variable from neural activity benefits from a known ground truth against which decoding performance can be compared. In contrast, the decoding of covert, cognitive neural activity, such as occurs in memory recall or planning, typically cannot be compared to a known ground truth. As a result, it is unclear how decoders of such internally generated activity should be configured in practice. We suggest that if the true code for covert activity is unknown, decoders should be optimized for generalization performance using cross-validation. Using ensemble recording data from hippocampal place cells, we show that this cross-validation approach results in different decoding error, different optimal decoding parameters, and different distributions of error across the decoded variable space. In addition, we show that a minor modification to the commonly used Bayesian decoding procedure, which enables the use of spike density functions, results in substantially lower decoding errors. These results have implications for the interpretation of covert neural activity, and suggest easy-to-implement changes to commonly used procedures across domains, with applications to hippocampal place cells in particular. © 2017 Wiley Periodicals, Inc. © 2017 Wiley Periodicals, Inc.

  20. Photovoltaic generator. Estimate of the energy produced by neural networks; Generador fotovoltaico. Estimacion de la energia producida mediante redes neuronales

    Energy Technology Data Exchange (ETDEWEB)

    Almonacid, F.; Rus, C.; Perez-Higueras, P.; Hontoria, L.

    2010-07-01

    Despite the great technological advances in photovoltaic and in particular in network-connected systems, efforts are still required in research, technological development and innovation (i + d + i) must be aimed primarily at addressing the different system parts. one aspect that can help achieve this goal is majorette estimation methods of energy produced by photovoltaic generators. There are a number of cases resulting in a decrease of the expected energy. In this paper we will compare a standard method widely used in the estimation of the power of the photovoltaic generator with another novel method, developed at the University of Jaen, based on artificial neural networks (ANN). (Author) 9 refs.

  1. Demystifying Multitask Deep Neural Networks for Quantitative Structure-Activity Relationships.

    Science.gov (United States)

    Xu, Yuting; Ma, Junshui; Liaw, Andy; Sheridan, Robert P; Svetnik, Vladimir

    2017-10-23

    Deep neural networks (DNNs) are complex computational models that have found great success in many artificial intelligence applications, such as computer vision1,2 and natural language processing.3,4 In the past four years, DNNs have also generated promising results for quantitative structure-activity relationship (QSAR) tasks.5,6 Previous work showed that DNNs can routinely make better predictions than traditional methods, such as random forests, on a diverse collection of QSAR data sets. It was also found that multitask DNN models-those trained on and predicting multiple QSAR properties simultaneously-outperform DNNs trained separately on the individual data sets in many, but not all, tasks. To date there has been no satisfactory explanation of why the QSAR of one task embedded in a multitask DNN can borrow information from other unrelated QSAR tasks. Thus, using multitask DNNs in a way that consistently provides a predictive advantage becomes a challenge. In this work, we explored why multitask DNNs make a difference in predictive performance. Our results show that during prediction a multitask DNN does borrow "signal" from molecules with similar structures in the training sets of the other tasks. However, whether this borrowing leads to better or worse predictive performance depends on whether the activities are correlated. On the basis of this, we have developed a strategy to use multitask DNNs that incorporate prior domain knowledge to select training sets with correlated activities, and we demonstrate its effectiveness on several examples.

  2. Neural Activations of Guided Imagery and Music in Negative Emotional Processing: A Functional MRI Study.

    Science.gov (United States)

    Lee, Sang Eun; Han, Yeji; Park, HyunWook

    2016-01-01

    The Bonny Method of Guided Imagery and Music uses music and imagery to access and explore personal emotions associated with episodic memories. Understanding the neural mechanism of guided imagery and music (GIM) as combined stimuli for emotional processing informs clinical application. We performed functional magnetic resonance imaging (fMRI) to demonstrate neural mechanisms of GIM for negative emotional processing when personal episodic memory is recalled and re-experienced through GIM processes. Twenty-four healthy volunteers participated in the study, which used classical music and verbal instruction stimuli to evoke negative emotions. To analyze the neural mechanism, activated regions associated with negative emotional and episodic memory processing were extracted by conducting volume analyses for the contrast between GIM and guided imagery (GI) or music (M). The GIM stimuli showed increased activation over the M-only stimuli in five neural regions associated with negative emotional and episodic memory processing, including the left amygdala, left anterior cingulate gyrus, left insula, bilateral culmen, and left angular gyrus (AG). Compared with GI alone, GIM showed increased activation in three regions associated with episodic memory processing in the emotional context, including the right posterior cingulate gyrus, bilateral parahippocampal gyrus, and AG. No neural regions related to negative emotional and episodic memory processing showed more activation for M and GI than for GIM. As a combined multimodal stimulus, GIM may increase neural activations related to negative emotions and episodic memory processing. Findings suggest a neural basis for GIM with personal episodic memories affecting cortical and subcortical structures and functions. © the American Music Therapy Association 2016. All rights reserved. For permissions, please e-mail: journals.permissions@oup.com.

  3. Isolating Discriminant Neural Activity in the Presence of Eye Movements and Concurrent Task Demands

    Directory of Open Access Journals (Sweden)

    Jon Touryan

    2017-07-01

    Full Text Available A growing number of studies use the combination of eye-tracking and electroencephalographic (EEG measures to explore the neural processes that underlie visual perception. In these studies, fixation-related potentials (FRPs are commonly used to quantify early and late stages of visual processing that follow the onset of each fixation. However, FRPs reflect a mixture of bottom-up (sensory-driven and top-down (goal-directed processes, in addition to eye movement artifacts and unrelated neural activity. At present there is little consensus on how to separate this evoked response into its constituent elements. In this study we sought to isolate the neural sources of target detection in the presence of eye movements and over a range of concurrent task demands. Here, participants were asked to identify visual targets (Ts amongst a grid of distractor stimuli (Ls, while simultaneously performing an auditory N-back task. To identify the discriminant activity, we used independent components analysis (ICA for the separation of EEG into neural and non-neural sources. We then further separated the neural sources, using a modified measure-projection approach, into six regions of interest (ROIs: occipital, fusiform, temporal, parietal, cingulate, and frontal cortices. Using activity from these ROIs, we identified target from non-target fixations in all participants at a level similar to other state-of-the-art classification techniques. Importantly, we isolated the time course and spectral features of this discriminant activity in each ROI. In addition, we were able to quantify the effect of cognitive load on both fixation-locked potential and classification performance across regions. Together, our results show the utility of a measure-projection approach for separating task-relevant neural activity into meaningful ROIs within more complex contexts that include eye movements.

  4. Increased neural activity of a mushroom body neuron subtype in the brains of forager honeybees.

    Directory of Open Access Journals (Sweden)

    Taketoshi Kiya

    Full Text Available Honeybees organize a sophisticated society, and the workers transmit information about the location of food sources using a symbolic dance, known as 'dance communication'. Recent studies indicate that workers integrate sensory information during foraging flight for dance communication. The neural mechanisms that account for this remarkable ability are, however, unknown. In the present study, we established a novel method to visualize neural activity in the honeybee brain using a novel immediate early gene, kakusei, as a marker of neural activity. The kakusei transcript was localized in the nuclei of brain neurons and did not encode an open reading frame, suggesting that it functions as a non-coding nuclear RNA. Using this method, we show that neural activity of a mushroom body neuron subtype, the small-type Kenyon cells, is prominently increased in the brains of dancer and forager honeybees. In contrast, the neural activity of the two mushroom body neuron subtypes, the small-and large-type Kenyon cells, is increased in the brains of re-orienting workers, which memorize their hive location during re-orienting flights. These findings demonstrate that the small-type Kenyon cell-preferential activity is associated with foraging behavior, suggesting its involvement in information integration during foraging flight, which is an essential basis for dance communication.

  5. Entropy-based generation of supervised neural networks for classification of structured patterns.

    Science.gov (United States)

    Tsai, Hsien-Leing; Lee, Shie-Jue

    2004-03-01

    Sperduti and Starita proposed a new type of neural network which consists of generalized recursive neurons for classification of structures. In this paper, we propose an entropy-based approach for constructing such neural networks for classification of acyclic structured patterns. Given a classification problem, the architecture, i.e., the number of hidden layers and the number of neurons in each hidden layer, and all the values of the link weights associated with the corresponding neural network are automatically determined. Experimental results have shown that the networks constructed by our method can have a better performance, with respect to network size, learning speed, or recognition accuracy, than the networks obtained by other methods.

  6. The Ising decoder: reading out the activity of large neural ensembles.

    Science.gov (United States)

    Schaub, Michael T; Schultz, Simon R

    2012-02-01

    The Ising model has recently received much attention for the statistical description of neural spike train data. In this paper, we propose and demonstrate its use for building decoders capable of predicting, on a millisecond timescale, the stimulus represented by a pattern of neural activity. After fitting to a training dataset, the Ising decoder can be applied "online" for instantaneous decoding of test data. While such models can be fit exactly using Boltzmann learning, this approach rapidly becomes computationally intractable as neural ensemble size increases. We show that several approaches, including the Thouless-Anderson-Palmer (TAP) mean field approach from statistical physics, and the recently developed Minimum Probability Flow Learning (MPFL) algorithm, can be used for rapid inference of model parameters in large-scale neural ensembles. Use of the Ising model for decoding, unlike other problems such as functional connectivity estimation, requires estimation of the partition function. As this involves summation over all possible responses, this step can be limiting. Mean field approaches avoid this problem by providing an analytical expression for the partition function. We demonstrate these decoding techniques by applying them to simulated neural ensemble responses from a mouse visual cortex model, finding an improvement in decoder performance for a model with heterogeneous as opposed to homogeneous neural tuning and response properties. Our results demonstrate the practicality of using the Ising model to read out, or decode, spatial patterns of activity comprised of many hundreds of neurons.

  7. Artificial neural networks from MATLAB in medicinal chemistry. Bayesian-regularized genetic neural networks (BRGNN): application to the prediction of the antagonistic activity against human platelet thrombin receptor (PAR-1).

    Science.gov (United States)

    Caballero, Julio; Fernández, Michael

    2008-01-01

    Artificial neural networks (ANNs) have been widely used for medicinal chemistry modeling. In the last two decades, too many reports used MATLAB environment as an adequate platform for programming ANNs. Some of these reports comprise a variety of applications intended to quantitatively or qualitatively describe structure-activity relationships. A powerful tool is obtained when there are combined Bayesian-regularized neural networks (BRANNs) and genetic algorithm (GA): Bayesian-regularized genetic neural networks (BRGNNs). BRGNNs can model complicated relationships between explanatory variables and dependent variables. Thus, this methodology is regarded as useful tool for QSAR analysis. In order to demonstrate the use of BRGNNs, we developed a reliable method for predicting the antagonistic activity of 5-amino-3-arylisoxazole derivatives against Human Platelet Thrombin Receptor (PAR-1), using classical 3D-QSAR methodologies: Comparative Molecular Field Analysis (CoMFA) and Comparative Molecular Similarity Indices Analysis (CoMSIA). In addition, 3D vectors generated from the molecular structures were correlated with antagonistic activities by multivariate linear regression (MLR) and Bayesian-regularized neural networks (BRGNNs). All models were trained with 34 compounds, after which they were evaluated for predictive ability with additional 6 compounds. CoMFA and CoMSIA were unable to describe this structure-activity relationship, while BRGNN methodology brings the best results according to validation statistics.

  8. A Combination of Central Pattern Generator-based and Reflex-based Neural Networks for Dynamic, Adaptive, Robust Bipedal Locomotion

    DEFF Research Database (Denmark)

    Di Canio, Giuliano; Larsen, Jørgen Christian; Wörgötter, Florentin

    2016-01-01

    Robotic systems inspired from humans have always been lightening up the curiosity of engineers and scientists. Of many challenges, human locomotion is a very difficult one where a number of different systems needs to interact in order to generate a correct and balanced pattern. To simulate the in...... network to generate basic walking patterns of a dynamic bipedal walking robot (DACBOT) and then a CPG-based neural network to ensure robust walking behavior......Robotic systems inspired from humans have always been lightening up the curiosity of engineers and scientists. Of many challenges, human locomotion is a very difficult one where a number of different systems needs to interact in order to generate a correct and balanced pattern. To simulate...... the interaction of these systems, implementations with reflexbased or central pattern generator (CPG)-based controllers have been tested on bipedal robot systems. In this paper we will combine the two controller types, into a controller that works with both reflex and CPG signals. We use a reflex-based neural...

  9. Strategies influence neural activity for feedback learning across child and adolescent development.

    Science.gov (United States)

    Peters, Sabine; Koolschijn, P Cédric M P; Crone, Eveline A; Van Duijvenvoorde, Anna C K; Raijmakers, Maartje E J

    2014-09-01

    Learning from feedback is an important aspect of executive functioning that shows profound improvements during childhood and adolescence. This is accompanied by neural changes in the feedback-learning network, which includes pre-supplementary motor area (pre- SMA)/anterior cingulate cortex (ACC), dorsolateral prefrontal cortex (DLPFC), superior parietal cortex (SPC), and the basal ganglia. However, there can be considerable differences within age ranges in performance that are ascribed to differences in strategy use. This is problematic for traditional approaches of analyzing developmental data, in which age groups are assumed to be homogenous in strategy use. In this study, we used latent variable models to investigate if underlying strategy groups could be detected for a feedback-learning task and whether there were differences in neural activation patterns between strategies. In a sample of 268 participants between ages 8 to 25 years, we observed four underlying strategy groups, which were cut across age groups and varied in the optimality of executive functioning. These strategy groups also differed in neural activity during learning; especially the most optimal performing group showed more activity in DLPFC, SPC and pre-SMA/ACC compared to the other groups. However, age differences remained an important contributor to neural activation, even when correcting for strategy. These findings contribute to the debate of age versus performance predictors of neural development, and highlight the importance of studying individual differences in strategy use when studying development. Copyright © 2014 Elsevier Ltd. All rights reserved.

  10. DNA methylation-based forensic age prediction using artificial neural networks and next generation sequencing.

    Science.gov (United States)

    Vidaki, Athina; Ballard, David; Aliferi, Anastasia; Miller, Thomas H; Barron, Leon P; Syndercombe Court, Denise

    2017-05-01

    The ability to estimate the age of the donor from recovered biological material at a crime scene can be of substantial value in forensic investigations. Aging can be complex and is associated with various molecular modifications in cells that accumulate over a person's lifetime including epigenetic patterns. The aim of this study was to use age-specific DNA methylation patterns to generate an accurate model for the prediction of chronological age using data from whole blood. In total, 45 age-associated CpG sites were selected based on their reported age coefficients in a previous extensive study and investigated using publicly available methylation data obtained from 1156 whole blood samples (aged 2-90 years) analysed with Illumina's genome-wide methylation platforms (27K/450K). Applying stepwise regression for variable selection, 23 of these CpG sites were identified that could significantly contribute to age prediction modelling and multiple regression analysis carried out with these markers provided an accurate prediction of age (R2=0.92, mean absolute error (MAE)=4.6 years). However, applying machine learning, and more specifically a generalised regression neural network model, the age prediction significantly improved (R2=0.96) with a MAE=3.3 years for the training set and 4.4 years for a blind test set of 231 cases. The machine learning approach used 16 CpG sites, located in 16 different genomic regions, with the top 3 predictors of age belonged to the genes NHLRC1, SCGN and CSNK1D. The proposed model was further tested using independent cohorts of 53 monozygotic twins (MAE=7.1 years) and a cohort of 1011 disease state individuals (MAE=7.2 years). Furthermore, we highlighted the age markers' potential applicability in samples other than blood by predicting age with similar accuracy in 265 saliva samples (R2=0.96) with a MAE=3.2 years (training set) and 4.0 years (blind test). In an attempt to create a sensitive and accurate age prediction test, a next

  11. The neural coding of creative idea generation across adolescence and early adulthood

    NARCIS (Netherlands)

    Kleibeuker, S.W.; Koolschijn, P.C.M.P.; Jolles, D.D.; de Dreu, C.K.W.; Crone, E.A.

    2013-01-01

    Creativity is considered key to human prosperity, yet the neurocognitive principles underlying creative performance, and their development, are still poorly understood. To fill this void, we examined the neural correlates of divergent thinking in adults (25-30 years) and adolescents (15-17 years).

  12. Derivation of stellar parameters from Gaia RVS spectra with prediction uncertainty using Generative Artificial Neural Networks (GANNs)

    Science.gov (United States)

    Manteiga, Minia; Dafonte, Jose Carlos; Ulla, Ana; Alvarez, Marco Antonio; Garabato, Daniel; Fustes, Diego

    2015-08-01

    The main purpose of Gaia Radial Velocity Spectrograph (RVS) is to measure the radial velocity of stars in the near infrared CaII spectral region. However, RVS will be used also for estimating the main stellar astrophysical parameters: effective temperature (Teff), logarithm of surface gravity (logg), abundance of metal elements with respect to hydrogen ([Fe/H]) and abundance of alpha elements with respect to iron ([α/Fe]). The software package being developed by Gaia DPAC (Data Processing and Analysis Consorcium) is composed by a bunch of modules which address the problem of parameterization from different perspectives This work focuses on developments carried out in the framework of one of these modules, called ANN, that is based on the application of Artificial Neural Networks.ANNs are a great tool that offers non-linear regression capabilities to any degree of complexity. Furthermore, they can provide accurate predictions when new data is presented to them, since they can generalize their solutions. However, in principle, ANNs are not able to give a measure of uncertainty over their predictions. Giving a measure of uncertainty over predictions is desirable in application domains where posterior inferences need to assess the quality of the predictions, especially when the behaviour of the system is not completely known. This is the case of data analysis coming from complex scientific missions like Gaia. This work presents a new architecture for ANNs, Generative ANNs (GANNs), that models the forward function instead of the inverse one. The advantage of forward modelling is that it estimates the actual observation, so that the fit between the estimated observation and the actual observation can be assessed, which allows for novelty detection, model evaluation and active learning. Furthermore, GANNs can be integrated in a Bayesian framework, which allows to estimate the full posterior distribution over the parameters of interest, to perform model comparisons, etc.

  13. Survey of Neutron Generators for Active Interrogation

    Energy Technology Data Exchange (ETDEWEB)

    Moss, Calvin Elroy [Los Alamos National Lab. (LANL), Los Alamos, NM (United States); Myers, William L. [Los Alamos National Lab. (LANL), Los Alamos, NM (United States); Sundby, Gary M. [Los Alamos National Lab. (LANL), Los Alamos, NM (United States); Chichester, David L. [Idaho National Lab. (INL), Idaho Falls, ID (United States); Johnson, James P. [Idaho National Lab. (INL), Idaho Falls, ID (United States)

    2017-05-02

    Some of these commercially available generators meet all of the requirements in Table 1, but there are other concerns. Most generators containing SF6 will be required to have the SF6 gas removed for shipping because of DOT regulations. However, Thermo Fisher has a DOT exemption. The P211 and B211 from Thermo Fisher meet the requirements listed in Table 1, but they are old designs and are no longer offered for sale. Also, they require 15 minutes or more of warmup before neutron output is available, and they lack a modern digital control. The nGen-300C from Starfire Industries is interesting because it is a portable system, but it uses the DD reaction for 2.5 MeV neutrons, which are not as penetrating as the 14 MeV neutrons from the DT reaction. The MP 320 from Thermo Fisher is another portable system, but the minimum pulse rate is 250 Hz, which is too fast for measurement of delayed neutrons and re-interrogation by delayed neutrons between pulses. The Genie 16 from Sodern (from France) probably meets the requirements, but the required power is probably too high for battery operation. The generators from Russia and China may be difficult to purchase, and service may not be available. The power required by some of these generators is low enough that batteries can be used. The portable units, nGen-300C and the MP320, could easily be operated with batteries. Other generators with low power requirements, as specified in the above vendors list, could possibly be operated with reason size batteries. The batteries do not need to be internal to the generator, but can be in a separate package. The availability of high capacity lithium batteries with sophisticated safety circuits makes battery operation more possible now than when lead acid batteries were used. The best path forward probably requires working with vendors of the existing systems. If Starfire Industries could be persuaded to put tritium in their nGen-300C generator, possibly in collaboration with a national

  14. Commonality of neural representations of sentences across languages: Predicting brain activation during Portuguese sentence comprehension using an English-based model of brain function.

    Science.gov (United States)

    Yang, Ying; Wang, Jing; Bailer, Cyntia; Cherkassky, Vladimir; Just, Marcel Adam

    2017-02-01

    The aim of the study was to test the cross-language generative capability of a model that predicts neural activation patterns evoked by sentence reading, based on a semantic characterization of the sentence. In a previous study on English monolingual speakers (Wang et al., submitted), a computational model performed a mapping from a set of 42 concept-level semantic features (Neurally Plausible Semantic Features, NPSFs) as well as 6 thematic role markers to neural activation patterns (assessed with fMRI), to predict activation levels in a network of brain locations. The model used two types of information gained from the English-based fMRI data to predict the activation for individual sentences in Portuguese. First, it used the mapping weights from NPSFs to voxel activation levels derived from the model for English reading. Second, the brain locations for which the activation levels were predicted were derived from a factor analysis of the brain activation patterns during English reading. These meta-language locations were defined by the clusters of voxels with high loadings on each of the four main dimensions (factors), namely people, places, actions and feelings, underlying the neural representations of the stimulus sentences. This cross-language model succeeded in predicting the brain activation patterns associated with the reading of 60 individual Portuguese sentences that were entirely new to the model, attaining accuracies reliably above chance level. The prediction accuracy was not affected by whether the Portuguese speaker was monolingual or Portuguese-English bilingual. The model's confusion errors indicated an accurate capture of the events or states described in the sentence at a conceptual level. Overall, the cross-language predictive capability of the model demonstrates the neural commonality between speakers of different languages in the representations of everyday events and states, and provides an initial characterization of the common meta

  15. Comparison of 2D and 3D neural induction methods for the generation of neural progenitor cells from human induced pluripotent stem cells

    DEFF Research Database (Denmark)

    Chandrasekaran, Abinaya; Avci, Hasan; Ochalek, Anna

    2017-01-01

    Neural progenitor cells (NPCs) from human induced pluripotent stem cells (hiPSCs) are frequently induced using 3D culture methodologies however, it is unknown whether spheroid-based (3D) neural induction is actually superior to monolayer (2D) neural induction. Our aim was to compare the efficiency...

  16. Computational modeling of neural activities for statistical inference

    CERN Document Server

    Kolossa, Antonio

    2016-01-01

    This authored monograph supplies empirical evidence for the Bayesian brain hypothesis by modeling event-related potentials (ERP) of the human electroencephalogram (EEG) during successive trials in cognitive tasks. The employed observer models are useful to compute probability distributions over observable events and hidden states, depending on which are present in the respective tasks. Bayesian model selection is then used to choose the model which best explains the ERP amplitude fluctuations. Thus, this book constitutes a decisive step towards a better understanding of the neural coding and computing of probabilities following Bayesian rules. The target audience primarily comprises research experts in the field of computational neurosciences, but the book may also be beneficial for graduate students who want to specialize in this field. .

  17. Active random noise control using adaptive learning rate neural networks with an immune feedback law

    Science.gov (United States)

    Sasaki, Minoru; Kuribayashi, Takumi; Ito, Satoshi

    2005-12-01

    In this paper an active random noise control using adaptive learning rate neural networks with an immune feedback law is presented. The adaptive learning rate strategy increases the learning rate by a small constant if the current partial derivative of the objective function with respect to the weight and the exponential average of the previous derivatives have the same sign, otherwise the learning rate is decreased by a proportion of its value. The use of an adaptive learning rate attempts to keep the learning step size as large as possible without leading to oscillation. In the proposed method, because of the immune feedback law change a learning rate of the neural networks individually and adaptively, it is expected that a cost function minimize rapidly and training time is decreased. Numerical simulations and experiments of active random noise control with the transfer function of the error path will be performed, to validate the convergence properties of the adaptive learning rate Neural Networks with the immune feedback law. Control results show that adaptive learning rate Neural Networks control structure can outperform linear controllers and conventional neural network controller for the active random noise control.

  18. A Gustatory Neural Circuit of Caenorhabditis elegans Generates Memory-Dependent Behaviors in Na(+) Chemotaxis.

    Science.gov (United States)

    Wang, Lifang; Sato, Hirofumi; Satoh, Yohsuke; Tomioka, Masahiro; Kunitomo, Hirofumi; Iino, Yuichi

    2017-02-22

    Animals show various behaviors in response to environmental chemicals. These behaviors are often plastic depending on previous experiences. Caenorhabditis elegans, which has highly developed chemosensory system with a limited number of sensory neurons, is an ideal model for analyzing the role of each neuron in innate and learned behaviors. Here, we report a new type of memory-dependent behavioral plasticity in Na(+) chemotaxis generated by the left member of bilateral gustatory neuron pair ASE (ASEL neuron). When worms were cultivated in the presence of Na(+), they showed positive chemotaxis toward Na(+), but when cultivated under Na(+)-free conditions, they showed no preference regarding Na(+) concentration. Both channelrhodopsin-2 (ChR2) activation with blue light and up-steps of Na(+) concentration activated ASEL only after cultivation with Na(+), as judged by increase in intracellular Ca(2+) Under cultivation conditions with Na(+), photoactivation of ASEL caused activation of its downstream interneurons AIY and AIA, which stimulate forward locomotion, and inhibition of its downstream interneuron AIB, which inhibits the turning/reversal behavior, and overall drove worms toward higher Na(+) concentrations. We also found that the Gq signaling pathway and the neurotransmitter glutamate are both involved in the behavioral response generated by ASEL.SIGNIFICANCE STATEMENT Animals have acquired various types of behavioral plasticity during their long evolutionary history. Caenorhabditis elegans prefers odors associated with food, but plastically changes its behavioral response according to previous experience. Here, we report a new type of behavioral response generated by a single gustatory sensory neuron, the ASE-left (ASEL) neuron. ASEL did not respond to photostimulation or upsteps of Na(+) concentration when worms were cultivated in Na(+)-free conditions; however, when worms were cultivated with Na(+), ASEL responded and inhibited AIB to avoid turning and

  19. Fluidic Active Transducer for Electricity Generation

    Science.gov (United States)

    Yang, Youngjun; Park, Junwoo; Kwon, Soon-Hyung; Kim, Youn Sang

    2015-10-01

    Flows in small size channels have been studied for a long time over multidisciplinary field such as chemistry, biology and medical through the various topics. Recently, the attempts of electricity generation from the small flows as a new area for energy harvesting in microfluidics have been reported. Here, we propose for the first time a new fluidic electricity generator (FEG) by modulating the electric double layer (EDL) with two phase flows of water and air without external power sources. We find that an electric current flowed by the forming/deforming of the EDL with a simple separated phase flow of water and air at the surface of the FEG. Electric signals between two electrodes of the FEG are checked from various water/air passing conditions. Moreover, we verify the possibility of a self-powered air slug sensor by applying the FEG in the detection of an air slug.

  20. A Computational Model of Torque Generation: Neural, Contractile, Metabolic and Musculoskeletal Components

    Science.gov (United States)

    Callahan, Damien M.; Umberger, Brian R.; Kent-Braun, Jane A.

    2013-01-01

    The pathway of voluntary joint torque production includes motor neuron recruitment and rate-coding, sarcolemmal depolarization and calcium release by the sarcoplasmic reticulum, force generation by motor proteins within skeletal muscle, and force transmission by tendon across the joint. The direct source of energetic support for this process is ATP hydrolysis. It is possible to examine portions of this physiologic pathway using various in vivo and in vitro techniques, but an integrated view of the multiple processes that ultimately impact joint torque remains elusive. To address this gap, we present a comprehensive computational model of the combined neuromuscular and musculoskeletal systems that includes novel components related to intracellular bioenergetics function. Components representing excitatory drive, muscle activation, force generation, metabolic perturbations, and torque production during voluntary human ankle dorsiflexion were constructed, using a combination of experimentally-derived data and literature values. Simulation results were validated by comparison with torque and metabolic data obtained in vivo. The model successfully predicted peak and submaximal voluntary and electrically-elicited torque output, and accurately simulated the metabolic perturbations associated with voluntary contractions. This novel, comprehensive model could be used to better understand impact of global effectors such as age and disease on various components of the neuromuscular system, and ultimately, voluntary torque output. PMID:23405245

  1. Fundamental Active Current Adaptive Linear Neural Networks for Photovoltaic Shunt Active Power Filters

    Directory of Open Access Journals (Sweden)

    Muhammad Ammirrul Atiqi Mohd Zainuri

    2016-05-01

    Full Text Available This paper presents improvement of a harmonics extraction algorithm, known as the fundamental active current (FAC adaptive linear element (ADALINE neural network with the integration of photovoltaic (PV to shunt active power filters (SAPFs as active current source. Active PV injection in SAPFs should reduce dependency on grid supply current to supply the system. In addition, with a better and faster harmonics extraction algorithm, the SAPF should perform well, especially under dynamic PV and load conditions. The role of the actual injection current from SAPF after connecting PVs will be evaluated, and the better effect of using FAC ADALINE will be confirmed. The proposed SAPF was simulated and evaluated in MATLAB/Simulink first. Then, an experimental laboratory prototype was also developed to be tested with a PV simulator (CHROMA 62100H-600S, and the algorithm was implemented using a TMS320F28335 Digital Signal Processor (DSP. From simulation and experimental results, significant improvements in terms of total harmonic distortion (THD, time response and reduction of source power from grid have successfully been verified and achieved.

  2. Enhancing neural activity to drive respiratory plasticity following cervical spinal cord injury.

    Science.gov (United States)

    Hormigo, Kristiina M; Zholudeva, Lyandysha V; Spruance, Victoria M; Marchenko, Vitaliy; Cote, Marie-Pascale; Vinit, Stephane; Giszter, Simon; Bezdudnaya, Tatiana; Lane, Michael A

    2017-01-01

    Cervical spinal cord injury (SCI) results in permanent life-altering sensorimotor deficits, among which impaired breathing is one of the most devastating and life-threatening. While clinical and experimental research has revealed that some spontaneous respiratory improvement (functional plasticity) can occur post-SCI, the extent of the recovery is limited and significant deficits persist. Thus, increasing effort is being made to develop therapies that harness and enhance this neuroplastic potential to optimize long-term recovery of breathing in injured individuals. One strategy with demonstrated therapeutic potential is the use of treatments that increase neural and muscular activity (e.g. locomotor training, neural and muscular stimulation) and promote plasticity. With a focus on respiratory function post-SCI, this review will discuss advances in the use of neural interfacing strategies and activity-based treatments, and highlights some recent results from our own research. Copyright © 2016 Elsevier Inc. All rights reserved.

  3. Dissipativity and Synchronization of Generalized BAM Neural Networks With Multivariate Discontinuous Activations.

    Science.gov (United States)

    Wang, Dongshu; Huang, Lihong; Tang, Longkun

    2017-09-14

    This paper is concerned with the dissipativity and synchronization problems of a class of delayed bidirectional associative memory (BAM) neural networks in which neuron activations are modeled by discontinuous bivariate functions. First, the concept of the Filippov solution is extended to functional differential equations with discontinuous right-hand sides and mixed delays via functional differential inclusions. The global dissipativity of the Filippov solution to the considered BAM neural networks is proven using generalized Halanay inequalities and matrix measure approaches. Second, to realize global exponential complete synchronization of BAM neural networks with multivariate discontinuous activations, discontinuous state feedback controllers are designed using functional differential inclusions theory and nonsmooth analysis theory with generalized Lyapunov functional method. Finally, several numerical examples are provided to demonstrate the applicability and effectiveness of our proposed results.

  4. Grid cells generate an analog error-correcting code for singularly precise neural computation.

    Science.gov (United States)

    Sreenivasan, Sameet; Fiete, Ila

    2011-09-11

    Entorhinal grid cells in mammals fire as a function of animal location, with spatially periodic response patterns. This nonlocal periodic representation of location, a local variable, is unlike other neural codes. There is no theoretical explanation for why such a code should exist. We examined how accurately the grid code with noisy neurons allows an ideal observer to estimate location and found this code to be a previously unknown type of population code with unprecedented robustness to noise. In particular, the representational accuracy attained by grid cells over the coding range was in a qualitatively different class from what is possible with observed sensory and motor population codes. We found that a simple neural network can effectively correct the grid code. To the best of our knowledge, these results are the first demonstration that the brain contains, and may exploit, powerful error-correcting codes for analog variables. © 2011 Nature America, Inc. All rights reserved.

  5. [Neural codes for perception].

    Science.gov (United States)

    Romo, R; Salinas, E; Hernández, A; Zainos, A; Lemus, L; de Lafuente, V; Luna, R

    This article describes experiments designed to show the neural codes associated with the perception and processing of tactile information. The results of these experiments have shown the neural activity correlated with tactile perception. The neurones of the primary somatosensory cortex (S1) represent the physical attributes of tactile perception. We found that these representations correlated with tactile perception. By means of intracortical microstimulation we demonstrated the causal relationship between S1 activity and tactile perception. In the motor areas of the frontal lobe is to be found the connection between sensorial and motor representation whilst decisions are being taken. S1 generates neural representations of the somatosensory stimuli which seen to be sufficient for tactile perception. These neural representations are subsequently processed by central areas to S1 and seem useful in perception, memory and decision making.

  6. Idea-Generation Techniques: A Formulary of Active Ingredients.

    Science.gov (United States)

    Smith, Gerald F.

    1998-01-01

    Reports the results of a study of active ingredients of creativity techniques, devices that promote idea generation, through an analysis of 172 idea-generation methods which identified three types of idea-generation devices--strategies, tactics, and enablers. These devices were organized into meaningful categories comprising a formulary of active…

  7. Neural speech recognition: continuous phoneme decoding using spatiotemporal representations of human cortical activity

    Science.gov (United States)

    Moses, David A.; Mesgarani, Nima; Leonard, Matthew K.; Chang, Edward F.

    2016-10-01

    Objective. The superior temporal gyrus (STG) and neighboring brain regions play a key role in human language processing. Previous studies have attempted to reconstruct speech information from brain activity in the STG, but few of them incorporate the probabilistic framework and engineering methodology used in modern speech recognition systems. In this work, we describe the initial efforts toward the design of a neural speech recognition (NSR) system that performs continuous phoneme recognition on English stimuli with arbitrary vocabulary sizes using the high gamma band power of local field potentials in the STG and neighboring cortical areas obtained via electrocorticography. Approach. The system implements a Viterbi decoder that incorporates phoneme likelihood estimates from a linear discriminant analysis model and transition probabilities from an n-gram phonemic language model. Grid searches were used in an attempt to determine optimal parameterizations of the feature vectors and Viterbi decoder. Main results. The performance of the system was significantly improved by using spatiotemporal representations of the neural activity (as opposed to purely spatial representations) and by including language modeling and Viterbi decoding in the NSR system. Significance. These results emphasize the importance of modeling the temporal dynamics of neural responses when analyzing their variations with respect to varying stimuli and demonstrate that speech recognition techniques can be successfully leveraged when decoding speech from neural signals. Guided by the results detailed in this work, further development of the NSR system could have applications in the fields of automatic speech recognition and neural prosthetics.

  8. Effects of furosemide on cochlear neural activity, central hyperactivity and behavioural tinnitus after cochlear trauma in guinea pig.

    Science.gov (United States)

    Mulders, Wilhelmina H A M; Barry, Kristin M; Robertson, Donald

    2014-01-01

    Cochlear trauma causes increased spontaneous activity (hyperactivity) to develop in central auditory structures, and this has been suggested as a neural substrate for tinnitus. Using a guinea pig model we have previously demonstrated that for some time after cochlear trauma, central hyperactivity is dependent on peripheral afferent drive and only later becomes generated intrinsically within central structures. Furosemide, a loop diuretic, reduces spontaneous firing of auditory afferents. We investigated in our guinea pig model the efficacy of furosemide in reducing 1) spontaneous firing of auditory afferents, using the spectrum of neural noise (SNN) from round window recording, 2) hyperactivity in inferior colliculus, using extracellular single neuron recordings and 3) tinnitus at early time-points after cochlear trauma. Tinnitus was assessed using gap prepulse inhibition of acoustic startle (GPIAS). Intraperitoneal furosemide, but not saline, caused a marked decrease in both SNN and central hyperactivity. Intracochlear perfusion with furosemide similarly reversed central hyperactivity. In animals in which GPIAS measurements suggested the presence of tinnitus (reduced GPIAS), this could be reversed with an intraperitoneal injection with furosemide but not saline. The results are consistent with furosemide reducing central hyperactivity and behavioural signs of tinnitus by acting peripherally to decrease spontaneous firing of auditory afferents. The data support the notion that hyperactivity may be involved in the generation of tinnitus and further suggest that there may be a therapeutic window after cochlear trauma using drug treatments that target peripheral spontaneous activity.

  9. Wakefulness suppresses retinal wave-related neural activity in visual cortex.

    Science.gov (United States)

    Mukherjee, Didhiti; Yonk, Alex J; Sokoloff, Greta; Blumberg, Mark S

    2017-08-01

    In the developing visual system before eye opening, spontaneous retinal waves trigger bursts of neural activity in downstream structures, including visual cortex. At the same ages when retinal waves provide the predominant input to the visual system, sleep is the predominant behavioral state. However, the interactions between behavioral state and retinal wave-driven activity have never been explicitly examined. Here we characterized unit activity in visual cortex during spontaneous sleep-wake cycles in 9- and 12-day-old rats. At both ages, cortical activity occurred in discrete rhythmic bursts, ~30-60 s apart, mirroring the timing of retinal waves. Interestingly, when pups spontaneously woke up and moved their limbs in the midst of a cortical burst, the activity was suppressed. Finally, experimentally evoked arousals also suppressed intraburst cortical activity. All together, these results indicate that active wake interferes with the activation of the developing visual cortex by retinal waves. They also suggest that sleep-wake processes can modulate visual cortical plasticity at earlier ages than has been previously considered.NEW & NOTEWORTHY By recording in visual cortex in unanesthetized infant rats, we show that neural activity attributable to retinal waves is specifically suppressed when pups spontaneously awaken or are experimentally aroused. These findings suggest that the relatively abundant sleep of early development plays a permissive functional role for the visual system. It follows, then, that biological or environmental factors that disrupt sleep may interfere with the development of these neural networks. Copyright © 2017 the American Physiological Society.

  10. Neural activity in the hippocampus predicts individual visual short-term memory capacity.

    Science.gov (United States)

    von Allmen, David Yoh; Wurmitzer, Karoline; Martin, Ernst; Klaver, Peter

    2013-07-01

    Although the hippocampus had been traditionally thought to be exclusively involved in long-term memory, recent studies raised controversial explanations why hippocampal activity emerged during short-term memory tasks. For example, it has been argued that long-term memory processes might contribute to performance within a short-term memory paradigm when memory capacity has been exceeded. It is still unclear, though, whether neural activity in the hippocampus predicts visual short-term memory (VSTM) performance. To investigate this question, we measured BOLD activity in 21 healthy adults (age range 19-27 yr, nine males) while they performed a match-to-sample task requiring processing of object-location associations (delay period  =  900 ms; set size conditions 1, 2, 4, and 6). Based on individual memory capacity (estimated by Cowan's K-formula), two performance groups were formed (high and low performers). Within whole brain analyses, we found a robust main effect of "set size" in the posterior parietal cortex (PPC). In line with a "set size × group" interaction in the hippocampus, a subsequent Finite Impulse Response (FIR) analysis revealed divergent hippocampal activation patterns between performance groups: Low performers (mean capacity  =  3.63) elicited increased neural activity at set size two, followed by a drop in activity at set sizes four and six, whereas high performers (mean capacity  =  5.19) showed an incremental activity increase with larger set size (maximal activation at set size six). Our data demonstrated that performance-related neural activity in the hippocampus emerged below capacity limit. In conclusion, we suggest that hippocampal activity reflected successful processing of object-location associations in VSTM. Neural activity in the PPC might have been involved in attentional updating. Copyright © 2013 Wiley Periodicals, Inc.

  11. Modeling electrocortical activity through improved local approximations of integral neural field equations.

    NARCIS (Netherlands)

    Coombes, S.; Venkov, N.A.; Shiau, L.; Bojak, I.; Liley, D.T.; Laing, C.R.

    2007-01-01

    Neural field models of firing rate activity typically take the form of integral equations with space-dependent axonal delays. Under natural assumptions on the synaptic connectivity we show how one can derive an equivalent partial differential equation (PDE) model that properly treats the axonal

  12. Distinct neural pathways mediate alpha7 nicotinic acetylcholine receptor-dependent activation of the forebrain

    DEFF Research Database (Denmark)

    Thomsen, Morten S; Hay-Schmidt, Anders; Hansen, Henrik H

    2010-01-01

    important for cognitive function. However, the neural substrates involved in these effects remain elusive. Here we identify cortically projecting cholinergic neurons in the horizontal limb of the diagonal band of Broca (HDB) in the basal forebrain (BF) as important targets for alpha(7) nAChR activation...

  13. Differences in Feedback- and Inhibition-Related Neural Activity in Adult ADHD

    Science.gov (United States)

    Dibbets, Pauline; Evers, Lisbeth; Hurks, Petra; Marchetta, Natalie; Jolles, Jelle

    2009-01-01

    The objective of this study was to examine response inhibition- and feedback-related neural activity in adults with attention deficit hyperactivity disorder (ADHD) using event-related functional MRI. Sixteen male adults with ADHD and 13 healthy/normal controls participated in this study and performed a modified Go/NoGo task. Behaviourally,…

  14. Differential neural activity patterns for spatial relations in humans: a MEG study.

    Science.gov (United States)

    Scott, Nicole M; Leuthold, Arthur; Sera, Maria D; Georgopoulos, Apostolos P

    2016-02-01

    Children learn the words for above-below relations earlier than for left-right relations, despite treating these equally well in a simple visual categorization task. Even as adults--conflicts in congruency, such as when a stimulus is depicted in a spatially incongruent manner with respect to salient global cues--can be challenging. Here we investigated the neural correlates of encoding and maintaining in working memory above-below and left-right relational planes in 12 adults using magnetoencephalography in order to discover whether above-below relations are represented by the brain differently than left-right relations. Adults performed perfectly on the task behaviorally, so any differences in neural activity were attributed to the stimuli's cognitive attributes. In comparing above-below to left-right relations during stimulus encoding, we found the greatest differences in neural activity in areas associated with space and movement. In comparing congruent to incongruent trials, we found the greatest differential activity in premotor areas. For both contrasts, brain areas involved in the encoding phase were also involved in the maintenance phase, which provides evidence that those brain areas are particularly important in representing the relational planes or congruency types throughout the trial. When comparing neural activity associated with the relational planes during working memory, additional right posterior areas were implicated, whereas the congruent-incongruent contrast implicated additional bilateral frontal and temporal areas. These findings are consistent with the hypothesis left-right relations are represented differently than above-below relations.

  15. Higher-order cognitive training effects on processing speed-related neural activity: a randomized trial.

    Science.gov (United States)

    Motes, Michael A; Yezhuvath, Uma S; Aslan, Sina; Spence, Jeffrey S; Rypma, Bart; Chapman, Sandra B

    2017-10-12

    Higher-order cognitive training has shown to enhance performance in older adults, but the neural mechanisms underlying performance enhancement have yet to be fully disambiguated. This randomized trial examined changes in processing speed and processing speed-related neural activity in older participants (57-71 years of age) who underwent cognitive training (CT, N = 12) compared with wait-listed (WLC, N = 15) or exercise-training active (AC, N = 14) controls. The cognitive training taught cognitive control functions of strategic attention, integrative reasoning, and innovation over 12 weeks. All 3 groups worked through a functional magnetic resonance imaging processing speed task during 3 sessions (baseline, mid-training, and post-training). Although all groups showed faster reaction times (RTs) across sessions, the CT group showed a significant increase, and the WLC and AC groups showed significant decreases across sessions in the association between RT and BOLD signal change within the left prefrontal cortex (PFC). Thus, cognitive training led to a change in processing speed-related neural activity where faster processing speed was associated with reduced PFC activation, fitting previously identified neural efficiency profiles. Copyright © 2017 The Authors. Published by Elsevier Inc. All rights reserved.

  16. Specific and Nonspecific Neural Activity during Selective Processing of Visual Representations in Working Memory

    Science.gov (United States)

    Oh, Hwamee; Leung, Hoi-Chung

    2010-01-01

    In this fMRI study, we investigated prefrontal cortex (PFC) and visual association regions during selective information processing. We recorded behavioral responses and neural activity during a delayed recognition task with a cue presented during the delay period. A specific cue ("Face" or "Scene") was used to indicate which one of the two…

  17. Identification of children's activity type with accelerometer-based neural networks

    NARCIS (Netherlands)

    Vries, S.I. de; Engels, M.; Garre, F.G.

    2011-01-01

    Purpose: The study's purpose was to identify children's physical activity type using artificial neural network (ANN) models based on uniaxial or triaxial accelerometer data from the hip or the ankle. Methods: Fifty-eight children (31 boys and 27 girls, age range = 9-12 yr) performed the following

  18. Evaluation of neural networks to identify types of activity using accelerometers

    NARCIS (Netherlands)

    Vries, S.I. de; Garre, F.G.; Engbers, L.H.; Hildebrandt, V.H.; Buuren, S. van

    2011-01-01

    Purpose: To develop and evaluate two artificial neural network (ANN) models based on single-sensor accelerometer data and an ANN model based on the data of two accelerometers for the identification of types of physical activity in adults. Methods: Forty-nine subjects (21 men and 28 women; age range

  19. Differences in Neural Activation as a Function of Risk-taking Task Parameters

    Directory of Open Access Journals (Sweden)

    Eliza eCongdon

    2013-09-01

    Full Text Available Despite evidence supporting a relationship between impulsivity and naturalistic risk-taking, the relationship of impulsivity with laboratory-based measures of risky decision-making remains unclear. One factor contributing to this gap in our understanding is the degree to which different risky decision-making tasks vary in their details. We conducted an fMRI investigation of the Angling Risk Task (ART, which is an improved behavioral measure of risky decision-making. In order to examine whether the observed pattern of neural activation was specific to the ART or generalizable, we also examined correlates of the Balloon Analogue Risk Taking (BART task in the same sample of 23 healthy adults. Exploratory analyses were conducted to examine the relationship between neural activation, performance, impulsivity and self-reported risk-taking. While activation in a valuation network was associated with reward tracking during the ART but not the BART, increased fronto-cingulate activation was seen during risky choice trials in the BART as compared to the ART. Thus, neural activation during risky decision-making trials differed between the two tasks, and this observation was likely driven by differences in task parameters, namely the absence vs. presence of ambiguity and/or stationary vs. increasing probability of loss on the ART and BART, respectively. Exploratory association analyses suggest that sensitivity of neural response to the magnitude of potential reward during the ART was associated with a suboptimal performance strategy, higher scores on a scale of dysfunctional impulsivity and a greater likelihood of engaging in risky behaviors, while this pattern was not seen for the BART. Our results suggest that the ART is decomposable and associated with distinct patterns of neural activation; this represents a preliminary step towards characterizing a behavioral measure of risky decision-making that may support a better understanding of naturalistic risk-taking.

  20. Cognitive-affective neural plasticity following active-controlled mindfulness intervention

    DEFF Research Database (Denmark)

    Allen, Micah Galen

    Mindfulness meditation is a set of attention-based, regulatory and self-inquiry training regimes. Although the impact of mindfulness meditation training (MT) on self-regulation is well established, the neural mechanisms supporting such plasticity are poorly understood. MT is thought to act through...... prefrontal cortex (mPFC), and right anterior insula during negative valence processing. Our findings highlight the importance of active control in MT research, indicate unique neural mechanisms for progressive stages of mindfulness training, and suggest that optimal application of MT may differ depending...

  1. Measurement of weld penetration depths in thin structures using transmission coefficients of laser-generated Lamb waves and neural network.

    Science.gov (United States)

    Yang, Lei; Ume, I Charles

    2017-07-01

    The Laser/EMAT ultrasonic (LEU) technique has shown the capability to measure weld penetration depths in thick structures based on ray-tracing of laser-generated bulk and surface waves. The ray-tracing method is not applicable to laser-generated Lamb waves when the LEU technique is used to measure weld penetration depths in thin structures. In this work, transmission coefficients of Lamb waves present in the LEU signals are investigated against varying weld penetration depths. An artificial neural network is developed to use transmission coefficients of sensitive Lamb waves and LEU signal energy to predict weld penetration depths accurately. The developed method is very attractive because it allows a quick inspection of weld penetration depths in thin structures. Copyright © 2017 Elsevier B.V. All rights reserved.

  2. Comparison of 2D and 3D neural induction methods for the generation of neural progenitor cells from human induced pluripotent stem cells

    DEFF Research Database (Denmark)

    Chandrasekaran, Abinaya; Avci, Hasan; Ochalek, Anna

    2017-01-01

    Neural progenitor cells (NPCs) from human induced pluripotent stem cells (hiPSCs) are frequently induced using 3D culture methodologies however, it is unknown whether spheroid-based (3D) neural induction is actually superior to monolayer (2D) neural induction. Our aim was to compare the efficiency......), cortical layer (TBR1, CUX1) and glial markers (SOX9, GFAP, AQP4). Electron microscopy demonstrated that both methods resulted in morphologically similar neural rosettes. However, quantification of NPCs derived from 3D neural induction exhibited an increase in the number of PAX6/NESTIN double positive cells...... and the derived neurons exhibited longer neurites. In contrast, 2D neural induction resulted in more SOX1 positive cells. While 2D monolayer induction resulted in slightly less mature neurons, at an early stage of differentiation, the patch clamp analysis failed to reveal any significant differences between...

  3. Simultaneous imaging of neural activity in three dimensions

    Directory of Open Access Journals (Sweden)

    Sean eQuirin

    2014-04-01

    Full Text Available We introduce a scanless optical method to image neuronal activity in three dimensions simultaneously. Using a spatial light modulator and a custom-designed phase mask, we illuminate and collect light simultaneously from different focal planes and perform calcium imaging of neuronal activity in vitro and in vivo. This method, combining structured illumination with volume projection imaging, could be used as a technological platform for brain activity mapping.

  4. Dispositional Mindfulness and Depressive Symptomatology: Correlations with Limbic and Self-Referential Neural Activity during Rest

    Science.gov (United States)

    Way, Baldwin M.; Creswell, J. David; Eisenberger, Naomi I.; Lieberman, Matthew D.

    2010-01-01

    To better understand the relationship between mindfulness and depression, we studied normal young adults (n=27) who completed measures of dispositional mindfulness and depressive symptomatology, which were then correlated with: a) Rest: resting neural activity during passive viewing of a fixation cross, relative to a simple goal-directed task (shape-matching); and b) Reactivity: neural reactivity during viewing of negative emotional faces, relative to the same shape-matching task. Dispositional mindfulness was negatively correlated with resting activity in self-referential processing areas, while depressive symptomatology was positively correlated with resting activity in similar areas. In addition, dispositional mindfulness was negatively correlated with resting activity in the amygdala, bilaterally, while depressive symptomatology was positively correlated with activity in the right amygdala. Similarly, when viewing emotional faces, amygdala reactivity was positively correlated with depressive symptomatology and negatively correlated with dispositional mindfulness, an effect that was largely attributable to differences in resting activity. These findings indicate that mindfulness is associated with intrinsic neural activity and that changes in resting amygdala activity could be a potential mechanism by which mindfulness-based depression treatments elicit therapeutic improvement. PMID:20141298

  5. Performance assessment of electric power generations using an adaptive neural network algorithm and fuzzy DEA

    Energy Technology Data Exchange (ETDEWEB)

    Javaheri, Zahra

    2010-09-15

    Modeling, evaluating and analyzing performance of Iranian thermal power plants is the main goal of this study which is based on multi variant methods analysis. These methods include fuzzy DEA and adaptive neural network algorithm. At first, we determine indicators, then data is collected, next we obtained values of ranking and efficiency by Fuzzy DEA, Case study is thermal power plants In view of the fact that investment to establish on power plant is very high, and maintenance of power plant causes an expensive expenditure, moreover using fossil fuel effected environment hence optimum produce of current power plants is important.

  6. Concurrent OCT imaging of stimulus evoked retinal neural activation and hemodynamic responses

    Science.gov (United States)

    Son, Taeyoon; Wang, Benquan; Lu, Yiming; Chen, Yanjun; Cao, Dingcai; Yao, Xincheng

    2017-02-01

    It is well established that major retinal diseases involve distortions of the retinal neural physiology and blood vascular structures. However, the details of distortions in retinal neurovascular coupling associated with major eye diseases are not well understood. In this study, a multi-modal optical coherence tomography (OCT) imaging system was developed to enable concurrent imaging of retinal neural activity and vascular hemodynamics. Flicker light stimulation was applied to mouse retinas to evoke retinal neural responses and hemodynamic changes. The OCT images were acquired continuously during the pre-stimulation, light-stimulation, and post-stimulation phases. Stimulus-evoked intrinsic optical signals (IOSs) and hemodynamic changes were observed over time in blood-free and blood regions, respectively. Rapid IOSs change occurred almost immediately after stimulation. Both positive and negative signals were observed in adjacent retinal areas. The hemodynamic changes showed time delays after stimulation. The signal magnitudes induced by light stimulation were observed in blood regions and did not show significant changes in blood-free regions. These differences may arise from different mechanisms in blood vessels and neural tissues in response to light stimulation. These characteristics agreed well with our previous observations in mouse retinas. Further development of the multimodal OCT may provide a new imaging method for studying how retinal structures and metabolic and neural functions are affected by age-related macular degeneration (AMD), glaucoma, diabetic retinopathy (DR), and other diseases, which promises novel noninvasive biomarkers for early disease detection and reliable treatment evaluations of eye diseases.

  7. Complete stability of delayed recurrent neural networks with Gaussian activation functions.

    Science.gov (United States)

    Liu, Peng; Zeng, Zhigang; Wang, Jun

    2017-01-01

    This paper addresses the complete stability of delayed recurrent neural networks with Gaussian activation functions. By means of the geometrical properties of Gaussian function and algebraic properties of nonsingular M-matrix, some sufficient conditions are obtained to ensure that for an n-neuron neural network, there are exactly 3(k) equilibrium points with 0≤k≤n, among which 2(k) and 3(k)-2(k) equilibrium points are locally exponentially stable and unstable, respectively. Moreover, it concludes that all the states converge to one of the equilibrium points; i.e., the neural networks are completely stable. The derived conditions herein can be easily tested. Finally, a numerical example is given to illustrate the theoretical results. Copyright © 2016 Elsevier Ltd. All rights reserved.

  8. Navigation of autonomous mobile robot using different activation functions of wavelet neural network

    Directory of Open Access Journals (Sweden)

    Panigrahi Pratap Kumar

    2015-03-01

    Full Text Available An autonomous mobile robot is a robot which can move and act autonomously without the help of human assistance. Navigation problem of mobile robot in unknown environment is an interesting research area. This is a problem of deducing a path for the robot from its initial position to a given goal position without collision with the obstacles. Different methods such as fuzzy logic, neural networks etc. are used to find collision free path for mobile robot. This paper examines behavior of path planning of mobile robot using three activation functions of wavelet neural network i.e. Mexican Hat, Gaussian and Morlet wavelet functions by MATLAB. The simulation result shows that WNN has faster learning speed with respect to traditional artificial neural network.

  9. Amygdala neural activity reflects spatial attention towards stimuli promising reward or threatening punishment.

    Science.gov (United States)

    Peck, Christopher J; Salzman, C Daniel

    2014-10-30

    Humans and other animals routinely identify and attend to sensory stimuli so as to rapidly acquire rewards or avoid aversive experiences. Emotional arousal, a process mediated by the amygdala, can enhance attention to stimuli in a non-spatial manner. However, amygdala neural activity was recently shown to encode spatial information about reward-predictive stimuli, and to correlate with spatial attention allocation. If representing the motivational significance of sensory stimuli within a spatial framework reflects a general principle of amygdala function, then spatially selective neural responses should also be elicited by sensory stimuli threatening aversive events. Recordings from amygdala neurons were therefore obtained while monkeys directed spatial attention towards stimuli promising reward or threatening punishment. Neural responses encoded spatial information similarly for stimuli associated with both valences of reinforcement, and responses reflected spatial attention allocation. The amygdala therefore may act to enhance spatial attention to sensory stimuli associated with rewarding or aversive experiences.

  10. Social power and approach-related neural activity

    NARCIS (Netherlands)

    M.A.S. Boksem (Maarten); R. Smolders (Ruud); D. de Cremer (David)

    2009-01-01

    textabstractIt has been argued that power activates a general tendency to approach whereas powerlessness activates a tendency to inhibit. The assumption is that elevated power involves reward-rich environments, freedom and, as a consequence, triggers an approach-related motivational orientation and

  11. Review of mesoscopic optical tomography for depth-resolved imaging of hemodynamic changes and neural activities

    Science.gov (United States)

    Tang, Qinggong; Lin, Jonathan; Tsytsarev, Vassiliy; Erzurumlu, Reha S.; Liu, Yi; Chen, Yu

    2016-01-01

    Abstract. Understanding the functional wiring of neural circuits and their patterns of activation following sensory stimulations is a fundamental task in the field of neuroscience. Furthermore, charting the activity patterns is undoubtedly important to elucidate how neural networks operate in the living brain. However, optical imaging must overcome the effects of light scattering in the tissue, which limit the light penetration depth and affect both the imaging quantitation and sensitivity. Laminar optical tomography (LOT) is a three-dimensional (3-D) in-vivo optical imaging technique that can be used for functional imaging. LOT can achieve both a resolution of 100 to 200  μm and a penetration depth of 2 to 3 mm based either on absorption or fluorescence contrast, as well as large field-of-view and high acquisition speed. These advantages make LOT suitable for 3-D depth-resolved functional imaging of the neural functions in the brain and spinal cords. We review the basic principles and instrumentations of representative LOT systems, followed by recent applications of LOT on 3-D imaging of neural activities in the rat forepaw stimulation model and mouse whisker-barrel system. PMID:27990452

  12. Local active information storage as a tool to understand distributed neural information processing

    Science.gov (United States)

    Wibral, Michael; Lizier, Joseph T.; Vögler, Sebastian; Priesemann, Viola; Galuske, Ralf

    2013-01-01

    Every act of information processing can in principle be decomposed into the component operations of information storage, transfer, and modification. Yet, while this is easily done for today's digital computers, the application of these concepts to neural information processing was hampered by the lack of proper mathematical definitions of these operations on information. Recently, definitions were given for the dynamics of these information processing operations on a local scale in space and time in a distributed system, and the specific concept of local active information storage was successfully applied to the analysis and optimization of artificial neural systems. However, no attempt to measure the space-time dynamics of local active information storage in neural data has been made to date. Here we measure local active information storage on a local scale in time and space in voltage sensitive dye imaging data from area 18 of the cat. We show that storage reflects neural properties such as stimulus preferences and surprise upon unexpected stimulus change, and in area 18 reflects the abstract concept of an ongoing stimulus despite the locally random nature of this stimulus. We suggest that LAIS will be a useful quantity to test theories of cortical function, such as predictive coding. PMID:24501593

  13. Local active information storage as a tool to understand distributed neural information processing

    Directory of Open Access Journals (Sweden)

    Michael eWibral

    2014-01-01

    Full Text Available Every act of information processing can in principle be decomposed into the component operations of information storage, transfer, and modification. Yet, while this is easily done for today’s digital computers, the application of these concepts to neural information processing was hampered by the lack of proper mathematical definitions of these operations on information. Recently, such definitions were given and the specific concept of local active information storage was successfully applied to the analysis and optimization of artificial neural systems. However, no attempt to measure local active information storage in neural data has been made to date. Here we measure local active information storage on a local scale in time and space in voltage sensitive dye imaging data from area 18 of the cat. We show that storage reflects neural properties such as stimulus preferences and surprise upon unexpected stimulus change, and in area 18 reflects the abstract concept of an ongoing stimulus despite the locally random nature of this stimulus. We suggest that LAIS will be a useful quantity to test theories of cortical function, such as predictive coding.

  14. Convergence of inhibitory neural inputs regulate motor activity in the murine and monkey stomach.

    Science.gov (United States)

    Shaylor, Lara A; Hwang, Sung Jin; Sanders, Kenton M; Ward, Sean M

    2016-11-01

    Inhibitory motor neurons regulate several gastric motility patterns including receptive relaxation, gastric peristaltic motor patterns, and pyloric sphincter opening. Nitric oxide (NO) and purines have been identified as likely candidates that mediate inhibitory neural responses. However, the contribution from each neurotransmitter has received little attention in the distal stomach. The aims of this study were to identify the roles played by NO and purines in inhibitory motor responses in the antrums of mice and monkeys. By using wild-type mice and mutants with genetically deleted neural nitric oxide synthase (Nos1-/-) and P2Y1 receptors (P2ry1-/-) we examined the roles of NO and purines in postjunctional inhibitory responses in the distal stomach and compared these responses to those in primate stomach. Activation of inhibitory motor nerves using electrical field stimulation (EFS) produced frequency-dependent inhibitory junction potentials (IJPs) that produced muscle relaxations in both species. Stimulation of inhibitory nerves during slow waves terminated pacemaker events and associated contractions. In Nos1-/- mice IJPs and relaxations persisted whereas in P2ry1-/- mice IJPs were absent but relaxations persisted. In the gastric antrum of the non-human primate model Macaca fascicularis, similar NO and purine neural components contributed to inhibition of gastric motor activity. These data support a role of convergent inhibitory neural responses in the regulation of gastric motor activity across diverse species. Copyright © 2016 the American Physiological Society.

  15. Effect of short-term escitalopram treatment on neural activation during emotional processing.

    Science.gov (United States)

    Maron, Eduard; Wall, Matt; Norbury, Ray; Godlewska, Beata; Terbeck, Sylvia; Cowen, Philip; Matthews, Paul; Nutt, David J

    2016-01-01

    Recent functional magnetic resonance (fMRI) imaging studies have revealed that subchronic medication with escitalopram leads to significant reduction in both amygdala and medial frontal gyrus reactivity during processing of emotional faces, suggesting that escitalopram may have a distinguishable modulatory effect on neural activation as compared with other serotonin-selective antidepressants. In this fMRI study we aimed to explore whether short-term medication with escitalopram in healthy volunteers is associated with reduced neural response to emotional processing, and whether this effect is predicted by drug plasma concentration. The neural response to fearful and happy faces was measured before and on day 7 of treatment with escitalopram (10mg) in 15 healthy volunteers and compared with those in a control unmedicated group (n=14). Significantly reduced activation to fearful, but not to happy facial expressions was observed in the bilateral amygdala, cingulate and right medial frontal gyrus following escitalopram medication. This effect was not correlated with plasma drug concentration. In accordance with previous data, we showed that escitalopram exerts its rapid direct effect on emotional processing via attenuation of neural activation in pathways involving medial frontal gyrus and amygdala, an effect that seems to be distinguishable from that of other SSRIs. © The Author(s) 2015.

  16. The capacity for generating cognitive reappraisals is reflected in asymmetric activation of frontal brain regions.

    Science.gov (United States)

    Papousek, Ilona; Weiss, Elisabeth M; Perchtold, Corinna M; Weber, Hannelore; de Assunção, Vera Loureiro; Schulter, Günter; Lackner, Helmut K; Fink, Andreas

    2017-04-01

    Encouraging patients to use cognitive reappraisal constitutes the core of modern psychotherapeutic approaches. However, evidence for specific neural correlates of the capacity for cognitive reappraisal, which is a necessary prerequisite for the effective implementation of cognitive reappraisal in everyday life, has been sparse to date. In the present study, the capacity for cognitive reappraisal was studied in terms of the participants' inventiveness in generating alternative appraisals of anger-evoking events, and was correlated with frontal EEG alpha asymmetry recorded while the participants were generating reappraisals as well as during a common creative idea generation task. During cognitive reappraisal efforts, individuals higher on the capacity for generating cognitive reappraisals showed more left-lateralized activity in lateral prefrontal cortex, specifically in ventrolateral prefrontal cortex extending toward the frontal pole. This effect was observed independently from the activation during novel idea generation without emotional component, indicating that specific demands are implicated in the generation of reappraisals of emotional events. Taken together, the results indicate that individuals higher on the capacity for cognitive reappraisal are more capable or more prone to recruit appropriate brain regions when the situation demands coming up with alternative appraisals of stressful events. The findings may stimulate the development of more individually targeted interventions.

  17. An investigation of the relationship between activation of a social cognitive neural network and social functioning.

    Science.gov (United States)

    Pinkham, Amy E; Hopfinger, Joseph B; Ruparel, Kosha; Penn, David L

    2008-07-01

    Previous work examining the neurobiological substrates of social cognition in healthy individuals has reported modulation of a social cognitive network such that increased activation of the amygdala, fusiform gyrus, and superior temporal sulcus are evident when individuals judge a face to be untrustworthy as compared with trustworthy. We examined whether this pattern would be present in individuals with schizophrenia who are known to show reduced activation within these same neural regions when processing faces. Additionally, we sought to determine how modulation of this social cognitive network may relate to social functioning. Neural activation was measured using functional magnetic resonance imaging with blood oxygenation level dependent contrast in 3 groups of individuals--nonparanoid individuals with schizophrenia, paranoid individuals with schizophrenia, and healthy controls--while they rated faces as either trustworthy or untrustworthy. Analyses of mean percent signal change extracted from a priori regions of interest demonstrated that both controls and nonparanoid individuals with schizophrenia showed greater activation of this social cognitive network when they rated a face as untrustworthy relative to trustworthy. In contrast, paranoid individuals did not show a significant difference in levels of activation based on how they rated faces. Further, greater activation of this social cognitive network to untrustworthy faces was significantly and positively correlated with social functioning. These findings indicate that impaired modulation of neural activity while processing social stimuli may underlie deficits in social cognition and social dysfunction in schizophrenia.

  18. Neural correlates of apparent motion perception of impoverished facial stimuli: a comparison of ERP and ERSP activity.

    Science.gov (United States)

    Rossi, Alejandra; Parada, Francisco J; Kolchinsky, Artemy; Puce, Aina

    2014-09-01

    Our brains readily decode human movements, as shown by neural responses to face and body motion. N170 event-related potentials (ERPs) are earlier and larger to mouth opening movements relative to closing in both line-drawn and natural faces, and gaze aversions relative to direct gaze in natural faces (Puce and Perrett, 2003; Puce et al., 2000). Here we extended this work by recording both ERP and oscillatory EEG activity (event-related spectral perturbations, ERSPs) to line-drawn faces depicting eye and mouth movements (Eyes: Direct vs Away; Mouth: Closed vs Open) and non-face motion controls. Neural activity was measured in 2 occipito-temporal clusters of 9 electrodes, one in each hemisphere. Mouth opening generated larger N170s than mouth closing, replicating earlier work. Eye motion elicited robust N170s that did not differ between gaze conditions. Control condition differences were seen, and generated the largest N170. ERSP difference plots across conditions in the occipito-temporal electrode clusters (Eyes: Direct vs Away; Mouth: Closed vs Open) showed statistically significant differences in beta and gamma bands for gaze direction changes and mouth opening at similar post-stimulus times and frequencies. In contrast, control stimuli showed activity in the gamma band with a completely different time profile and hemispheric distribution to facial stimuli. ERSP plots were generated in two 9 electrode clusters centered on central sites, C3 and C4. In the left cluster for all stimulus conditions, broadband beta suppression persisted from about 250ms post-motion onset. In the right cluster, beta suppression was seen for control conditions only. Statistically significant differences between conditions were confined between 4 and 15Hz, unlike the occipito-temporal sites where differences occurred at much higher frequencies (high beta/gamma). Our data indicate that N170 amplitude is sensitive to the amount of movement in the visual field, independent of stimulus type

  19. The macaque lateral grasping network: A neural substrate for generating purposeful hand actions.

    Science.gov (United States)

    Borra, Elena; Gerbella, Marzio; Rozzi, Stefano; Luppino, Giuseppe

    2017-04-01

    In primates, neural mechanisms for controlling skilled hand actions primarily rely on sensorimotor transformations. These transformations are mediated by circuits linking specific inferior parietal with ventral premotor areas in which sensory coding of objects' features automatically triggers appropriate hand motor programs. Recently, connectional studies in macaques showed that these parietal and premotor areas are nodes of a large-scale cortical network, designated as "lateral grasping network," including specific temporal and prefrontal sectors involved in object recognition and executive functions, respectively. These data extend grasping models so far proposed in providing a possible substrate for interfacing perceptual, cognitive, and hand-related sensorimotor processes for controlling hand actions based on object identity, goals, and memory-based or contextual information and for the contribution of motor signals to cognitive motor functions. Human studies provided evidence for a possible counterpart of the macaque lateral grasping network, suggesting that in primate evolution the neural mechanisms for controlling hand actions described in the macaque have been retained and exploited for the emergence of human-specific motor and cognitive motor capacities. Copyright © 2017 Elsevier Ltd. All rights reserved.

  20. Prediction of activity coefficients at infinite dilution for organic solutes in ionic liquids by artificial neural network

    Energy Technology Data Exchange (ETDEWEB)

    Nami, Faezeh [Department of Chemistry, Shahid Beheshti University, G.C., Evin-Tehran 1983963113 (Iran, Islamic Republic of); Deyhimi, Farzad, E-mail: f-deyhimi@sbu.ac.i [Department of Chemistry, Shahid Beheshti University, G.C., Evin-Tehran 1983963113 (Iran, Islamic Republic of)

    2011-01-15

    To our knowledge, this work illustrates for the first time the ability of artificial neural network (ANN) to predict activity coefficients at infinite dilution for organic solutes in ionic liquids (ILs). Activity coefficient at infinite dilution ({gamma}{sup {infinity}}) is a useful parameter which can be used for the selection of effective solvent in the separation processes. Using a multi-layer feed-forward network with Levenberg-Marquardt optimization algorithm, the resulting ANN model generated activity coefficient at infinite dilution data over a temperature range of 298 to 363 K. The unavailable input data concerning softness (S) of organic compounds (solutes) and dipole moment ({mu}) of ionic liquids were calculated using GAMESS suites of quantum chemistry programs. The resulting ANN model and its validation are based on the investigation of up to 24 structurally different organic compounds (alkanes, alkenes, alkynes, cycloalkanes, aromatics, and alcohols) in 16 common imidazolium-based ionic liquids, at different temperatures within the range of 298 to 363 K (i.e. a total number of 914 {gamma}{sub Solute}{sup {infinity}}for each IL data point). The results show a satisfactory agreement between the predicted ANN and experimental data, where, the root mean square error (RMSE) and the determination coefficient (R{sup 2}) of the designed neural network were found to be 0.103, 0.996 for training data and 0.128, 0.994 for testing data, respectively.

  1. Sensitive red protein calcium indicators for imaging neural activity

    OpenAIRE

    Dana, Hod; Mohar, Boaz; Sun, Yi; Narayan, Sujatha; Gordus, Andrew; Hasseman, Jeremy P; Tsegaye, Getahun; Holt, Graham T.; Hu, Amy; Walpita, Deepika; Patel, Ronak; Macklin, John J.; Bargmann, Cornelia I; Ahrens, Misha B.; Schreiter, Eric R

    2016-01-01

    eLife digest Neurons encode information with brief electrical pulses called spikes. Monitoring spikes in large populations of neurons is a powerful method for studying how networks of neurons process information and produce behavior. This activity can be detected using fluorescent protein indicators, or ?probes?, which light up when neurons are active. The best existing probes produce green fluorescence. However, red fluorescent probes would allow us to see deeper into the brain, and could al...

  2. Deep Recurrent Neural Network for Mobile Human Activity Recognition with High Throughput

    OpenAIRE

    Inoue, Masaya; Inoue, Sozo; Nishida, Takeshi

    2016-01-01

    In this paper, we propose a method of human activity recognition with high throughput from raw accelerometer data applying a deep recurrent neural network (DRNN), and investigate various architectures and its combination to find the best parameter values. The "high throughput" refers to short time at a time of recognition. We investigated various parameters and architectures of the DRNN by using the training dataset of 432 trials with 6 activity classes from 7 people. The maximum recognition ...

  3. Generation of NSE-MerCreMer transgenic mice with tamoxifen inducible Cre activity in neurons.

    Directory of Open Access Journals (Sweden)

    Mandy Ka Man Kam

    Full Text Available To establish a genetic tool for conditional deletion or expression of gene in neurons in a temporally controlled manner, we generated a transgenic mouse (NSE-MerCreMer, which expressed a tamoxifen inducible type of Cre recombinase specifically in neurons. The tamoxifen inducible Cre recombinase (MerCreMer is a fusion protein containing Cre recombinase with two modified estrogen receptor ligand binding domains at both ends, and is driven by the neural-specific rat neural specific enolase (NSE promoter. A total of two transgenic lines were established, and expression of MerCreMer in neurons of the central and enteric nervous systems was confirmed. Transcript of MerCreMer was detected in several non-neural tissues such as heart, liver, and kidney in these lines. In the background of the Cre reporter mouse strain Rosa26R, Cre recombinase activity was inducible in neurons of adult NSE-MerCreMer mice treated with tamoxifen by intragastric gavage, but not in those fed with corn oil only. We conclude that NSE-MerCreMer lines will be useful for studying gene functions in neurons for the conditions that Cre-mediated recombination resulting in embryonic lethality, which precludes investigation of gene functions in neurons through later stages of development and in adult.

  4. Locking of correlated neural activity to ongoing oscillations.

    Directory of Open Access Journals (Sweden)

    Tobias Kühn

    2017-06-01

    Full Text Available Population-wide oscillations are ubiquitously observed in mesoscopic signals of cortical activity. In these network states a global oscillatory cycle modulates the propensity of neurons to fire. Synchronous activation of neurons has been hypothesized to be a separate channel of signal processing information in the brain. A salient question is therefore if and how oscillations interact with spike synchrony and in how far these channels can be considered separate. Experiments indeed showed that correlated spiking co-modulates with the static firing rate and is also tightly locked to the phase of beta-oscillations. While the dependence of correlations on the mean rate is well understood in feed-forward networks, it remains unclear why and by which mechanisms correlations tightly lock to an oscillatory cycle. We here demonstrate that such correlated activation of pairs of neurons is qualitatively explained by periodically-driven random networks. We identify the mechanisms by which covariances depend on a driving periodic stimulus. Mean-field theory combined with linear response theory yields closed-form expressions for the cyclostationary mean activities and pairwise zero-time-lag covariances of binary recurrent random networks. Two distinct mechanisms cause time-dependent covariances: the modulation of the susceptibility of single neurons (via the external input and network feedback and the time-varying variances of single unit activities. For some parameters, the effectively inhibitory recurrent feedback leads to resonant covariances even if mean activities show non-resonant behavior. Our analytical results open the question of time-modulated synchronous activity to a quantitative analysis.

  5. Neural activity in the macaque putamen associated with saccades and behavioral outcome.

    Directory of Open Access Journals (Sweden)

    Jessica M Phillips

    Full Text Available It is now widely accepted that the basal ganglia nuclei form segregated, parallel loops with neocortical areas. The prevalent view is that the putamen is part of the motor loop, which receives inputs from sensorimotor areas, whereas the caudate, which receives inputs from frontal cortical eye fields and projects via the substantia nigra pars reticulata to the superior colliculus, belongs to the oculomotor loop. Tracer studies in monkeys and functional neuroimaging studies in human subjects, however, also suggest a potential role for the putamen in oculomotor control. To investigate the role of the putamen in saccadic eye movements, we recorded single neuron activity in the caudal putamen of two rhesus monkeys while they alternated between short blocks of pro- and anti-saccades. In each trial, the instruction cue was provided after the onset of the peripheral stimulus, thus the monkeys could either generate an immediate response to the stimulus based on the internal representation of the rule from the previous trial, or alternatively, could await the visual rule-instruction cue to guide their saccadic response. We found that a subset of putamen neurons showed saccade-related activity, that the preparatory mode (internally- versus externally-cued influenced the expression of task-selectivity in roughly one third of the task-modulated neurons, and further that a large proportion of neurons encoded the outcome of the saccade. These results suggest that the caudal putamen may be part of the neural network for goal-directed saccades, wherein the monitoring of saccadic eye movements, context and performance feedback may be processed together to ensure optimal behavioural performance and outcomes are achieved during ongoing behaviour.

  6. Neural activations associated with feedback and retrieval success

    Science.gov (United States)

    Wiklund-Hörnqvist, Carola; Andersson, Micael; Jonsson, Bert; Nyberg, Lars

    2017-11-01

    There is substantial behavioral evidence for a phenomenon commonly called "the testing effect", i.e. superior memory performance after repeated testing compared to re-study of to-be-learned materials. However, considerably less is known about the underlying neuro-cognitive processes that are involved in the initial testing phase, and thus underlies the actual testing effect. Here, we investigated functional brain activity related to test-enhanced learning with feedback. Subjects learned foreign vocabulary across three consecutive tests with correct-answer feedback. Functional brain-activity responses were analyzed in relation to retrieval and feedback events, respectively. Results revealed up-regulated activity in fronto-striatal regions during the first successful retrieval, followed by a marked reduction in activity as a function of improved learning. Whereas feedback improved behavioral performance across consecutive tests, feedback had a negligable role after the first successful retrieval for functional brain-activity modulations. It is suggested that the beneficial effects of test-enhanced learning is regulated by feedback-induced updating of memory representations, mediated via the striatum, that might underlie the stabilization of memory commonly seen in behavioral studies of the testing effect.

  7. Rapid regulation of sialidase activity in response to neural activity and sialic acid removal during memory processing in rat hippocampus.

    Science.gov (United States)

    Minami, Akira; Meguro, Yuko; Ishibashi, Sayaka; Ishii, Ami; Shiratori, Mako; Sai, Saki; Horii, Yuuki; Shimizu, Hirotaka; Fukumoto, Hokuto; Shimba, Sumika; Taguchi, Risa; Takahashi, Tadanobu; Otsubo, Tadamune; Ikeda, Kiyoshi; Suzuki, Takashi

    2017-04-07

    Sialidase cleaves sialic acids on the extracellular cell surface as well as inside the cell and is necessary for normal long-term potentiation (LTP) at mossy fiber-CA3 pyramidal cell synapses and for hippocampus-dependent spatial memory. Here, we investigated in detail the role of sialidase in memory processing. Sialidase activity measured with 4-methylumbelliferyl-α-d-N-acetylneuraminic acid (4MU-Neu5Ac) or 5-bromo-4-chloroindol-3-yl-α-d-N-acetylneuraminic acid (X-Neu5Ac) and Fast Red Violet LB was increased by high-K+-induced membrane depolarization. Sialidase activity was also increased by chemical LTP induction with forskolin and activation of BDNF signaling, non-NMDA receptors, or NMDA receptors. The increase in sialidase activity with neural excitation appears to be caused not by secreted sialidase or by an increase in sialidase expression but by a change in the subcellular localization of sialidase. Astrocytes as well as neurons are also involved in the neural activity-dependent increase in sialidase activity. Sialidase activity visualized with a benzothiazolylphenol-based sialic acid derivative (BTP3-Neu5Ac), a highly sensitive histochemical imaging probe for sialidase activity, at the CA3 stratum lucidum of rat acute hippocampal slices was immediately increased in response to LTP-inducible high-frequency stimulation on a time scale of seconds. To obtain direct evidence for sialic acid removal on the extracellular cell surface during neural excitation, the extracellular free sialic acid level in the hippocampus was monitored using in vivo microdialysis. The free sialic acid level was increased by high-K+-induced membrane depolarization. Desialylation also occurred during hippocampus-dependent memory formation in a contextual fear-conditioning paradigm. Our results show that neural activity-dependent desialylation by sialidase may be involved in hippocampal memory processing. © 2017 by The American Society for Biochemistry and Molecular Biology, Inc.

  8. Artificial Neural Networks as an Architectural Design Tool-Generating New Detail Forms Based On the Roman Corinthian Order Capital

    Science.gov (United States)

    Radziszewski, Kacper

    2017-10-01

    The following paper presents the results of the research in the field of the machine learning, investigating the scope of application of the artificial neural networks algorithms as a tool in architectural design. The computational experiment was held using the backward propagation of errors method of training the artificial neural network, which was trained based on the geometry of the details of the Roman Corinthian order capital. During the experiment, as an input training data set, five local geometry parameters combined has given the best results: Theta, Pi, Rho in spherical coordinate system based on the capital volume centroid, followed by Z value of the Cartesian coordinate system and a distance from vertical planes created based on the capital symmetry. Additionally during the experiment, artificial neural network hidden layers optimal count and structure was found, giving results of the error below 0.2% for the mentioned before input parameters. Once successfully trained artificial network, was able to mimic the details composition on any other geometry type given. Despite of calculating the transformed geometry locally and separately for each of the thousands of surface points, system could create visually attractive and diverse, complex patterns. Designed tool, based on the supervised learning method of machine learning, gives possibility of generating new architectural forms- free of the designer’s imagination bounds. Implementing the infinitely broad computational methods of machine learning, or Artificial Intelligence in general, not only could accelerate and simplify the design process, but give an opportunity to explore never seen before, unpredictable forms or everyday architectural practice solutions.

  9. Auto-deleting brain machine interface: Error detection using spiking neural activity in the motor cortex.

    Science.gov (United States)

    Even-Chen, Nir; Stavisky, Sergey D; Kao, Jonathan C; Ryu, Stephen I; Shenoy, Krishna V

    2015-01-01

    Brain machine interfaces (BMIs) aim to assist people with paralysis by increasing their independence and ability to communicate, e.g., by using a cursor-based virtual keyboard. Current BMI clinical trials are hampered by modest performance that causes selection of wrong characters (errors) and thus reduces achieved typing rate. If it were possible to detect these errors without explicit knowledge of the task goal, this could be used to automatically "undo" wrong selections or even prevent upcoming wrong selections. We decoded imminent or recent errors during closed-loop BMI control from intracortical spiking neural activity. In our experiment, a non-human primate controlled a neurally-driven BMI cursor to acquire targets on a grid, which simulates a virtual keyboard. In offline analyses of this closed-loop BMI control data, we identified motor cortical neural signals indicative of task error occurrence. We were able to detect task outcomes (97% accuracy) and even predict upcoming task outcomes (86% accuracy) using neural activity alone. This novel strategy may help increase the performance and clinical viability of BMIs.

  10. Artificial neural Network-Based modeling and monitoring of photovoltaic generator

    Directory of Open Access Journals (Sweden)

    H. MEKKI

    2015-03-01

    Full Text Available In this paper, an artificial neural network based-model (ANNBM is introduced for partial shading detection losses in photovoltaic (PV panel. A Multilayer Perceptron (MLP is used to estimate the electrical outputs (current and voltage of the photovoltaic module using the external meteorological data: solar irradiation G (W/m2 and the module temperature T (°C. Firstly, a database of the BP150SX photovoltaic module operating without any defect has been used to train the considered MLP. Subsequently, in the first case of this study, the developed model is used to estimate the output current and voltage of the PV module considering the partial shading effect. Results confirm the good ability of the ANNBM to detect the partial shading effect in the photovoltaic module with logical accuracy. The proposed strategy could also be used for the online monitoring and supervision of PV modules.

  11. Generating Alignments Using Target Foresight in Attention-Based Neural Machine Translation

    Directory of Open Access Journals (Sweden)

    Peter Jan-Thorsten

    2017-06-01

    Full Text Available Neural machine translation (NMT has shown large improvements in recent years. The currently most successful approach in this area relies on the attention mechanism, which is often interpreted as an alignment, even though it is computed without explicit knowledge of the target word. This limitation is the most likely reason that the quality of attention-based alignments is inferior to the quality of traditional alignment methods. Guided alignment training has shown that alignments are still capable of improving translation quality. In this work, we propose an extension of the attention-based NMT model that introduces target information into the attention mechanism to produce high-quality alignments. In comparison to the conventional attention-based alignments, our model halves the Aer with an absolute improvement of 19.1% Aer. Compared to GIZA++ it shows an absolute improvement of 2.0% Aer.

  12. Exposure to GDNF Enhances the Ability of Enteric Neural Progenitors to Generate an Enteric Nervous System

    Directory of Open Access Journals (Sweden)

    Sonja J. McKeown

    2017-02-01

    Full Text Available Cell therapy is a promising approach to generate an enteric nervous system (ENS and treat enteric neuropathies. However, for translation to the clinic, it is highly likely that enteric neural progenitors will require manipulation prior to transplantation to enhance their ability to migrate and generate an ENS. In this study, we examine the effects of exposure to several factors on the ability of ENS progenitors, grown as enteric neurospheres, to migrate and generate an ENS. Exposure to glial-cell-line-derived neurotrophic factor (GDNF resulted in a 14-fold increase in neurosphere volume and a 12-fold increase in cell number. Following co-culture with embryonic gut or transplantation into the colon of postnatal mice in vivo, cells derived from GDNF-treated neurospheres showed a 2-fold increase in the distance migrated compared with controls. Our data show that the ability of enteric neurospheres to generate an ENS can be enhanced by exposure to appropriate factors.

  13. Neural activities during affective processing in people with Alzheimer's disease

    NARCIS (Netherlands)

    Lee, Tatia M. C.; Sun, Delin; Leung, Mei-Kei; Chu, Leung-Wing; Keysers, Christian

    This study examined brain activities in people with Alzheimer's disease when viewing happy, sad, and fearful facial expressions of others. A functional magnetic resonance imaging and a voxel-based morphometry methodology together with a passive viewing of emotional faces paradigm were employed to

  14. Concurrent multitasking : From neural activity to human cognition

    NARCIS (Netherlands)

    Nijboer, Menno

    2016-01-01

    Multitasking has become an important part of our daily lives. This delicate juggling act between several activities occurs when people drive, when they are working, and even when they should be paying attention in the classroom. While multitasking is typically considered as something to avoid, there

  15. Video-based convolutional neural networks for activity recognition from robot-centric videos

    Science.gov (United States)

    Ryoo, M. S.; Matthies, Larry

    2016-05-01

    In this evaluation paper, we discuss convolutional neural network (CNN)-based approaches for human activity recognition. In particular, we investigate CNN architectures designed to capture temporal information in videos and their applications to the human activity recognition problem. There have been multiple previous works to use CNN-features for videos. These include CNNs using 3-D XYT convolutional filters, CNNs using pooling operations on top of per-frame image-based CNN descriptors, and recurrent neural networks to learn temporal changes in per-frame CNN descriptors. We experimentally compare some of these different representatives CNNs while using first-person human activity videos. We especially focus on videos from a robots viewpoint, captured during its operations and human-robot interactions.

  16. Model Integrating Fuzzy Argument with Neural Network Enhancing the Performance of Active Queue Management

    Directory of Open Access Journals (Sweden)

    Nguyen Kim Quoc

    2015-08-01

    Full Text Available The bottleneck control by active queue management mechanisms at network nodes is essential. In recent years, some researchers have used fuzzy argument to improve the active queue management mechanisms to enhance the network performance. However, the projects using the fuzzy controller depend heavily on professionals and their parameters cannot be updated according to changes in the network, so the effectiveness of this mechanism is not high. Therefore, we propose a model combining the fuzzy controller with neural network (FNN to overcome the limitations above. Results of the training of the neural networks will find the optimal parameters for the adaptive fuzzy controller well to changes of the network. This improves the operational efficiency of the active queue management mechanisms at network nodes.

  17. Differential neural activation when voluntarily regulating emotions in service members with chronic mild traumatic brain injury.

    Science.gov (United States)

    Dretsch, Michael N; Daniel, Thomas A; Goodman, Adam M; Katz, Jeffrey S; Denney, Thomas; Deshpande, Gopikrishna; Robinson, Jennifer L

    2017-09-19

    The objective of this study was to characterize the functional activation of the neural correlates of voluntary regulation of emotion in soldiers both with and without chronic mild traumatic brain injury (mTBI). Using functional magnetic resonance imaging (fMRI) and a battery of cognitive and psychological health measures, we assessed differences between active-duty U.S. soldiers with chronic mTBI (n = 37) and without (Controls, n = 35). Participants were instructed to maintain (passively view), enhance, and suppress emotions associated with negative and neutral visual stimuli. The mTBI group showed significantly greater clinical symptoms, but only a mild decrement in attention. Group contrasts, while controlling for posttraumatic stress disorder (PTSD) symptoms, revealed a differential neural activation pattern compared to controls, but only during the enhance condition. Specifically, the mTBI group showed greater activation in the precentral gyrus, postcentral gyrus, inferior parietal lobe, insula, and superior temporal gyrus. Finally, the effect of PTSD symptoms during the enhance condition was associated with accentuated activation of the frontal and limbic regions implicated in both emotion regulation and PTSD. Hyperactivation of neural regions in the mTBI group during the enhance condition may reflect vigilance towards negative contextual stimuli and/or poor strategy that might result in suboptimal allocation of resources to regulate emotions.

  18. Age-related shift in neural complexity related to task performance and physical activity.

    Science.gov (United States)

    Heisz, Jennifer J; Gould, Michelle; McIntosh, Anthony R

    2015-03-01

    The human brain undergoes marked structural changes with age including cortical thinning and reduced connectivity because of the degradation of myelin. Although these changes can compromise cognitive function, the brain is able to functionally reorganize to compensate for some of this structural loss. However, there are interesting individual differences in outcome: When comparing individuals of similar age, those who engage in regular physical activity are less affected by the typical age-related decline in cognitive function. This study used multiscale entropy to reveal a shift in the way the brain processes information in older adults that is related to physical activity. Specifically, older adults who were more physically active engaged in more local neural information processing. Interestingly, this shift toward local information processing was also associated with improved executive function performance in older adults, suggesting that physical activity may help to improve aspects of cognitive function in older adults by biasing the neural system toward local information processing. In the face of age-related structural decline, the neural plasticity that is enhanced through physical activity may help older adults maintain cognitive health longer into their lifespan.

  19. Emergent Public Spaces: Generative Activities on Function Interpolation

    Science.gov (United States)

    Carmona, Guadalupe; Dominguez, Angeles; Krause, Gladys; Duran, Pablo

    2011-01-01

    This study highlights ways in which generative activities may be coupled with network-based technologies in the context of teacher preparation to enhance preservice teachers' cognizance of how their own experience as students provides a blueprint for the learning environments they may need to generate in their future classrooms. In this study, the…

  20. An Analysis of Generational Differences Among Active Duty Members

    Science.gov (United States)

    2004-03-01

    DIFFERENCES AMONG ACTIVE DUTY MEMBERS THESIS Presented to the Faculty Department of Systems and Engineering Management Graduate School of...generations of Air Force members and the affects these potential differences have on leadership strategies. Hypotheses were developed based on generational...life. Clearly, these observed differences have implications for managers and leaders. Actions taken by leaders (who are often older) might be

  1. What are the odds? The neural correlates of active choice during gambling

    Directory of Open Access Journals (Sweden)

    Bettina eStuder

    2012-04-01

    Full Text Available Gambling is a widespread recreational activity and requires pitting the values of potential wins and losses against their probability of occurrence. Neuropsychological research showed that betting behavior on laboratory gambling tasks is highly sensitive to focal lesions to the ventromedial prefrontal cortex (vmPFC and insula. In the current study, we assessed the neural basis of betting choices in healthy participants, using functional magnetic resonance imaging of the Roulette Betting Task. In half of the trials participants actively chose their bets; in the other half the computer dictated the bet size. Our results highlight the impact of volitional choice upon the neural substrates of gambling: Neural activity in a distributed network - including key structures of the reward circuitry (midbrain, striatum - was higher during active compared to computer-dictated bet selection. In line with neuropsychological data, the anterior insula and vmPFC were more activated during self-directed bet selection, and responses in these areas were differentially modulated by the odds of winning in the two choice conditions. In addition, responses in the vmPFC and ventral striatum were modulated by the bet size. Convergent with electrophysiological research in macaques, our results further implicate the inferior parietal cortex (IPC in the processing of the likelihood of potential outcomes: Neural responses in the IPC bilaterally reflected the probability of winning during bet selection. Moreover, the IPC was particularly sensitive to the odds of winning in the active choice condition, where this information was used to guide bet selection. Our results indicate a neglected role of the IPC in human decision-making under risk and help to integrate neuropsychological data of risk-taking following vmPFC and insula damage with models of choice derived from human neuroimaging and monkey electrophysiology.

  2. Optimal Recognition Method of Human Activities Using Artificial Neural Networks

    Directory of Open Access Journals (Sweden)

    Oniga Stefan

    2015-12-01

    Full Text Available The aim of this research is an exhaustive analysis of the various factors that may influence the recognition rate of the human activity using wearable sensors data. We made a total of 1674 simulations on a publically released human activity database by a group of researcher from the University of California at Berkeley. In a previous research, we analyzed the influence of the number of sensors and their placement. In the present research we have examined the influence of the number of sensor nodes, the type of sensor node, preprocessing algorithms, type of classifier and its parameters. The final purpose is to find the optimal setup for best recognition rates with lowest hardware and software costs.

  3. Environmental layout complexity affects neural activity during navigation in humans.

    Science.gov (United States)

    Slone, Edward; Burles, Ford; Iaria, Giuseppe

    2016-05-01

    Navigating large-scale surroundings is a fundamental ability. In humans, it is commonly assumed that navigational performance is affected by individual differences, such as age, sex, and cognitive strategies adopted for orientation. We recently showed that the layout of the environment itself also influences how well people are able to find their way within it, yet it remains unclear whether differences in environmental complexity are associated with changes in brain activity during navigation. We used functional magnetic resonance imaging to investigate how the brain responds to a change in environmental complexity by asking participants to perform a navigation task in two large-scale virtual environments that differed solely in interconnection density, a measure of complexity defined as the average number of directional choices at decision points. The results showed that navigation in the simpler, less interconnected environment was faster and more accurate relative to the complex environment, and such performance was associated with increased activity in a number of brain areas (i.e. precuneus, retrosplenial cortex, and hippocampus) known to be involved in mental imagery, navigation, and memory. These findings provide novel evidence that environmental complexity not only affects navigational behaviour, but also modulates activity in brain regions that are important for successful orientation and navigation. © 2016 Federation of European Neuroscience Societies and John Wiley & Sons Ltd.

  4. Alternative Sensor System and MLP Neural Network for Vehicle Pedal Activity Estimation

    Directory of Open Access Journals (Sweden)

    Ahmed M. Wefky

    2010-04-01

    Full Text Available It is accepted that the activity of the vehicle pedals (i.e., throttle, brake, clutch reflects the driver’s behavior, which is at least partially related to the fuel consumption and vehicle pollutant emissions. This paper presents a solution to estimate the driver activity regardless of the type, model, and year of fabrication of the vehicle. The solution is based on an alternative sensor system (regime engine, vehicle speed, frontal inclination and linear acceleration that reflects the activity of the pedals in an indirect way, to estimate that activity by means of a multilayer perceptron neural network with a single hidden layer.

  5. Implications of the Dependence of Neuronal Activity on Neural Network States for the Design of Brain-Machine Interfaces.

    Science.gov (United States)

    Panzeri, Stefano; Safaai, Houman; De Feo, Vito; Vato, Alessandro

    2016-01-01

    Brain-machine interfaces (BMIs) can improve the quality of life of patients with sensory and motor disabilities by both decoding motor intentions expressed by neural activity, and by encoding artificially sensed information into patterns of neural activity elicited by causal interventions on the neural tissue. Yet, current BMIs can exchange relatively small amounts of information with the brain. This problem has proved difficult to overcome by simply increasing the number of recording or stimulating electrodes, because trial-to-trial variability of neural activity partly arises from intrinsic factors (collectively known as the network state) that include ongoing spontaneous activity and neuromodulation, and so is shared among neurons. Here we review recent progress in characterizing the state dependence of neural responses, and in particular of how neural responses depend on endogenous slow fluctuations of network excitability. We then elaborate on how this knowledge may be used to increase the amount of information that BMIs exchange with brain. Knowledge of network state can be used to fine-tune the stimulation pattern that should reliably elicit a target neural response used to encode information in the brain, and to discount part of the trial-by-trial variability of neural responses, so that they can be decoded more accurately.

  6. Implications of the dependence of neuronal activity on neural network states for the design of brain-machine interfaces

    Directory of Open Access Journals (Sweden)

    Stefano ePanzeri

    2016-04-01

    Full Text Available Brain-machine interfaces (BMIs can improve the quality of life of patients with sensory and motor disabilities by both decoding motor intentions expressed by neural activity, and by encoding artificially sensed information into patterns of neural activity elicited by causal interventions on the neural tissue. Yet, current BMIs can exchange relatively small amounts of information with the brain. This problem has proved difficult to overcome by simply increasing the number of recording or stimulating electrodes, because trial-to-trial variability of neural activity partly arises from intrinsic factors (collectively known as the network state that include ongoing spontaneous activity and neuromodulation, and so is shared among neurons. Here we review recent progress in characterizing the state dependence of neural responses, and in particular of how neural responses depend on endogenous slow fluctuations of network excitability. We then elaborate on how this knowledge may be used to increase the amount of information that BMIs exchange with brains. Knowledge of network state can be used to fine-tune the stimulation pattern that should reliably elicit a target neural response used to encode information in the brain, and to discount part of the trial-by-trial variability of neural responses, so that they can be decoded more accurately.

  7. Placebo-Activated Neural Systems are Linked to Antidepressant Responses

    Science.gov (United States)

    Peciña, Marta; Bohnert, Amy S. B.; Sikora, Magdalena; Avery, Erich T.; Langenecker, Scott A.; Mickey, Brian J.; Zubieta, Jon-Kar

    2016-01-01

    Importance High placebo responses have been observed across a wide range of pathologies, severely impacting drug development. Objective Here we examined neurochemical mechanisms underlying the formation of placebo effects in patients with Major Depressive Disorder (MDD). Participants Thirty-five medication-free MDD patients. Design and Intervention We performed a single-blinded two-week cross-over randomized controlled trial of two identical oral placebos (described as having either “active” or “inactive” fast-acting antidepressant-like effects) followed by a 10-week open-label treatment with a selective serotonin reuptake inhibitor (SSRI) or in some cases, another agent as clinically indicated. The volunteers were studied with PET and the μ-opioid receptor (MOR)-selective radiotracer [11C]carfentanil after each 1-week “inactive” and “active” oral placebo treatment. In addition, 1 mL of isotonic saline was administered intravenously (i.v.) within sight of the volunteer during PET scanning every 4 min over 20 min only after the 1-week active placebo treatment, with instructions that the compound may be associated with the activation of brain systems involved in mood improvement. This challenge stimulus was utilized to test the individual capacity to acutely activate endogenous opioid neurotransmision under expectations of antidepressant effect. Setting A University Health System. Main Outcomes and Measures Changes in depressive symptoms in response to “active” placebo and antidepressant. Baseline and activation measures of MOR binding. Results Higher baseline MOR binding in the nucleus accumbens (NAc) was associated with better response to antidepressant treatment (r=0.48; p=0.02). Reductions in depressive symptoms after 1-week of “active” placebo treatment, compared to the “inactive”, were associated with increased placebo-induced μ-opioid neurotransmission in a network of regions implicated in emotion, stress regulation, and the

  8. Acute stress evokes sexually dimorphic, stressor-specific patterns of neural activation across multiple limbic brain regions in adult rats.

    Science.gov (United States)

    Sood, Ankit; Chaudhari, Karina; Vaidya, Vidita A

    2018-03-01

    Stress enhances the risk for psychiatric disorders such as anxiety and depression. Stress responses vary across sex and may underlie the heightened vulnerability to psychopathology in females. Here, we examined the influence of acute immobilization stress (AIS) and a two-day short-term forced swim stress (FS) on neural activation in multiple cortical and subcortical brain regions, implicated as targets of stress and in the regulation of neuroendocrine stress responses, in male and female rats using Fos as a neural activity marker. AIS evoked a sex-dependent pattern of neural activation within the cingulate and infralimbic subdivisions of the medial prefrontal cortex (mPFC), lateral septum (LS), habenula, and hippocampal subfields. The degree of neural activation in the mPFC, LS, and habenula was higher in males. Female rats exhibited reduced Fos positive cell numbers in the dentate gyrus hippocampal subfield, an effect not observed in males. We addressed whether the sexually dimorphic neural activation pattern noted following AIS was also observed with the short-term stress of FS. In the paraventricular nucleus of the hypothalamus and the amygdala, FS similar to AIS resulted in robust increases in neural activation in both sexes. The pattern of neural activation evoked by FS was distinct across sexes, with a heightened neural activation noted in the prelimbic mPFC subdivision and hippocampal subfields in females and differed from the pattern noted with AIS. This indicates that the sex differences in neural activation patterns observed within stress-responsive brain regions are dependent on the nature of stressor experience.

  9. Application of computational neural networks in predicting atmospheric pollutant concentrations due to fossil-fired electric power generation

    Energy Technology Data Exchange (ETDEWEB)

    El-Hawary, F. [BH Engineering Systems & Technical Univ. of Nova Scotia (Canada)

    1995-12-31

    The ability to accurately predict the behavior of a dynamic system is of essential importance in monitoring and control of complex processes. In this regard recent advances in neural-net based system identification represent a significant step toward development and design of a new generation of control tools for increased system performance and reliability. The enabling functionality is the one of accurate representation of a model of a nonlinear and nonstationary dynamic system. This functionality provides valuable new opportunities including: (1) The ability to predict future system behavior on the basis of actual system observations, (2) On-line evaluation and display of system performance and design of early warning systems, and (3) Controller optimization for improved system performance. In this presentation, we discuss the issues involved in definition and design of learning control systems and their impact on power system control. Several numerical examples are provided for illustrative purpose.

  10. Neural Network based Control of SG based Standalone Generating System with Energy Storage for Power Quality Enhancement

    Science.gov (United States)

    Nayar, Priya; Singh, Bhim; Mishra, Sukumar

    2017-08-01

    An artificial intelligence based control algorithm is used in solving power quality problems of a diesel engine driven synchronous generator with automatic voltage regulator and governor based standalone system. A voltage source converter integrated with a battery energy storage system is employed to mitigate the power quality problems. An adaptive neural network based signed regressor control algorithm is used for the estimation of the fundamental component of load currents for control of a standalone system with load leveling as an integral feature. The developed model of the system performs accurately under varying load conditions and provides good dynamic response to the step changes in loads. The real time performance is achieved using MATLAB along with simulink/simpower system toolboxes and results adhere to an IEEE-519 standard for power quality enhancement.

  11. Real time selective harmonic minimization for multilevel inverters using genetic algorithm and artifical neural network angle generation

    Energy Technology Data Exchange (ETDEWEB)

    Filho, Faete J [ORNL; Tolbert, Leon M [ORNL; Ozpineci, Burak [ORNL

    2012-01-01

    The work developed here proposes a methodology for calculating switching angles for varying DC sources in a multilevel cascaded H-bridges converter. In this approach the required fundamental is achieved, the lower harmonics are minimized, and the system can be implemented in real time with low memory requirements. Genetic algorithm (GA) is the stochastic search method to find the solution for the set of equations where the input voltages are the known variables and the switching angles are the unknown variables. With the dataset generated by GA, an artificial neural network (ANN) is trained to store the solutions without excessive memory storage requirements. This trained ANN then senses the voltage of each cell and produces the switching angles in order to regulate the fundamental at 120 V and eliminate or minimize the low order harmonics while operating in real time.

  12. Neural regulation of interdigestive motor activity in canine jejunum.

    Science.gov (United States)

    Itoh, Z; Aizawa, I; Takeuchi, S

    1981-04-01

    The hypothesis that extrinsic innervation of the small bowel provides pathways for initiation and coordinated propagation of the interdigestive migrating contractions (IMC) was reinvestigated in dogs. Motor activity was measured by chronically implanted force transducers. After a control study, 40-cm segments of the jejunum were extrinsically denervated. All IMC migrated distally through the extrinsically denervated segments. Thiry loops were then constructed from the extrinsically denervated segments, and continuity of the intestine was restored by end-to-end anastomosis. IMC proximal to the anastomosis did not migrate through the extrinsically denervated loop but migrated to sites across the anastomosis. In the extrinsically denervated loop, bands of strong contractions, quite similar to the IMC, occurred at the orad end of the loop independent of the IMC and propagated distally to the caudad end of the loop. The duration, frequency, and migrating velocity of these bands of contraction were different from those of IMC. These results suggest that extrinsic innervation is not essential for the initiation and orad sequential propagation of periodic motor activity like IMC, even when intrinsic innervation is discontinued.

  13. Differences in neural activity when processing emotional arousal and valence in autism spectrum disorders.

    Science.gov (United States)

    Tseng, Angela; Wang, Zhishun; Huo, Yuankai; Goh, Suzanne; Russell, James A; Peterson, Bradley S

    2016-02-01

    Individuals with autism spectrum disorders (ASD) often have difficulty recognizing and interpreting facial expressions of emotion, which may impair their ability to navigate and communicate successfully in their social, interpersonal environments. Characterizing specific differences between individuals with ASD and their typically developing (TD) counterparts in the neural activity subserving their experience of emotional faces may provide distinct targets for ASD interventions. Thus we used functional magnetic resonance imaging (fMRI) and a parametric experimental design to identify brain regions in which neural activity correlated with ratings of arousal and valence for a broad range of emotional faces. Participants (51 ASD, 84 TD) were group-matched by age, sex, IQ, race, and socioeconomic status. Using task-related change in blood-oxygen-level-dependent (BOLD) fMRI signal as a measure, and covarying for age, sex, FSIQ, and ADOS scores, we detected significant differences across diagnostic groups in the neural activity subserving the dimension of arousal but not valence. BOLD-signal in TD participants correlated inversely with ratings of arousal in regions associated primarily with attentional functions, whereas BOLD-signal in ASD participants correlated positively with arousal ratings in regions commonly associated with impulse control and default-mode activity. Only minor differences were detected between groups in the BOLD signal correlates of valence ratings. Our findings provide unique insight into the emotional experiences of individuals with ASD. Although behavioral responses to face-stimuli were comparable across diagnostic groups, the corresponding neural activity for our ASD and TD groups differed dramatically. The near absence of group differences for valence correlates and the presence of strong group differences for arousal correlates suggest that individuals with ASD are not atypical in all aspects of emotion-processing. Studying these similarities

  14. Relation of obesity to neural activation in response to food commercials

    Science.gov (United States)

    Yokum, Sonja; Stice, Eric; Harris, Jennifer L.; Brownell, Kelly D.

    2014-01-01

    Adolescents view thousands of food commercials annually, but the neural response to food advertising and its association with obesity is largely unknown. This study is the first to examine how neural response to food commercials differs from other stimuli (e.g. non-food commercials and television show) and to explore how this response may differ by weight status. The blood oxygen level-dependent functional magnetic resonance imaging activation was measured in 30 adolescents ranging from lean to obese in response to food and non-food commercials imbedded in a television show. Adolescents exhibited greater activation in regions implicated in visual processing (e.g. occipital gyrus), attention (e.g. parietal lobes), cognition (e.g. temporal gyrus and posterior cerebellar lobe), movement (e.g. anterior cerebellar cortex), somatosensory response (e.g. postcentral gyrus) and reward [e.g. orbitofrontal cortex and anterior cingulate cortex (ACC)] during food commercials. Obese participants exhibited less activation during food relative to non-food commercials in neural regions implicated in visual processing (e.g. cuneus), attention (e.g. posterior cerebellar lobe), reward (e.g. ventromedial prefrontal cortex and ACC) and salience detection (e.g. precuneus). Obese participants did exhibit greater activation in a region implicated in semantic control (e.g. medial temporal gyrus). These findings may inform current policy debates regarding the impact of food advertising to minors. PMID:23576811

  15. Young Adults with Autism Spectrum Disorder Show Early Atypical Neural Activity during Emotional Face Processing

    Directory of Open Access Journals (Sweden)

    Rachel C. Leung

    2018-02-01

    Full Text Available Social cognition is impaired in autism spectrum disorder (ASD. The ability to perceive and interpret affect is integral to successful social functioning and has an extended developmental course. However, the neural mechanisms underlying emotional face processing in ASD are unclear. Using magnetoencephalography (MEG, the present study explored neural activation during implicit emotional face processing in young adults with and without ASD. Twenty-six young adults with ASD and 26 healthy controls were recruited. Participants indicated the location of a scrambled pattern (target that was presented alongside a happy or angry face. Emotion-related activation sources for each emotion were estimated using the Empirical Bayes Beamformer (pcorr ≤ 0.001 in Statistical Parametric Mapping 12 (SPM12. Emotional faces elicited elevated fusiform, amygdala and anterior insula and reduced anterior cingulate cortex (ACC activity in adults with ASD relative to controls. Within group comparisons revealed that angry vs. happy faces elicited distinct neural activity in typically developing adults; there was no distinction in young adults with ASD. Our data suggest difficulties in affect processing in ASD reflect atypical recruitment of traditional emotional processing areas. These early differences may contribute to difficulties in deriving social reward from faces, ascribing salience to faces, and an immature threat processing system, which collectively could result in deficits in emotional face processing.

  16. Separating neural activity associated with emotion and implied motion: An fMRI study.

    Science.gov (United States)

    Kolesar, Tiffany A; Kornelsen, Jennifer; Smith, Stephen D

    2017-02-01

    Previous research provides evidence for an emo-motoric neural network allowing emotion to modulate activity in regions of the nervous system related to movement. However, recent research suggests that these results may be due to the movement depicted in the stimuli. The purpose of the current study was to differentiate the unique neural activity of emotion and implied motion using functional MRI. Thirteen healthy participants viewed 4 sets of images: (a) negative stimuli implying movement, (b) negative stimuli not implying movement, (c) neutral stimuli implying movement, and (d) neutral stimuli not implying movement. A main effect for implied motion was found, primarily in regions associated with multimodal integration (bilateral insula and cingulate), and visual areas that process motion (bilateral middle temporal gyrus). A main effect for emotion was found primarily in occipital and parietal regions, indicating that emotion enhances visual perception. Surprisingly, emotion also activated the left precentral gyrus, a motor region. These results demonstrate that emotion elicits activity above and beyond that evoked by the perception of implied movement, but that the neural representations of these characteristics overlap. (PsycINFO Database Record (c) 2017 APA, all rights reserved).

  17. Two-photon imaging of cerebral hemodynamics and neural activity in awake and anesthetized marmosets.

    Science.gov (United States)

    Santisakultarm, Thom P; Kersbergen, Calvin J; Bandy, Daryl K; Ide, David C; Choi, Sang-Ho; Silva, Afonso C

    2016-09-15

    Marmosets are a powerful, emerging model for human behavior and neurological disorders. However, longitudinal imaging modalities that visualize both cellular structure and function within the cortex are not available in this animal model. Hence, we implemented an approach to quantify vascular topology, hemodynamics, and neural activity in awake marmosets using two-photon microscopy (2PM). Marmosets were acclimated to a custom stereotaxic system. AAV1-GCaMP5G was injected into somatosensory cortex to optically indicate neural activity, and a cranial chamber was implanted. Longitudinal 2PM revealed vasculature and neurons 500μm below the cortical surface. Vascular response and neural activity during sensory stimulation were preserved over 5 and 3 months, respectively, before optical quality deteriorated. Vascular remodeling including increased tortuosity and branching was quantified. However, capillary connectivity from arterioles to venules remained unchanged. Further, behavioral assessment before and after surgery demonstrated no impact on cognitive and motor function. Immunohistochemistry confirmed minimal astrocyte activation with no focal damage. Over 6 months, total cortical depth visualized decreased. When under anesthesia, the most prominent isoflurane-induced vasodilation occurred in capillaries and smaller arterioles. These results demonstrate the capability to repeatedly observe cortical physiology in awake marmosets over months. This work provides a novel and insightful technique to investigate critical mechanisms in neurological disorders in awake marmosets without introducing confounds from anesthesia. Published by Elsevier B.V.

  18. Relation of obesity to neural activation in response to food commercials.

    Science.gov (United States)

    Gearhardt, Ashley N; Yokum, Sonja; Stice, Eric; Harris, Jennifer L; Brownell, Kelly D

    2014-07-01

    Adolescents view thousands of food commercials annually, but the neural response to food advertising and its association with obesity is largely unknown. This study is the first to examine how neural response to food commercials differs from other stimuli (e.g. non-food commercials and television show) and to explore how this response may differ by weight status. The blood oxygen level-dependent functional magnetic resonance imaging activation was measured in 30 adolescents ranging from lean to obese in response to food and non-food commercials imbedded in a television show. Adolescents exhibited greater activation in regions implicated in visual processing (e.g. occipital gyrus), attention (e.g. parietal lobes), cognition (e.g. temporal gyrus and posterior cerebellar lobe), movement (e.g. anterior cerebellar cortex), somatosensory response (e.g. postcentral gyrus) and reward [e.g. orbitofrontal cortex and anterior cingulate cortex (ACC)] during food commercials. Obese participants exhibited less activation during food relative to non-food commercials in neural regions implicated in visual processing (e.g. cuneus), attention (e.g. posterior cerebellar lobe), reward (e.g. ventromedial prefrontal cortex and ACC) and salience detection (e.g. precuneus). Obese participants did exhibit greater activation in a region implicated in semantic control (e.g. medial temporal gyrus). These findings may inform current policy debates regarding the impact of food advertising to minors. © The Author (2013). Published by Oxford University Press. For Permissions, please email: journals.permissions@oup.com.

  19. Deep neural nets as a method for quantitative structure-activity relationships.

    Science.gov (United States)

    Ma, Junshui; Sheridan, Robert P; Liaw, Andy; Dahl, George E; Svetnik, Vladimir

    2015-02-23

    Neural networks were widely used for quantitative structure-activity relationships (QSAR) in the 1990s. Because of various practical issues (e.g., slow on large problems, difficult to train, prone to overfitting, etc.), they were superseded by more robust methods like support vector machine (SVM) and random forest (RF), which arose in the early 2000s. The last 10 years has witnessed a revival of neural networks in the machine learning community thanks to new methods for preventing overfitting, more efficient training algorithms, and advancements in computer hardware. In particular, deep neural nets (DNNs), i.e. neural nets with more than one hidden layer, have found great successes in many applications, such as computer vision and natural language processing. Here we show that DNNs can routinely make better prospective predictions than RF on a set of large diverse QSAR data sets that are taken from Merck's drug discovery effort. The number of adjustable parameters needed for DNNs is fairly large, but our results show that it is not necessary to optimize them for individual data sets, and a single set of recommended parameters can achieve better performance than RF for most of the data sets we studied. The usefulness of the parameters is demonstrated on additional data sets not used in the calibration. Although training DNNs is still computationally intensive, using graphical processing units (GPUs) can make this issue manageable.

  20. Acupuncture stimulation on GB34 activates neural responses associated with Parkinson's disease.

    Science.gov (United States)

    Yeo, Sujung; Lim, Sabina; Choe, Il-Hwan; Choi, Yeong-Gon; Chung, Kyung-Cheon; Jahng, Geon-Ho; Kim, Sung-Hoon

    2012-09-01

    Parkinson's disease (PD) is a degenerative brain disorder that is caused by neural defects in the substantia nigra. Numerous studies have reported that acupuncture treatment on GB34 (Yanglingquan) leads to significant improvements in patients with PD and in PD animal models. Studies using functional magnetic resonance imaging (fMRI) have shown that patients with PD, compared to healthy participants, have lower neural responses in extensive brain regions including the putamen, thalamus, and the supplementary motor area. This study investigated the reported association between acupuncture point GB34 and PD. Using fMRI, neural responses of 12 patients with PD and 12 healthy participants were examined before and after acupuncture stimulation. Acupuncture stimulation increased neural responses in regions including the substantia nigra, caudate, thalamus, and putamen, which are impaired caused by PD. Areas associated with PD were activated by the acupuncture stimulation on GB34. This shows that acupuncture treatment on GB34 may be effective in improving the symptoms of PD. Although more randomized controlled trials on the topic will be needed, this study shows that acupuncture may be helpful in the treatment of symptoms involving PD. © 2012 Blackwell Publishing Ltd.

  1. Abnormal Task Modulation of Oscillatory Neural Activity in Schizophrenia

    Directory of Open Access Journals (Sweden)

    Elisa C Dias

    2013-08-01

    Full Text Available Schizophrenia patients have deficits in cognitive function that are a core feature of the disorder. AX-CPT is commonly used to study cognition in schizophrenia, and patients have characteristic pattern of behavioral and ERP response. In AX-CPT subjects respond when a flashed cue A is followed by a target X, ignoring other letter combinations. Patients show reduced hit rate to go trials, and increased false alarms to sequences that require inhibition of a prepotent response. EEG recordings show reduced sensory (P1/N1, as well as later cognitive components (N2, P3, CNV. Behavioral deficits correlate most strongly with sensory dysfunction. Oscillatory analyses provide critical information regarding sensory/cognitive processing over and above standard ERP analyses. Recent analyses of induced oscillatory activity in single trials during AX-CPT in healthy volunteers showed characteristic response patterns in theta, alpha and beta frequencies tied to specific sensory and cognitive processes. Alpha and beta modulated during the trials and beta modulation over the frontal cortex correlated with reaction time. In this study, EEG data was obtained from 18 schizophrenia patients and 13 controls during AX-CPT performance, and single trial decomposition of the signal yielded power in the target wavelengths.Significant task-related event-related desynchronization (ERD was observed in both alpha and beta frequency bands over parieto-occipital cortex related to sensory encoding of the cue. This modulation was reduced in patients for beta, but not for alpha. In addition, significant beta ERD was observed over motor cortex, related to motor preparation for the response, and was also reduced in patients. These findings demonstrate impaired dynamic modulation of beta frequency rhythms in schizophrenia, and suggest that failures of oscillatory activity may underlie impaired sensory information processing in schizophrenia that in turn contributes to cognitive deficits.

  2. Wind Turbine Driving a PM Synchronous Generator Using Novel Recurrent Chebyshev Neural Network Control with the Ideal Learning Rate

    Directory of Open Access Journals (Sweden)

    Chih-Hong Lin

    2016-06-01

    Full Text Available A permanent magnet (PM synchronous generator system driven by wind turbine (WT, connected with smart grid via AC-DC converter and DC-AC converter, are controlled by the novel recurrent Chebyshev neural network (NN and amended particle swarm optimization (PSO to regulate output power and output voltage in two power converters in this study. Because a PM synchronous generator system driven by WT is an unknown non-linear and time-varying dynamic system, the on-line training novel recurrent Chebyshev NN control system is developed to regulate DC voltage of the AC-DC converter and AC voltage of the DC-AC converter connected with smart grid. Furthermore, the variable learning rate of the novel recurrent Chebyshev NN is regulated according to discrete-type Lyapunov function for improving the control performance and enhancing convergent speed. Finally, some experimental results are shown to verify the effectiveness of the proposed control method for a WT driving a PM synchronous generator system in smart grid.

  3. Neural plasticity and proliferation in the generation of antidepressant effects: hippocampal implication.

    Science.gov (United States)

    Pilar-Cuéllar, Fuencisla; Vidal, Rebeca; Díaz, Alvaro; Castro, Elena; dos Anjos, Severiano; Pascual-Brazo, Jesús; Linge, Raquel; Vargas, Veronica; Blanco, Helena; Martínez-Villayandre, Beatriz; Pazos, Ángel; Valdizán, Elsa M

    2013-01-01

    It is widely accepted that changes underlying depression and antidepressant-like effects involve not only alterations in the levels of neurotransmitters as monoamines and their receptors in the brain, but also structural and functional changes far beyond. During the last two decades, emerging theories are providing new explanations about the neurobiology of depression and the mechanism of action of antidepressant strategies based on cellular changes at the CNS level. The neurotrophic/plasticity hypothesis of depression, proposed more than a decade ago, is now supported by multiple basic and clinical studies focused on the role of intracellular-signalling cascades that govern neural proliferation and plasticity. Herein, we review the state-of-the-art of the changes in these signalling pathways which appear to underlie both depressive disorders and antidepressant actions. We will especially focus on the hippocampal cellularity and plasticity modulation by serotonin, trophic factors as brain-derived neurotrophic factor (BDNF), and vascular endothelial growth factor (VEGF) through intracellular signalling pathways-cAMP, Wnt/ β -catenin, and mTOR. Connecting the classic monoaminergic hypothesis with proliferation/neuroplasticity-related evidence is an appealing and comprehensive attempt for improving our knowledge about the neurobiological events leading to depression and associated to antidepressant therapies.

  4. Adolescents' Reward-related Neural Activation: Links to Thoughts of Nonsuicidal Self-Injury.

    Science.gov (United States)

    Poon, Jennifer A; Thompson, James C; Forbes, Erika E; Chaplin, Tara M

    2018-01-19

    Adolescence is a critical developmental period marked by an increase in risk behaviors, including nonsuicidal self-injury (NSSI). Heightened reward-related brain activation and relatively limited recruitment of prefrontal regions contribute to the initiation of risky behaviors in adolescence. However, neural reward processing has not been examined among adolescents who are at risk for future engagement for NSSI specifically, but who have yet to actually engage in this behavior. In the current fMRI study (N = 71), we hypothesized that altered reward processing would be associated with adolescents' thoughts of NSSI. Results showed that NSSI youth exhibited heightened activation in the bilateral putamen in response to a monetary reward. This pattern of findings suggests that heightened neural sensitivity to reward is associated with thoughts of NSSI in early adolescence. Implications for prevention are discussed. © 2018 The American Association of Suicidology.

  5. On the Relationships between Generative Encodings, Regularity, and Learning Abilities when Evolving Plastic Artificial Neural Networks: e79138

    National Research Council Canada - National Science Library

    Paul Tonelli; Jean-Baptiste Mouret

    2013-01-01

    .... It is commonly believed that two keys for evolving nature-like artificial neural networks are (1) the developmental process that links genes to nervous systems, which enables the evolution of large, regular neural networks...

  6. Individual differences in sensitivity to reward and punishment and neural activity during reward and avoidance learning.

    Science.gov (United States)

    Kim, Sang Hee; Yoon, HeungSik; Kim, Hackjin; Hamann, Stephan

    2015-09-01

    In this functional neuroimaging study, we investigated neural activations during the process of learning to gain monetary rewards and to avoid monetary loss, and how these activations are modulated by individual differences in reward and punishment sensitivity. Healthy young volunteers performed a reinforcement learning task where they chose one of two fractal stimuli associated with monetary gain (reward trials) or avoidance of monetary loss (avoidance trials). Trait sensitivity to reward and punishment was assessed using the behavioral inhibition/activation scales (BIS/BAS). Functional neuroimaging results showed activation of the striatum during the anticipation and reception periods of reward trials. During avoidance trials, activation of the dorsal striatum and prefrontal regions was found. As expected, individual differences in reward sensitivity were positively associated with activation in the left and right ventral striatum during reward reception. Individual differences in sensitivity to punishment were negatively associated with activation in the left dorsal striatum during avoidance anticipation and also with activation in the right lateral orbitofrontal cortex during receiving monetary loss. These results suggest that learning to attain reward and learning to avoid loss are dependent on separable sets of neural regions whose activity is modulated by trait sensitivity to reward or punishment. © The Author (2015). Published by Oxford University Press. For Permissions, please email: journals.permissions@oup.com.

  7. A fast image registration approach of neural activities in light-sheet fluorescence microscopy images

    Science.gov (United States)

    Meng, Hui; Hui, Hui; Hu, Chaoen; Yang, Xin; Tian, Jie

    2017-03-01

    The ability of fast and single-neuron resolution imaging of neural activities enables light-sheet fluorescence microscopy (LSFM) as a powerful imaging technique in functional neural connection applications. The state-of-art LSFM imaging system can record the neuronal activities of entire brain for small animal, such as zebrafish or C. elegans at single-neuron resolution. However, the stimulated and spontaneous movements in animal brain result in inconsistent neuron positions during recording process. It is time consuming to register the acquired large-scale images with conventional method. In this work, we address the problem of fast registration of neural positions in stacks of LSFM images. This is necessary to register brain structures and activities. To achieve fast registration of neural activities, we present a rigid registration architecture by implementation of Graphics Processing Unit (GPU). In this approach, the image stacks were preprocessed on GPU by mean stretching to reduce the computation effort. The present image was registered to the previous image stack that considered as reference. A fast Fourier transform (FFT) algorithm was used for calculating the shift of the image stack. The calculations for image registration were performed in different threads while the preparation functionality was refactored and called only once by the master thread. We implemented our registration algorithm on NVIDIA Quadro K4200 GPU under Compute Unified Device Architecture (CUDA) programming environment. The experimental results showed that the registration computation can speed-up to 550ms for a full high-resolution brain image. Our approach also has potential to be used for other dynamic image registrations in biomedical applications.

  8. Visual Working Memory Load-Related Changes in Neural Activity and Functional Connectivity

    OpenAIRE

    Ling Li; Jin-Xiang Zhang; Tao Jiang

    2011-01-01

    BACKGROUND: Visual working memory (VWM) helps us store visual information to prepare for subsequent behavior. The neuronal mechanisms for sustaining coherent visual information and the mechanisms for limited VWM capacity have remained uncharacterized. Although numerous studies have utilized behavioral accuracy, neural activity, and connectivity to explore the mechanism of VWM retention, little is known about the load-related changes in functional connectivity for hemi-field VWM retention. MET...

  9. Distinct neural activity associated with focused-attention meditation and loving-kindness meditation.

    Science.gov (United States)

    Lee, Tatia M C; Leung, Mei-Kei; Hou, Wai-Kai; Tang, Joey C Y; Yin, Jing; So, Kwok-Fai; Lee, Chack-Fan; Chan, Chetwyn C H

    2012-01-01

    This study examined the dissociable neural effects of ānāpānasati (focused-attention meditation, FAM) and mettā (loving-kindness meditation, LKM) on BOLD signals during cognitive (continuous performance test, CPT) and affective (emotion-processing task, EPT, in which participants viewed affective pictures) processing. Twenty-two male Chinese expert meditators (11 FAM experts, 11 LKM experts) and 22 male Chinese novice meditators (11 FAM novices, 11 LKM novices) had their brain activity monitored by a 3T MRI scanner while performing the cognitive and affective tasks in both meditation and baseline states. We examined the interaction between state (meditation vs. baseline) and expertise (expert vs. novice) separately during LKM and FAM, using a conjunction approach to reveal common regions sensitive to the expert meditative state. Additionally, exclusive masking techniques revealed distinct interactions between state and group during LKM and FAM. Specifically, we demonstrated that the practice of FAM was associated with expertise-related behavioral improvements and neural activation differences in attention task performance. However, the effect of state LKM meditation did not carry over to attention task performance. On the other hand, both FAM and LKM practice appeared to affect the neural responses to affective pictures. For viewing sad faces, the regions activated for FAM practitioners were consistent with attention-related processing; whereas responses of LKM experts to sad pictures were more in line with differentiating emotional contagion from compassion/emotional regulation processes. Our findings provide the first report of distinct neural activity associated with forms of meditation during sustained attention and emotion processing.

  10. Distinct Neural Activity Associated with Focused-Attention Meditation and Loving-Kindness Meditation

    Science.gov (United States)

    Lee, Tatia M. C.; Leung, Mei-Kei; Hou, Wai-Kai; Tang, Joey C. Y.; Yin, Jing; So, Kwok-Fai; Lee, Chack-Fan; Chan, Chetwyn C. H.

    2012-01-01

    This study examined the dissociable neural effects of ānāpānasati (focused-attention meditation, FAM) and mettā (loving-kindness meditation, LKM) on BOLD signals during cognitive (continuous performance test, CPT) and affective (emotion-processing task, EPT, in which participants viewed affective pictures) processing. Twenty-two male Chinese expert meditators (11 FAM experts, 11 LKM experts) and 22 male Chinese novice meditators (11 FAM novices, 11 LKM novices) had their brain activity monitored by a 3T MRI scanner while performing the cognitive and affective tasks in both meditation and baseline states. We examined the interaction between state (meditation vs. baseline) and expertise (expert vs. novice) separately during LKM and FAM, using a conjunction approach to reveal common regions sensitive to the expert meditative state. Additionally, exclusive masking techniques revealed distinct interactions between state and group during LKM and FAM. Specifically, we demonstrated that the practice of FAM was associated with expertise-related behavioral improvements and neural activation differences in attention task performance. However, the effect of state LKM meditation did not carry over to attention task performance. On the other hand, both FAM and LKM practice appeared to affect the neural responses to affective pictures. For viewing sad faces, the regions activated for FAM practitioners were consistent with attention-related processing; whereas responses of LKM experts to sad pictures were more in line with differentiating emotional contagion from compassion/emotional regulation processes. Our findings provide the first report of distinct neural activity associated with forms of meditation during sustained attention and emotion processing. PMID:22905090

  11. Distinct neural activity associated with focused-attention meditation and loving-kindness meditation.

    Directory of Open Access Journals (Sweden)

    Tatia M C Lee

    Full Text Available This study examined the dissociable neural effects of ānāpānasati (focused-attention meditation, FAM and mettā (loving-kindness meditation, LKM on BOLD signals during cognitive (continuous performance test, CPT and affective (emotion-processing task, EPT, in which participants viewed affective pictures processing. Twenty-two male Chinese expert meditators (11 FAM experts, 11 LKM experts and 22 male Chinese novice meditators (11 FAM novices, 11 LKM novices had their brain activity monitored by a 3T MRI scanner while performing the cognitive and affective tasks in both meditation and baseline states. We examined the interaction between state (meditation vs. baseline and expertise (expert vs. novice separately during LKM and FAM, using a conjunction approach to reveal common regions sensitive to the expert meditative state. Additionally, exclusive masking techniques revealed distinct interactions between state and group during LKM and FAM. Specifically, we demonstrated that the practice of FAM was associated with expertise-related behavioral improvements and neural activation differences in attention task performance. However, the effect of state LKM meditation did not carry over to attention task performance. On the other hand, both FAM and LKM practice appeared to affect the neural responses to affective pictures. For viewing sad faces, the regions activated for FAM practitioners were consistent with attention-related processing; whereas responses of LKM experts to sad pictures were more in line with differentiating emotional contagion from compassion/emotional regulation processes. Our findings provide the first report of distinct neural activity associated with forms of meditation during sustained attention and emotion processing.

  12. Research on image retrieval using deep convolutional neural network combining L1 regularization and PRelu activation function

    Science.gov (United States)

    QingJie, Wei; WenBin, Wang

    2017-06-01

    In this paper, the image retrieval using deep convolutional neural network combined with regularization and PRelu activation function is studied, and improves image retrieval accuracy. Deep convolutional neural network can not only simulate the process of human brain to receive and transmit information, but also contains a convolution operation, which is very suitable for processing images. Using deep convolutional neural network is better than direct extraction of image visual features for image retrieval. However, the structure of deep convolutional neural network is complex, and it is easy to over-fitting and reduces the accuracy of image retrieval. In this paper, we combine L1 regularization and PRelu activation function to construct a deep convolutional neural network to prevent over-fitting of the network and improve the accuracy of image retrieval

  13. Active Generations: An Intergenerational Approach to Preventing Childhood Obesity

    Science.gov (United States)

    Werner, Danilea; Teufel, James; Holtgrave, Peter L.; Brown, Stephen L.

    2012-01-01

    Background: Over the last 3 decades, US obesity rates have increased dramatically as more children and more adults become obese. This study explores an innovative program, Active Generations, an intergenerational nutrition education and activity program implemented in out-of-school environments (after school and summer camps). It utilizes older…

  14. Suppressed expression of mitogen-activated protein kinases in hyperthermia induced defective neural tube.

    Science.gov (United States)

    Zhang, Tianliang; Leng, Zhaoting; Liu, Wenjing; Wang, Xia; Yan, Xue; Yu, Li

    2015-05-06

    Neural tube defects (NTDs) are common congenital malformations. Mitogen-activated protein kinases (MAPKs) pathway is involved in many physiological processes. HMGB1 has been showed closely associated with neurulation and NTDs induced by hyperthermia and could activate MAPKs pathway. Since hyperthermia caused increased activation of MAPKs in many systems, the present study aims to investigate whether HMGB1 contributes to hyperthermia induced NTDs through MAPKs pathway. The mRNA levels of MAPKs and HMGB1 between embryonic day 8.5 and 10 (E8.5-10) in hyperthermia induced defective neural tube were detected by real-time quantitative polymerase chain reaction (qPCR). By immunofluorescence and western blotting, the expressions of HMGB1 and phosphorylated MAPKs (ERK1/2, JNK and p38) in neural tubes after hyperthermia were studied. The mRNA levels of MAPKs and HMGB1, as well as the expressions of HMGB1 along with phosphorylated JNK, p38 and ERK, were downregulated in NTDs groups induced by hyperthermia compared with control. The findings suggested that HMGB1 may contribute to hyperthermia induced NTDs formation through decreased cell proliferation due to inhibited phosphorylated ERK1/2 MAPK. Copyright © 2015 The Authors. Published by Elsevier Ireland Ltd.. All rights reserved.

  15. Dynamics of modularity of neural activity in the brain during development

    Science.gov (United States)

    Deem, Michael; Chen, Man

    2014-03-01

    Theory suggests that more modular systems can have better response functions at short times. This theory suggests that greater cognitive performance may be achieved for more modular neural activity, and that modularity of neural activity may, therefore, likely increase with development in children. We study the relationship between age and modularity of brain neural activity in developing children. The value of modularity calculated from fMRI data is observed to increase during childhood development and peak in young adulthood. We interpret these results as evidence of selection for plasticity in the cognitive function of the human brain. We present a model to illustrate how modularity can provide greater cognitive performance at short times and enhance fast, low-level, automatic cognitive processes. Conversely, high-level, effortful, conscious cognitive processes may not benefit from modularity. We use quasispecies theory to predict how the average modularity evolves with age, given a fitness function extracted from the model. We suggest further experiments exploring the effect of modularity on cognitive performance and suggest that modularity may be a potential biomarker for injury, rehabilitation, or disease.

  16. Altered spontaneous neural activity in the occipital face area reflects behavioral deficits in developmental prosopagnosia.

    Science.gov (United States)

    Zhao, Yuanfang; Li, Jingguang; Liu, Xiqin; Song, Yiying; Wang, Ruosi; Yang, Zetian; Liu, Jia

    2016-08-01

    Individuals with developmental prosopagnosia (DP) exhibit severe difficulties in recognizing faces and to a lesser extent, also exhibit difficulties in recognizing non-face objects. We used fMRI to investigate whether these behavioral deficits could be accounted for by altered spontaneous neural activity. Two aspects of spontaneous neural activity were measured: the intensity of neural activity in a voxel indexed by the fractional amplitude of spontaneous low-frequency fluctuations (fALFF), and the connectivity of a voxel to neighboring voxels indexed by regional homogeneity (ReHo). Compared with normal adults, both the fALFF and ReHo values within the right occipital face area (rOFA) were significantly reduced in DP subjects. Follow-up studies on the normal adults revealed that these two measures indicated further functional division of labor within the rOFA. The fALFF in the rOFA was positively correlated with behavioral performance in recognition of non-face objects, whereas ReHo in the rOFA was positively correlated with processing of faces. When considered together, the altered fALFF and ReHo within the same region (rOFA) may account for the comorbid deficits in both face and object recognition in DPs, whereas the functional division of labor in these two measures helps to explain the relative independency of deficits in face recognition and object recognition in DP. Copyright © 2016 Elsevier Ltd. All rights reserved.

  17. Neural generators of the auditory evoked potential components P3a and P3b

    NARCIS (Netherlands)

    Wronka, E.; Kaiser, J.; Coenen, A.M.L.

    2012-01-01

    The aim of the present study was to define the scalp topography of the two subcomponents of the P3 component of the auditory evoked potential elicited in a three-stimulus oddball paradigm and to identify their cortical generators using the standardized low resolution electromagnetic tomography

  18. A direct comparison of appetitive and aversive anticipation: Overlapping and distinct neural activation.

    Science.gov (United States)

    Sege, Christopher T; Bradley, Margaret M; Weymar, Mathias; Lang, Peter J

    2017-05-30

    fMRI studies of reward find increased neural activity in ventral striatum and medial prefrontal cortex (mPFC), whereas other regions, including the dorsolateral prefrontal cortex (dlPFC), anterior cingulate cortex (ACC), and anterior insula, are activated when anticipating aversive exposure. Although these data suggest differential activation during anticipation of pleasant or of unpleasant exposure, they also arise in the context of different paradigms (e.g., preparation for reward vs. threat of shock) and participants. To determine overlapping and unique regions active during emotional anticipation, we compared neural activity during anticipation of pleasant or unpleasant exposure in the same participants. Cues signalled the upcoming presentation of erotic/romantic, violent, or everyday pictures while BOLD activity during the 9-s anticipatory period was measured using fMRI. Ventral striatum and a ventral mPFC subregion were activated when anticipating pleasant, but not unpleasant or neutral, pictures, whereas activation in other regions was enhanced when anticipating appetitive or aversive scenes. Copyright © 2017 Elsevier B.V. All rights reserved.

  19. Accelerometer signal-based human activity recognition using augmented autoregressive model coefficients and artificial neural nets.

    Science.gov (United States)

    Khan, A M; Lee, Y K; Kim, T S

    2008-01-01

    Automatic recognition of human activities is one of the important and challenging research areas in proactive and ubiquitous computing. In this work, we present some preliminary results of recognizing human activities using augmented features extracted from the activity signals measured using a single triaxial accelerometer sensor and artificial neural nets. The features include autoregressive (AR) modeling coefficients of activity signals, signal magnitude areas (SMA), and title angles (TA). We have recognized four human activities using AR coefficients (ARC) only, ARC with SMA, and ARC with SMA and TA. With the last augmented features, we have achieved the recognition rate above 99% for all four activities including lying, standing, walking, and running. With our proposed technique, real time recognition of some human activities is possible.

  20. Rejuvenation of MPTP-induced human neural precursor cell senescence by activating autophagy

    Energy Technology Data Exchange (ETDEWEB)

    Zhu, Liang [East Hospital, Tongji University School of Medicine, Shanghai (China); Dong, Chuanming [East Hospital, Tongji University School of Medicine, Shanghai (China); Department of Anatomy and Neurobiology, The Jiangsu Key Laboratory of Neuroregeneration, Nantong University, Nantong (China); Sun, Chenxi; Ma, Rongjie; Yang, Danjing [East Hospital, Tongji University School of Medicine, Shanghai (China); Zhu, Hongwen, E-mail: hongwen_zhu@hotmail.com [Tianjin Hospital, Tianjin Academy of Integrative Medicine, Tianjin (China); Xu, Jun, E-mail: xunymc2000@yahoo.com [East Hospital, Tongji University School of Medicine, Shanghai (China)

    2015-08-21

    Aging of neural stem cell, which can affect brain homeostasis, may be caused by many cellular mechanisms. Autophagy dysfunction was found in aged and neurodegenerative brains. However, little is known about the relationship between autophagy and human neural stem cell (hNSC) aging. The present study used 1-methyl-4-phenyl-1, 2, 3, 6-tetrahydropyridine (MPTP) to treat neural precursor cells (NPCs) derived from human embryonic stem cell (hESC) line H9 and investigate related molecular mechanisms involved in this process. MPTP-treated NPCs were found to undergo premature senescence [determined by increased senescence-associated-β-galactosidase (SA-β-gal) activity, elevated intracellular reactive oxygen species level, and decreased proliferation] and were associated with impaired autophagy. Additionally, the cellular senescence phenotypes were manifested at the molecular level by a significant increase in p21 and p53 expression, a decrease in SOD2 expression, and a decrease in expression of some key autophagy-related genes such as Atg5, Atg7, Atg12, and Beclin 1. Furthermore, we found that the senescence-like phenotype of MPTP-treated hNPCs was rejuvenated through treatment with a well-known autophagy enhancer rapamycin, which was blocked by suppression of essential autophagy gene Beclin 1. Taken together, these findings reveal the critical role of autophagy in the process of hNSC aging, and this process can be reversed by activating autophagy. - Highlights: • We successfully establish hESC-derived neural precursor cells. • MPTP treatment induced senescence-like state in hESC-derived NPCs. • MPTP treatment induced impaired autophagy of hESC-derived NPCs. • MPTP-induced hESC-derived NPC senescence was rejuvenated by activating autophagy.

  1. Amplified induced neural oscillatory activity predicts musicians' benefits in categorical speech perception.

    Science.gov (United States)

    Bidelman, Gavin M

    2017-04-21

    Event-related brain potentials (ERPs) reveal musical experience refines neural encoding and confers stronger categorical perception (CP) and neural organization for speech sounds. In addition to evoked brain activity, the human EEG can be decomposed into induced (non-phase-locked) responses whose various frequency bands reflect different mechanisms of perceptual-cognitive processing. Here, we aimed to clarify which spectral properties of these neural oscillations are most prone to music-related neuroplasticity and which are linked to behavioral benefits in the categorization of speech. We recorded electrical brain activity while musicians and nonmusicians rapidly identified speech tokens from a sound continuum. Time-frequency analysis parsed evoked and induced EEG into alpha- (∼10Hz), beta- (∼20Hz), and gamma- (>30Hz) frequency bands. We found that musicians' enhanced behavioral CP was accompanied by improved evoked speech responses across the frequency spectrum, complementing previously observed enhancements in evoked potential studies (i.e., ERPs). Brain-behavior correlations implied differences in the underlying neural mechanisms supporting speech CP in each group: modulations in induced gamma power predicted the slope of musicians' speech identification functions whereas early evoked alpha activity predicted behavior in nonmusicians. Collectively, findings indicate that musical training tunes speech processing via two complementary mechanisms: (i) strengthening the formation of auditory object representations for speech signals (gamma-band) and (ii) improving network control and/or the matching of sounds to internalized memory templates (alpha/beta-band). Both neurobiological enhancements may be deployed behaviorally and account for musicians' benefits in the perceptual categorization of speech. Copyright © 2017 IBRO. Published by Elsevier Ltd. All rights reserved.

  2. Sentinel-1 data exploitation for geohazard activity map generation

    Science.gov (United States)

    Barra, Anna; Solari, Lorenzo; Béjar-Pizarro, Marta; Monserrat, Oriol; Herrera, Gerardo; Bianchini, Silvia; Crosetto, Michele; María Mateos, Rosa; Sarro, Roberto; Moretti, Sandro

    2017-04-01

    This work is focused on geohazard mapping and monitoring by exploiting Sentinel-1 (A and B) data and the DInSAR (Differential interferometric SAR (Synthetic Aperture Radar)) techniques. Sometimes the interpretation of the DInSAR derived product (like the velocity map) can be complex, mostly for a final user who do not usually works with radar. The aim of this work is to generate, in a rapid way, a clear product to be easily exploited by the authorities in the geohazard management: intervention planning and prevention activities. Specifically, the presented methodology has been developed in the framework of the European project SAFETY, which is aimed at providing Civil Protection Authorities (CPA) with the capability of periodically evaluating and assessing the potential impact of geohazards (volcanic activity, earthquakes, landslides and subsidence) on urban areas. The methodology has three phases, the interferograms generation, the activity map generation, in terms of velocity and accumulated deformation (with time-series), and the Active Deformation Area (ADA) map generation. The last one is the final product, derived from the original activity map by analyzing the data in a Geographic Information System (GIS) environment, which isolate only the true deformation areas over the noise. This product can be more easily read by the authorities than the original activity map, i.e. can be better exploited to integrate other information and analysis. This product also permit an easy monitoring of the active areas.

  3. Behavioral activation can normalize neural hypoactivation in subthreshold depression during a monetary incentive delay task.

    Science.gov (United States)

    Mori, Asako; Okamoto, Yasumasa; Okada, Go; Takagaki, Koki; Jinnin, Ran; Takamura, Masahiro; Kobayakawa, Makoto; Yamawaki, Shigeto

    2016-01-01

    Late adolescents are under increased risk of developing depressive symptoms. Behavioral activation is an effective treatment for subthreshold depression, which can prevent the development of subthreshold depression into a major depressive disorder. However, the neural mechanisms underlying the efficacy of behavioral activation have not been clearly understood. We investigated neural responses during reward processing by individuals with subthreshold depression to clarify the neural mechanisms of behavioral activation. Late adolescent university students with subthreshold depression (n=15, age 18-19 years) as indicated by a high score on the Beck's Depression Inventory-ll (BDI-ll) and 15 age-matched controls with a low BDI-ll score participated in functional magnetic resonance imaging scanning conducted during a monetary incentive delay task on two occasions. The Individuals in the subthreshold depression group received five, weekly behavioral activation sessions between the two scanning sessions. Moreover, they did not receive any medication until the study was completed. Behavioral activation significantly reduced depressive symptoms. Moreover, compared to the changes in brain functions in the control group, the behavioral activation group showed functional changes during loss anticipation in brain structures that mediates cognitive and emotional regulation, including the left ventrolateral prefrontal cortex and angular gyrus. Replication of the study with a larger sample size is required to increase the generalizability of these results. Behavioral activation results in improved functioning of the fronto-parietal region during loss anticipation. These results increase our understanding of the mechanisms underlying specific psychotherapies. Copyright © 2015 Elsevier B.V. All rights reserved.

  4. Eddy Current Signature Classification of Steam Generator Tube Defects Using A Learning Vector Quantization Neural Network

    Energy Technology Data Exchange (ETDEWEB)

    Gabe V. Garcia

    2005-01-03

    A major cause of failure in nuclear steam generators is degradation of their tubes. Although seven primary defect categories exist, one of the principal causes of tube failure is intergranular attack/stress corrosion cracking (IGA/SCC). This type of defect usually begins on the secondary side surface of the tubes and propagates both inwards and laterally. In many cases this defect is found at or near the tube support plates.

  5. Chondroitinase and growth factors enhance activation and oligodendrocyte differentiation of endogenous neural precursor cells after spinal cord injury.

    Directory of Open Access Journals (Sweden)

    Soheila Karimi-Abdolrezaee

    Full Text Available The adult spinal cord harbours a population of multipotent neural precursor cells (NPCs with the ability to replace oligodendrocytes. However, despite this capacity, proliferation and endogenous remyelination is severely limited after spinal cord injury (SCI. In the post-traumatic microenvironment following SCI, endogenous spinal NPCs mainly differentiate into astrocytes which could contribute to astrogliosis that exacerbate the outcomes of SCI. These findings emphasize a key role for the post-SCI niche in modulating the behaviour of spinal NPCs after SCI. We recently reported that chondroitin sulphate proteoglycans (CSPGs in the glial scar restrict the outcomes of NPC transplantation in SCI by reducing the survival, migration and integration of engrafted NPCs within the injured spinal cord. These inhibitory effects were attenuated by administration of chondroitinase (ChABC prior to NPC transplantation. Here, in a rat model of compressive SCI, we show that perturbing CSPGs by ChABC in combination with sustained infusion of growth factors (EGF, bFGF and PDGF-AA optimize the activation and oligodendroglial differentiation of spinal NPCs after injury. Four days following SCI, we intrathecally delivered ChABC and/or GFs for seven days. We performed BrdU incorporation to label proliferating cells during the treatment period after SCI. This strategy increased the proliferation of spinal NPCs, reduced the generation of new astrocytes and promoted their differentiation along an oligodendroglial lineage, a prerequisite for remyelination. Furthermore, ChABC and GF treatments enhanced the response of non-neural cells by increasing the generation of new vascular endothelial cells and decreasing the number of proliferating macrophages/microglia after SCI. In conclusions, our data strongly suggest that optimization of the behaviour of endogenous spinal NPCs after SCI is critical not only to promote endogenous oligodendrocyte replacement, but also to reverse

  6. Multiple-color optical activation, silencing, and desynchronization of neural activity, with single-spike temporal resolution.

    Directory of Open Access Journals (Sweden)

    Xue Han

    Full Text Available The quest to determine how precise neural activity patterns mediate computation, behavior, and pathology would be greatly aided by a set of tools for reliably activating and inactivating genetically targeted neurons, in a temporally precise and rapidly reversible fashion. Having earlier adapted a light-activated cation channel, channelrhodopsin-2 (ChR2, for allowing neurons to be stimulated by blue light, we searched for a complementary tool that would enable optical neuronal inhibition, driven by light of a second color. Here we report that targeting the codon-optimized form of the light-driven chloride pump halorhodopsin from the archaebacterium Natronomas pharaonis (hereafter abbreviated Halo to genetically-specified neurons enables them to be silenced reliably, and reversibly, by millisecond-timescale pulses of yellow light. We show that trains of yellow and blue light pulses can drive high-fidelity sequences of hyperpolarizations and depolarizations in neurons simultaneously expressing yellow light-driven Halo and blue light-driven ChR2, allowing for the first time manipulations of neural synchrony without perturbation of other parameters such as spiking rates. The Halo/ChR2 system thus constitutes a powerful toolbox for multichannel photoinhibition and photostimulation of virally or transgenically targeted neural circuits without need for exogenous chemicals, enabling systematic analysis and engineering of the brain, and quantitative bioengineering of excitable cells.

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

    Science.gov (United States)

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

    2012-04-01

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

  8. Adaptive neural networks control for camera stabilization with active suspension system

    Directory of Open Access Journals (Sweden)

    Feng Zhao

    2015-08-01

    Full Text Available The camera always suffers from image instability on the moving vehicle due to unintentional vibrations caused by road roughness. This article presents an adaptive neural network approach mixed with linear quadratic regulator control for a quarter-car active suspension system to stabilize the image captured area of the camera. An active suspension system provides extra force through the actuator which allows it to suppress vertical vibration of sprung mass. First, to deal with the road disturbance and the system uncertainties, radial basis function neural network is proposed to construct the map between the state error and the compensation component, which can correct the optimal state-feedback control law. The weights matrix of radial basis function neural network is adaptively tuned online. Then, the closed-loop stability and asymptotic convergence performance is guaranteed by Lyapunov analysis. Finally, the simulation results demonstrate that the proposed controller effectively suppresses the vibration of the camera and enhances the stabilization of the entire camera, where different excitations are considered to validate the system performance.

  9. High-frequency neural activity predicts word parsing in ambiguous speech streams.

    Science.gov (United States)

    Kösem, Anne; Basirat, Anahita; Azizi, Leila; van Wassenhove, Virginie

    2016-12-01

    During speech listening, the brain parses a continuous acoustic stream of information into computational units (e.g., syllables or words) necessary for speech comprehension. Recent neuroscientific hypotheses have proposed that neural oscillations contribute to speech parsing, but whether they do so on the basis of acoustic cues (bottom-up acoustic parsing) or as a function of available linguistic representations (top-down linguistic parsing) is unknown. In this magnetoencephalography study, we contrasted acoustic and linguistic parsing using bistable speech sequences. While listening to the speech sequences, participants were asked to maintain one of the two possible speech percepts through volitional control. We predicted that the tracking of speech dynamics by neural oscillations would not only follow the acoustic properties but also shift in time according to the participant's conscious speech percept. Our results show that the latency of high-frequency activity (specifically, beta and gamma bands) varied as a function of the perceptual report. In contrast, the phase of low-frequency oscillations was not strongly affected by top-down control. Whereas changes in low-frequency neural oscillations were compatible with the encoding of prelexical segmentation cues, high-frequency activity specifically informed on an individual's conscious speech percept. Copyright © 2016 the American Physiological Society.

  10. A neural measure of behavioral engagement: Task-residual low frequency blood oxygenation level dependent activity in the precuneus

    OpenAIRE

    Zhang, Sheng; Li, Chiang-shan Ray

    2009-01-01

    Brain imaging has provided a useful tool to examine the neural processes underlying human cognition. A critical question is whether and how task engagement influences the observed regional brain activations. Here we highlighted this issue and derived a neural measure of task engagement from the task-residual low frequency blood oxygenation level dependent (BOLD) activity in the precuneus. Using independent component analysis, we identified brain regions in the default circuit – including the ...

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

    Science.gov (United States)

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

    2012-10-01

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

  12. Neural network based semi-active control strategy for structural vibration mitigation with magnetorheological damper

    DEFF Research Database (Denmark)

    Bhowmik, Subrata

    2011-01-01

    This paper presents a neural network based semi-active control method for a rotary type magnetorheological (MR) damper. The characteristics of the MR damper are described by the classic Bouc-Wen model, and the performance of the proposed control method is evaluated in terms of a base exited shear...... frame structure. As demonstrated in the literature effective damping of flexible structures is obtained by a suitable combination of pure friction and negative damper stiffness. This damper model is rate-independent and fully described by the desired shape of the hysteresis loops or force...... mode of the structure. The neural network control is then developed to reproduce the desired force based on damper displacement and velocity as network input, and it is therefore referred to as an amplitude dependent model reference control method. An inverse model of the MR damper is needed...

  13. Neural networkbased semi-active control strategy for structural vibration mitigation with magnetorheological damper

    DEFF Research Database (Denmark)

    Bhowmik, Subrata

    2011-01-01

    This paper presents a neural network based semi-active control method for a rotary type magnetorheological (MR) damper. The characteristics of the MR damper are described by the classic Bouc-Wen model, and the performance of the proposed control method is evaluated in terms of a base exited shear...... frame structure. As demonstrated in the literature effective damping of flexible structures is obtained by a suitable combination of pure friction and negative damper stiffness. This damper model is rate-independent and fully described by the desired shape of the hysteresis loops or force...... mode of the structure. The neural network control is then developed to reproduce the desired force based on damper displacement and velocity as network input, and it is therefore referred to as an amplitude dependent model reference control method. An inverse model of the MR damper is needed...

  14. Splanchnic neural activity modulates ultradian and circadian rhythms in adrenocortical secretion in awake rats.

    Science.gov (United States)

    Jasper, M S; Engeland, W C

    1994-02-01

    An ultradian rhythm in adrenal secretion of corticosterone has been described in awake rats using intra-adrenal microdialysis. To determine the role of the autonomic innervation of the adrenal on the expression of the corticosterone rhythm, adrenal extracellular fluid was sampled by intra-adrenal microdialysis in intact (CTRL) and splanchnicectomized (SPLNX) rats 5-7 h before (light period) and after dark onset (dark period). Experiments conducted 1, 2, or 5 days after surgical insertion of the microdialysis probe consisted of continuous collection of dialysate at intervals of 10 min. Time domain pulse detection using PC-PULSAR showed that 5 days after surgery, SPLNX decreased interpulse interval (IPI) during the light period, but had no effect during the dark period, resulting in the loss of the diurnal rhythm in corticosterone secretion. Although diurnal modulation of both pulse amplitude and pulse frequency was observed, only the frequency was altered by SPLNX. In CTRL animals IPI increased at 5 days postsurgery, relative to 1 and 2 days, but the amplitude of normalized secretory pulses did not change. The decrease in IPI caused by SPLNX was observed 5 days, but not 1 or 2 days after surgery, suggesting that surgical stress obscures the inhibitory effect of splanchnic neural activity. Power spectral analysis showed significant periodicities in corticosterone secretion rate in individual CTRL and SPLNX animals at 1, 2, and 5 days. One day after surgery, SPLNX reduced the frequency of the ultradian rhythm detected by power spectral analysis. This finding suggests that splanchnic neural activity may increase pulse frequency in stressed rats, in opposition to the effect seen after extended recovery from surgery. In conclusion, our data suggest that the nadir of the diurnal rhythm in corticosterone secretion results in part from neural inhibitory control. Splanchnic neural innervation may also have an excitatory role in the adrenocortical stress response.

  15. Neural activity during emotion recognition after combined cognitive plus social cognitive training in schizophrenia.

    Science.gov (United States)

    Hooker, Christine I; Bruce, Lori; Fisher, Melissa; Verosky, Sara C; Miyakawa, Asako; Vinogradov, Sophia

    2012-08-01

    Cognitive remediation training has been shown to improve both cognitive and social cognitive deficits in people with schizophrenia, but the mechanisms that support this behavioral improvement are largely unknown. One hypothesis is that intensive behavioral training in cognition and/or social cognition restores the underlying neural mechanisms that support targeted skills. However, there is little research on the neural effects of cognitive remediation training. This study investigated whether a 50 h (10-week) remediation intervention which included both cognitive and social cognitive training would influence neural function in regions that support social cognition. Twenty-two stable, outpatient schizophrenia participants were randomized to a treatment condition consisting of auditory-based cognitive training (AT) [Brain Fitness Program/auditory module ~60 min/day] plus social cognition training (SCT) which was focused on emotion recognition [~5-15 min per day] or a placebo condition of non-specific computer games (CG) for an equal amount of time. Pre and post intervention assessments included an fMRI task of positive and negative facial emotion recognition, and standard behavioral assessments of cognition, emotion processing, and functional outcome. There were no significant intervention-related improvements in general cognition or functional outcome. fMRI results showed the predicted group-by-time interaction. Specifically, in comparison to CG, AT+SCT participants had a greater pre-to-post intervention increase in postcentral gyrus activity during emotion recognition of both positive and negative emotions. Furthermore, among all participants, the increase in postcentral gyrus activity predicted behavioral improvement on a standardized test of emotion processing (MSCEIT: Perceiving Emotions). Results indicate that combined cognition and social cognition training impacts neural mechanisms that support social cognition skills. Copyright © 2012 Elsevier B.V. All

  16. Using convolutional neural networks for human activity classification on micro-Doppler radar spectrograms

    Science.gov (United States)

    Jordan, Tyler S.

    2016-05-01

    This paper presents the findings of using convolutional neural networks (CNNs) to classify human activity from micro-Doppler features. An emphasis on activities involving potential security threats such as holding a gun are explored. An automotive 24 GHz radar on chip was used to collect the data and a CNN (normally applied to image classification) was trained on the resulting spectrograms. The CNN achieves an error rate of 1.65 % on classifying running vs. walking, 17.3 % error on armed walking vs. unarmed walking, and 22 % on classifying six different actions.

  17. Inactivity-induced respiratory plasticity: protecting the drive to breathe in disorders that reduce respiratory neural activity.

    Science.gov (United States)

    Strey, K A; Baertsch, N A; Baker-Herman, T L

    2013-11-01

    Multiple forms of plasticity are activated following reduced respiratory neural activity. For example, in ventilated rats, a central neural apnea elicits a rebound increase in phrenic and hypoglossal burst amplitude upon resumption of respiratory neural activity, forms of plasticity called inactivity-induced phrenic and hypoglossal motor facilitation (iPMF and iHMF), respectively. Here, we provide a conceptual framework for plasticity following reduced respiratory neural activity to guide future investigations. We review mechanisms giving rise to iPMF and iHMF, present new data suggesting that inactivity-induced plasticity is observed in inspiratory intercostals (iIMF) and point out gaps in our knowledge. We then survey conditions relevant to human health characterized by reduced respiratory neural activity and discuss evidence that inactivity-induced plasticity is elicited during these conditions. Understanding the physiological impact and circumstances in which inactivity-induced respiratory plasticity is elicited may yield novel insights into the treatment of disorders characterized by reductions in respiratory neural activity. Copyright © 2013 Elsevier B.V. All rights reserved.

  18. Enhanced food anticipatory activity associated with enhanced activation of extrahypothalamic neural pathways in serotonin2C receptor null mutant mice.

    Directory of Open Access Journals (Sweden)

    Jennifer L Hsu

    Full Text Available The ability to entrain circadian rhythms to food availability is important for survival. Food-entrained circadian rhythms are characterized by increased locomotor activity in anticipation of food availability (food anticipatory activity. However, the molecular components and neural circuitry underlying the regulation of food anticipatory activity remain unclear. Here we show that serotonin(2C receptor (5-HT2CR null mutant mice subjected to a daytime restricted feeding schedule exhibit enhanced food anticipatory activity compared to wild-type littermates, without phenotypic differences in the impact of restricted feeding on food consumption, body weight loss, or blood glucose levels. Moreover, we show that the enhanced food anticipatory activity in 5-HT2CR null mutant mice develops independent of external light cues and persists during two days of total food deprivation, indicating that food anticipatory activity in 5-HT2CR null mutant mice reflects the locomotor output of a food-entrainable oscillator. Whereas restricted feeding induces c-fos expression to a similar extent in hypothalamic nuclei of wild-type and null mutant animals, it produces enhanced expression in the nucleus accumbens and other extrahypothalamic regions of null mutant mice relative to wild-type subjects. These data suggest that 5-HT2CRs gate food anticipatory activity through mechanisms involving extrahypothalamic neural pathways.

  19. Auditory P3a and P3b neural generators in schizophrenia: An adaptive sLORETA P300 localization approach.

    Science.gov (United States)

    Bachiller, Alejandro; Romero, Sergio; Molina, Vicente; Alonso, Joan F; Mañanas, Miguel A; Poza, Jesús; Hornero, Roberto

    2015-12-01

    The present study investigates the neural substrates underlying cognitive processing in schizophrenia (Sz) patients. To this end, an auditory 3-stimulus oddball paradigm was used to identify P3a and P3b components, elicited by rare-distractor and rare-target tones, respectively. Event-related potentials (ERP) were recorded from 31 Sz patients and 38 healthy controls. The P3a and P3b brain-source generators were identified by time-averaging of low-resolution brain electromagnetic tomography (LORETA) current density images. In contrast with the commonly used fixed window of interest (WOI), we proposed to apply an adaptive WOI, which takes into account subjects' P300 latency variability. Our results showed different P3a and P3b source activation patterns in both groups. P3b sources included frontal, parietal and limbic lobes, whereas P3a response generators were localized over bilateral frontal and superior temporal regions. These areas have been related to the discrimination of auditory stimulus and to the inhibition (P3a) or the initiation (P3b) of motor response in a cognitive task. In addition, differences in source localization between Sz and control groups were observed. Sz patients showed lower P3b source activity in bilateral frontal structures and the cingulate. P3a generators were less widespread for Sz patients than for controls in right superior, medial and middle frontal gyrus. Our findings suggest that target and distractor processing involves distinct attentional subsystems, both being altered in Sz. Hence, the study of neuroelectric brain information can provide further insights to understand cognitive processes and underlying mechanisms in Sz. Copyright © 2015 Elsevier B.V. All rights reserved.

  20. Thinking about the thoughts of others; temporal and spatial neural activation during false belief reasoning.

    Science.gov (United States)

    Mossad, Sarah I; AuCoin-Power, Michelle; Urbain, Charline; Smith, Mary Lou; Pang, Elizabeth W; Taylor, Margot J

    2016-07-01

    Theory of Mind (ToM) is the ability to understand the perspectives, mental states and beliefs of others in order to anticipate their behaviour and is therefore crucial to social interactions. Although fMRI has been widely used to establish the neural networks implicated in ToM, little is known about the timing of ToM-related brain activity. We used magnetoencephalography (MEG) to measure the neural processes underlying ToM, as MEG provides very accurate timing and excellent spatial localization of brain processes. We recorded MEG activity during a false belief task, a reliable measure of ToM, in twenty young adults (10 females). MEG data were recorded in a 151 sensor CTF system (MISL, Coquitlam, BC) and data were co-registered to each participant's MRI (Siemens 3T) for source reconstruction. We found stronger right temporoparietal junction (rTPJ) activations in the false belief condition from 150ms to 225ms, in the right precuneus from 275ms to 375ms, in the right inferior frontal gyrus from 200ms to 300ms and the superior frontal gyrus from 300ms to 400ms. Our findings extend the literature by demonstrating the timing and duration of neural activity in the main regions involved in the "mentalizing" network, showing that activations related to false belief in adults are predominantly right lateralized and onset around 100ms. The sensitivity of MEG will allow us to determine spatial and temporal differences in the brain processes in ToM in younger populations or those who demonstrate deficits in this ability. Copyright © 2016 Elsevier Inc. All rights reserved.

  1. Touching moments: desire modulates the neural anticipation of active romantic caress.

    Science.gov (United States)

    Ebisch, Sjoerd J; Ferri, Francesca; Gallese, Vittorio

    2014-01-01

    A romantic caress is a basic expression of affiliative behavior and a primary reinforcer. Given its inherent affective valence, its performance also would imply the prediction of reward values. For example, touching a person for whom one has strong passionate feelings likely is motivated by a strong desire for physical contact and associated with the anticipation of hedonic experiences. The present study aims at investigating how the anticipatory neural processes of active romantic caress are modulated by the intensity of the desire for affective contact as reflected by passionate feelings for the other. Functional magnetic resonance imaging scanning was performed in romantically involved partners using a paradigm that allowed to isolate the specific anticipatory representations of active romantic caress, compared with control caress, while testing for the relationship between neural activity and measures of feelings of passionate love for the other. The results demonstrated that right posterior insula activity in anticipation of romantic caress significantly co-varied with the intensity of desire for union with the other. This effect was independent of the sensory-affective properties of the performed touch, like its pleasantness. Furthermore, functional connectivity analysis showed that the same posterior insula cluster interacted with brain regions related to sensory-motor functions as well as to the processing and anticipation of reward. The findings provide insight on the neural substrate mediating between the desire for and the performance of romantic caress. In particular, we propose that anticipatory activity patterns in posterior insula may modulate subsequent sensory-affective processing of skin-to-skin contact.

  2. TOUCHING MOMENTS: DESIRE MODULATES THE NEURAL ANTICIPATION OF ACTIVE ROMANTIC CARESS

    Directory of Open Access Journals (Sweden)

    Sjoerd J.H. Ebisch

    2014-02-01

    Full Text Available A romantic caress is a basic expression of affiliative behavior and a primary reinforcer. Given its inherent affective valence, its performance also would imply the prediction of reward values. For example, touching a person for whom one has strong passionate feelings likely is motivated by a strong desire for physical contact and associated with the anticipation of hedonic experiences. The present study aims at investigating how the anticipatory neural processes of active romantic caress are modulated by the intensity of the desire for affective contact as reflected by passionate feelings for the other. Functional magnetic resonance imaging scanning was performed in romantically involved partners using a paradigm that allowed to isolate the specific anticipatory representations of active romantic caress, compared with control caress, while testing for the relationship between neural activity and measures of feelings of passionate love for the other. The results demonstrated that right posterior insula activity in anticipation of romantic caress significantly co-varied with the intensity of desire for union with the other. This effect was independent of the sensory-affective properties of the performed touch, like its pleasantness. Furthermore, functional connectivity analysis showed that the same posterior insula cluster interacted with brain regions related to sensory-motor functions as well as to the processing and anticipation of reward. The findings provide insight on the neural substrate mediating between the desire for and the performance of romantic caress. In particular, we propose that anticipatory activity patterns in posterior insula may modulate subsequent sensory-affective processing of skin-to-skin contact.

  3. Selective neural activation in a histologically derived model of peripheral nerve

    Science.gov (United States)

    Butson, Christopher R.; Miller, Ian O.; Normann, Richard A.; Clark, Gregory A.

    2011-06-01

    Functional electrical stimulation (FES) is a general term for therapeutic methods that use electrical stimulation to aid or replace lost ability. For FES systems that communicate with the nervous system, one critical component is the electrode interface through which the machine-body information transfer must occur. In this paper, we examine the influence of inhomogeneous tissue conductivities and positions of nodes of Ranvier on activation of myelinated axons for neuromuscular control as a function of electrode configuration. To evaluate these effects, we developed a high-resolution bioelectric model of a fascicle from a stained cross-section of cat sciatic nerve. The model was constructed by digitizing a fixed specimen of peripheral nerve, extruding the image along the axis of the nerve, and assigning each anatomical component to one of several different tissue types. Electrodes were represented by current sources in monopolar, transverse bipolar, and longitudinal bipolar configurations; neural activation was determined using coupled field-neuron simulations with myelinated axon cable models. We found that the use of an isotropic tissue medium overestimated neural activation thresholds compared with the use of physiologically based, inhomogeneous tissue medium, even after controlling for mean impedance levels. Additionally, the positions of the cathodic sources relative to the nodes of Ranvier had substantial effects on activation, and these effects were modulated by the electrode configuration. Our results indicate that physiologically based tissue properties cause considerable variability in the neural response, and the inclusion of these properties is an important component in accurately predicting activation. The results are used to suggest new electrode designs to enable selective stimulation of small diameter fibers.

  4. Touching moments: desire modulates the neural anticipation of active romantic caress

    Science.gov (United States)

    Ebisch, Sjoerd J.; Ferri, Francesca; Gallese, Vittorio

    2014-01-01

    A romantic caress is a basic expression of affiliative behavior and a primary reinforcer. Given its inherent affective valence, its performance also would imply the prediction of reward values. For example, touching a person for whom one has strong passionate feelings likely is motivated by a strong desire for physical contact and associated with the anticipation of hedonic experiences. The present study aims at investigating how the anticipatory neural processes of active romantic caress are modulated by the intensity of the desire for affective contact as reflected by passionate feelings for the other. Functional magnetic resonance imaging scanning was performed in romantically involved partners using a paradigm that allowed to isolate the specific anticipatory representations of active romantic caress, compared with control caress, while testing for the relationship between neural activity and measures of feelings of passionate love for the other. The results demonstrated that right posterior insula activity in anticipation of romantic caress significantly co-varied with the intensity of desire for union with the other. This effect was independent of the sensory-affective properties of the performed touch, like its pleasantness. Furthermore, functional connectivity analysis showed that the same posterior insula cluster interacted with brain regions related to sensory-motor functions as well as to the processing and anticipation of reward. The findings provide insight on the neural substrate mediating between the desire for and the performance of romantic caress. In particular, we propose that anticipatory activity patterns in posterior insula may modulate subsequent sensory-affective processing of skin-to-skin contact. PMID:24616676

  5. Menstrual cycle phase does not affect sympathetic neural activity in women with postural orthostatic tachycardia syndrome.

    Science.gov (United States)

    Stickford, Abigail S L; VanGundy, Tiffany B; Levine, Benjamin D; Fu, Qi

    2015-05-01

    Women with the postural orthostatic tachycardia syndrome (POTS) report fluctuations in orthostatic tolerance throughout the menstrual cycle. The mechanism(s) underlying blood pressure control across the menstrual cycle in women with POTS are unknown. The findings of the present study indicate that the menstrual cycle does not affect muscle sympathetic nerve activity but modulates blood pressure and vasoconstriction in POTS women during orthostatic stress. Factors other than sympathetic neural activity are likely responsible for the symptoms of orthostatic intolerance across the menstrual cycle in women with POTS. Patients with the postural orthostatic tachycardia syndrome (POTS) are primarily premenopausal women, which may be attributed to female sex hormones. We tested the hypothesis that hormonal fluctuations of the menstrual cycle alter sympathetic neural activity and orthostatic tolerance in POTS women. Ten POTS women were studied during the early follicular (EF) and mid-luteal (ML) phases of the menstrual cycle. Haemodynamics and muscle sympathetic nerve activity (MSNA) were measured when supine, during 60 deg upright tilt for 45 min or until presyncope, and during the cold pressor test (CPT) and Valsalva manoeuvres. Blood pressure and total peripheral resistance were higher during rest and tilting in the ML than EF phase; however, heart rate, stroke volume and cardiac output were similar between phases. There were no mean ± SD differences in MSNA burst frequency (8 ± 8 EF phase vs. 10 ± 10 bursts min(-1) ML phase at rest; 34 ± 15 EF phase vs. 36 ± 16 bursts min(-1) ML phase at 5 min tilt), burst incidence or total activity, nor any differences in the cardiovagal and sympathetic baroreflex sensitivities between phases under any condition. The incidence of presyncope was also the same between phases. There were no differences in haemodynamic or sympathetic responses to CPT or Valsalva. These results suggest that the menstrual cycle does

  6. Altered neural activation during prepotent response inhibition in breast cancer survivors treated with chemotherapy: an fMRI study.

    Science.gov (United States)

    Kam, Julia W Y; Boyd, Lara A; Hsu, Chun L; Liu-Ambrose, Teresa; Handy, Todd C; Lim, Howard J; Hayden, Sherri; Campbell, Kristin L

    2016-09-01

    While impairments in executive functions have been reported in breast cancer survivors (BCS) who have undergone adjuvant chemotherapy, only a limited number of functional neuroimaging studies have associated alterations in cerebral activity with executive functions deficits in BCS. Using fMRI, the current study assessed the neural basis underlying a specific facet of executive function, namely prepotent response inhibition. 12 BCS who self-reported cognitive problems up to 3 years following cancer treatment and 12 female healthy comparisons (HC) performed the Stroop task. We compared their neural activation between the incongruent and neutral experimental conditions. Relative to the HC group, BCS showed lower blood-oxygen level dependent signal in several frontal regions, including the anterior cingulate cortex, a region critical for response inhibition. Our data indicates reduced neural activation in BCS during a prepotent response inhibition task, providing support for the prevailing notion of neural alterations observed in BCS treated with chemotherapy.

  7. A cry in the dark: depressed mothers show reduced neural activation to their own infant's cry.

    Science.gov (United States)

    Laurent, Heidemarie K; Ablow, Jennifer C

    2012-02-01

    This study investigated depression-related differences in primiparous mothers' neural response to their own infant's distress cues. Mothers diagnosed with major depressive disorder (n = 11) and comparison mothers with no diagnosable psychopathology (n = 11) were exposed to their own 18-months-old infant's cry sound, as well as unfamiliar infant's cry and control sound, during functional neuroimaging. Depressed mothers' response to own infant cry greater than other sounds was compared to non-depressed mothers' response in the whole brain [false discovery rate (FDR) corrected]. A continuous measure of self-reported depressive symptoms (CESD) was also tested as a predictor of maternal response. Non-depressed mothers activated to their own infant's cry greater than control sound in a distributed network of para/limbic and prefrontal regions, whereas depressed mothers as a group failed to show activation. Non-depressed compared to depressed mothers showed significantly greater striatal (caudate, nucleus accumbens) and medial thalamic activation. Additionally, mothers with lower depressive symptoms activated more strongly in left orbitofrontal, dorsal anterior cingulate and medial superior frontal regions. Non-depressed compared to depressed mothers activated uniquely to own infant greater than other infant cry in occipital fusiform areas. Disturbance of these neural networks involved in emotional response and regulation may help to explain parenting deficits in depressed mothers.

  8. Neural interaction of speech and gesture: differential activations of metaphoric co-verbal gestures.

    Science.gov (United States)

    Kircher, Tilo; Straube, Benjamin; Leube, Dirk; Weis, Susanne; Sachs, Olga; Willmes, Klaus; Konrad, Kerstin; Green, Antonia

    2009-01-01

    Gestures are an important part of human communication. However, little is known about the neural correlates of gestures accompanying speech comprehension. The goal of this study is to investigate the neural basis of speech-gesture interaction as reflected in activation increase and decrease during observation of natural communication. Fourteen German participants watched video clips of 5 s duration depicting an actor who performed metaphoric gestures to illustrate the abstract content of spoken sentences. Furthermore, video clips of isolated gestures (without speech), isolated spoken sentences (without gestures) and gestures in the context of an unknown language (Russian) were additionally presented while functional magnetic resonance imaging (fMRI) data were acquired. Bimodal speech and gesture processing led to left hemispheric activation increases of the posterior middle temporal gyrus, the premotor cortex, the inferior frontal gyrus, and the right superior temporal sulcus. Activation reductions during the bimodal condition were located in the left superior temporal gyrus and the left posterior insula. Gesture related activation increases and decreases were dependent on language semantics and were not found in the unknown-language condition. Our results suggest that semantic integration processes for bimodal speech plus gesture comprehension are reflected in activation increases in the classical left hemispheric language areas. Speech related gestures seem to enhance language comprehension during the face-to-face communication.

  9. Deep Convolutional and LSTM Recurrent Neural Networks for Multimodal Wearable Activity Recognition

    Science.gov (United States)

    Ordóñez, Francisco Javier; Roggen, Daniel

    2016-01-01

    Human activity recognition (HAR) tasks have traditionally been solved using engineered features obtained by heuristic processes. Current research suggests that deep convolutional neural networks are suited to automate feature extraction from raw sensor inputs. However, human activities are made of complex sequences of motor movements, and capturing this temporal dynamics is fundamental for successful HAR. Based on the recent success of recurrent neural networks for time series domains, we propose a generic deep framework for activity recognition based on convolutional and LSTM recurrent units, which: (i) is suitable for multimodal wearable sensors; (ii) can perform sensor fusion naturally; (iii) does not require expert knowledge in designing features; and (iv) explicitly models the temporal dynamics of feature activations. We evaluate our framework on two datasets, one of which has been used in a public activity recognition challenge. Our results show that our framework outperforms competing deep non-recurrent networks on the challenge dataset by 4% on average; outperforming some of the previous reported results by up to 9%. Our results show that the framework can be applied to homogeneous sensor modalities, but can also fuse multimodal sensors to improve performance. We characterise key architectural hyperparameters’ influence on performance to provide insights about their optimisation. PMID:26797612

  10. Age of acquisition modulates neural activity for both regular and irregular syntactic functions.

    Science.gov (United States)

    Hernandez, Arturo E; Hofmann, Juliane; Kotz, Sonja A

    2007-07-01

    Studies have found that neural activity is greater for irregular grammatical items than regular items. Findings with monolingual Spanish speakers have revealed a similar effect when making gender decisions for visually presented nouns. The current study extended previous studies by looking at the role of regularity in modulating differences in groups that differ in the age of acquisition of a language. Early and late learners of Spanish matched on measures of language proficiency were asked to make gender decisions to regular (-o for masculine and -a for feminine) and irregular items (which can end in e, l, n, r, s, t and z). Results revealed increased activity in left BA 44 for irregular compared to regular items in separate comparisons for both early and late learners. In addition, within-group comparisons revealed that neural activity for irregulars extended into left BA 47 for late learners and into left BA 6 for early learners. Direct comparisons between groups revealed increased activity in left BA 44/45 for irregular items indicating the need for more extensive syntactic processing in late learners. The results revealed that processing of irregular grammatical gender leads to increased activity in left BA 44 and adjacent areas in the left IFG regardless of when a language is learned. Furthermore, these findings suggest differential recruitment of brain areas associated with grammatical processing in late learners. The results are discussed with regard to a model which considers L2 learning as emerging from the competitive interplay between two languages.

  11. Active and reactive power neurocontroller for grid-connected photovoltaic generation system

    Directory of Open Access Journals (Sweden)

    I. Abadlia

    2016-03-01

    Full Text Available Many researchers have contributed to the development of a firm foundation for analysis and design of control applications in grid-connected renewable energy sources. This paper presents an intelligent control algorithm fond on artificial neural networks for active and reactive power controller in grid-connected photovoltaic generation system. The system is devices into two parts in which each part contains an inverter with control algorithm. A DC/DC converter in output voltage established by control magnitude besides maximum power point tracker algorithm always finds optimal power of the PV array in use. A DC/AC hysteresis inverter designed can synchronize a sinusoidal current output with the grid voltage and accurate an independent active and reactive power control. Simulation results confirm the validation of the purpose. Neurocontroller based active and reactive power presents an efficiency control that guarantees good response to the steps changing in active and reactive power with an acceptable current/voltage synchronism. In this paper the power circuit and the control system of the presented grid-connected photovoltaic generation system is simulated and tested by MatLab/Simulink.

  12. Aural localization of silent objects by active human biosonar: neural representations of virtual echo-acoustic space.

    Science.gov (United States)

    Wallmeier, Ludwig; Kish, Daniel; Wiegrebe, Lutz; Flanagin, Virginia L

    2015-03-01

    Some blind humans have developed the remarkable ability to detect and localize objects through the auditory analysis of self-generated tongue clicks. These echolocation experts show a corresponding increase in 'visual' cortex activity when listening to echo-acoustic sounds. Echolocation in real-life settings involves multiple reflections as well as active sound production, neither of which has been systematically addressed. We developed a virtualization technique that allows participants to actively perform such biosonar tasks in virtual echo-acoustic space during magnetic resonance imaging (MRI). Tongue clicks, emitted in the MRI scanner, are picked up by a microphone, convolved in real time with the binaural impulse responses of a virtual space, and presented via headphones as virtual echoes. In this manner, we investigated the brain activity during active echo-acoustic localization tasks. Our data show that, in blind echolocation experts, activations in the calcarine cortex are dramatically enhanced when a single reflector is introduced into otherwise anechoic virtual space. A pattern-classification analysis revealed that, in the blind, calcarine cortex activation patterns could discriminate left-side from right-side reflectors. This was found in both blind experts, but the effect was significant for only one of them. In sighted controls, 'visual' cortex activations were insignificant, but activation patterns in the planum temporale were sufficient to discriminate left-side from right-side reflectors. Our data suggest that blind and echolocation-trained, sighted subjects may recruit different neural substrates for the same active-echolocation task. © 2015 Federation of European Neuroscience Societies and John Wiley & Sons Ltd.

  13. Neural activation during processing of aversive faces predicts treatment outcome in alcoholism.

    Science.gov (United States)

    Charlet, Katrin; Schlagenhauf, Florian; Richter, Anne; Naundorf, Karina; Dornhof, Lina; Weinfurtner, Christopher E J; König, Friederike; Walaszek, Bernadeta; Schubert, Florian; Müller, Christian A; Gutwinski, Stefan; Seissinger, Annette; Schmitz, Lioba; Walter, Henrik; Beck, Anne; Gallinat, Jürgen; Kiefer, Falk; Heinz, Andreas

    2014-05-01

    Neuropsychological studies reported decoding deficits of emotional facial expressions in alcohol-dependent patients, and imaging studies revealed reduced prefrontal and limbic activation during emotional face processing. However, it remains unclear whether this reduced neural activation is mediated by alcohol-associated volume reductions and whether it interacts with treatment outcome. We combined analyses of neural activation during an aversive face-cue-comparison task and local gray matter volumes (GM) using Biological Parametric Mapping in 33 detoxified alcohol-dependent patients and 33 matched healthy controls. Alcoholics displayed reduced activation toward aversive faces-neutral shapes in bilateral fusiform gyrus [FG; Brodmann areas (BA) 18/19], right middle frontal gyrus (BA46/47), right inferior parietal gyrus (BA7) and left cerebellum compared with controls, which were explained by GM differences (except for cerebellum). Enhanced functional activation in patients versus controls was found in left rostral anterior cingulate cortex (ACC) and medial frontal gyrus (BA10/11), even after GM reduction control. Increased ACC activation correlated significantly with less (previous) lifetime alcohol intake [Lifetime Drinking History (LDH)], longer abstinence and less subsequent binge drinking in patients. High LDH appear to impair treatment outcome via its neurotoxicity on ACC integrity. Thus, high activation of the rostral ACC elicited by affective faces appears to be a resilience factor predicting better treatment outcome. Although no group differences were found, increased FG activation correlated with patients' higher LDH. Because high LDH correlated with worse task performance for facial stimuli in patients, elevated activation in the fusiform 'face' area may reflect inefficient compensatory activation. Therapeutic interventions (e.g. emotion evaluation training) may enable patients to cope with social stress and to decrease relapses after detoxification.

  14. Reduction in neural performance following recovery from anoxic stress is mimicked by AMPK pathway activation.

    Directory of Open Access Journals (Sweden)

    Tomas G A Money

    Full Text Available Nervous systems are energetically expensive to operate and maintain. Both synaptic and action potential signalling require a significant investment to maintain ion homeostasis. We have investigated the tuning of neural performance following a brief period of anoxia in a well-characterized visual pathway in the locust, the LGMD/DCMD looming motion-sensitive circuit. We hypothesised that the energetic cost of signalling can be dynamically modified by cellular mechanisms in response to metabolic stress. We examined whether recovery from anoxia resulted in a decrease in excitability of the electrophysiological properties in the DCMD neuron. We further examined the effect of these modifications on behavioural output. We show that recovery from anoxia affects metabolic rate, flight steering behaviour, and action potential properties. The effects of anoxia on action potentials can be mimicked by activation of the AMPK metabolic pathway. We suggest this is evidence of a coordinated cellular mechanism to reduce neural energetic demand following an anoxic stress. Together, this represents a dynamically-regulated means to link the energetic demands of neural signaling with the environmental constraints faced by the whole animal.

  15. Mild blast events alter anxiety, memory, and neural activity patterns in the anterior cingulate cortex.

    Directory of Open Access Journals (Sweden)

    Kun Xie

    Full Text Available There is a general interest in understanding of whether and how exposure to emotionally traumatizing events can alter memory function and anxiety behaviors. Here we have developed a novel laboratory-version of mild blast exposure comprised of high decibel bomb explosion sound coupled with strong air blast to mice. This model allows us to isolate the effects of emotionally fearful components from those of traumatic brain injury or bodily injury typical associated with bomb blasts. We demonstrate that this mild blast exposure is capable of impairing object recognition memory, increasing anxiety in elevated O-maze test, and resulting contextual generalization. Our in vivo neural ensemble recording reveal that such mild blast exposures produced diverse firing changes in the anterior cingulate cortex, a region processing emotional memory and inhibitory control. Moreover, we show that these real-time neural ensemble patterns underwent post-event reverberations, indicating rapid consolidation of those fearful experiences. Identification of blast-induced neural activity changes in the frontal brain may allow us to better understand how mild blast experiences result in abnormal changes in memory functions and excessive fear generalization related to post-traumatic stress disorder.

  16. Automated Generation of Models of Activities of Daily Living

    OpenAIRE

    Saives, Jérémie; Faraut, Gregory

    2014-01-01

    International audience; In order to increase the safety of autonomous elderly people in their home, Ambient Assisted Living technologies are currently emerging. Namely, the recognition of their activities might be a way to detect eventual health problems, and can be performed in a Smarthome equipped with binary sensors. Hence, this communication aims at providing means to automatically generate a formal model of the Activities of Daily Living. A data mining approach in order to discover frequ...

  17. The effects of dynamical synapses on firing rate activity: a spiking neural network model.

    Science.gov (United States)

    Khalil, Radwa; Moftah, Marie Z; Moustafa, Ahmed A

    2017-11-01

    Accumulating evidence relates the fine-tuning of synaptic maturation and regulation of neural network activity to several key factors, including GABA A signaling and a lateral spread length between neighboring neurons (i.e., local connectivity). Furthermore, a number of studies consider short-term synaptic plasticity (STP) as an essential element in the instant modification of synaptic efficacy in the neuronal network and in modulating responses to sustained ranges of external Poisson input frequency (IF). Nevertheless, evaluating the firing activity in response to the dynamical interaction between STP (triggered by ranges of IF) and these key parameters in vitro remains elusive. Therefore, we designed a spiking neural network (SNN) model in which we incorporated the following parameters: local density of arbor essences and a lateral spread length between neighboring neurons. We also created several network scenarios based on these key parameters. Then, we implemented two classes of STP: (1) short-term synaptic depression (STD) and (2) short-term synaptic facilitation (STF). Each class has two differential forms based on the parametric value of its synaptic time constant (either for depressing or facilitating synapses). Lastly, we compared the neural firing responses before and after the treatment with STP. We found that dynamical synapses (STP) have a critical differential role on evaluating and modulating the firing rate activity in each network scenario. Moreover, we investigated the impact of changing the balance between excitation (E) and inhibition (I) on stabilizing this firing activity. © 2017 Federation of European Neuroscience Societies and John Wiley & Sons Ltd.

  18. Mdm2 mediates FMRP- and Gp1 mGluR-dependent protein translation and neural network activity.

    Science.gov (United States)

    Liu, Dai-Chi; Seimetz, Joseph; Lee, Kwan Young; Kalsotra, Auinash; Chung, Hee Jung; Lu, Hua; Tsai, Nien-Pei

    2017-10-15

    Activating Group 1 (Gp1) metabotropic glutamate receptors (mGluRs), including mGluR1 and mGluR5, elicits translation-dependent neural plasticity mechanisms that are crucial to animal behavior and circuit development. Dysregulated Gp1 mGluR signaling has been observed in numerous neurological and psychiatric disorders. However, the molecular pathways underlying Gp1 mGluR-dependent plasticity mechanisms are complex and have been elusive. In this study, we identified a novel mechanism through which Gp1 mGluR mediates protein translation and neural plasticity. Using a multi-electrode array (MEA) recording system, we showed that activating Gp1 mGluR elevates neural network activity, as demonstrated by increased spontaneous spike frequency and burst activity. Importantly, we validated that elevating neural network activity requires protein translation and is dependent on fragile X mental retardation protein (FMRP), the protein that is deficient in the most common inherited form of mental retardation and autism, fragile X syndrome (FXS). In an effort to determine the mechanism by which FMRP mediates protein translation and neural network activity, we demonstrated that a ubiquitin E3 ligase, murine double minute-2 (Mdm2), is required for Gp1 mGluR-induced translation and neural network activity. Our data showed that Mdm2 acts as a translation suppressor, and FMRP is required for its ubiquitination and down-regulation upon Gp1 mGluR activation. These data revealed a novel mechanism by which Gp1 mGluR and FMRP mediate protein translation and neural network activity, potentially through de-repressing Mdm2. Our results also introduce an alternative way for understanding altered protein translation and brain circuit excitability associated with Gp1 mGluR in neurological diseases such as FXS. © The Author 2017. Published by Oxford University Press. All rights reserved. For Permissions, please email: journals.permissions@oup.com.

  19. Effects of climate change on income generating activities of farmers ...

    African Journals Online (AJOL)

    The need to examine the changes that the effect of climate change brings about on the income generating activities of farmers necessitated this study. Two local government areas (LGAs) were randomly selected and simple random sampling was used to sample 160 farmers from the 2 LGAs. Chi-square and Pearson ...

  20. Income Generation Activities among Academic Staffs at Malaysian Public Universities

    Science.gov (United States)

    Ahmad, Abd Rahman; Soon, Ng Kim; Ting, Ngeoh Pei

    2015-01-01

    Income generation activities have been acquainted among public higher education institutions (HEIs) in Malaysia. Various factors that brought to insufficient of funding caused Higher Education Institutions(HEIs) to seek for additional income as to support the operation expenses. Financial sustainability issues made up the significant impact…

  1. Density of Plutonium Turnings Generated from Machining Activities

    Energy Technology Data Exchange (ETDEWEB)

    Gonzales, John Robert [Los Alamos National Lab. (LANL), Los Alamos, NM (United States); Vigil, Duane M. [Los Alamos National Lab. (LANL), Los Alamos, NM (United States); Jachimowski, Thomas A. [Los Alamos National Lab. (LANL), Los Alamos, NM (United States); Archuleta, Alonso [Los Alamos National Lab. (LANL), Los Alamos, NM (United States); Arellano, Gerald Joseph [Los Alamos National Lab. (LANL), Los Alamos, NM (United States); Melton, Vince Lee [Los Alamos National Lab. (LANL), Los Alamos, NM (United States)

    2016-10-20

    The purpose of this project was to determine the density of plutonium (Pu) turnings generated from the range of machining activities, using both surrogate material and machined Pu turnings. Verify that 500 grams (g) of plutonium will fit in a one quart container using a surrogate equivalent volume and that 100 grams of Pu will fit in a one quart Savy container.

  2. Right hemisphere neural activations in the recall of waking fantasies and of dreams.

    Science.gov (United States)

    Benedetti, Francesco; Poletti, Sara; Radaelli, Daniele; Ranieri, Rebecca; Genduso, Valeria; Cavallotti, Simone; Castelnovo, Anna; Smeraldi, Enrico; Scarone, Silvio; D'Agostino, Armando

    2015-10-01

    The story-like organization of dreams is characterized by a pervasive bizarreness of events and actions that resembles psychotic thought, and largely exceeds that observed in normal waking fantasies. Little is known about the neural correlates of the confabulatory narrative construction of dreams. In this study, dreams, fantasies elicited by ambiguous pictorial stimuli, and non-imaginative first- and third-person narratives from healthy participants were recorded, and were then studied for brain blood oxygen level-dependent functional magnetic resonance imaging on a 3.0-Tesla scanner while listening to their own narrative reports and attempting a retrieval of the corresponding experience. In respect to non-bizarre reports of daytime activities, the script-driven recall of dreams and fantasies differentially activated a right hemisphere network including areas in the inferior frontal gyrus, and superior and middle temporal gyrus. Neural responses were significantly greater for fantasies than for dreams in all regions, and inversely proportional to the degree of bizarreness observed in narrative reports. The inferior frontal gyrus, superior and middle temporal gyrus have been implicated in the semantic activation, integration and selection needed to build a coherent story representation and to resolve semantic ambiguities; in deductive and inferential reasoning; in self- and other-perspective taking, theory of mind, moral and autobiographical reasoning. Their degree of activation could parallel the level of logical robustness or inconsistency experienced when integrating information and mental representations in the process of building fantasy and dream narratives. © 2015 European Sleep Research Society.

  3. Monitoring the neural activity of the state of mental silence while practicing Sahaja yoga meditation.

    Science.gov (United States)

    Hernández, Sergio E; Suero, José; Rubia, Katya; González-Mora, José L

    2015-03-01

    To identify the neural correlates of the state of mental silence as experienced through Sahaja yoga meditation. Nineteen experienced meditators underwent functional magnetic resonance imaging during three short consecutive meditation periods, contrasted with a control relaxation condition. Relative to baseline, at the beginning of the meditation sessions there was a significant increase of activation in bilateral inferior frontal and temporal regions. Activation became progressively more reduced with deeper meditation stages and in the last meditation session it became localized to the right inferior frontal cortex/ right insula and right middle/superior temporal cortex. Furthermore, right inferior frontal activation was directly associated with the subjective depth of the mental silence experience. Meditators appear to pass through an initial intense neural self-control process necessary to silence their mind. After this they experience relatively reduced brain activation concomitant with the deepening of the state of mental silence over right inferior frontal cortex, probably reflecting an effortless process of attentional contemplation associated with this state.

  4. Emergence of spatially heterogeneous burst suppression in a neural field model of electrocortical activity

    Directory of Open Access Journals (Sweden)

    Ingo eBojak

    2015-02-01

    Full Text Available Burst suppression in the electroencephalogram (EEG is a well described phenomenon that occurs during deep anaesthesia, as well as in a variety of congenital and acquired brain insults. Classically it is thought of as spatially synchronous, quasi-periodic bursts of high amplitude EEG separated by low amplitude activity. However, its characterisation as a ``global brain state'' has been challenged by recent results obtained with intracranial electrocortigraphy. Not only does it appear that burst suppression activity is highly asynchronous across cortex, but also that it may occur in isolated regions of circumscribed spatial extent. Here we outline a realistic neural field model for burst suppression by adding a slow process of synaptic resource depletion and recovery, which is able to reproduce qualitatively the empirically observed features during general anaesthesia at the whole cortex level. Simulations reveal heterogeneous bursting over the model cortex and complex spatiotemporal dynamics during simulated anaesthetic action, and provide forward predictions of neuroimaging signals for subsequent empirical comparisons and more detailed characterisation.Because burst suppression corresponds to a dynamical end-point of brain activity, theoretically accounting for its spatiotemporal emergence will vitally contribute to efforts aimed at clarifying whether a common physiological trajectory is induced by the actions of general anaesthetic agents. We have taken a first step in this direction by showing that a neural field model can qualitatively match recent experimental data that indicate spatial differentiation of burst suppression activity across cortex.

  5. Overlapping patterns of neural activity for different forms of novelty in fMRI

    Directory of Open Access Journals (Sweden)

    Colin Shaun Hawco

    2014-09-01

    Full Text Available When stimuli are presented multiple times, the neural response to repeated stimuli is reduced relative to novel stimuli (repetition suppression. Responses to different types of novelty were examined. Stimulus novelty was examined by contrasting first vs. second presentation of triads of objects during memory encoding. Semantic novelty was contrasted by comparing unrelated (semantically novel triads of objects to triads in which all three objects were related (e.g. all objects were tools. In recognition, associative novelty was examined by contrasting rearranged triads (previously seen objects in a new association with intact triads. Activity was observed in posterior regions (occipital and fusiform, with the largest extent of activity for stimulus novelty and smallest for associational novelty. Frontal activity was also observed in stimulus and semantic novelty. Additional analysis indicated that the hemodynamic response in voxels identified in the stimulus and semantic novelty contrasts was modulated by reaction time on a trial-by-trial basis. That is, the duration of the hemodynamic response was driven by reaction time. This was not the case for associative novelty. The high level of overlap across different forms of novelty suggests a similar mechanism for reduced neural activity, which may be related to reduced visual processing time. This is consistent with a facilitation model of repetition suppression, which posits a reduced peak and duration of neuronal firing for repeated stimuli.

  6. Tracking cortical entrainment in neural activity: Auditory processes in human temporal cortex

    Directory of Open Access Journals (Sweden)

    Andrew eThwaites

    2015-02-01

    Full Text Available A primary objective for cognitive neuroscience is to identify how features of the sensory environment are encoded in neural activity. Current auditory models of loudness perception can be used to make detailed predictions about the neural activity of the cortex as an individual listens to speech. We used two such models (loudness-sones and loudness-phons, varying in their psychophysiological realism, to predict the instantaneous loudness contours produced by 480 isolated words. These two sets of 480 contours were used to search for electrophysiological evidence of loudness processing in whole-brain recordings of electro- and magneto-encephalographic (EMEG activity, recorded while subjects listened to the words. The technique identified a bilateral sequence of loudness processes, predicted by the more realistic loudness-sones model, that begin in auditory cortex at ~80 ms and subsequently reappear, tracking progressively down the superior temporal sulcus (STS at lags from 230 to 330 ms. The technique was then extended to search for regions sensitive to the fundamental frequency (F0 of the voiced parts of the speech. It identified a bilateral F0 process in auditory cortex at a lag of ~90 ms, which was not followed by activity in STS. The results suggest that loudness information is being used to guide the analysis of the speech stream as it proceeds beyond auditory cortex down STS towards the temporal pole.

  7. Bioimpedance Harmonic Analysis as a Diagnostic Tool to Assess Regional Circulation and Neural Activity

    Science.gov (United States)

    Mudraya, I. S.; Revenko, S. V.; Khodyreva, L. A.; Markosyan, T. G.; Dudareva, A. A.; Ibragimov, A. R.; Romich, V. V.; Kirpatovsky, V. I.

    2013-04-01

    The novel technique based on harmonic analysis of bioimpedance microvariations with original hard- and software complex incorporating a high-resolution impedance converter was used to assess the neural activity and circulation in human urinary bladder and penis in patients with pelvic pain, erectile dysfunction, and overactive bladder. The therapeutic effects of shock wave therapy and Botulinum toxin detrusor injections were evaluated quantitatively according to the spectral peaks at low 0.1 Hz frequency (M for Mayer wave), respiratory (R) and cardiac (C) rhythms with their harmonics. Enhanced baseline regional neural activity identified according to M and R peaks was found to be presumably sympathetic in pelvic pain patients, and parasympathetic - in patients with overactive bladder. Total pulsatile activity and pulsatile resonances found in the bladder as well as in the penile spectrum characterised regional circulation and vascular tone. The abnormal spectral parameters characteristic of the patients with genitourinary diseases shifted to the norm in the cases of efficient therapy. Bioimpedance harmonic analysis seems to be a potent tool to assess regional peculiarities of circulatory and autonomic nervous activity in the course of patient treatment.

  8. Neural activation in speech production and reading aloud in native and non-native languages.

    Science.gov (United States)

    Berken, Jonathan A; Gracco, Vincent L; Chen, Jen-Kai; Soles, Jennika; Watkins, Kate E; Baum, Shari; Callahan, Megan; Klein, Denise

    2015-05-15

    We used fMRI to investigate neural activation in reading aloud in bilinguals differing in age of acquisition. Three groups were compared: French-English bilinguals who acquired two languages from birth (simultaneous), French-English bilinguals who learned their L2 after the age of 5 years (sequential), and English-speaking monolinguals. While the bilingual groups contrasted in age of acquisition, they were matched for language proficiency, although sequential bilinguals produced speech with a less native-like accent in their L2 than in their L1. Simultaneous bilinguals activated similar brain regions to an equivalent degree when reading in their two languages. In contrast, sequential bilinguals more strongly activated areas related to speech-motor control and orthographic to phonological mapping, the left inferior frontal gyrus, left premotor cortex, and left fusiform gyrus, when reading aloud in L2 compared to L1. In addition, the activity in these regions showed a significant positive correlation with age of acquisition. The results provide evidence for the engagement of overlapping neural substrates for processing two languages when acquired in native context from birth. However, it appears that the maturation of certain brain regions for both speech production and phonological encoding is limited by a sensitive period for L2 acquisition regardless of language proficiency. Copyright © 2015 Elsevier Inc. All rights reserved.

  9. An Intelligent Active Video Surveillance System Based on the Integration of Virtual Neural Sensors and BDI Agents

    Science.gov (United States)

    Gregorio, Massimo De

    In this paper we present an intelligent active video surveillance system currently adopted in two different application domains: railway tunnels and outdoor storage areas. The system takes advantages of the integration of Artificial Neural Networks (ANN) and symbolic Artificial Intelligence (AI). This hybrid system is formed by virtual neural sensors (implemented as WiSARD-like systems) and BDI agents. The coupling of virtual neural sensors with symbolic reasoning for interpreting their outputs, makes this approach both very light from a computational and hardware point of view, and rather robust in performances. The system works on different scenarios and in difficult light conditions.

  10. New generation non-stationary portable neutron generators for biophysical applications of Neutron Activation Analysis.

    Science.gov (United States)

    Marchese, N; Cannuli, A; Caccamo, M T; Pace, C

    2017-01-01

    Neutron sources are increasingly employed in a wide range of research fields. For some specific purposes an alternative to existing large-scale neutron scattering facilities, can be offered by the new generation of portable neutron devices. This review reports an overview for such recently available neutron generators mainly addressed to biophysics applications with specific reference to portable non-stationary neutron generators applied in Neutron Activation Analysis (NAA). The review reports a description of a typical portable neutron generator set-up addressed to biophysics applications. New generation portable neutron devices, for some specific applications, can constitute an alternative to existing large-scale neutron scattering facilities. Deuterium-Deuterium pulsed neutron sources able to generate 2.5MeV neutrons, with a neutron yield of 1.0×10(6)n/s, a pulse rate of 250Hz to 20kHz and a duty factor varying from 5% to 100%, when combined with solid-state photon detectors, show that this kind of compact devices allow rapid and user-friendly elemental analysis. "This article is part of a Special Issue entitled "Science for Life" Guest Editor: Dr. Austen Angell, Dr. Salvatore Magazù and Dr. Federica Migliardo". Copyright © 2016 Elsevier B.V. All rights reserved.

  11. Forecast and restoration of geomagnetic activity indices by using the software-computational neural network complex

    Science.gov (United States)

    Barkhatov, Nikolay; Revunov, Sergey

    2010-05-01

    It is known that currently used indices of geomagnetic activity to some extent reflect the physical processes occurring in the interaction of the perturbed solar wind with Earth's magnetosphere. Therefore, they are connected to each other and with the parameters of near-Earth space. The establishment of such nonlinear connections is interest. For such purposes when the physical problem is complex or has many parameters the technology of artificial neural networks is applied. Such approach for development of the automated forecast and restoration method of geomagnetic activity indices with the establishment of creative software-computational neural network complex is used. Each neural network experiments were carried out at this complex aims to search for a specific nonlinear relation between the analyzed indices and parameters. At the core of the algorithm work program a complex scheme of the functioning of artificial neural networks (ANN) of different types is contained: back propagation Elman network, feed forward network, fuzzy logic network and Kohonen layer classification network. Tools of the main window of the complex (the application) the settings used by neural networks allow you to change: the number of hidden layers, the number of neurons in the layer, the input and target data, the number of cycles of training. Process and the quality of training the ANN is a dynamic plot of changing training error. Plot of comparison of network response with the test sequence is result of the network training. The last-trained neural network with established nonlinear connection for repeated numerical experiments can be run. At the same time additional training is not executed and the previously trained network as a filter input parameters get through and output parameters with the test event are compared. At statement of the large number of different experiments provided the ability to run the program in a "batch" mode is stipulated. For this purpose the user a

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

    Science.gov (United States)

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

    2012-03-27

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

  13. Voltage Control of PM Synchronous Motor Driven PM Synchronous Generator System Using Recurrent Wavelet Neural Network Controller

    Directory of Open Access Journals (Sweden)

    C.H. Lin

    2013-04-01

    Full Text Available In this paper the two novel recurrent wavelet neural network (RWNN controllers are proposed for controlling output direct current (DC voltage of the rectifier and output alternate current (AC voltage of the inverter. The output power of the rectifier and the inverter is provided by three-phase permanent magnet synchronous generator (PMSG system directly-driven by permanent magnet synchronous motor (PMSM. Firstly, the field-oriented mechanism is implemented for controlling output of the PMSG system. Then, one RWNN controller is developed for controlling rectifier to convert AC voltage into DC link voltage and the other RWNN controller is implemented for controlling inverter to convert DC link voltage into AC line voltage. Moreover, two online trained RWNNs using backpropagation learning algorithms are developed for regulating both the DC link voltage of the rectifier and the AC line voltage of the inverter. Finally, the effectiveness and advantages of the proposed two RWNN controllers are demonstrated in comparison with the two PI controllers from some experimental results.

  14. Neural activations are related to body-shape, anxiety, and outcomes in adolescent anorexia nervosa.

    Science.gov (United States)

    Xu, Jie; Harper, Jessica A; Van Enkevort, Erin A; Latimer, Kelsey; Kelley, Urszula; McAdams, Carrie J

    2017-04-01

    Anorexia nervosa (AN) is an illness that frequently begins during adolescence and involves weight loss. Two groups of adolescent girls (AN-A, weight-recovered following AN) and (HC-A, healthy comparison) completed a functional magnetic resonance imaging task involving social evaluations, allowing comparison of neural activations during self-evaluations, friend-evaluations, and perspective-taking self-evaluations. Although the two groups were not different in their whole-brain activations, anxiety and body shape concerns were correlated with neural activity in a priori regions of interest. A cluster in medial prefrontal cortex and the dorsal anterior cingulate correlated with the body shape questionnaire; subjects with more body shape concerns used this area less during self than friend evaluations. A cluster in medial prefrontal cortex and the cingulate also correlated with anxiety such that more anxiety was associated with engagement when disagreeing rather than agreeing with social terms during self-evaluations. This data suggests that differences in the utilization of frontal brain regions during social evaluations may contribute to both anxiety and body shape concerns in adolescents with AN. Clinical follow-up was obtained, allowing exploration of whether brain function early in course of disease relates to illness trajectory. The adolescents successful in recovery used the posterior cingulate and precuneus more for friend than self evaluations than the adolescents that remained ill, suggesting that neural differences related to social evaluations may provide clinical predictive value. Utilization of both MPFC and the precuneus during social and self evaluations may be a key biological component for achieving sustained weight-recovery in adolescents with AN. Copyright © 2016 Elsevier Ltd. All rights reserved.

  15. Sex differences in neural activation to facial expressions denoting contempt and disgust.

    Directory of Open Access Journals (Sweden)

    André Aleman

    Full Text Available The facial expression of contempt has been regarded to communicate feelings of moral superiority. Contempt is an emotion that is closely related to disgust, but in contrast to disgust, contempt is inherently interpersonal and hierarchical. The aim of this study was twofold. First, to investigate the hypothesis of preferential amygdala responses to contempt expressions versus disgust. Second, to investigate whether, at a neural level, men would respond stronger to biological signals of interpersonal superiority (e.g., contempt than women. We performed an experiment using functional magnetic resonance imaging (fMRI, in which participants watched facial expressions of contempt and disgust in addition to neutral expressions. The faces were presented as distractors in an oddball task in which participants had to react to one target face. Facial expressions of contempt and disgust activated a network of brain regions, including prefrontal areas (superior, middle and medial prefrontal gyrus, anterior cingulate, insula, amygdala, parietal cortex, fusiform gyrus, occipital cortex, putamen and thalamus. Contemptuous faces did not elicit stronger amygdala activation than did disgusted expressions. To limit the number of statistical comparisons, we confined our analyses of sex differences to the frontal and temporal lobes. Men displayed stronger brain activation than women to facial expressions of contempt in the medial frontal gyrus, inferior frontal gyrus, and superior temporal gyrus. Conversely, women showed stronger neural responses than men to facial expressions of disgust. In addition, the effect of stimulus sex differed for men versus women. Specifically, women showed stronger responses to male contemptuous faces (as compared to female expressions, in the insula and middle frontal gyrus. Contempt has been conceptualized as signaling perceived moral violations of social hierarchy, whereas disgust would signal violations of physical purity. Thus, our

  16. Inertial effects on the stress generation of active fluids

    Science.gov (United States)

    Takatori, S. C.; Brady, J. F.

    2017-09-01

    Suspensions of self-propelled bodies generate a unique mechanical stress owing to their motility that impacts their large-scale collective behavior. For microswimmers suspended in a fluid with negligible particle inertia, we have shown that the virial swim stress is a useful quantity to understand the rheology and nonequilibrium behaviors of active soft matter systems. For larger self-propelled organisms such as fish, it is unclear how particle inertia impacts their stress generation and collective movement. Here we analyze the effects of finite particle inertia on the mechanical pressure (or stress) generated by a suspension of self-propelled bodies. We find that swimmers of all scales generate a unique swim stress and Reynolds stress that impact their collective motion. We discover that particle inertia plays a similar role as confinement in overdamped active Brownian systems, where the reduced run length of the swimmers decreases the swim stress and affects the phase behavior. Although the swim and Reynolds stresses vary individually with the magnitude of particle inertia, the sum of the two contributions is independent of particle inertia. This points to an important concept when computing stresses in computer simulations of nonequilibrium systems: The Reynolds and the virial stresses must both be calculated to obtain the overall stress generated by a system.

  17. Neural network radiative transfer solvers for the generation of high resolution solar irradiance spectra parameterized by cloud and aerosol parameters

    Science.gov (United States)

    Taylor, M.; Kosmopoulos, P. G.; Kazadzis, S.; Keramitsoglou, I.; Kiranoudis, C. T.

    2016-01-01

    This paper reports on the development of a neural network (NN) model for instantaneous and accurate estimation of solar radiation spectra and budgets geared toward satellite cloud data using a ≈2.4 M record, high-spectral resolution look up table (LUT) generated with the radiative transfer model libRadtran. Two NN solvers, one for clear sky conditions dominated by aerosol and one for cloudy skies, were trained on a normally-distributed and multiparametric subset of the LUT that spans a very broad class of atmospheric and meteorological conditions as inputs with corresponding high resolution solar irradiance target spectra as outputs. The NN solvers were tested by feeding them with a large (10 K record) ;off-grid; random subset of the LUT spanning the training data space, and then comparing simulated outputs with target values provided by the LUT. The NN solvers demonstrated a capability to interpolate accurately over the entire multiparametric space. Once trained, the NN solvers allow for high-speed estimation of solar radiation spectra with high spectral resolution (1 nm) and for a quantification of the effect of aerosol and cloud optical parameters on the solar radiation budget without the need for a massive database. The cloudy sky NN solver was applied to high spatial resolution (54 K pixel) cloud data extracted from the Spinning Enhanced Visible and Infrared Imager (SEVIRI) onboard the geostationary Meteosat Second Generation 3 (MSG3) satellite and demonstrated that coherent maps of spectrally-integrated global horizontal irradiance at this resolution can be produced on the order of 1 min.

  18. The effects of inhibitory control training for preschoolers on reasoning ability and neural activity

    DEFF Research Database (Denmark)

    Liu, Qian; Zhu, Xinyi; Ziegler, Albert

    2015-01-01

    Inhibitory control (including response inhibition and interference control) develops rapidly during the preschool period and is important for early cognitive development. This study aimed to determine the training and transfer effects on response inhibition in young children. Children in the trai......Inhibitory control (including response inhibition and interference control) develops rapidly during the preschool period and is important for early cognitive development. This study aimed to determine the training and transfer effects on response inhibition in young children. Children....... Furthermore, gender differences in the training-induced changes in neural activity were found in preschoolers....

  19. Neural activity related to discrimination and vocal production of consonant and dissonant musical intervals.

    Science.gov (United States)

    González-García, Nadia; González, Martha A; Rendón, Pablo L

    2016-07-15

    Relationships between musical pitches are described as either consonant, when associated with a pleasant and harmonious sensation, or dissonant, when associated with an inharmonious feeling. The accurate singing of musical intervals requires communication between auditory feedback processing and vocal motor control (i.e. audio-vocal integration) to ensure that each note is produced correctly. The objective of this study is to investigate the neural mechanisms through which trained musicians produce consonant and dissonant intervals. We utilized 4 musical intervals (specifically, an octave, a major seventh, a fifth, and a tritone) as the main stimuli for auditory discrimination testing, and we used the same interval tasks to assess vocal accuracy in a group of musicians (11 subjects, all female vocal students at conservatory level). The intervals were chosen so as to test for differences in recognition and production of consonant and dissonant intervals, as well as narrow and wide intervals. The subjects were studied using fMRI during performance of the interval tasks; the control condition consisted of passive listening. Singing dissonant intervals as opposed to singing consonant intervals led to an increase in activation in several regions, most notably the primary auditory cortex, the primary somatosensory cortex, the amygdala, the left putamen, and the right insula. Singing wide intervals as opposed to singing narrow intervals resulted in the activation of the right anterior insula. Moreover, we also observed a correlation between singing in tune and brain activity in the premotor cortex, and a positive correlation between training and activation of primary somatosensory cortex, primary motor cortex, and premotor cortex during singing. When singing dissonant intervals, a higher degree of training correlated with the right thalamus and the left putamen. Our results indicate that singing dissonant intervals requires greater involvement of neural mechanisms

  20. Application of an artificial neural network for evaluation of activity concentration exemption limits in NORM industry.

    Science.gov (United States)

    Wiedner, Hannah; Peyrés, Virginia; Crespo, Teresa; Mejuto, Marcos; García-Toraño, Eduardo; Maringer, Franz Josef

    2017-08-01

    NORM emits many different gamma energies that have to be analysed by an expert. Alternatively, artificial neural networks (ANNs) can be used. These mathematical software tools can generalize "knowledge" gained from training datasets, applying it to new problems. No expert knowledge of gamma-ray spectrometry is needed by the end-user. In this work an ANN was created that is able to decide from the raw gamma-ray spectrum if the activity concentrations in a sample are above or below the exemption limits. Copyright © 2017 Elsevier Ltd. All rights reserved.

  1. Neural activity in human primary motor cortex areas 4a and 4p is modulated differentially by attention to action

    OpenAIRE

    Binkofski, F.; Fink, Gereon R.; Geyer, Stefan; Buccino, G.; Gruber, Oliver; Shah, N. Jon; Taylor, John G.; Seitz, Rüdiger J.; Zilles, Karl; Freund, Hans-Joachim

    2002-01-01

    The mechanisms underlying attention to action are poorly understood. Although distracted by something else, we often maintain the accuracy of a movement, which suggests that differential neural mechanisms for the control of attended and nonattended action exist. Using functional magnetic resonance imaging (fMRI) in normal volunteers and probabilistic cytoarchitectonic maps, we observed that neural activity in subarea 4p (posterior) within the primary motor cortex was modulated by attention to...

  2. Co-speech gestures influence neural activity in brain regions associated with processing semantic information.

    Science.gov (United States)

    Dick, Anthony Steven; Goldin-Meadow, Susan; Hasson, Uri; Skipper, Jeremy I; Small, Steven L

    2009-11-01

    Everyday communication is accompanied by visual information from several sources, including co-speech gestures, which provide semantic information listeners use to help disambiguate the speaker's message. Using fMRI, we examined how gestures influence neural activity in brain regions associated with processing semantic information. The BOLD response was recorded while participants listened to stories under three audiovisual conditions and one auditory-only (speech alone) condition. In the first audiovisual condition, the storyteller produced gestures that naturally accompany speech. In the second, the storyteller made semantically unrelated hand movements. In the third, the storyteller kept her hands still. In addition to inferior parietal and posterior superior and middle temporal regions, bilateral posterior superior temporal sulcus and left anterior inferior frontal gyrus responded more strongly to speech when it was further accompanied by gesture, regardless of the semantic relation to speech. However, the right inferior frontal gyrus was sensitive to the semantic import of the hand movements, demonstrating more activity when hand movements were semantically unrelated to the accompanying speech. These findings show that perceiving hand movements during speech modulates the distributed pattern of neural activation involved in both biological motion perception and discourse comprehension, suggesting listeners attempt to find meaning, not only in the words speakers produce, but also in the hand movements that accompany speech.

  3. Neural control of computer cursor velocity by decoding motor cortical spiking activity in humans with tetraplegia

    Science.gov (United States)

    Kim, Sung-Phil; Simeral, John D.; Hochberg, Leigh R.; Donoghue, John P.; Black, Michael J.

    2008-12-01

    Computer-mediated connections between human motor cortical neurons and assistive devices promise to improve or restore lost function in people with paralysis. Recently, a pilot clinical study of an intracortical neural interface system demonstrated that a tetraplegic human was able to obtain continuous two-dimensional control of a computer cursor using neural activity recorded from his motor cortex. This control, however, was not sufficiently accurate for reliable use in many common computer control tasks. Here, we studied several central design choices for such a system including the kinematic representation for cursor movement, the decoding method that translates neuronal ensemble spiking activity into a control signal and the cursor control task used during training for optimizing the parameters of the decoding method. In two tetraplegic participants, we found that controlling a cursor's velocity resulted in more accurate closed-loop control than controlling its position directly and that cursor velocity control was achieved more rapidly than position control. Control quality was further improved over conventional linear filters by using a probabilistic method, the Kalman filter, to decode human motor cortical activity. Performance assessment based on standard metrics used for the evaluation of a wide range of pointing devices demonstrated significantly improved cursor control with velocity rather than position decoding. Disclosure. JPD is the Chief Scientific Officer and a director of Cyberkinetics Neurotechnology Systems (CYKN); he holds stock and receives compensation. JDS has been a consultant for CYKN. LRH receives clinical trial support from CYKN.

  4. Neural Activities Underlying the Feedback Express Salience Prediction Errors for Appetitive and Aversive Stimuli.

    Science.gov (United States)

    Gu, Yan; Hu, Xueping; Pan, Weigang; Yang, Chun; Wang, Lijun; Li, Yiyuan; Chen, Antao

    2016-10-03

    Feedback information is essential for us to adapt appropriately to the environment. The feedback-related negativity (FRN), a frontocentral negative deflection after the delivery of feedback, has been found to be larger for outcomes that are worse than expected, and it reflects a reward prediction error derived from the midbrain dopaminergic projections to the anterior cingulate cortex (ACC), as stated in reinforcement learning theory. In contrast, the prediction of response-outcome (PRO) model claims that the neural activity in the mediofrontal cortex (mPFC), especially the ACC, is sensitive to the violation of expectancy, irrespective of the valence of feedback. Additionally, increasing evidence has demonstrated significant activities in the striatum, anterior insula and occipital lobe for unexpected outcomes independently of their valence. Thus, the neural mechanism of the feedback remains under dispute. Here, we investigated the feedback with monetary reward and electrical pain shock in one task via functional magnetic resonance imaging. The results revealed significant prediction-error-related activities in the bilateral fusiform gyrus, right middle frontal gyrus and left cingulate gyrus for both money and pain. This implies that some regions underlying the feedback may signal a salience prediction error rather than a reward prediction error.

  5. Prediction of enzyme activity with neural network models based on electronic and geometrical features of substrates.

    Science.gov (United States)

    Szaleniec, Maciej

    2012-01-01

    Artificial Neural Networks (ANNs) are introduced as robust and versatile tools in quantitative structure-activity relationship (QSAR) modeling. Their application to the modeling of enzyme reactivity is discussed, along with methodological issues. Methods of input variable selection, optimization of network internal structure, data set division and model validation are discussed. The application of ANNs in the modeling of enzyme activity over the last 20 years is briefly recounted. The discussed methodology is exemplified by the case of ethylbenzene dehydrogenase (EBDH). Intelligent Problem Solver and genetic algorithms are applied for input vector selection, whereas k-means clustering is used to partition the data into training and test cases. The obtained models exhibit high correlation between the predicted and experimental values (R(2) > 0.9). Sensitivity analyses and study of the response curves are used as tools for the physicochemical interpretation of the models in terms of the EBDH reaction mechanism. Neural networks are shown to be a versatile tool for the construction of robust QSAR models that can be applied to a range of aspects important in drug design and the prediction of biological activity.

  6. Computerized cognitive training restores neural activity within the reality monitoring network in schizophrenia.

    Science.gov (United States)

    Subramaniam, Karuna; Luks, Tracy L; Fisher, Melissa; Simpson, Gregory V; Nagarajan, Srikantan; Vinogradov, Sophia

    2012-02-23

    Schizophrenia patients suffer from severe cognitive deficits, such as impaired reality monitoring. Reality monitoring is the ability to distinguish the source of internal experiences from outside reality. During reality monitoring tasks, schizophrenia patients make errors identifying "I made it up" items, and even during accurate performance, they show abnormally low activation of the medial prefrontal cortex (mPFC), a region that supports self-referential cognition. We administered 80 hr of computerized training of cognitive processes to schizophrenia patients and found improvement in reality monitoring that correlated with increased mPFC activity. In contrast, patients in a computer games control condition did not show any behavioral or neural improvements. Notably, recovery in mPFC activity after training was associated with improved social functioning 6 months later. These findings demonstrate that a serious behavioral deficit in schizophrenia, and its underlying neural dysfunction, can be improved by well-designed computerized cognitive training, resulting in better quality of life. Copyright © 2012 Elsevier Inc. All rights reserved.

  7. Operant conditioning of neural activity in freely behaving monkeys with intracranial reinforcement.

    Science.gov (United States)

    Eaton, Ryan W; Libey, Tyler; Fetz, Eberhard E

    2017-03-01

    Operant conditioning of neural activity has typically been performed under controlled behavioral conditions using food reinforcement. This has limited the duration and behavioral context for neural conditioning. To reward cell activity in unconstrained primates, we sought sites in nucleus accumbens (NAc) whose stimulation reinforced operant responding. In three monkeys, NAc stimulation sustained performance of a manual target-tracking task, with response rates that increased monotonically with increasing NAc stimulation. We recorded activity of single motor cortex neurons and documented their modulation with wrist force. We conditioned increased firing rates with the monkey seated in the training booth and during free behavior in the cage using an autonomous head-fixed recording and stimulating system. Spikes occurring above baseline rates triggered single or multiple electrical pulses to the reinforcement site. Such rate-contingent, unit-triggered stimulation was made available for periods of 1-3 min separated by 3-10 min time-out periods. Feedback was presented as event-triggered clicks both in-cage and in-booth, and visual cues were provided in many in-booth sessions. In-booth conditioning produced increases in single neuron firing probability with intracranial reinforcement in 48 of 58 cells. Reinforced cell activity could rise more than five times that of non-reinforced activity. In-cage conditioning produced significant increases in 21 of 33 sessions. In-cage rate changes peaked later and lasted longer than in-booth changes, but were often comparatively smaller, between 13 and 18% above non-reinforced activity. Thus intracranial stimulation reinforced volitional increases in cortical firing rates during both free behavior and a controlled environment, although changes in the latter were more robust.NEW & NOTEWORTHY Closed-loop brain-computer interfaces (BCI) were used to operantly condition increases in muscle and neural activity in monkeys by delivering

  8. DataHigh: Graphical user interface for visualizing and interacting with high-dimensional neural activity

    Science.gov (United States)

    Cowley, Benjamin R.; Kaufman, Matthew T.; Butler, Zachary S.; Churchland, Mark M.; Ryu, Stephen I.; Shenoy, Krishna V.; Yu, Byron M.

    2014-01-01

    Objective Analyzing and interpreting the activity of a heterogeneous population of neurons can be challenging, especially as the number of neurons, experimental trials, and experimental conditions increases. One approach is to extract a set of latent variables that succinctly captures the prominent co-fluctuation patterns across the neural population. A key problem is that the number of latent variables needed to adequately describe the population activity is often greater than three, thereby preventing direct visualization of the latent space. By visualizing a small number of 2-d projections of the latent space or each latent variable individually, it is easy to miss salient features of the population activity. Approach To address this limitation, we developed a Matlab graphical user interface (called DataHigh) that allows the user to quickly and smoothly navigate through a continuum of different 2-d projections of the latent space. We also implemented a suite of additional visualization tools (including playing out population activity timecourses as a movie and displaying summary statistics, such as covariance ellipses and average timecourses) and an optional tool for performing dimensionality reduction. Main results To demonstrate the utility and versatility of DataHigh, we used it to analyze single-trial spike count and single-trial timecourse population activity recorded using a multi-electrode array, as well as trial-averaged population activity recorded using single electrodes. Significance DataHigh was developed to fulfill a need for visualization in exploratory neural data analysis, which can provide intuition that is critical for building scientific hypotheses and models of population activity. PMID:24216250

  9. The neural coding of expected and unexpected monetary performance outcomes: dissociations between active and observational learning.

    Science.gov (United States)

    Bellebaum, C; Jokisch, D; Gizewski, E R; Forsting, M; Daum, I

    2012-02-01

    Successful adaptation to the environment requires the learning of stimulus-response-outcome associations. Such associations can be learned actively by trial and error or by observing the behaviour and accompanying outcomes in other persons. The present study investigated similarities and differences in the neural mechanisms of active and observational learning from monetary feedback using functional magnetic resonance imaging. Two groups of 15 subjects each - active and observational learners - participated in the experiment. On every trial, active learners chose between two stimuli and received monetary feedback. Each observational learner observed the choices and outcomes of one active learner. Learning performance as assessed via active test trials without feedback was comparable between groups. Different activation patterns were observed for the processing of unexpected vs. expected monetary feedback in active and observational learners, particularly for positive outcomes. Activity for unexpected vs. expected reward was stronger in the right striatum in active learning, while activity in the hippocampus was bilaterally enhanced in observational and reduced in active learning. Modulation of activity by prediction error (PE) magnitude was observed in the right putamen in both types of learning, whereas PE related activations in the right anterior caudate nucleus and in the medial orbitofrontal cortex were stronger for active learning. The striatum and orbitofrontal cortex thus appear to link reward stimuli to own behavioural reactions and are less strongly involved when the behavioural outcome refers to another person's action. Alternative explanations such as differences in reward value between active and observational learning are also discussed. Copyright © 2011 Elsevier B.V. All rights reserved.

  10. Human intracranial high-frequency activity during memory processing: neural oscillations or stochastic volatility?

    Science.gov (United States)

    Burke, John F; Ramayya, Ashwin G; Kahana, Michael J

    2015-04-01

    Intracranial high-frequency activity (HFA), which refers to fast fluctuations in electrophysiological recordings, increases during memory processing. Two views have emerged to explain this effect: (1) HFA reflects a synchronous signal, related to underlying gamma oscillations, that plays a mechanistic role in human memory and (2) HFA reflects an asynchronous signal that is a non-specific marker of brain activation. We review recent data supporting each of these views and conclude that HFA during memory processing is more consistent with an asynchronous signal. Memory-related HFA is therefore best conceptualized as a biomarker of neural activation that can functionally map memory with high spatial and temporal precision. Copyright © 2014 Elsevier Ltd. All rights reserved.

  11. Contact system activation and high thrombin generation in hyperthyroidism.

    Science.gov (United States)

    Kim, Namhee; Gu, Ja-Yoon; Yoo, Hyun Ju; Han, Se Eun; Kim, Young Il; Nam-Goong, Il Sung; Kim, Eun Sook; Kim, Hyun Kyung

    2017-05-01

    Hyperthyroidism is associated with increased thrombotic risk. As contact system activation through formation of neutrophil extracellular traps (NET) has emerged as an important trigger of thrombosis, we hypothesized that the contact system is activated along with active NET formation in hyperthyroidism and that their markers correlate with disease severity. In 61 patients with hyperthyroidism and 40 normal controls, the levels of coagulation factors (fibrinogen, and factor VII, VIII, IX, XI and XII), D-dimer, thrombin generation assay (TGA) markers, NET formation markers (histone-DNA complex, double-stranded DNA and neutrophil elastase) and contact system markers (activated factor XII (XIIa), high-molecular-weight kininogen (HMWK), prekallikrein and bradykinin) were measured. Patients with hyperthyroidism showed higher levels of fibrinogen (median (interquartile range), 315 (280-344) vs 262 (223-300), P = 0.001), D-dimer (103.8 (64.8-151.5) vs 50.7 (37.4-76.0), P hyperthyroidism's contribution to coagulation and contact system activation. Free T4 was significantly correlated with factors VIII and IX, D-dimer, double-stranded DNA and bradykinin. This study demonstrated that contact system activation and abundant NET formation occurred in the high thrombin generation state in hyperthyroidism and were correlated with free T4 level. © 2017 European Society of Endocrinology.

  12. Improvement of cognitive function and physical activity of aging mice by human neural stem cells over-expressing choline acetyltransferase.

    Science.gov (United States)

    Park, Dongsun; Yang, Yun-Hui; Bae, Dae Kwon; Lee, Sun Hee; Yang, Goeun; Kyung, Jangbeen; Kim, Dajeong; Choi, Ehn-Kyoung; Lee, Seong Won; Kim, Gon Hyung; Hong, Jin Tae; Choi, Kyung-Chul; Lee, Hong Jun; Kim, Seung U; Kim, Yun-Bae

    2013-11-01

    Aging is characterized by progressive loss of cognitive and memory functions as well as decrease in physical activities. In the present study, a human neural stem cell line (F3 NSC) over-expressing choline acetyltransferase (F3.ChAT), an enzyme responsible for acetylcholine synthesis, was generated and transplanted in the brain of 18-month-old male ICR mice. Four weeks post-transplantation, neurobehavioral functions, expression of ChAT enzyme, production of acetylcholine and neurotrophic factors, and expression of cholinergic nervous system markers in transplanted animals were investigated. F3.ChAT NSCs markedly improved both the cognitive function and physical activity of aging animals, in parallel with the elevation of brain acetylcholine level. Transplanted F3 and F3.ChAT cells were found to differentiate into neurons and astrocytes, and to produce ChAT proteins. Transplantation of the stem cells increased brain-derived neurotrophic factor (BDNF) and nerve growth factor (NGF), enhanced expression of Trk B, and restored host microtubule-associated protein 2 and cholinergic nervous system. The results demonstrate that human NSCs over-expressing ChAT improve cognitive function and physical activity of aging mice, not only by producing ACh directly but also by restoring cholinergic neuronal integrity, which might be mediated by neurotrophins BDNF and NGF. Copyright © 2013 Elsevier Inc. All rights reserved.

  13. The relation of ongoing brain activity, evoked neural responses, and cognition

    Directory of Open Access Journals (Sweden)

    Sepideh Sadaghiani

    2010-06-01

    Full Text Available Ongoing brain activity has been observed since the earliest neurophysiological recordings and is found over a wide range of temporal and spatial scales. It is characterized by remarkably large spontaneous modulations. Here, we review evidence for the functional role of these ongoing activity fluctuations and argue that they constitute an essential property of the neural architecture underlying cognition. The role of spontaneous activity fluctuations is probably best understood when considering both their spatiotemporal structure and their functional impact on cognition. We first briefly argue against a ‘segregationist’ view on ongoing activity, both in time and space, countering this view with an emphasis on integration within a hierarchical spatiotemporal organization of intrinsic activity. We then highlight the flexibility and context-sensitivity of intrinsic functional connectivity that suggest its involvement in functionally relevant information processing. This role in information processing is pursued by reviewing how ongoing brain activity interacts with afferent and efferent information exchange of the brain with its environment. We focus on the relationship between the variability of ongoing and evoked brain activity, and review recent reports that tie ongoing brain activity fluctuations to variability in human perception and behavior. Finally, these observations are discussed within the framework of the free-energy principle which – applied to human brain function - provides a theoretical account for a non-random, coordinated interaction of ongoing and evoked activity in perception and behaviour.

  14. Artificial Neural Network Model for Alkali-Surfactant-Polymer Flooding in Viscous Oil Reservoirs: Generation and Application

    Directory of Open Access Journals (Sweden)

    Si Le Van

    2016-12-01

    Full Text Available Chemical flooding has been widely utilized to recover a large portion of the oil remaining in light and viscous oil reservoirs after the primary and secondary production processes. As core-flood tests and reservoir simulations take time to accurately estimate the recovery performances as well as analyzing the feasibility of an injection project, it is necessary to find a powerful tool to quickly predict the results with a level of acceptable accuracy. An approach involving the use of an artificial neural network to generate a representative model for estimating the alkali-surfactant-polymer flooding performance and evaluating the economic feasibility of viscous oil reservoirs from simulation is proposed in this study. A typical chemical flooding project was referenced for this numerical study. A number of simulations have been made for training on the basis of a base case from the design of 13 parameters. After training, the network scheme generated from a ratio data set of 50%-20%-30% corresponding to the number of samples used for training-validation-testing was selected for estimation with the total coefficient of determination of 0.986 and a root mean square error of 1.63%. In terms of model application, the chemical concentration and injection strategy were optimized to maximize the net present value (NPV of the project at a specific oil price from the just created ANN model. To evaluate the feasibility of the project comprehensively in terms of market variations, a range of oil prices from 30 $/bbl to 60 $/bbl referenced from a real market situation was considered in conjunction with its probability following a statistical distribution on the NPV computation. Feasibility analysis of the optimal chemical injection scheme revealed a variation of profit from 0.42 $MM to 1.0 $MM, corresponding to the changes in oil price. In particular, at the highest possible oil prices, the project can earn approximately 0.61 $MM to 0.87 $MM for a quarter

  15. Imaging neural activity using Thy1-GCaMP transgenic mice

    National Research Council Canada - National Science Library

    Chen, Qian; Cichon, Joseph; Wang, Wenting; Qiu, Li; Lee, Seok-Jin R; Campbell, Nolan R; Destefino, Nicholas; Goard, Michael J; Fu, Zhanyan; Yasuda, Ryohei; Looger, Loren L; Arenkiel, Benjamin R; Gan, Wen-Biao; Feng, Guoping

    2012-01-01

    ... by neuronal activities. Here we report the generation and characterization of transgenic mice that express improved GCaMPs in various neuronal subpopulations under the control of the Thy1 promoter. In vitro...

  16. Constitutively active Notch1 converts cranial neural crest-derived frontonasal mesenchyme to perivascular cells in vivo

    Directory of Open Access Journals (Sweden)

    Sophie R. Miller

    2017-03-01

    Full Text Available Perivascular/mural cells originate from either the mesoderm or the cranial neural crest. Regardless of their origin, Notch signalling is necessary for their formation. Furthermore, in both chicken and mouse, constitutive Notch1 activation (via expression of the Notch1 intracellular domain is sufficient in vivo to convert trunk mesoderm-derived somite cells to perivascular cells, at the expense of skeletal muscle. In experiments originally designed to investigate the effect of premature Notch1 activation on the development of neural crest-derived olfactory ensheathing glial cells (OECs, we used in ovo electroporation to insert a tetracycline-inducible NotchΔE construct (encoding a constitutively active mutant of mouse Notch1 into the genome of chicken cranial neural crest cell precursors, and activated NotchΔE expression by doxycycline injection at embryonic day 4. NotchΔE-targeted cells formed perivascular cells within the frontonasal mesenchyme, and expressed a perivascular marker on the olfactory nerve. Hence, constitutively activating Notch1 is sufficient in vivo to drive not only somite cells, but also neural crest-derived frontonasal mesenchyme and perhaps developing OECs, to a perivascular cell fate. These results also highlight the plasticity of neural crest-derived mesenchyme and glia.

  17. Adaptive Neural-Sliding Mode Control of Active Suspension System for Camera Stabilization

    Directory of Open Access Journals (Sweden)

    Feng Zhao

    2015-01-01

    Full Text Available The camera always suffers from image instability on the moving vehicle due to the unintentional vibrations caused by road roughness. This paper presents a novel adaptive neural network based on sliding mode control strategy to stabilize the image captured area of the camera. The purpose is to suppress vertical displacement of sprung mass with the application of active suspension system. Since the active suspension system has nonlinear and time varying characteristics, adaptive neural network (ANN is proposed to make the controller robustness against systematic uncertainties, which release the model-based requirement of the sliding model control, and the weighting matrix is adjusted online according to Lyapunov function. The control system consists of two loops. The outer loop is a position controller designed with sliding mode strategy, while the PID controller in the inner loop is to track the desired force. The closed loop stability and asymptotic convergence performance can be guaranteed on the basis of the Lyapunov stability theory. Finally, the simulation results show that the employed controller effectively suppresses the vibration of the camera and enhances the stabilization of the entire camera, where different excitations are considered to validate the system performance.

  18. Trait self-esteem and neural activities related to self-evaluation and social feedback

    Science.gov (United States)

    Yang, Juan; Xu, Xiaofan; Chen, Yu; Shi, Zhenhao; Han, Shihui

    2016-01-01

    Self-esteem has been associated with neural responses to self-reflection and attitude toward social feedback but in different brain regions. The distinct associations might arise from different tasks or task-related attitudes in the previous studies. The current study aimed to clarify these by investigating the association between self-esteem and neural responses to evaluation of one’s own personality traits and of others’ opinion about one’s own personality traits. We scanned 25 college students using functional MRI during evaluation of oneself or evaluation of social feedback. Trait self-esteem was measured using the Rosenberg self-esteem scale after scanning. Whole-brain regression analyses revealed that trait self-esteem was associated with the bilateral orbitofrontal activity during evaluation of one’s own positive traits but with activities in the medial prefrontal cortex, posterior cingulate, and occipital cortices during evaluation of positive social feedback. Our findings suggest that trait self-esteem modulates the degree of both affective processes in the orbitofrontal cortex during self-reflection and cognitive processes in the medial prefrontal cortex during evaluation of social feedback. PMID:26842975

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

    Directory of Open Access Journals (Sweden)

    Man-Li Hu

    2016-01-01

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

  20. Abnormal Resting-State Neural Activity and Connectivity of Fatigue in Parkinson's Disease.

    Science.gov (United States)

    Zhang, Jie-Jin; Ding, Jian; Li, Jun-Yi; Wang, Min; Yuan, Yong-Sheng; Zhang, Li; Jiang, Si-Ming; Wang, Xi-Xi; Zhu, Lin; Zhang, Ke-Zhong

    2017-03-01

    Fatigue is a common burdensome problem in patients with Parkinson's disease (PD), but its pathophysiological mechanisms are poorly understood. This study aimed at investigating the neural substrates of fatigue in patients with PD. A total of 17 PD patients with fatigue, 32 PD patients without fatigue, and 25 matched healthy controls were recruited. The 9-item fatigue severity scale (FSS) was used for fatigue screening and severity rating. Resting-state functional magnetic resonance imaging (RS-fMRI) data were obtained from all subjects. Amplitude of low-frequency fluctuations (ALFF) was used to measure regional brain activity, and functional connectivity (FC) was applied to investigate functional connectivity at a network level. PD-related fatigue was associated with ALFF changes in right middle frontal gyrus within the attention network and in left insula as well as right midcingulate cortex within the salience network. FC analysis revealed that above three regions showing ALFF differences had altered functional connectivity mainly in the temporal, parietal, and motor cortices. Our findings do reveal that abnormal regional brain activity within attention and salience network and altered FC of above abnormal regions are involved in neural mechanism of fatigue in patients with PD. © 2017 John Wiley & Sons Ltd.

  1. Model of brain activation predicts the neural collective influence map of the brain.

    Science.gov (United States)

    Morone, Flaviano; Roth, Kevin; Min, Byungjoon; Stanley, H Eugene; Makse, Hernán A

    2017-04-11

    Efficient complex systems have a modular structure, but modularity does not guarantee robustness, because efficiency also requires an ingenious interplay of the interacting modular components. The human brain is the elemental paradigm of an efficient robust modular system interconnected as a network of networks (NoN). Understanding the emergence of robustness in such modular architectures from the interconnections of its parts is a longstanding challenge that has concerned many scientists. Current models of dependencies in NoN inspired by the power grid express interactions among modules with fragile couplings that amplify even small shocks, thus preventing functionality. Therefore, we introduce a model of NoN to shape the pattern of brain activations to form a modular environment that is robust. The model predicts the map of neural collective influencers (NCIs) in the brain, through the optimization of the influence of the minimal set of essential nodes responsible for broadcasting information to the whole-brain NoN. Our results suggest intervention protocols to control brain activity by targeting influential neural nodes predicted by network theory.

  2. Trait self-esteem and neural activities related to self-evaluation and social feedback.

    Science.gov (United States)

    Yang, Juan; Xu, Xiaofan; Chen, Yu; Shi, Zhenhao; Han, Shihui

    2016-02-04

    Self-esteem has been associated with neural responses to self-reflection and attitude toward social feedback but in different brain regions. The distinct associations might arise from different tasks or task-related attitudes in the previous studies. The current study aimed to clarify these by investigating the association between self-esteem and neural responses to evaluation of one's own personality traits and of others' opinion about one's own personality traits. We scanned 25 college students using functional MRI during evaluation of oneself or evaluation of social feedback. Trait self-esteem was measured using the Rosenberg self-esteem scale after scanning. Whole-brain regression analyses revealed that trait self-esteem was associated with the bilateral orbitofrontal activity during evaluation of one's own positive traits but with activities in the medial prefrontal cortex, posterior cingulate, and occipital cortices during evaluation of positive social feedback. Our findings suggest that trait self-esteem modulates the degree of both affective processes in the orbitofrontal cortex during self-reflection and cognitive processes in the medial prefrontal cortex during evaluation of social feedback.

  3. Patterns of neural activity predict picture-naming performance of a patient with chronic aphasia.

    Science.gov (United States)

    Lee, Yune Sang; Zreik, Jihad T; Hamilton, Roy H

    2017-01-08

    Naming objects represents a substantial challenge for patients with chronic aphasia. This could be in part because the reorganized compensatory language networks of persons with aphasia may be less stable than the intact language systems of healthy individuals. Here, we hypothesized that the degree of stability would be instantiated by spatially differential neural patterns rather than either increased or diminished amplitudes of neural activity within a putative compensatory language system. We recruited a chronic aphasic patient (KL; 66 year-old male) who exhibited a semantic deficit (e.g., often said "milk" for "cow" and "pillow" for "blanket"). Over the course of four behavioral sessions involving a naming task performed in a mock scanner, we identified visual objects that yielded an approximately 50% success rate. We then conducted two fMRI sessions in which the patient performed a naming task for multiple exemplars of those objects. Multivoxel pattern analysis (MVPA) searchlight revealed differential activity patterns associated with correct and incorrect trials throughout intact brain regions. The most robust and largest cluster was found in the right occipito-temporal cortex encompassing fusiform cortex, lateral occipital cortex (LOC), and middle occipital cortex, which may account for the patient's propensity for semantic naming errors. None of these areas were found by a conventional univariate analysis. By using an alternative approach, we extend current evidence for compensatory naming processes that operate through spatially differential patterns within the reorganized language system. Copyright © 2016 Elsevier Ltd. All rights reserved.

  4. Artificial Neural Networks for Reducing Computational Effort in Active Truncated Model Testing of Mooring Lines

    DEFF Research Database (Denmark)

    Christiansen, Niels Hørbye; Voie, Per Erlend Torbergsen; Høgsberg, Jan Becker

    2015-01-01

    simultaneously, this method is very demanding in terms of numerical efficiency and computational power. Therefore, this method has not yet proved to be feasible. It has recently been shown how a hybrid method combining classical numerical models and artificial neural networks (ANN) can provide a dramatic...... model. Hence, in principal it is possible to achieve reliable experimental data for much larger water depths than what the actual depth of the test basin would suggest. However, since the computations must be faster than real time, as the numerical simulations and the physical experiment run...... reduction in computational effort when performing time domain simulation of mooring lines. The hybrid method uses a classical numerical model to generate simulation data, which are then subsequently used to train the ANN. After successful training the ANN is able to take over the simulation at a speed two...

  5. Determination of platinum by radiochemical neutron activation analysis in neural tissues from rats, monkeys and patients treated with cisplatin

    DEFF Research Database (Denmark)

    Rietz, B.; Krarup-Hansen, A.; Rorth, M.

    2001-01-01

    of the animals mentioned and in the neural tissues of human patients. For the determination of platinum in the tissues radiochemical neutron activation analysis has been used. The detection limit is 1 ng Pt g(-1). The platinum results indicate that platinum becomes accumulated in the dorsal root ganglia......Cisplatin is one of the most used antineoplastic drugs, essential for the treatment of germ cell tumours. Its use in medical treatment of cancer patients often causes chronic peripheral neuropathy in these patients. The distribution of cisplatin in neural tissues is, therefore, of great interest....... Rats and monkeys were used as animal models for the study of sensory changes in different neural tissues, like spinal cord (ventral and dorsal part), dorsal root ganglia and sural nerve. The study was combined with quantitative measurements of the content of platinum in the neural tissues...

  6. Neural Differentiation of Human Adipose Tissue-Derived Stem Cells Involves Activation of the Wnt5a/JNK Signalling

    Directory of Open Access Journals (Sweden)

    Sujeong Jang

    2015-01-01

    Full Text Available Stem cells are a powerful resource for cell-based transplantation therapies, but understanding of stem cell differentiation at the molecular level is not clear yet. We hypothesized that the Wnt pathway controls stem cell maintenance and neural differentiation. We have characterized the transcriptional expression of Wnt during the neural differentiation of hADSCs. After neural induction, the expressions of Wnt2, Wnt4, and Wnt11 were decreased, but the expression of Wnt5a was increased compared with primary hADSCs in RT-PCR analysis. In addition, the expression levels of most Fzds and LRP5/6 ligand were decreased, but not Fzd3 and Fzd5. Furthermore, Dvl1 and RYK expression levels were downregulated in NI-hADSCs. There were no changes in the expression of ß-catenin and GSK3ß. Interestingly, Wnt5a expression was highly increased in NI-hADSCs by real time RT-PCR analysis and western blot. Wnt5a level was upregulated after neural differentiation and Wnt3, Dvl2, and Naked1 levels were downregulated. Finally, we found that the JNK expression was increased after neural induction and ERK level was decreased. Thus, this study shows for the first time how a single Wnt5a ligand can activate the neural differentiation pathway through the activation of Wnt5a/JNK pathway by binding Fzd3 and Fzd5 and directing Axin/GSK-3ß in hADSCs.

  7. Micrurus snake venoms activate human complement system and generate anaphylatoxins.

    Science.gov (United States)

    Tanaka, Gabriela D; Pidde-Queiroz, Giselle; de Fátima D Furtado, Maria; van den Berg, Carmen; Tambourgi, Denise V

    2012-01-16

    The genus Micrurus, coral snakes (Serpentes, Elapidae), comprises more than 120 species and subspecies distributed from the south United States to the south of South America. Micrurus snake bites can cause death by muscle paralysis and further respiratory arrest within a few hours after envenomation. Clinical observations show mainly neurotoxic symptoms, although other biological activities have also been experimentally observed, including cardiotoxicity, hemolysis, edema and myotoxicity. In the present study we have investigated the action of venoms from seven species of snakes from the genus Micrurus on the complement system in in vitro studies. Several of the Micrurus species could consume the classical and/or the lectin pathways, but not the alternative pathway, and C3a, C4a and C5a were generated in sera treated with the venoms as result of this complement activation. Micrurus venoms were also able to directly cleave the α chain of the component C3, but not of the C4, which was inhibited by 1,10 Phenanthroline, suggesting the presence of a C3α chain specific metalloprotease in Micrurus spp venoms. Furthermore, complement activation was in part associated with the cleavage of C1-Inhibitor by protease(s) present in the venoms, which disrupts complement activation control. Micrurus venoms can activate the complement system, generating a significant amount of anaphylatoxins, which may assist due to their vasodilatory effects, to enhance the spreading of other venom components during the envenomation process.

  8. Micrurus snake venoms activate human complement system and generate anaphylatoxins

    Directory of Open Access Journals (Sweden)

    Tanaka Gabriela D

    2012-01-01

    Full Text Available Abstract Background The genus Micrurus, coral snakes (Serpentes, Elapidae, comprises more than 120 species and subspecies distributed from the south United States to the south of South America. Micrurus snake bites can cause death by muscle paralysis and further respiratory arrest within a few hours after envenomation. Clinical observations show mainly neurotoxic symptoms, although other biological activities have also been experimentally observed, including cardiotoxicity, hemolysis, edema and myotoxicity. Results In the present study we have investigated the action of venoms from seven species of snakes from the genus Micrurus on the complement system in in vitro studies. Several of the Micrurus species could consume the classical and/or the lectin pathways, but not the alternative pathway, and C3a, C4a and C5a were generated in sera treated with the venoms as result of this complement activation. Micrurus venoms were also able to directly cleave the α chain of the component C3, but not of the C4, which was inhibited by 1,10 Phenanthroline, suggesting the presence of a C3α chain specific metalloprotease in Micrurus spp venoms. Furthermore, complement activation was in part associated with the cleavage of C1-Inhibitor by protease(s present in the venoms, which disrupts complement activation control. Conclusion Micrurus venoms can activate the complement system, generating a significant amount of anaphylatoxins, which may assist due to their vasodilatory effects, to enhance the spreading of other venom components during the envenomation process.

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

    Science.gov (United States)

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

    2012-01-01

    Recent imaging studies have demonstrated that levels of resting γ-aminobutyric acid (GABA) in the visual cortex predict the degree of stimulus-induced activity in the same region. These studies have used the presentation of discrete visual stimulus; the change from closed eyes to open also represents a simple visual stimulus, however, and has been shown to induce changes in local brain activity and in functional connectivity between regions. We thus aimed to investigate the role of the GABA system, specifically GABAA receptors, in the changes in brain activity between the eyes closed (EC) and eyes open (EO) state in order to provide detail at the receptor level to complement previous studies of GABA concentrations. We conducted an fMRI study involving two different modes of the change from EC to EO: an EO and EC block design, allowing the modeling of the haemodynamic response, followed by longer periods of EC and EO to allow the measuring of functional connectivity. The same subjects also underwent [18F]Flumazenil PET to measure GABAA receptor binding potentials. It was demonstrated that the local-to-global ratio of GABAA receptor binding potential in the visual cortex predicted the degree of changes in neural activity from EC to EO. This same relationship was also shown in the auditory cortex. Furthermore, the local-to-global ratio of GABAA receptor binding potential in the visual cortex also predicted the change in functional connectivity between the visual and auditory cortex from EC to EO. These findings contribute to our understanding of the role of GABAA receptors in stimulus-induced neural activity in local regions and in inter-regional functional connectivity. PMID:23293594

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

    Directory of Open Access Journals (Sweden)

    Pengmin eQin

    2012-12-01

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

  11. Striatal Activity and Reward Relativity: Neural Signals Encoding Dynamic Outcome Valuation.

    Science.gov (United States)

    Webber, Emily S; Mankin, David E; Cromwell, Howard C

    2016-01-01

    The striatum is a key brain region involved in reward processing. Striatal activity has been linked to encoding reward magnitude and integrating diverse reward outcome information. Recent work has supported the involvement of striatum in the valuation of outcomes. The present work extends this idea by examining striatal activity during dynamic shifts in value that include different levels and directions of magnitude disparity. A novel task was used to produce diverse relative reward effects on a chain of instrumental action. Rats (Rattus norvegicus) were trained to respond to cues associated with specific outcomes varying by food pellet magnitude. Animals were exposed to single-outcome sessions followed by mixed-outcome sessions, and neural activity was compared among identical outcome trials from the different behavioral contexts. Results recording striatal activity show that neural responses to different task elements reflect incentive contrast as well as other relative effects that involve generalization between outcomes or possible influences of outcome variety. The activity that was most prevalent was linked to food consumption and post-food consumption periods. Relative encoding was sensitive to magnitude disparity. A within-session analysis showed strong contrast effects that were dependent upon the outcome received in the immediately preceding trial. Significantly higher numbers of responses were found in ventral striatum linked to relative outcome effects. Our results support the idea that relative value can incorporate diverse relationships, including comparisons from specific individual outcomes to general behavioral contexts. The striatum contains these diverse relative processes, possibly enabling both a higher information yield concerning value shifts and a greater behavioral flexibility.

  12. Histone deacetylase-4 is required during early cranial neural crest development for generation of the zebrafish palatal skeleton

    Directory of Open Access Journals (Sweden)

    DeLaurier April

    2012-06-01

    Full Text Available Abstract Background Histone deacetylase-4 (Hdac4 is a class II histone deacetylase that inhibits the activity of transcription factors. In humans, HDAC4 deficiency is associated with non-syndromic oral clefts and brachydactyly mental retardation syndrome (BDMR with craniofacial abnormalities. Results We identify hdac4 in zebrafish and characterize its function in craniofacial morphogenesis. The gene is present as a single copy, and the deduced Hdac4 protein sequence shares all known functional domains with human HDAC4. The zebrafish hdac4 transcript is widely present in migratory cranial neural crest (CNC cells of the embryo, including populations migrating around the eye, which previously have been shown to contribute to the formation of the palatal skeleton of the early larva. Embryos injected with hdac4 morpholinos (MO have reduced or absent CNC populations that normally migrate medial to the eye. CNC-derived palatal precursor cells do not recover at the post-migratory stage, and subsequently we found that defects in the developing cartilaginous palatal skeleton correlate with reduction or absence of early CNC cells. Palatal skeletal defects prominently include a shortened, clefted, or missing ethmoid plate, and are associated with a shortening of the face of young larvae. Conclusions Our results demonstrate that Hdac4 is a regulator of CNC-derived palatal skeletal precursors during early embryogenesis. Cleft palate resulting from HDAC4 mutations in human patients may result from defects in a homologous CNC progenitor cell population.

  13. Abnormal neural activation patterns underlying working memory impairment in chronic phencyclidine-treated mice.

    Directory of Open Access Journals (Sweden)

    Yosefu Arime

    Full Text Available Working memory impairment is a hallmark feature of schizophrenia and is thought be caused by dysfunctions in the prefrontal cortex (PFC and associated brain regions. However, the neural circuit anomalies underlying this impairment are poorly understood. The aim of this study is to assess working memory performance in the chronic phencyclidine (PCP mouse model of schizophrenia, and to identify the neural substrates of working memory. To address this issue, we conducted the following experiments for mice after withdrawal from chronic administration (14 days of either saline or PCP (10 mg/kg: (1 a discrete paired-trial variable-delay task in T-maze to assess working memory, and (2 brain-wide c-Fos mapping to identify activated brain regions relevant to this task performance either 90 min or 0 min after the completion of the task, with each time point examined under working memory effort and basal conditions. Correct responses in the test phase of the task were significantly reduced across delays (5, 15, and 30 s in chronic PCP-treated mice compared with chronic saline-treated controls, suggesting delay-independent impairments in working memory in the PCP group. In layer 2-3 of the prelimbic cortex, the number of working memory effort-elicited c-Fos+ cells was significantly higher in the chronic PCP group than in the chronic saline group. The main effect of working memory effort relative to basal conditions was to induce significantly increased c-Fos+ cells in the other layers of prelimbic cortex and the anterior cingulate and infralimbic cortex regardless of the different chronic regimens. Conversely, this working memory effort had a negative effect (fewer c-Fos+ cells in the ventral hippocampus. These results shed light on some putative neural networks relevant to working memory impairments in mice chronically treated with PCP, and emphasize the importance of the layer 2-3 of the prelimbic cortex of the PFC.

  14. Complexity of VTA DA neural activities in response to PFC transection in nicotine treated rats

    Directory of Open Access Journals (Sweden)

    Akay Yasemin M

    2011-02-01

    Full Text Available Abstract Background The dopaminergic (DA neurons in the ventral tegmental area (VTA are widely implicated in the addiction and natural reward circuitry of the brain. These neurons project to several areas of the brain, including prefrontal cortex (PFC, nucleus accubens (NAc and amygdala. The functional coupling between PFC and VTA has been demonstrated, but little is known about how PFC mediates nicotinic modulation in VTA DA neurons. The objectives of this study were to investigate the effect of acute nicotine exposure on the VTA DA neuronal firing and to understand how the disruption of communication from PFC affects the firing patterns of VTA DA neurons. Methods Extracellular single-unit recordings were performed on Sprague-Dawley rats and nicotine was administered after stable recording was established as baseline. In order to test how input from PFC affects the VTA DA neuronal firing, bilateral transections were made immediate caudal to PFC to mechanically delete the interaction between VTA and PFC. Results The complexity of the recorded neural firing was subsequently assessed using a method based on the Lempel-Ziv estimator. The results were compared with those obtained when computing the entropy of neural firing. Exposure to nicotine triggered a significant increase in VTA DA neurons firing complexity when communication between PFC and VTA was present, while transection obliterated the effect of nicotine. Similar results were obtained when entropy values were estimated. Conclusions Our findings suggest that PFC plays a vital role in mediating VTA activity. We speculate that increased firing complexity with acute nicotine administration in PFC intact subjects is due to the close functional coupling between PFC and VTA. This hypothesis is supported by the fact that deletion of PFC results in minor alterations of VTA DA neural firing when nicotine is acutely administered.

  15. Abnormal neural activation patterns underlying working memory impairment in chronic phencyclidine-treated mice.

    Science.gov (United States)

    Arime, Yosefu; Akiyama, Kazufumi

    2017-01-01

    Working memory impairment is a hallmark feature of schizophrenia and is thought be caused by dysfunctions in the prefrontal cortex (PFC) and associated brain regions. However, the neural circuit anomalies underlying this impairment are poorly understood. The aim of this study is to assess working memory performance in the chronic phencyclidine (PCP) mouse model of schizophrenia, and to identify the neural substrates of working memory. To address this issue, we conducted the following experiments for mice after withdrawal from chronic administration (14 days) of either saline or PCP (10 mg/kg): (1) a discrete paired-trial variable-delay task in T-maze to assess working memory, and (2) brain-wide c-Fos mapping to identify activated brain regions relevant to this task performance either 90 min or 0 min after the completion of the task, with each time point examined under working memory effort and basal conditions. Correct responses in the test phase of the task were significantly reduced across delays (5, 15, and 30 s) in chronic PCP-treated mice compared with chronic saline-treated controls, suggesting delay-independent impairments in working memory in the PCP group. In layer 2-3 of the prelimbic cortex, the number of working memory effort-elicited c-Fos+ cells was significantly higher in the chronic PCP group than in the chronic saline group. The main effect of working memory effort relative to basal conditions was to induce significantly increased c-Fos+ cells in the other layers of prelimbic cortex and the anterior cingulate and infralimbic cortex regardless of the different chronic regimens. Conversely, this working memory effort had a negative effect (fewer c-Fos+ cells) in the ventral hippocampus. These results shed light on some putative neural networks relevant to working memory impairments in mice chronically treated with PCP, and emphasize the importance of the layer 2-3 of the prelimbic cortex of the PFC.

  16. Lack of aspartoacylase activity disrupts survival and differentiation of neural progenitors and oligodendrocytes in a mouse model of Canavan disease.

    Science.gov (United States)

    Kumar, Shalini; Biancotti, Juan Carlos; Matalon, Reuben; de Vellis, Jean

    2009-11-15

    Loss of the oligodendrocyte (OL)-specific enzyme aspartoacylase (ASPA) from gene mutation results in the sponginess and loss of white matter (WM) in Canavan disease (CD). This study addresses the fate of OLs during the pathophysiology of CD in an adult ASPA knockout (KO) mouse strain. Massive arrays of neural stem/progenitor cells, immunopositive for PSA-NCAM, nestin, vimentin, and NG2, were observed within the severely affected spongy WM of the KO mouse brain. In these mice, G1-->S cell cycle progression was confirmed by an increase in cdk2-kinase activity, a reduction in mitotic inhibitors p21(Cip1) and p27(Kip1), and an increase in bromodeoxyuridine (BrdU) incorporation. Highly acetylated nuclear histones H2B and H3 were detected in adult KO mouse WM, suggesting the existence of noncompact chromatin as seen during early development. Costaining for BrdU- or Ki67-positive cells with markers for neural progenitors confirmed a continuous generation of OL lineage cells in KO WM. We observed a severe reduction in 21.5- and 18.5-kDa myelin basic protein and PLP/DM20 proteolipid proteins combined with a decrease in myelinated fibers and a perinuclear retention of myelin protein staining, indicating impairment in protein trafficking. Death of OLs, neurons, and astrocytes was identified in every region of the KO brain. Immature OLs constituted the largest population of dying cells, particularly in WM. We also report an early expression of full-length ASPA mRNA in normal mouse brain at embryonic day 12.5, when OL progenitors first appear during development. These findings support involvement of ASPA in CNS development and function.

  17. A 3D Active Learning Application for NeMO-Net, the NASA Neural Multi-Modal Observation and Training Network for Global Coral Reef Assessment

    Science.gov (United States)

    van den Bergh, Jarrett; Schutz, Joey; Li, Alan; Chirayath, Ved

    2017-01-01

    NeMO-Net, the NASA neural multi-modal observation and training network for global coral reef assessment, is an open-source deep convolutional neural network and interactive active learning training software aiming to accurately assess the present and past dynamics of coral reef ecosystems through determination of percent living cover and morphology as well as mapping of spatial distribution. We present an interactive video game prototype for tablet and mobile devices where users interactively label morphology classifications over mm-scale 3D coral reef imagery captured using fluid lensing to create a dataset that will be used to train NeMO-Nets convolutional neural network. The application currently allows for users to classify preselected regions of coral in the Pacific and will be expanded to include additional regions captured using our NASA FluidCam instrument, presently the highest-resolution remote sensing benthic imaging technology capable of removing ocean wave distortion, as well as lower-resolution airborne remote sensing data from the ongoing NASA CORAL campaign. Active learning applications present a novel methodology for efficiently training large-scale Neural Networks wherein variances in identification can be rapidly mitigated against control data. NeMO-Net periodically checks users input against pre-classified coral imagery to gauge their accuracy and utilize in-game mechanics to provide classification training. Users actively communicate with a server and are requested to classify areas of coral for which other users had conflicting classifications and contribute their input to a larger database for ranking. In partnering with Mission Blue and IUCN, NeMO-Net leverages an international consortium of subject matter experts to classify areas of confusion identified by NeMO-Net and generate additional labels crucial for identifying decision boundary locations in coral reef assessment.

  18. Differences in autonomic neural activity during exercise between the second and third trimesters of pregnancy.

    Science.gov (United States)

    Nakagaki, Akemi; Inami, Takayuki; Minoura, Tetsuji; Baba, Reizo; Iwase, Satoshi; Sato, Motohiko

    2016-08-01

    To test the hypothesis that autonomic neural activity in pregnant women during exercise varies according to gestational age. This cross-sectional study involved 20 healthy women in their second (n = 13) or third (n = 7) trimester of pregnancy. Incremental cardiopulmonary exercise testing was performed with an electromagnetic cycle ergometer. Heart rate variability was analyzed by frequency analysis software. The low-frequency to high-frequency (LF/HF) ratio, an indicator of the sympathetic nervous system, was significantly higher in third trimester than in second trimester subjects (P exercise testing. In contrast, the HF/total power ratio, an indicator of rapidly acting parasympathetic activity, was significantly higher in second trimester than in third trimester subjects (P exercise testing (r = -0.49, P = 0.028). The autonomic response to exercise in pregnant women differs between the second and third trimesters. These differences should be considered when prescribing exercise to pregnant women. © 2016 Japan Society of Obstetrics and Gynecology.

  19. Neural correlates of durable memories across the adult lifespan: brain activity at encoding and retrieval.

    Science.gov (United States)

    Vidal-Piñeiro, Didac; Sneve, Markus H; Storsve, Andreas B; Roe, James M; Walhovd, Kristine B; Fjell, Anders M

    2017-12-01

    Age-related effects on brain activity during encoding and retrieval of episodic memories are well documented. However, research typically tests memory only once, shortly after encoding. Retaining information over extended periods is critical, and there are reasons to expect age-related effects on the neural correlates of durable memories. Here, we tested whether age was associated with the activity elicited by durable memories. One hundred forty-three participants (22-78 years) underwent an episodic memory experiment where item-context relationships were encoded and tested twice. Participants were scanned during encoding and the first test. Memories retained after 90 minutes but later forgotten were classified as transient, whereas memories retained after 5 weeks were classified as durable. Durable memories were associated with greater encoding activity in inferior lateral parietal and posteromedial regions and greater retrieval activity in frontal and insular regions. Older adults exhibited lower posteromedial activity during encoding and higher frontal activity during retrieval, possibly reflecting greater involvement of control processes. This demonstrates that long-lasting memories are supported by specific patterns of cortical activity that are related to age. Copyright © 2017 Elsevier Inc. All rights reserved.

  20. Anti-glycated activity prediction of polysaccharides from two guava fruits using artificial neural networks.

    Science.gov (United States)

    Yan, Chunyan; Lee, Jinsheng; Kong, Fansheng; Zhang, Dezhi

    2013-10-15

    High-efficiency ultrasonic treatment was used to extract the polysaccharides of Psidium guajava (PPG) and Psidium littorale (PPL). The aims of this study were to compare polysaccharide activities from these two guavas, as well as to investigate the relationship between ultrasonic conditions and anti-glycated activity. A mathematical model of anti-glycated activity was constructed with the artificial neural network (ANN) toolbox of MATLAB software. Response surface plots showed the correlation between ultrasonic conditions and bioactivity. The optimal ultrasonic conditions of PPL for the highest anti-glycated activity were predicted to be 256 W, 60 °C, and 12 min, and the predicted activity was 42.2%. The predicted highest anti-glycated activity of PPG was 27.2% under its optimal predicted ultrasonic condition. The experimental result showed that PPG and PPL possessed anti-glycated and antioxidant activities, and those of PPL were greater. The experimental data also indicated that ANN had good prediction and optimization capability. Copyright © 2013 Elsevier Ltd. All rights reserved.

  1. Rules of engagement: factors that regulate activity-dependent synaptic plasticity during neural network development.

    Science.gov (United States)

    Stoneham, Emily T; Sanders, Erin M; Sanyal, Mohima; Dumas, Theodore C

    2010-10-01

    Overproduction and pruning during development is a phenomenon that can be observed in the number of organisms in a population, the number of cells in many tissue types, and even the number of synapses on individual neurons. The sculpting of synaptic connections in the brain of a developing organism is guided by its personal experience, which on a neural level translates to specific patterns of activity. Activity-dependent plasticity at glutamatergic synapses is an integral part of neuronal network formation and maturation in developing vertebrate and invertebrate brains. As development of the rodent forebrain transitions away from an over-proliferative state, synaptic plasticity undergoes modification. Late developmental changes in synaptic plasticity signal the establishment of a more stable network and relate to pronounced perceptual and cognitive abilities. In large part, activation of glutamate-sensitive N-methyl-d-aspartate (NMDA) receptors regulates synaptic stabilization during development and is a necessary step in memory formation processes that occur in the forebrain. A developmental change in the subunits that compose NMDA receptors coincides with developmental modifications in synaptic plasticity and cognition, and thus much research in this area focuses on NMDA receptor composition. We propose that there are additional, equally important developmental processes that influence synaptic plasticity, including mechanisms that are upstream (factors that influence NMDA receptors) and downstream (intracellular processes regulated by NMDA receptors) from NMDA receptor activation. The goal of this review is to summarize what is known and what is not well understood about developmental changes in functional plasticity at glutamatergic synapses, and in the end, attempt to relate these changes to maturation of neural networks.

  2. Adolescents' risky decision-making activates neural networks related to social cognition and cognitive control processes.

    Science.gov (United States)

    Rodrigo, María José; Padrón, Iván; de Vega, Manuel; Ferstl, Evelyn C

    2014-01-01

    This study examines by means of functional magnetic resonance imaging the neural mechanisms underlying adolescents' risk decision-making in social contexts. We hypothesize that the social context could engage brain regions associated with social cognition processes and developmental changes are also expected. Sixty participants (adolescents: 17-18, and young adults: 21-22 years old) read narratives describing typical situations of decision-making in the presence of peers. They were asked to make choices in risky situations (e.g., taking or refusing a drug) or ambiguous situations (e.g., eating a hamburger or a hotdog). Risky as compared to ambiguous scenarios activated bilateral temporoparietal junction (TPJ), bilateral middle temporal gyrus (MTG), right medial prefrontal cortex, and the precuneus bilaterally; i.e., brain regions related to social cognition processes, such as self-reflection and theory of mind (ToM). In addition, brain structures related to cognitive control were active [right anterior cingulate cortex (ACC), bilateral dorsolateral prefrontal cortex (DLPFC), bilateral orbitofrontal cortex], whereas no significant clusters were obtained in the reward system (ventral striatum). Choosing the dangerous option involved a further activation of control areas (ACC) and emotional and social cognition areas (temporal pole). Adolescents employed more neural resources than young adults in the right DLPFC and the right TPJ in risk situations. When choosing the dangerous option, young adults showed a further engagement in ToM related regions (bilateral MTG) and in motor control regions related to the planning of actions (pre-supplementary motor area). Finally, the right insula and the right superior temporal gyrus were more activated in women than in men, suggesting more emotional involvement and more intensive modeling of the others' perspective in the risky conditions. These findings call for more comprehensive developmental accounts of decision-making in

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

    Directory of Open Access Journals (Sweden)

    Tatjana eAue

    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.

  4. Successful dieters have increased neural activity in cortical areas involved in the control of behavior.

    Science.gov (United States)

    DelParigi, A; Chen, K; Salbe, A D; Hill, J O; Wing, R R; Reiman, E M; Tataranni, P A

    2007-03-01

    To investigate whether dietary restraint, a landmark of successful dieting, is associated with specific patterns of brain responses to the sensory experience of food and meal consumption. Cross-sectional study of the brain's response to the sensory experience of food and meal consumption in nine successful dieters (age: 38+/-7 years, body fat (%): 28+/-3) and 20 non-dieters (age: 31+/-9 years, body fat (%): 33+/-9), all women. Changes in brain activity in response to the sensory experience of food and meal consumption were assessed by using positron emission tomography and (15)O water as a radiotracer. Body fatness was assessed by dual X-ray absorptiometry. Subjective ratings of hunger and fullness were measured by visual analogue scale. Dietary restraint, disinhibition and hunger were assessed by the Three Factor Eating Questionnaire. Successful dieters had a significantly higher level of dietary restraint compared to non-dieters. In response to meal consumption, successful dieters had a greater activation in the dorsal prefrontal cortex (DPFC), dorsal striatum and anterior cerebellar lobe as compared to non-dieters. In response to the same stimulation, the orbitofrontal cortex (OFC) was significantly more activated in non-dieters as compared to successful dieters. Dietary restraint was positively correlated with the response in the DPFC and negatively with the response in the OFC. The responses in the DPFC and OFC were negatively intercorrelated. Cortical areas involved in controlling inappropriate behavioral responses, such as the DPFC, are particularly activated in successful dieters in response to meal consumption. The association between the degree of dietary restraint and the coordinated neural changes in the DPFC and OFC raises the possibility that cognitive control of food intake is achieved by modulating neural circuits controlling food reward.

  5. Adolescents’ risky decision-making activates neural networks related to social cognition and cognitive control processes

    Directory of Open Access Journals (Sweden)

    María José eRodrigo

    2014-02-01

    Full Text Available This study examines by means of fMRI the neural mechanisms underlying adolescents’ risk decision-making in social contexts. We hypothesize that the social context could engage brain regions associated with social cognition processes and developmental changes are also expected. Sixty participants (adolescents: 17-18, and young adults: 21-22 years old read narratives describing typical situations of decision-making in the presence of peers. They were asked to make choices in risky situations (e.g., taking or refusing a drug or ambiguous situations (e.g., eating a hamburger or a hotdog. Risky as compared to ambiguous scenarios activated bilateral temporoparietal junction (TPJ, bilateral middle temporal gyrus (MTG, right medial prefrontal cortex (mPFC, and the precuneus bilaterally; i.e., brain regions related to social cognition processes, such as self-reflection and theory of mind. In addition, brain structures related to cognitive control were active (right ACC, bilateral DLPFC, bilateral OFC, whereas no significant clusters were obtained in the reward system (VS. Choosing the dangerous option involved a further activation of control areas (ACC and emotional and social cognition areas (temporal pole. Adolescents employed more neural resources than young adults in the right DLPFC and the right TPJ in risk situations. When choosing the dangerous option, young adults showed a further engagement in theory of mind related regions (bilateral middle temporal gyrus and in motor control regions related to the planning of actions (pre-supplementary motor area. Finally, the right insula and the right superior temporal gyrus were more activated in women than in men, suggesting more emotional involvement and more intensive modeling of the others’ perspective in the risky conditions. These findings call for more comprehensive developmental accounts of decision-making in social contexts that incorporate the role of emotional and social cognition processes.

  6. Spatiotemporal consistency of local neural activities: A new imaging measure for functional MRI data.

    Science.gov (United States)

    Dong, Li; Luo, Cheng; Cao, Weifang; Zhang, Rui; Gong, Jinnan; Gong, Diankun; Yao, Dezhong

    2015-09-01

    To characterize the local consistency by integrating temporal and spatial information in the local region using functional magnetic resonance imaging (fMRI). One simulation was implemented to explain the definition of FOur-dimensional (spatiotemporal) Consistency of local neural Activities (FOCA). Then three experiments included resting state data (33 subjects), resting state reproducibility data (16 subjects), and event state data (motor execution task, 26 subjects) were designed. Finally, FOCA were respectively analyzed using statistical analysis methods, such as one-sample t-test and paired t-test, etc. During resting state (Experiment 1), the FOCA values (P 621 mm(3) ) were found to be distinct at the bilateral inferior frontal gyrus, middle frontal gyrus, angular gyrus, and precuneus/cuneus. In Experiment 2 (reproducibility), a high degree of consistency within subjects (correlation ≈0.8) and between subjects (correlation ≈0.6) of FOCA were obtained. Comparing event with resting state in Experiment 3, enhanced FOCA (P 621 mm(3) ) was observed mainly in the precentral gyrus and lingual gyrus. These findings suggest that FOCA has the potential to provide further information that will help to better understand brain function in neural imaging. © 2014 Wiley Periodicals, Inc.

  7. Neural correlates of envy: Regional homogeneity of resting-state brain activity predicts dispositional envy.

    Science.gov (United States)

    Xiang, Yanhui; Kong, Feng; Wen, Xue; Wu, Qihan; Mo, Lei

    2016-11-15

    Envy differs from common negative emotions across cultures. Although previous studies have explored the neural basis of episodic envy via functional magnetic resonance imaging (fMRI), little is known about the neural processes associated with dispositional envy. In the present study, we used regional homogeneity (ReHo) as an index in resting-state fMRI (rs-fMRI) to identify brain regions involved in individual differences in dispositional envy, as measured by the Dispositional Envy Scale (DES). Results showed that ReHo in the inferior/middle frontal gyrus (IFG/MFG) and dorsomedial prefrontal cortex (DMPFC) positively predicted dispositional envy. Moreover, of all the personality traits measured by the Revised NEO Personality Inventory (NEO-PI-R), only neuroticism was significantly associated with dispositional envy. Furthermore, neuroticism mediated the underlying association between the ReHo of the IFG/MFG and dispositional envy. Hence, to the best of our knowledge, this study provides the first evidence that spontaneous brain activity in multiple regions related to self-evaluation, social perception, and social emotion contributes to dispositional envy. In addition, our findings reveal that neuroticism may play an important role in the cognitive processing of dispositional envy. Copyright © 2016 Elsevier Inc. All rights reserved.

  8. Effect of external auditory pacing on the neural activity of stuttering speakers.

    Science.gov (United States)

    Toyomura, Akira; Fujii, Tetsunoshin; Kuriki, Shinya

    2011-08-15

    External auditory pacing, such as metronome sound and speaking in unison with others, has a fluency-enhancing effect in stuttering speakers. The present study investigated the neural mechanism of the fluency-enhancing effect by using functional magnetic resonance imaging (fMRI). 12 stuttering speakers and 12 nonstuttering controls were scanned while performing metronome-timed speech, choral speech, and normal speech. Compared to nonstuttering controls, stuttering speakers showed a significantly greater increase in activation in the superior temporal gyrus under both metronome-timed and choral speech conditions relative to a normal speech condition. The caudate, globus pallidus, and putamen of the basal ganglia showed clearly different patterns of signal change from rest among the different conditions and between stuttering and nonstuttering speakers. The signal change of stuttering speakers was significantly lower than that of nonstuttering controls under the normal speech condition but was raised to the level of the controls, with no intergroup difference, in metronome-timed speech. In contrast, under the chorus condition the signal change of stuttering speakers remained lower than that of the controls. Correlation analysis further showed that the signal change of the basal ganglia and motor areas was negatively correlated with stuttering severity, but it was not significantly correlated with the stuttering rate during MRI scanning. These findings shed light on the specific neural processing of stuttering speakers when they time their speech to auditory stimuli, and provide additional evidence of the efficacy of external auditory pacing. Copyright © 2011 Elsevier Inc. All rights reserved.

  9. A customizable stochastic state point process filter (SSPPF) for neural spiking activity.

    Science.gov (United States)

    Xin, Yao; Li, Will X Y; Min, Biao; Han, Yan; Cheung, Ray C C

    2013-01-01

    Stochastic State Point Process Filter (SSPPF) is effective for adaptive signal processing. In particular, it has been successfully applied to neural signal coding/decoding in recent years. Recent work has proven its efficiency in non-parametric coefficients tracking in modeling of mammal nervous system. However, existing SSPPF has only been realized in commercial software platforms which limit their computational capability. In this paper, the first hardware architecture of SSPPF has been designed and successfully implemented on field-programmable gate array (FPGA), proving a more efficient means for coefficient tracking in a well-established generalized Laguerre-Volterra model for mammalian hippocampal spiking activity research. By exploring the intrinsic parallelism of the FPGA, the proposed architecture is able to process matrices or vectors with random size, and is efficiently scalable. Experimental result shows its superior performance comparing to the software implementation, while maintaining the numerical precision. This architecture can also be potentially utilized in the future hippocampal cognitive neural prosthesis design.

  10. Detection of micro solder balls using active thermography and probabilistic neural network

    Science.gov (United States)

    He, Zhenzhi; Wei, Li; Shao, Minghui; Lu, Xingning

    2017-03-01

    Micro solder ball/bump has been widely used in electronic packaging. It has been challenging to inspect these structures as the solder balls/bumps are often embedded between the component and substrates, especially in flip-chip packaging. In this paper, a detection method for micro solder ball/bump based on the active thermography and the probabilistic neural network is investigated. A VH680 infrared imager is used to capture the thermal image of the test vehicle, SFA10 packages. The temperature curves are processed using moving average technique to remove the peak noise. And the principal component analysis (PCA) is adopted to reconstruct the thermal images. The missed solder balls can be recognized explicitly in the second principal component image. Probabilistic neural network (PNN) is then established to identify the defective bump intelligently. The hot spots corresponding to the solder balls are segmented from the PCA reconstructed image, and statistic parameters are calculated. To characterize the thermal properties of solder bump quantitatively, three representative features are selected and used as the input vector in PNN clustering. The results show that the actual outputs and the expected outputs are consistent in identification of the missed solder balls, and all the bumps were recognized accurately, which demonstrates the viability of the PNN in effective defect inspection in high-density microelectronic packaging.

  11. Robust fixed-time synchronization for uncertain complex-valued neural networks with discontinuous activation functions.

    Science.gov (United States)

    Ding, Xiaoshuai; Cao, Jinde; Alsaedi, Ahmed; Alsaadi, Fuad E; Hayat, Tasawar

    2017-06-01

    This paper is concerned with the fixed-time synchronization for a class of complex-valued neural networks in the presence of discontinuous activation functions and parameter uncertainties. Fixed-time synchronization not only claims that the considered master-slave system realizes synchronization within a finite time segment, but also requires a uniform upper bound for such time intervals for all initial synchronization errors. To accomplish the target of fixed-time synchronization, a novel feedback control procedure is designed for the slave neural networks. By means of the Filippov discontinuity theories and Lyapunov stability theories, some sufficient conditions are established for the selection of control parameters to guarantee synchronization within a fixed time, while an upper bound of the settling time is acquired as well, which allows to be modulated to predefined values independently on initial conditions. Additionally, criteria of modified controller for assurance of fixed-time anti-synchronization are also derived for the same system. An example is included to illustrate the proposed methodologies. Copyright © 2017 Elsevier Ltd. All rights reserved.

  12. Neural activation in cognitive motor processes: comparing motor imagery and observation of gymnastic movements.

    Science.gov (United States)

    Munzert, Jörn; Zentgraf, Karen; Stark, Rudolf; Vaitl, Dieter

    2008-07-01

    The simulation concept suggested by Jeannerod (Neuroimage 14:S103-S109, 2001) defines the S-states of action observation and mental simulation of action as action-related mental states lacking overt execution. Within this framework, similarities and neural overlap between S-states and overt execution are interpreted as providing the common basis for the motor representations implemented within the motor system. The present brain imaging study compared activation overlap and differential activation during mental simulation (motor imagery) with that while observing gymnastic movements. The fMRI conjunction analysis revealed overlapping activation for both S-states in primary motor cortex, premotor cortex, and the supplementary motor area as well as in the intraparietal sulcus, cerebellar hemispheres, and parts of the basal ganglia. A direct contrast between the motor imagery and observation conditions revealed stronger activation for imagery in the posterior insula and the anterior cingulate gyrus. The hippocampus, the superior parietal lobe, and the cerebellar areas were differentially activated in the observation condition. In general, these data corroborate the concept of action-related S-states because of the high overlap in core motor as well as in motor-related areas. We argue that differential activity between S-states relates to task-specific and modal information processing.

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

    Science.gov (United States)

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

    2015-11-01

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

  14. A Cognition-Related Neural Oscillation Pattern, Generated in the Prelimbic Cortex, Can Control Operant Learning in Rats.

    Science.gov (United States)

    Hernández-González, Samuel; Andreu-Sánchez, Celia; Martín-Pascual, Miguel Ángel; Gruart, Agnès; Delgado-García, José María

    2017-06-14

    The prelimbic (PrL) cortex constitutes one of the highest levels of cortical hierarchy dedicated to the execution of adaptive behaviors. We have identified a specific local field potential (LFP) pattern generated in the PrL cortex and associated with cognition-related behaviors. We used this pattern to trigger the activation of a visual display on a touch screen as part of an operant conditioning task. Rats learned to increase the presentation rate of the selected θ to β-γ (θ/β-γ) transition pattern across training sessions. The selected LFP pattern appeared to coincide with a significant decrease in the firing of PrL pyramidal neurons and did not seem to propagate to other cortical or subcortical areas. An indication of the PrL cortex's cognitive nature is that the experimental disruption of this θ/β-γ transition pattern prevented the proper performance of the acquired task without affecting the generation of other motor responses. The use of this LFP pattern to trigger an operant task evoked only minor changes in its electrophysiological properties. Thus, the PrL cortex has the capability of generating an oscillatory pattern for dealing with environmental constraints. In addition, the selected θ/β-γ transition pattern could be a useful tool to activate the presentation of external cues or to modify the current circumstances.SIGNIFICANCE STATEMENT Brain-machine interfaces represent a solution for physically impaired people to communicate with external devices. We have identified a specific local field potential pattern generated in the prelimbic cortex and associated with goal-directed behaviors. We used the pattern to trigger the activation of a visual display on a touch screen as part of an operant conditioning task. Rats learned to increase the presentation rate of the selected field potential pattern across training. The selected pattern was not modified when used to activate the touch screen. Electrical stimulation of the recording site prevented

  15. Neural signatures of language co-activation and control in bilingual spoken word comprehension.

    Science.gov (United States)

    Chen, Peiyao; Bobb, Susan C; Hoshino, Noriko; Marian, Viorica

    2017-06-15

    To examine the neural signatures of language co-activation and control during bilingual spoken word comprehension, Korean-English bilinguals and English monolinguals were asked to make overt or covert semantic relatedness judgments on auditorily-presented English word pairs. In two critical conditions, participants heard word pairs consisting of an English-Korean interlingual homophone (e.g., the sound /mu:n/ means "moon" in English and "door" in Korean) as the prime and an English word as the target. In the homophone-related condition, the target (e.g., "lock") was related to the homophone's Korean meaning, but not related to the homophone's English meaning. In the homophone-unrelated condition, the target was unrelated to either the homophone's Korean meaning or the homophone's English meaning. In overtly responded situations, ERP results revealed that the reduced N400 effect in bilinguals for homophone-related word pairs correlated positively with the amount of their daily exposure to Korean. In covertly responded situations, ERP results showed a reduced late positive component for homophone-related word pairs in the right hemisphere, and this late positive effect was related to the neural efficiency of suppressing interference in a non-linguistic task. Together, these findings suggest 1) that the degree of language co-activation in bilingual spoken word comprehension is modulated by the amount of daily exposure to the non-target language; and 2) that bilinguals who are less influenced by cross-language activation may also have greater efficiency in suppressing interference in a non-linguistic task. Copyright © 2017 Elsevier B.V. All rights reserved.

  16. DNA methyltransferase activity is required for memory-related neural plasticity in the lateral amygdala.

    Science.gov (United States)

    Maddox, Stephanie A; Watts, Casey S; Schafe, Glenn E

    2014-01-01

    We have previously shown that auditory Pavlovian fear conditioning is associated with an increase in DNA methyltransferase (DNMT) expression in the lateral amygdala (LA) and that intra-LA infusion or bath application of an inhibitor of DNMT activity impairs the consolidation of an auditory fear memory and long-term potentiation (LTP) at thalamic and cortical inputs to the LA, in vitro. In the present study, we use awake behaving neurophysiological techniques to examine the role of DNMT activity in memory-related neurophysiological changes accompanying fear memory consolidation and reconsolidation in the LA, in vivo. We show that auditory fear conditioning results in a training-related enhancement in the amplitude of short-latency auditory-evoked field potentials (AEFPs) in the LA. Intra-LA infusion of a DNMT inhibitor impairs both fear memory consolidation and, in parallel, the consolidation of training-related neural plasticity in the LA; that is, short-term memory (STM) and short-term training-related increases in AEFP amplitude in the LA are intact, while long-term memory (LTM) and long-term retention of training-related increases in AEFP amplitudes are impaired. In separate experiments, we show that intra-LA infusion of a DNMT inhibitor following retrieval of an auditory fear memory has no effect on post-retrieval STM or short-term retention of training-related changes in AEFP amplitude in the LA, but significantly impairs both post-retrieval LTM and long-term retention of AEFP amplitude changes in the LA. These findings are the first to demonstrate the necessity of DNMT activity in the consolidation and reconsolidation of memory-associated neural plasticity, in vivo. Copyright © 2013 Elsevier Inc. All rights reserved.

  17. Effects of aripiprazole on caffeine-induced hyperlocomotion and neural activation in the striatum.

    Science.gov (United States)

    Batista, Luara A; Viana, Thércia G; Silveira, Vívian T; Aguiar, Daniele C; Moreira, Fabrício A

    2016-01-01

    Aripiprazole is an antipsychotic that acts as a partial agonist at dopamine D2 receptors. In addition to its antipsychotic activity, this compound blocks the effects of some psychostimulant drugs. It has not been verified, however, if aripiprazole interferes with the effects of caffeine. Hence, this study tested the hypothesis that aripiprazole prevents caffeine-induced hyperlocomotion and investigated the effects of these drugs on neural activity in the striatum. Male Swiss mice received injections of vehicle or antipsychotic drugs followed by vehicle or caffeine. Locomotion was analyzed in a circular arena and c-Fos protein expression was quantified in the dorsolateral, dorsomedial, and ventrolateral striatum, and in the core and shell regions of nucleus accumbens. Aripiprazole (0.1, 1, and 10 mg/kg) prevented caffeine (10 mg/kg)-induced hyperlocomotion at doses that do not change basal locomotion. Haloperidol (0.01, 0.03, and 0.1 mg/kg) also decreased caffeine-induced hyperlocomotion at all doses, although at the two higher doses, this compound reduced basal locomotion. Immunohistochemistry analysis showed that aripiprazole increases c-Fos protein expression in all regions studied, whereas caffeine did not alter c-Fos protein expression. Combined treatment of aripiprazole and caffeine resulted in a decrease in the number of c-Fos positive cells as compared to the group receiving aripiprazole alone. In conclusion, aripiprazole prevents caffeine-induced hyperlocomotion and increases neural activation in the striatum. This latter effect is reduced by subsequent administration of caffeine. These results advance our understanding on the pharmacological profile of aripiprazole.

  18. Characterization of K-complexes and slow wave activity in a neural mass model.

    Directory of Open Access Journals (Sweden)

    Arne Weigenand

    2014-11-01

    Full Text Available NREM sleep is characterized by two hallmarks, namely K-complexes (KCs during sleep stage N2 and cortical slow oscillations (SOs during sleep stage N3. While the underlying dynamics on the neuronal level is well known and can be easily measured, the resulting behavior on the macroscopic population level remains unclear. On the basis of an extended neural mass model of the cortex, we suggest a new interpretation of the mechanisms responsible for the generation of KCs and SOs. As the cortex transitions from wake to deep sleep, in our model it approaches an oscillatory regime via a Hopf bifurcation. Importantly, there is a canard phenomenon arising from a homoclinic bifurcation, whose orbit determines the shape of large amplitude SOs. A KC corresponds to a single excursion along the homoclinic orbit, while SOs are noise-driven oscillations around a stable focus. The model generates both time series and spectra that strikingly resemble real electroencephalogram data and points out possible differences between the different stages of natural sleep.

  19. Neural activity in the posterior superior temporal region during eye contact perception correlates with autistic traits.

    Science.gov (United States)

    Hasegawa, Naoya; Kitamura, Hideaki; Murakami, Hiroatsu; Kameyama, Shigeki; Sasagawa, Mutsuo; Egawa, Jun; Endo, Taro; Someya, Toshiyuki

    2013-08-09

    The present study investigated the relationship between neural activity associated with gaze processing and autistic traits in typically developed subjects using magnetoencephalography. Autistic traits in 24 typically developed college students with normal intelligence were assessed using the Autism Spectrum Quotient (AQ). The Minimum Current Estimates method was applied to estimate the cortical sources of magnetic responses to gaze stimuli. These stimuli consisted of apparent motion of the eyes, displaying direct or averted gaze motion. Results revealed gaze-related brain activations in the 150-250 ms time window in the right posterior superior temporal sulcus (pSTS), and in the 150-450 ms time window in medial prefrontal regions. In addition, the mean amplitude in the 150-250 ms time window in the right pSTS region was modulated by gaze direction, and its activity in response to direct gaze stimuli correlated with AQ score. pSTS activation in response to direct gaze is thought to be related to higher-order social processes. Thus, these results suggest that brain activity linking eye contact and social signals is associated with autistic traits in a typical population. Copyright © 2013 Elsevier Ireland Ltd. All rights reserved.

  20. Hedgehog Controls Quiescence and Activation of Neural Stem Cells in the Adult Ventricular-Subventricular Zone

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    Mathieu Daynac

    2016-10-01

    Full Text Available Identifying the mechanisms controlling quiescence and activation of neural stem cells (NSCs is crucial for understanding brain repair. Here, we demonstrate that Hedgehog (Hh signaling actively regulates different pools of quiescent and proliferative NSCs in the adult ventricular-subventricular zone (V-SVZ, one of the main brain neurogenic niches. Specific deletion of the Hh receptor Patched in NSCs during adulthood upregulated Hh signaling in quiescent NSCs, progressively leading to a large accumulation of these cells in the V-SVZ. The pool of non-neurogenic astrocytes was not modified, whereas the activated NSC pool increased after a short period, before progressively becoming exhausted. We also showed that Sonic Hedgehog regulates proliferation of activated NSCs in vivo and shortens both their G1 and S-G2/M phases in culture. These data demonstrate that Hh orchestrates the balance between quiescent and activated NSCs, with important implications for understanding adult neurogenesis under normal homeostatic conditions or during injury.

  1. DARPA Neural Network Study: October 1987 - February 1988

    Science.gov (United States)

    1989-03-22

    8217Neural Net’ Models Allen Waxman, Boston University 10-20-1987: Mobile Robots vs. Neural Navigators 01-19-1988: Motion Computation In Vision 63...34Weight." Neurodynamics The study of the generation and propagation of synchronized neural activity in biological systems. 70 Neuron The nerve cells in...Malsburg, "Frank Rosenblatt: Principles of neurodynamics : Perceptrons and the theory of brain mechanisms," in Brain Theory, (G. Palm and A. Aertsen, eds

  2. Landslide Activity Maps Generation by Means of Persistent Scatterer Interferometry

    Directory of Open Access Journals (Sweden)

    Silvia Bianchini

    2013-11-01

    Full Text Available In this paper a methodology is proposed to elaborate landslide activity maps through the use of PS (Persistent Scatterer data. This is illustrated through the case study of Tramuntana Range in the island of Majorca (Spain, where ALOS (Advanced Land Observing Satellite images have been processed through a Persistent Scatterer Interferometry (PSI technique during the period of 2007–2010. The landslide activity map provides, for every monitored landslide, an assessment of the PS visibility according to the relief, land use, and satellite acquisition parameters. Landslide displacement measurements are projected along the steepest slope, in order to compare landslide velocities with different slope orientations. Additionally, a ground motion activity map is also generated, based on active PS clusters not included within any known landslide phenomenon, but even moving, potentially referred to unmapped landslides or triggered by other kinds of geomorphological processes. In the Tramuntana range, 42 landslides were identified as active, four as being potential to produce moderate damage, intersecting the road Ma-10, which represents the most important road of the island and, thus, the main element at risk. In order to attest the reliability of measured displacements to represent landslide dynamics, a confidence degree evaluation is proposed. In this test site, seven landslides exhibit a high confidence degree, medium for 93 of them, and low for 51. A low confidence degree was also attributed to 615 detected active clusters with a potential to cause moderate damage, as their mechanism of the triggering cause is unknown. From this total amount, 18 of them intersect the Ma-10, representing further potentially hazardous areas. The outcomes of this work reveal the usefulness of landslide activity maps for environmental planning activities, being exportable to other radar data and different geomorphological settings.

  3. Intermittent reductions in respiratory neural activity elicit spinal TNF-α-independent, atypical PKC-dependent inactivity-induced phrenic motor facilitation

    Science.gov (United States)

    Baertsch, Nathan A.

    2015-01-01

    In many neural networks, mechanisms of compensatory plasticity respond to prolonged reductions in neural activity by increasing cellular excitability or synaptic strength. In the respiratory control system, a prolonged reduction in synaptic inputs to the phrenic motor pool elicits a TNF-α- and atypical PKC-dependent form of spinal plasticity known as inactivity-induced phrenic motor facilitation (iPMF). Although iPMF may be elicited by a prolonged reduction in respiratory neural activity, iPMF is more efficiently induced when reduced respiratory neural activity (neural apnea) occurs intermittently. Mechanisms giving rise to iPMF following intermittent neural apnea are unknown. The purpose of this study was to test the hypothesis that iPMF following intermittent reductions in respiratory neural activity requires spinal TNF-α and aPKC. Phrenic motor output was recorded in anesthetized and ventilated rats exposed to brief intermittent (5, ∼1.25 min), brief sustained (∼6.25 min), or prolonged sustained (30 min) neural apnea. iPMF was elicited following brief intermittent and prolonged sustained neural apnea, but not following brief sustained neural apnea. Unlike iPMF following prolonged neural apnea, spinal TNF-α was not required to initiate iPMF during intermittent neural apnea; however, aPKC was still required for its stabilization. These results suggest that different patterns of respiratory neural activity induce iPMF through distinct cellular mechanisms but ultimately converge on a similar downstream pathway. Understanding the diverse cellular mechanisms that give rise to inactivity-induced respiratory plasticity may lead to development of novel therapeutic strategies to treat devastating respiratory control disorders when endogenous compensatory mechanisms fail. PMID:25673781

  4. Global Mittag-Leffler synchronization of fractional-order neural networks with discontinuous activations.

    Science.gov (United States)

    Ding, Zhixia; Shen, Yi; Wang, Leimin

    2016-01-01

    This paper is concerned with the global Mittag-Leffler synchronization for a class of fractional-order neural networks with discontinuous activations (FNNDAs). We give the concept of Filippov solution for FNNDAs in the sense of Caputo's fractional derivation. By using a singular Gronwall inequality and the properties of fractional calculus, the existence of global solution under the framework of Filippov for FNNDAs is proved. Based on the nonsmooth analysis and control theory, some sufficient criteria for the global Mittag-Leffler synchronization of FNNDAs are derived by designing a suitable controller. The proposed results enrich and enhance the previous reports. Finally, one numerical example is given to demonstrate the effectiveness of the theoretical results. Copyright © 2015 Elsevier Ltd. All rights reserved.

  5. Outsourcing neural active control to passive composite mechanics: a tissue engineered cyborg ray

    Science.gov (United States)

    Gazzola, Mattia; Park, Sung Jin; Park, Kyung Soo; Park, Shirley; di Santo, Valentina; Deisseroth, Karl; Lauder, George V.; Mahadevan, L.; Parker, Kevin Kit

    2016-11-01

    Translating the blueprint that stingrays and skates provide, we create a cyborg swimming ray capable of orchestrating adaptive maneuvering and phototactic navigation. The impossibility of replicating the neural system of batoids fish is bypassed by outsourcing algorithmic functionalities to the body composite mechanics, hence casting the active control problem into a design, passive one. We present a first step in engineering multilevel "brain-body-flow" systems that couple sensory information to motor coordination and movement, leading to behavior. This work paves the way for the development of autonomous and adaptive artificial creatures able to process multiple sensory inputs and produce complex behaviors in distributed systems and may represent a path toward soft-robotic "embodied cognition".

  6. Topological defect launches 3D mound in the active nematic sheet of neural progenitors

    CERN Document Server

    Kawaguchi, Kyogo; Sano, Masaki

    2016-01-01

    Cultured stem cells have become a standard platform not only for regenerative medicine and developmental biology but also for biophysical studies. Yet, the characterization of cultured stem cells at the level of morphology and macroscopic patterns resulting from cell-to-cell interactions remain largely qualitative, even though they are the simplest features observed in everyday experiments. Here we report that neural progenitor cells (NPCs), which are multipotent stem cells that give rise to cells in the central nervous system, rapidly glide and stochastically reverse its velocity while locally aligning with neighboring cells, thus showing features of an active nematic system. Within the two-dimensional nematic pattern, we find interspaced topological defects with +1/2 and -1/2 charges. Remarkably, we identified rapid cell accumulation leading to three-dimensional mounds at the +1/2 topological defects. Single-cell level imaging around the defects allowed quantification of the evolving cell density, clarifyin...

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

    Science.gov (United States)

    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

  8. Cortical geometry as a determinant of brain activity eigenmodes: Neural field analysis

    Science.gov (United States)

    Gabay, Natasha C.; Robinson, P. A.

    2017-09-01

    Perturbation analysis of neural field theory is used to derive eigenmodes of neural activity on a cortical hemisphere, which have previously been calculated numerically and found to be close analogs of spherical harmonics, despite heavy cortical folding. The present perturbation method treats cortical folding as a first-order perturbation from a spherical geometry. The first nine spatial eigenmodes on a population-averaged cortical hemisphere are derived and compared with previous numerical solutions. These eigenmodes contribute most to brain activity patterns such as those seen in electroencephalography and functional magnetic resonance imaging. The eigenvalues of these eigenmodes are found to agree with the previous numerical solutions to within their uncertainties. Also in agreement with the previous numerics, all eigenmodes are found to closely resemble spherical harmonics. The first seven eigenmodes exhibit a one-to-one correspondence with their numerical counterparts, with overlaps that are close to unity. The next two eigenmodes overlap the corresponding pair of numerical eigenmodes, having been rotated within the subspace spanned by that pair, likely due to second-order effects. The spatial orientations of the eigenmodes are found to be fixed by gross cortical shape rather than finer-scale cortical properties, which is consistent with the observed intersubject consistency of functional connectivity patterns. However, the eigenvalues depend more sensitively on finer-scale cortical structure, implying that the eigenfrequencies and consequent dynamical properties of functional connectivity depend more strongly on details of individual cortical folding. Overall, these results imply that well-established tools from perturbation theory and spherical harmonic analysis can be used to calculate the main properties and dynamics of low-order brain eigenmodes.

  9. A method for locating regions containing neural activation at a given confidence level from MEG data

    Energy Technology Data Exchange (ETDEWEB)

    Schmidt, D.M.; George, J.S.

    1996-02-01

    The MEG inverse problem does not have a general, unique solution. Unless restrictive model assumptions are made, there are generally many more free parameters than measurements and there exist silent sources - current distributions which produce no external magnetic field. By weighting solutions according to how well each fits our prior notion about what properties good solutions should have, it may be possible to obtain a single current distribution that best fits the data and our expectations. However, in general there will still exist a number of different current distributions which fit both the data and our prior expectations sufficiently well. For example, a simulated data set based on a single or several dipoles can generally be fit equally well by a distributed current minimum-norm reconstruction. In experimental data it is often possible to find a relatively small number of dipoles which both fit the data and have a norm not much larger than that of the minimum-norm solution. Moreover, the few-dipole solutions often have currents in different regions than the corresponding minimum-norm solution. Because there exist well-fitting current distributions which may have current in significantly different locations, it can be misleading to infer locations of stimulus-correlated neural activity based on a single, best-fitting current distribution. we demonstrate here a method for inferring the location and number of regions containing neural activation by considering all possible current distributions within a given model (not just the most likely one) weighted according to how well each fits both the data and our prior expectations.

  10. False memory for face in short-term memory and neural activity in human amygdala.

    Science.gov (United States)

    Iidaka, Tetsuya; Harada, Tokiko; Sadato, Norihiro

    2014-12-03

    Human memory is often inaccurate. Similar to words and figures, new faces are often recognized as seen or studied items in long- and short-term memory tests; however, the neural mechanisms underlying this false memory remain elusive. In a previous fMRI study using morphed faces and a standard false memory paradigm, we found that there was a U-shaped response curve of the amygdala to old, new, and lure items. This indicates that the amygdala is more active in response to items that are salient (hit and correct rejection) compared to items that are less salient (false alarm), in terms of memory retrieval. In the present fMRI study, we determined whether the false memory for faces occurs within the short-term memory range (a few seconds), and assessed which neural correlates are involved in veridical and illusory memories. Nineteen healthy participants were scanned by 3T MRI during a short-term memory task using morphed faces. The behavioral results indicated that the occurrence of false memories was within the short-term range. We found that the amygdala displayed a U-shaped response curve to memory items, similar to those observed in our previous study. These results suggest that the amygdala plays a common role in both long- and short-term false memory for faces. We made the following conclusions: First, the amygdala is involved in detecting the saliency of items, in addition to fear, and supports goal-oriented behavior by modulating memory. Second, amygdala activity and response time might be related with a subject's response criterion for similar faces. Copyright © 2014 Elsevier B.V. All rights reserved.

  11. Is Neural Activity Detected by ERP-Based Brain-Computer Interfaces Task Specific?

    Directory of Open Access Journals (Sweden)

    Markus A Wenzel

    Full Text Available Brain-computer interfaces (BCIs that are based on event-related potentials (ERPs can estimate to which stimulus a user pays particular attention. In typical BCIs, the user silently counts the selected stimulus (which is repeatedly presented among other stimuli in order to focus the attention. The stimulus of interest is then inferred from the electroencephalogram (EEG. Detecting attention allocation implicitly could be also beneficial for human-computer interaction (HCI, because it would allow software to adapt to the user's interest. However, a counting task would be inappropriate for the envisaged implicit application in HCI. Therefore, the question was addressed if the detectable neural activity is specific for silent counting, or if it can be evoked also by other tasks that direct the attention to certain stimuli.Thirteen people performed a silent counting, an arithmetic and a memory task. The tasks required the subjects to pay particular attention to target stimuli of a random color. The stimulus presentation was the same in all three tasks, which allowed a direct comparison of the experimental conditions.Classifiers that were trained to detect the targets in one task, according to patterns present in the EEG signal, could detect targets in all other tasks (irrespective of some task-related differences in the EEG.The neural activity detected by the classifiers is not strictly task specific but can be generalized over tasks and is presumably a result of the attention allocation or of the augmented workload. The results may hold promise for the transfer of classification algorithms from BCI research to implicit relevance detection in HCI.

  12. Neural response during the activation of the attachment system in patients with borderline personality disorder: An fMRI study

    Directory of Open Access Journals (Sweden)

    Anna Buchheim

    2016-08-01

    Full Text Available Individuals with borderline personality disorder (BPD are characterized by emotional instability, impaired emotion regulation and unresolved attachment patterns associated with abusive childhood experiences. We investigated the neural response during the activation of the attachment system in BPD patients compared to healthy controls using functional magnetic resonance imaging. Eleven female patients with BPD without posttraumatic stress disorder and seventeen healthy female controls matched for age and education were telling stories in the scanner in response to the Adult Attachment Projective Picture System, an eight-picture set assessment of adult attachment. The picture set includes theoretically-derived attachment scenes, such as separation, death, threat and potential abuse. The picture presentation order is designed to gradually increase the activation of the attachment system. Each picture stimulus was presented for two minutes. Analyses examine group differences in attachment classifications and neural activation patterns over the course of the task. Unresolved attachment was associated with increasing amygdala activation over the course of the attachment task in patients as well as controls. Unresolved controls, but not patients, showed activation in the right dorsolateral prefrontal cortex and the rostral cingulate zone. We interpret this as a neural signature of BPD patients’ inability to exert top-down control under conditions of attachment distress. These findings point to possible neural mechanisms for underlying affective dysregulation in BPD in the context of attachment trauma and fear.

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

    Science.gov (United States)

    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

  14. Sex differences in neural activation following different routes of oxytocin administration in awake adult rats.

    Science.gov (United States)

    Dumais, Kelly M; Kulkarni, Praveen P; Ferris, Craig F; Veenema, Alexa H

    2017-07-01

    The neuropeptide oxytocin (OT) regulates social behavior in sex-specific ways across species. OT has promising effects on alleviating social deficits in sex-biased neuropsychiatric disorders. However little is known about potential sexually dimorphic effects of OT on brain function. Using the rat as a model organism, we determined whether OT administered centrally or peripherally induces sex differences in brain activation. Functional magnetic resonance imaging was used to examine blood oxygen level-dependent (BOLD) signal intensity changes in the brains of awake rats during the 20min following intracerebroventricular (ICV; 1μg/5μl) or intraperitoneal (IP; 0.1mg/kg) OT administration as compared to baseline. ICV OT induced sex differences in BOLD activation in 26 out of 172 brain regions analyzed, with 20 regions showing a greater volume of activation in males (most notably the nucleus accumbens and insular cortex), and 6 regions showing a greater volume of activation in females (including the lateral and central amygdala). IP OT also elicited sex differences in BOLD activation with a greater volume of activation in males, but this activation was found in different and fewer (10) brain regions compared to ICV OT. In conclusion, exogenous OT modulates neural activation differently in male versus female rats with the pattern and magnitude, but not the direction, of sex differences depending on the route of administration. These findings highlight the need to include both sexes in basic and clinical studies to fully understand the role of OT on brain function. Copyright © 2017 Elsevier Ltd. All rights reserved.

  15. DataHigh: graphical user interface for visualizing and interacting with high-dimensional neural activity.

    Science.gov (United States)

    Cowley, Benjamin R; Kaufman, Matthew T; Churchland, Mark M; Ryu, Stephen I; Shenoy, Krishna V; Yu, Byron M

    2012-01-01

    The activity of tens to hundreds of neurons can be succinctly summarized by a smaller number of latent variables extracted using dimensionality reduction methods. These latent variables define a reduced-dimensional space in which we can study how population activity varies over time, across trials, and across experimental conditions. Ideally, we would like to visualize the population activity directly in the reduced-dimensional space, whose optimal dimensionality (as determined from the data) is typically greater than 3. However, direct plotting can only provide a 2D or 3D view. To address this limitation, we developed a Matlab graphical user interface (GUI) that allows the user to quickly navigate through a continuum of different 2D projections of the reduced-dimensional space. To demonstrate the utility and versatility of this GUI, we applied it to visualize population activity recorded in premotor and motor cortices during reaching tasks. Examples include single-trial population activity recorded using a multi-electrode array, as well as trial-averaged population activity recorded sequentially using single electrodes. Because any single 2D projection may provide a misleading impression of the data, being able to see a large number of 2D projections is critical for intuition-and hypothesis-building during exploratory data analysis. The GUI includes a suite of additional interactive tools, including playing out population activity timecourses as a movie and displaying summary statistics, such as covariance ellipses and average timecourses. The use of visualization tools like the GUI developed here, in tandem with dimensionality reduction methods, has the potential to further our understanding of neural population activity.

  16. Contralateral delay activity provides a neural measure of the number of representations in visual working memory.

    Science.gov (United States)

    Ikkai, Akiko; McCollough, Andrew W; Vogel, Edward K

    2010-04-01

    Visual working memory (VWM) helps to temporarily represent information from the visual environment and is severely limited in capacity. Recent work has linked various forms of neural activity to the ongoing representations in VWM. One piece of evidence comes from human event-related potential studies, which find a sustained contralateral negativity during the retention period of VWM tasks. This contralateral delay activity (CDA) has previously been shown to increase in amplitude as the number of memory items increases, up to the individual's working memory capacity limit. However, significant alternative hypotheses remain regarding the true nature of this activity. Here we test whether the CDA is modulated by the perceptual requirements of the memory items as well as whether it is determined by the number of locations that are being attended within the display. Our results provide evidence against these two alternative accounts and instead strongly support the interpretation that this activity reflects the current number of objects that are being represented in VWM.

  17. Classification of human activity on water through micro-Dopplers using deep convolutional neural networks

    Science.gov (United States)

    Kim, Youngwook; Moon, Taesup

    2016-05-01

    Detecting humans and classifying their activities on the water has significant applications for surveillance, border patrols, and rescue operations. When humans are illuminated by radar signal, they produce micro-Doppler signatures due to moving limbs. There has been a number of research into recognizing humans on land by their unique micro-Doppler signatures, but there is scant research into detecting humans on water. In this study, we investigate the micro-Doppler signatures of humans on water, including a swimming person, a swimming person pulling a floating object, and a rowing person in a small boat. The measured swimming styles were free stroke, backstroke, and breaststroke. Each activity was observed to have a unique micro-Doppler signature. Human activities were classified based on their micro-Doppler signatures. For the classification, we propose to apply deep convolutional neural networks (DCNN), a powerful deep learning technique. Rather than using conventional supervised learning that relies on handcrafted features, we present an alternative deep learning approach. We apply the DCNN, one of the most successful deep learning algorithms for image recognition, directly to a raw micro-Doppler spectrogram of humans on the water. Without extracting any explicit features from the micro-Dopplers, the DCNN can learn the necessary features and build classification boundaries using the training data. We show that the DCNN can achieve accuracy of more than 87.8% for activity classification using 5- fold cross validation.

  18. [Gateway Reflex, a regulator of the inflammation feedback loop by regional neural activation].

    Science.gov (United States)

    Arima, Yasunobu; Kamimura, Daisuke; Atsumi, Toru; Murakami, Masaaki

    2015-04-01

    Inflammation is observed in many diseases and disorders. We discovered a key machinery of inflammation, the inflammation amplifier, which is induced by the simultaneous activation of NFκB and STAT3 followed by the hyper-activation of NFκB in non-immune cells, including endothelial cells and fibroblasts. Since that discovery, we found the Gateway Reflex, which describes regional neural activations that enhance the inflammation amplifier to create a gateway for immune cells to bypass the blood-brain barrier. In addition, we have identified over 1,000 positive regulators and over 500 targets of the inflammation amplifier, which include a significant numbers of human disease-associated genes. In parallel, we performed a comprehensive analysis of human disease samples and found that the inflammation amplifier was activated during the development of chronic inflammation. Thus, we concluded that the inflammation amplifier is associated with various human diseases and disorders, including autoimmune diseases, metabolic syndromes, neurodegenerative diseases, and other inflammatory diseases. We are now attempting drug discovery for inflammatory diseases and disorders based on the inflammation amplifier and Gateway Reflex. In this review, we discuss the Gateway Reflex as an example for the neuro-immune interaction in vivo.

  19. Dopamine-signalled reward predictions generated by competitive excitation and inhibition in a spiking neural network model

    Directory of Open Access Journals (Sweden)

    Paul eChorley

    2011-05-01

    Full Text Available Dopaminergic neurons in the mammalian substantia nigra displaycharacteristic phasic responses to stimuli which reliably predict thereceipt of primary rewards. These responses have been suggested toencode reward prediction-errors similar to those used in reinforcementlearning. Here, we propose a model of dopaminergic activity in whichprediction error signals are generated by the joint action ofshort-latency excitation and long-latency inhibition, in a networkundergoing dopaminergic neuromodulation of both spike-timing dependentsynaptic plasticity and neuronal excitability. In contrast toprevious models, sensitivity to recent events is maintained by theselective modification of specific striatal synapses, efferent tocortical neurons exhibiting stimulus-specific, temporally extendedactivity patterns. Our model shows, in the presence of significantbackground activity, (i a shift in dopaminergic response from rewardto reward predicting stimuli, (ii preservation of a response tounexpected rewards, and (iii a precisely-timed below-baseline dip inactivity observed when expected rewards are omitted.

  20. The effect of visual parameters on neural activation during nonsymbolic number comparison and its relation to math competency.

    Science.gov (United States)

    Wilkey, Eric D; Barone, Jordan C; Mazzocco, Michèle M M; Vogel, Stephan E; Price, Gavin R

    2017-10-01

    Nonsymbolic numerical comparison task performance (whereby a participant judges which of two groups of objects is numerically larger) is thought to index the efficiency of neural systems supporting numerical magnitude perception, and performance on such tasks has been related to individual differences in math competency. However, a growing body of research suggests task performance is heavily influenced by visual parameters of the stimuli (e.g. surface area and dot size of object sets) such that the correlation with math is driven by performance on trials in which number is incongruent with visual cues. Almost nothing is currently known about whether the neural correlates of nonsymbolic magnitude comparison are also affected by visual congruency. To investigate this issue, we used functional magnetic resonance imaging (fMRI) to analyze neural activity during a nonsymbolic comparison task as a function of visual congruency in a sample of typically developing high school students (n = 36). Further, we investigated the relation to math competency as measured by the preliminary scholastic aptitude test (PSAT) in 10th grade. Our results indicate that neural activity was modulated by the ratio of the dot sets being compared in brain regions previously shown to exhibit an effect of ratio (i.e. left anterior cingulate, left precentral gyrus, left intraparietal sulcus, and right superior parietal lobe) when calculated from the average of congruent and incongruent trials, as it is in most studies, and that the effect of ratio within those regions did not differ as a function of congruency condition. However, there were significant differences in other regions in overall task-related activation, as opposed to the neural ratio effect, when congruent and incongruent conditions were contrasted at the whole-brain level. Math competency negatively correlated with ratio-dependent neural response in the left insula across congruency conditions and showed distinct correlations when